National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

Aniakchak National Monument and Preserve 

Natural Resource Condition Assessment

Natural Resource Report NPS/ANIA/NRR—2016/1129
ON THE COVER

The Gates into Aniakchak Caldera. Origin of the Aniakchak River as it winds down through The Gates. Photograph by: Troy 

Hamon, NPS.
Aniakchak National Monument and Preserve

Natural Resource Condition Assessment

Natural Resource Report NPS/ANIA/NRR—2016/1129 

Jacob Zanon 

Mike R. Komp 

Jon Sopcak 

Kevin M. Benck 

Kathy Allen

Kevin J. Stark 

Lonnie J. Meinke 

Andrew Robertson 

Barry Drazkowski 

GeoSpatial Services

Saint Mary’s University of Minnesota 

890 Prairie Island Road 

Winona, Minnesota 55987 

February 2016

U.S. Department of the Interior 

National Park Service

Natural Resource Stewardship and Science 

Fort Collins, Colorado 
ii

The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, 

Colorado, publishes a range of reports that address natural resource topics. These reports are of 

interest and applicability to a broad audience in the National Park Service and others in natural 

resource management, including scientists, conservation and environmental constituencies, and the 

public. 

The Natural Resource Report Series is used to disseminate comprehensive information and analysis 

about natural resources and related topics concerning lands managed by the National Park Service. 

The series supports the advancement of science, informed decision-making, and the achievement of 

the National Park Service mission. The series also provides a forum for presenting more lengthy 

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All manuscripts in the series receive the appropriate level of peer review to ensure that the 

information is scientifically credible, technically accurate, appropriately written for the intended 

audience, and designed and published in a professional manner. 

This report received informal peer review by subject-matter experts who were not directly involved 

in the collection, analysis, or reporting of the data. 

Views, statements, findings, conclusions, recommendations, and data in this report do not necessarily 

reflect views and policies of the National Park Service, U.S. Department of the Interior. Mention of 

trade names or commercial products does not constitute endorsement or recommendation for use by 

the U.S. Government. 

This report is available from the Integrated Resource Management Applications website 

(http://irma.nps.gov) and the Natural Resource Publications Management website 

(http://www.nature.nps.gov/publications/nrpm/). To receive this report in a format optimized for 

screen readers, please email irma@nps.gov. 

Please cite this publication as:

Zanon, J., M. R. Komp, J. Sopcak, K. M. Benck, K. Allen, K. J. Stark, L. J. Meinke, Andrew 

Robertson, and B. Drazkowski. 2016. Aniakchak National Monument and Preserve: Natural resource 

condition assessment. Natural Resource Report NPS/ANIA/NRR—2016/1129. National Park 

Service, Fort Collins, Colorado.

NPS 181/131429, February 2016
iii

Contents 

Page

Figures...................................................................................................................................................ix

Tables....................................................................................................................................................ix

Plates...................................................................................................................................................xiii

Photos...................................................................................................................................................xv

Executive Summary...........................................................................................................................xvii

Acknowledgements.............................................................................................................................xix

Acronyms and Abbreviations..............................................................................................................xxi

Chapter 1: NRCA Background Information ..........................................................................................1

Chapter 2 Introduction and Resource Setting ........................................................................................5

2.1 Introduction ..............................................................................................................................5

2.1.1 Enabling Legislation.........................................................................................................5

2.1.2 Geographic Setting ...........................................................................................................6

2.1.3 Visitation Statistics...........................................................................................................7

2.2 Natural Resources.....................................................................................................................8

2.2.1 Ecological Units and Watersheds.....................................................................................8

2.2.2 Resource Descriptions......................................................................................................8

2.2.3. Resource Issues Overview...............................................................................................9

2.3 Resource Stewardship ............................................................................................................10

2.3.1 Management Directives and Planning Guidance............................................................10

2.3.2 Status of Supporting Science..........................................................................................12

2.4 Landcover and Landscape Processes......................................................................................13

2.4.1. ANIA Landcover...........................................................................................................13

2.4.2. Dominant Landscape Processes ....................................................................................15

2.5 Literature Cited.......................................................................................................................15

Chapter 3. Study Scoping and Design .................................................................................................21

3.1 Preliminary scoping................................................................................................................21

3.2 Study Design ..........................................................................................................................22

3.2.1 Indicator Framework, Focal Study Resources and Indicators........................................22
iv

Contents (continued)

Page

3.2.2 General Approach and Methods ..................................................................................... 26

3.3 Literature Cited ....................................................................................................................... 28

Chapter 4 Natural Resource Conditions............................................................................................... 29

4.1 Moose ..................................................................................................................................... 30

4.1.1 Description ..................................................................................................................... 30

4.1.2 Measures ......................................................................................................................... 31

4.1.3 Reference Conditions/Values ......................................................................................... 31

4.1.4 Data and Methods ........................................................................................................... 32

4.1.5 Current Condition and Trend .......................................................................................... 32

4.1.6 Sources of Expertise ....................................................................................................... 36

4.1.7 Literature Cited ............................................................................................................... 36

4.2 Bear ........................................................................................................................................ 40

4.2.1 Description ..................................................................................................................... 40

4.2.2 Measures ......................................................................................................................... 40

4.2.3 Reference Conditions/Values ......................................................................................... 40

4.2.4 Data and Methods ........................................................................................................... 41

4.2.5 Current Condition and Trend .......................................................................................... 41

4.2.6 Sources of Expertise ....................................................................................................... 42

4.2.7 Literature Cited ............................................................................................................... 42

4.3 Caribou ................................................................................................................................... 44

4.3.1 Description ..................................................................................................................... 44

4.3.2 Measures ......................................................................................................................... 44

4.3.3 Reference Conditions/Values ......................................................................................... 45

4.3.4 Data and Methods ........................................................................................................... 45

4.3.5 Current Condition and Trend .......................................................................................... 46

4.3.6 Sources of Expertise ....................................................................................................... 50

4.3.7 Literature Cited ............................................................................................................... 50

4.4 Passerines ............................................................................................................................... 52
v 

Contents (continued)

Page

4.4.1 Description ..................................................................................................................... 52

4.4.2 Measures ......................................................................................................................... 52

4.4.3 Data and Methods ........................................................................................................... 52

4.4.4 Current Condition and Trend .......................................................................................... 53

4.4.5 Sources of Expertise ....................................................................................................... 59

4.4.6 Literature Cited ............................................................................................................... 59

4.5 Salmon .................................................................................................................................... 62

4.5.1 Description ..................................................................................................................... 62

4.5.2 Measures ......................................................................................................................... 63

4.5.3 Reference Conditions/Values ......................................................................................... 63

4.5.4 Data and Methods ........................................................................................................... 63

4.5.5 Current Condition and Trend .......................................................................................... 64

4.5.6 Sources of Expertise ....................................................................................................... 66

4.5.7 Literature Cited ............................................................................................................... 66

4.6 Native Fish.............................................................................................................................. 69

4.6.1 Description ..................................................................................................................... 69

4.6.2 Analysis .......................................................................................................................... 70

4.6.3 Reference Conditions/Values ......................................................................................... 70

4.6.4 Data and Methods ........................................................................................................... 70

4.6.5 Current Condition and Trend .......................................................................................... 71

4.6.6 Sources of Expertise ....................................................................................................... 73

4.6.7 Literature Cited ............................................................................................................... 73

4.7 Seismic Activity ..................................................................................................................... 75

4.7.1 Description ..................................................................................................................... 75

4.7.2 Measures ......................................................................................................................... 76

4.7.3 Reference Conditions/Values ......................................................................................... 76

4.7.4 Data and Methods ........................................................................................................... 76

4.7.5 Current Condition and Trend .......................................................................................... 77
vi

Contents (continued)

Page

4.7.6 Sources of Expertise ....................................................................................................... 78

4.7.7 Literature Cited ............................................................................................................... 78

4.8 Climate ................................................................................................................................... 82

4.8.1 Description ..................................................................................................................... 82

4.8.2 Data and Methods ........................................................................................................... 82

4.8.3 Current Condition and Trend .......................................................................................... 83

4.8.4 Sources of Expertise ....................................................................................................... 88

4.8.5 Literature Cited ............................................................................................................... 89

4.9 Human Activity ...................................................................................................................... 93

4.9.1 Description ..................................................................................................................... 93

4.9.2 Specific Analysis ............................................................................................................ 93

4.9.3 Data and Methods ........................................................................................................... 93

4.9.4 Current Condition and Trend .......................................................................................... 93

4.9.5 Sources of Expertise ....................................................................................................... 95

4.9.6 Literature Cited ............................................................................................................... 95

4.10 Glaciers ................................................................................................................................. 98

4.10.1 Description ................................................................................................................... 98

4.10.2 Measures ....................................................................................................................... 99

4.10.3 Reference Conditions/Values ....................................................................................... 99

4.10.4 Data and Methods ......................................................................................................... 99

4.10.5 Current Condition and Trend ...................................................................................... 100

4.10.6 Sources of Expertise ................................................................................................... 101

4.10.7 Literature Cited ........................................................................................................... 102

4.11 Water Quality ..................................................................................................................... 105

4.11.1 Description ................................................................................................................. 105

4.11.2 Measures ..................................................................................................................... 105

4.11.3 Data and Methods ....................................................................................................... 106

4.11.4 Current Condition and Trend ...................................................................................... 130
vii

Contents (continued)

Page

4.11.5 Sources of Expertise ................................................................................................... 130

4.11.6 Literature Cited ........................................................................................................... 130

Chapter 5. Discussion ........................................................................................................................ 133

5.1 Component Data Gaps .......................................................................................................... 133

5.2 Park-wide Component Observations .................................................................................... 134

5.2.1 Biotic Composition ....................................................................................................... 134

5.2.2 Environmental Quality ................................................................................................. 136

5.2.3 Physical Characteristics ................................................................................................ 136

5.2.4 Park-wide Threats and Stressors .................................................................................. 138

5.2.5 Literature Cited ............................................................................................................. 138

ix

Figures

Page

Figure 1. Illustration of a glacier showing the accumulation zone, ablation zone, and 

equilibrium line (Valentine et al. 2004). .............................................................................................. 99

Tables 

Page

Table 1. Monthly temperature and precipitation normals (1981-2010) for ANIA ................................ 7

Table 2. SWAN Vital Signs selected for monitoring in ANIA ........................................................... 12

Table 3. 1983 landcover classes and coverage areas in ANIA............................................................ 13

Table 4. 2008 landcover classes and coverage areas in ANIA............................................................ 14

Table 5. ANIA natural resource condition assessment framework. .................................................... 24

Table 6. Moose population composition in Unit 9E, 1999, 2002-2005 .............................................. 33

Table 7. Annual moose harvest in Unit 9, 1998-2008 ......................................................................... 34

Table 8. Concession harvest of moose in ANIA from 2005 to 2010 .................................................. 34

Table 9. Concession harvest of brown bears in ANIA from 2005 to 2010 ......................................... 41

Table 10. Population size and composition of the NAPCH, 1984, 1990-2008 ................................... 48

Table 11. Passerines present or possibly present in ANIA ................................................................. 54

Table 12. Number of individuals of each passerine species documented in ANIA, and 

average occurrence. .............................................................................................................................. 57

Table 13. NPS certified species list of native fish present or probably present in ANIA ................... 69

Table 14. Fisheries survey of Surprise Lake and Surprise Lake Tributaries....................................... 71

Table 15. 1987 & 1988 fisheries survey of Surprise Lake, Surprise Lake Tributaries, and 

Aniakchak River Tributaries. ............................................................................................................... 71

Table 16. Species and number of fish sampled (2002 – 2003) in ANIA water bodies. ...................... 72

Table 17. Volcano located in ANIA ( ................................................................................................. 77

Table 18. Seismic monitoring stations located within ANIA ............................................................. 77

Table 19. Port Heiden monthly mean temperature (°C) by year and the mean from Oct. 

2008-Sept. 2011, according to AWOS data. ........................................................................................ 84

Table 20. Yantarni Bay monthly mean temperature (°C) by year and the mean over all 

years of available RAWS data ............................................................................................................. 84
x 

Tables (continued)

Page

Table 21. Mother Goose monthly mean temperature by year and the mean, 2010-2013 ................... 85

Table 22. Minimum and maximum temperatures recorded at each of the climate 

monitoring stations near ANIA, along with the month in which they occurred .................................. 85

Table 23. Mean minimum, mean maximum, and overall mean monthly temperatures at 

Port Heiden during the 2010 and 2012 hydrologic years ..................................................................... 86

Table 24. Yantarni Bay monthly precipitation by year and the mean over all years of 

available RAWS data ........................................................................................................................... 87

Table 25. Mother Goose monthly precipitation by year and the mean over all years of 

available RAWS data ........................................................................................................................... 87

Table 26. ANIA yearly visitation, 1989-2011 ..................................................................................... 94

Table 27. Yearly visitor days, by park location, from SWAN CUA database .................................... 94

Table 28. Total visitor days, by activity, from SWAN CUA database, 2005-2012 ........................... 95

Table 29. ANIA visitor days by month from SWAN CUA Database, 2005-2012 ............................. 95

Table 30. Extent of glaciers located in ANIA ................................................................................... 100

Table 31. Late July and August,1988-1989, trace element concentrations of inlet streams 

and warm spring 14 at the point of entry into Surprise Lake ............................................................. 107

Table 32. Late July and August,1988-1989 trace element concentrations in Surprise Lake 

at the Warm Spring stations, reference station, and the mid-lake station .......................................... 107

Table 33. Water quality and chlorophyll data from Surprise Lake ................................................... 108

Table 34. Concentrations of chemicals measured in μg/L that exceed drinking water 

standards developed by the U.S. EPA in the inlets of Surprise Lake. ............................................... 108

Table 35. Temperature, dissolved oxygen, therapeutic pH, and conductance measured 

with a hydrolab in the inlet streams of Surprise Lake, Aniakchak National Monument, 

Alaska ................................................................................................................................................ 109

Table 36. Temperature measured with a Bacharach thermometer in the inlet streams of 

Surprise Lake, Aniakchak National Monument, Alaska. ................................................................... 110

Table 37. Change in temperature with depth measured with a hydrolab at Station ML1 

Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 .......................................... 112

Table 38. Change in temperature with depth measured with a hydrolab at station RS1 

Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 .......................................... 113

Table 39. Change in temperature with depth measured with a hydrolab at station WS1 

Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 .......................................... 113
xi 

Tables (continued)

Page

Table 40. Change in temperature with depth measured with a hydrolab at station WS2 

Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 .......................................... 114

Table 41. Change in conductance with depth measured with a hydrolab at Surprise Lake 

station ML1 Aniakchak National Monument, Alaska, 1988 and 1989.............................................. 115

Table 42. Change in conductance with depth measured with a hydrolab at Surprise Lake 

station RS1 Aniakchak National Monument, Alaska, 1988 and 1989. .............................................. 116

Table 43. Change in conductance with depth measured with a hydrolab at Surprise Lake 

station WS1 Aniakchak National Monument, Alaska, 1988 and 1989.............................................. 116

Table 44. Change in conductance with depth measured with a hydrolab at Surprise Lake 

station WS2 Aniakchak National Monument, Alaska, 1988 and 1989.............................................. 117

Table 45. Change in pH with depth measured with a hydrolab at station ML1 Surprise 

Lake, Aniakchak National Monument, Alaska,1988 and 1989. ........................................................ 118

Table 46. Change in pH with depth measured with a hydrolab at station RS1 Surprise 

Lake, Aniakchak National Monument, Alaska,1988 and 1989 ......................................................... 119

Table 47. Change in pH with depth measured with a hydrolab at station WS1 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ........................................................ 119

Table 48. Change in pH with depth measured with a hydrolab at station WS2 Surprise 

Lake, Aniakchak National Monument, Alaska,1988 and 1989 ......................................................... 120

Table 49. Change in dissolved oxygen with depth measured with a hydrolab at station 

ML1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ................................. 121

Table 50. Change in dissolved oxygen with depth measured with a hydrolab at station 

RS1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 .................................. 122

Table 51. Change in dissolved oxygen with depth measured with a hydrolab at station 

WS1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ................................. 122

Table 52. Change in dissolved oxygen with depth measured with a hydrolab at station 

WS2 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ................................. 123

Table 53. Change in light with depth measured with a hydrolab at station ML1 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ........................................................ 124

Table 54. Change in light with depth measured with a hydrolab at station RS1 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989. ....................................................... 125

Table 55. Change in light with depth measured with a hydrolab at station WS1 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ........................................................ 125

Table 56. Change in light with depth measured with a hydrolab at station WS2 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989 ........................................................ 126
xii 

Tables (continued)

Page

Table 57. Water depth, depth of measurement and water quality parameters for six 

sampling locations in Surprise Lake, Aniakchak National Monument and Preserve, 

Alaska, 26 July 1987 .......................................................................................................................... 127

Table 58. Calculated stream discharge and water quality measurements of tributaries to 

Surprise Lake and the Aniakchak River, Aniakchak National Monument and Preserve, 

Alaska, 24-26 July 1987 .................................................................................................................... 128

Table 59. Vertical profile of water quality measurements taken at two meter intervals in 

Surprise Lake, Aniakchak National Monument and Preserve, Alaska, 26 July 1987 ....................... 128

Table 60. Identified data gaps or needs for the featured components. .............................................. 133
xiii

Plates 

Page

Plate 1. Aniakchak Park Map ............................................................................................................... 18

Plate 2. Landcover classes and coverage area for ANIA in 1983. ....................................................... 19

Plate 3. Landcover classes and coverage area for ANIA in 2008. ....................................................... 20

Plate 4. Alaska GMUs and subunits..................................................................................................... 38

Plate 5. Trend area survey boundaries. ................................................................................................ 39

Plate 6. Alaska game management units and subunits ......................................................................... 43

Plate 7. Alaska game management units and subunits ......................................................................... 51

Plate 8. Breeding bird inventory sites within ANIA. ........................................................................... 61

Plate 9. Major water bodies in and near ANIA. ................................................................................... 68

Plate 10. Area waterbodies of interest in Aniakchak National Monument and Preserve. ................... 74

Plate 11. Seismically monitored volcano and seismic stations within ANIA. ..................................... 80

Plate 12. Distribution and magnitudes of recorded seismic events of the KATM region ................... 81

Plate 13. Mean annual temperatures in the ANIA region, 1971-2000, according to PRISM 

data ....................................................................................................................................................... 91

Plate 14. Mean annual precipitation in the ANIA region, 1971-2000, according to PRISM 

data ....................................................................................................................................................... 92

Plate 15. SWAN visitor use monitoring areas. .................................................................................... 96

Plate 16. Total visitor days by park location from SWAN CUA Database, 2005-2012 ...................... 97

Plate 17. Glaciated areas of the Aniakchak Caldera in ANIA. .......................................................... 104

xv

Photos

Page

Photo 1. Aniakchak River delta.............................................................................................................5

Photo 2. Aerial photo of Aniakchak Caldera ........................................................................................6

Photo 3. A caribou in Aniakchak Caldera.............................................................................................8

Photo 4. Horned puffins. .......................................................................................................................9

Photo 5. Cow moose grazing with two calves.....................................................................................30

Photo 6. An Alaskan brown bear sow with three cubs .......................................................................40

Photo 7. Alaskan caribou bulls in early fall. .......................................................................................44

Photo 8. A male snow bunting in ANIA .............................................................................................52

Photo 9. Horned lark ...........................................................................................................................53

Photo 10. Orange-crowned warbler (Vermivora celata), black-billed magpie (Pica 

hudsonia) (USFWS photos), and golden-crowned sparrow (Zonotrichia atricapilla)........................57

Photo 11. A local fisherman drying salmon on a knoll east of the mouth of the Aniakchak 

River.....................................................................................................................................................62

Photo 12. An Alaskan Dolly Varden...................................................................................................69

Photo 14. AVO seismic monitoring station in ANIA .........................................................................76

Photo 15. Rafting the Aniakchak River...............................................................................................93

Photo 16. The Aniakchak Caldera area in ANIA................................................................................98

Photo 17. Water quality data collection in an Alaskan water body...................................................105

Photo 18. Surprise Lake in the Aniakchak Caldera...........................................................................109

xvii

Executive Summary

The Natural Resource Condition Assessment (NRCA) Program aims to provide documentation about 

the current conditions of important park natural resources through a spatially explicit, multidisciplinary synthesis of existing scientific data and knowledge. Findings from the NRCA will help 

Aniakchak National Monument and Preserve (ANIA) managers to develop near-term management

priorities, engage in watershed or landscape scale partnership and education efforts, conduct park 

planning, and report program performance (e.g., Department of the Interior’s Strategic Plan “land 

health” goals, Government Performance and Results Act).

The objectives of this assessment are to evaluate and report on current conditions of key park 

resources, to evaluate critical data and knowledge gaps, and to highlight selected existing stressors 

and emerging threats to resources or processes. For the purpose of this NRCA, staff from the 

National Park Service (NPS) and Saint Mary’s University of Minnesota – GeoSpatial Services 

(SMUMN GSS) identified key resources, referred to as “components” in the project. The selected 

components include natural resources and processes that are currently of the greatest concern to park 

management at ANIA. The final project framework contains 11 resource components, each featuring 

discussions of measures, stressors, and reference conditions.

This study involved reviewing existing literature and, where appropriate, analyzing data for each 

natural resource component in the framework to provide summaries of current condition and trends 

in selected resources. When possible, existing data for the established measures of each component 

were analyzed and compared to designated reference conditions. The discussions for each 

component, found in Chapter 4 of this report, represent a comprehensive summary of current 

available data and information for these resources, including unpublished park information and 

perspectives of park resource managers, and present a current condition designation when 

appropriate. Each component assessment was reviewed by ANIA park resource managers and NPS 

Southwest Alaska Network (SWAN) staff.

Overall, the conditions of the resources in this park are good. However, threats and stressors of high 

concern may cause resource impact in the near future. Several park-wide threats and stressors 

influence the condition of priority resources in ANIA. Those of primary concern include climate 

change and oil spills. Understanding these threats, and how they relate to the condition of these 

resources, can help the NPS prioritize management objectives and better focus conservation 

strategies to maintain the health and integrity of park ecosystems.

xix

Acknowledgements

We acknowledge the Aniakchak National Park and Monument staff for the technical expertise 

provided during scoping, through multiple stages of review, and via phone and email; specifically, 

Troy Hamon, Whitney Rapp, Carissa Turner, and Sherri Anderson. We also would like to 

acknowledge Michael Shephard, and Heather Coletti, and Chuck Lindsay from the Southwest Alaska 

Network (SWAN), and Bruce Giffen (NPS) for support in coordinating project efforts. 

xxi

Acronyms and Abbreviations

AAR- Accumulation Area Ratio

ADF&G- Alaska Department of Fish and Game

ADNR- Alaska Department of Natural Resources

ANIA- Aniakchak National Park and Preserve

ANILCA- Alaska National Interest Lands Conservation Act

ANM- Aniakchak National Monument

ANP- Aniakchak National Preserve

BLM- Bureau of Land Management

DO- Dissolved Oxygen

DU- Ducks Unlimited

ELA- Equilibrium Line Altitude

EPA- Environmental Protection Agency

EROS- Earth Resources Observation and Science Center

GMU- Game Management Units

I&M - Inventory and Monitoring

KATM- Katmai National Preserve and Park

NAPCH - Northern Alaska Peninsula Caribou Herd

NCEDC - Northern California Earthquake Data Center

NPS- National Park Service

NRCA- Natural Resource Condition Assessment

SMUMN GSS - Saint Mary’s University of Minnesota Geospatial Services

SWAN- Southwest Alaska Inventory and Monitoring Network

USFWS- U.S. Fish and Wildlife Service

USGS- U.S. Geological Survey

1 

Chapter 1: NRCA Background Information

Natural Resource Condition Assessments (NRCAs) evaluate current conditions for a subset of 

natural resources and resource indicators in national park units, hereafter “parks.” NRCAs also report 

on trends in resource condition (when possible), identify critical data gaps, and characterize a general 

level of confidence for study findings. The resources and indicators emphasized in a given project 

depend on the park’s resource setting, status of resource stewardship planning and science in 

identifying high-priority indicators, and availability of data and expertise to assess current conditions 

for a variety of potential study resources and indicators. 

NRCAs represent a relatively new approach to assessing 

and reporting on park resource conditions. They are 

meant to complement—not replace—traditional issueand threat-based resource assessments. As distinguishing 

characteristics, all NRCAs:

• are multi-disciplinary in scope;1

 

• employ hierarchical indicator frameworks;2

• identify or develop reference conditions/values 

for comparison against current conditions;3

• emphasize spatial evaluation of conditions and GIS (map) products;4

• summarize key findings by park areas; and5

• follow national NRCA guidelines and standards for study design and reporting products. 

 

NRCAs Strive to Provide...

Credible condition reporting for a 

subset of important park natural 

resources and indicators 

Useful condition summaries by 

broader resource categories or 

topics, and by park areas

1 The breadth of natural resources and number/type of indicators evaluated will vary by park. 

2 Frameworks help guide a multi-disciplinary selection of indicators and subsequent “roll up” and reporting of data 

for measures  conditions for indicators  condition summaries by broader topics and park areas 

3 NRCAs must consider ecologically-based reference conditions, must also consider applicable legal and regulatory 

standards, and can consider other management-specified condition objectives or targets; each study indicator can be 

evaluated against one or more types of logical reference conditions. Reference values can be expressed in qualitative 

to quantitative terms, as a single value or range of values; they represent desirable resource conditions or, 

alternatively, condition states that we wish to avoid or that require a follow-on response (e.g., ecological thresholds 

or management “triggers”).

4 As possible and appropriate, NRCAs describe condition gradients or differences across a park for important natural 

resources and study indicators through a set of GIS coverages and map products. 

5 In addition to reporting on indicator-level conditions, investigators are asked to take a bigger picture (more 

holistic) view and summarize overall findings and provide suggestions to managers on an area-by-area basis: 1) by 

park ecosystem/habitat types or watersheds, and 2) for other park areas as requested.
2

Although the primary objective of NRCAs is to report on current conditions relative to logical forms 

of reference conditions and values, NRCAs also report on trends, when appropriate (i.e., when the 

underlying data and methods support such reporting), as well as influences on resource conditions. 

These influences may include past activities or conditions that provide a helpful context for 

understanding current conditions, and/or present-day threats and stressors that are best interpreted at 

park, watershed, or landscape scales (though NRCAs do not report on condition status for land areas 

and natural resources beyond park boundaries). Intensive cause-and-effect analyses of threats and 

stressors, and development of detailed treatment options, are outside the scope of NRCAs.

Due to their modest funding, relatively quick timeframe for completion, and reliance on existing data 

and information, NRCAs are not intended to be exhaustive. Their methodology typically involves an 

informal synthesis of scientific data and information from multiple and diverse sources. Level of 

rigor and statistical repeatability will vary by resource or indicator, reflecting differences in existing

data and knowledge bases across the varied study components.

The credibility of NRCA results is derived from the data, methods, and reference values used in the 

project work, which are designed to be appropriate for the stated purpose of the project, as well as 

adequately documented. For each study indicator for which current condition or trend is reported, we 

will identify critical data gaps 

and describe the level of 

confidence in at least qualitative 

terms. Involvement of park staff 

and National Park Service 

(NPS) subject-matter experts at 

critical points during the project 

timeline is also important. These 

staff will be asked to assist with 

the selection of study indicators; 

recommend data sets, methods, 

and reference conditions and 

values; and help provide a 

multi-disciplinary review of 

draft study findings and 

products. Complied 

NRCAs can yield new insights about current park resource conditions but, in many cases, their 

greatest value may be the development of useful documentation regarding known or suspected 

resource conditions within parks. Reporting products can help park managers as they think about 

near-term workload priorities, frame data and study needs for important park resources, and 

communicate messages about current park resource conditions to various audiences. A successful 

NRCA delivers science-based information that is both credible and has practical uses for a variety of 

park decision making, planning, and partnership activities.

Important NRCA Success Factors

Obtaining good input from park staff and other NPS 

subject-matter experts at critical points in the project 

timeline 

Using study frameworks that accommodate meaningful 

condition reporting at multiple levels (measures 

indicators  broader resource topics and park areas)

Building credibility by clearly documenting the data and 

methods used, critical data gaps, and level of confidence 

for indicator-level condition findings 
3 

However, it is important to note that NRCAs do not establish management targets for study 

indicators. That process must occur through park planning and management activities. What an 

NRCA can do is deliver science-based information that will assist park managers in their ongoing, 

long-term efforts to describe and quantify a park’s desired resource conditions and management 

targets. In the near term, NRCA findings assist strategic park resource planning6

 and help parks to 

report on government accountability measures.7

 In addition, although in-depth analysis of the effects 

of climate change on park natural resources is outside the scope of NRCAs, the condition analyses 

and data sets developed for NRCAs will be useful for park-level climate-change studies and planning 

efforts. 

NRCA Reporting Products...

 Provide a credible, snapshot-in-time evaluation for a subset of important 

park natural resources and indicators, to help park managers: 

Direct limited staff and funding resources to park areas and natural resources 

that represent high need and/or high opportunity situations 

(near-term operational planning and management) 

Improve understanding and quantification for desired conditions for the park’s 

“fundamental” and “other important” natural resources and values 

(longer-term strategic planning)

Communicate succinct messages regarding current resource conditions to 

government program managers, to Congress, and to the general public 

(“resource condition status” reporting) 

NRCAs also provide a useful complement to rigorous NPS science support programs, such as the 

NPS Natural Resources Inventory & Monitoring (I&M) Program.8

 For example, NRCAs can provide 

current condition estimates and help establish reference conditions, or baseline values, for some of a 

 

6

An NRCA can be useful during the development of a park’s Resource Stewardship Strategy (RSS) and can also be 

tailored to act as a post-RSS project.

7 While accountability reporting measures are subject to change, the spatial and reference-based condition data 

provided by NRCAs will be useful for most forms of “resource condition status” reporting as may be required by the 

NPS, the Department of the Interior, or the Office of Management and Budget. 

8 The I&M program consists of 32 networks nationwide that are implementing “vital signs” monitoring in order to 

assess the condition of park ecosystems and develop a stronger scientific basis for stewardship and management of 

natural resources across the National Park System. “Vital signs” are a subset of physical, chemical, and biological 

elements and processes of park ecosystems that are selected to represent the overall health or condition of park 

resources, known or hypothesized effects of stressors, or elements that have important human values.
4 

park’s vital signs monitoring indicators. They can also draw upon non-NPS data to help evaluate 

current conditions for those same vital signs. In some cases, I&M data sets are incorporated into 

NRCA analyses and reporting products. 

Over the next several years, the NPS plans to fund a NRCA project for each of the approximately 

270 parks served by the NPS I&M Program. For more information on the NRCA program, visit 

http://nature.nps.gov/water/nrca/index.cfm. 
5 

Chapter 2 Introduction and Resource Setting

2.1 Introduction

2.1.1 Enabling Legislation

The Aniakchak Caldera formed approximately 3,500 years ago after a large volcanic eruption. The 

eruption caused the 2,134-m (7,000-ft) mountain to collapse nearly 914 m (3,000 ft), creating a 610-

m (2,000-ft) deep caldera (NPS 1986). The Aniakchak Caldera is one of the largest calderas found on 

the Alaska Peninsula. 

In December of 1978, Aniakchak Caldera and River (Photo 1) as well as the surrounding area of the 

Aniakchak National Park and Preserve (ANIA) became a unit of the National Park System. In order 

to ensure the protection of the surrounding area’s natural and cultural resources, ANIA was later 

designated a National Monument and Preserve on 2 December 1980 by section 201(1) of the Alaska 

National Interest Lands Conservation Act (ANILCA) (NPS 1986). 

Photo 1. Aniakchak River delta (NPS photo by Troy Hamon). 

ANILCA defines the purpose of designating ANIA to a National Monument and Preserve in section 

201(1): 

Maintain the Anikchak Caldera and its associated features and landscape, including the 

Anikchak River and other lakes and streams, in their natural state; to study, interpret, and 

assure continuation of the natural process of biological succession; to protect habitat for, and 

populations of fish and wildlife, including, but not limited to, brown/grizzly bears, moose, 

caribou, sea lions seals, and other marine mammals, geese, swans, and other waterfowl and in 

a manner consistent with the foregoing, to interpret geological and biological processes for 
6 

visitors. Subsistence uses by local residents shall be permitted in the monument where such 

uses are traditional (NPS 1986, p. 30). 

The Aniakchak River became a National Wild River on 2 December 1980 by ANILCA section 

601(27). This includes 51 km (32 mi) of river starting in Surprise Lake and ending in Aniakchak 

Bay, as well as 50 km (31 mi) of major tributaries (NPS 1986). This section was meant to preserve 

and protect the river and its corridor by maintaining its free-flowing condition, for future generations 

to enjoy and appreciate (NPS 2008). 

2.1.2 Geographic Setting

Aniakchak National Monument and Preserve is 

located in Southwest Alaska on the Alaska 

Peninsula (Plate 1). More specifically, ANIA is 

found at the southern edge of the Lake and 

Peninsula Borough which has a population of 

1,631 people (U.S. Census 2010). The national 

monument and preserve’s headquarters are 

located in King Salmon, which is located in 

Bristol Bay Borough with a population of 997 

(U.S. Census 2010). ANIA encompasses 

242,812 ha (600,000 ac) of land. 

Volcanism is an important geologic process 

within the monument. Aniakchak Caldera (Photo 2) is approximately 10 km (6 mi) wide and 78 km2

(30 mi2

) in area (Plate 1, NPS 1986). A dominant feature of the caldera is its largest vent, Vent 

Mountain. Vent Mountain reaches 671 m (2,200 ft) and was observed steaming during the last 

eruption in 1931 (APG 1973). Vegetation became sparse after the eruption, but with the volcano 

remaining inactive, the vegetation has had time to advance over the ash flows. The densest vegetation 

in the caldera is found near Surprise Lake (APG 1973). Wildlife were also absent for many years 

after the last eruption but eventually returned to the caldera (APG 1973). 

A diversity of soil types are found in the monument and preserve. At the high elevations of the peaks 

and ridges of the caldera, there is an absence of soil. The foothills of the caldera wall, the river 

drainages, and the coastal plains have the most developed and deep soil. Near the northwest region of 

the caldera, where the ash cover is deepest and most recent, there are shallow soils. The Meshik 

River valley contains rather deep soil that is poorly drained; fibrous peat is formed here due to the 

various layers of ash in combination with sedge and moss growth (NPS 1986). 

ANIA has two distinct climates. The eastern side of ANIA has a maritime climate, which is 

characterized by high levels of annual precipitation and strong winds. The western portion of the 

monument and preserve, near Bristol Bay, has more of a continental climate, which means there is a 

larger annual temperature range and lower levels of precipitation (NPS 1986). Port Heiden, just west 

of the monument, has average high temperatures reaching 14°C (57°F), with the warmer months 

being June through September. The coldest month in Port Heiden is February, with an average low 

Photo 2. Aerial photo of Aniakchak Caldera (NPS 

photo).
7 

temperature of -6.5°C (20°F); the cooler months include December through March (Table 1; WRCC 

2011). 

Table 1. Monthly temperature and precipitation normals (1981-2010) for ANIA (Station 507700, Port 

Heiden, Alaska) (Western Regional Climate Center 2011).

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual

Average Temperature (°C)

Max 0.2 -0.8 1.7 2.7 7.9 11.6 13.8 14.2 11.6 6.4 1.9 1.4 6.1

Min -4.7 -6.5 -3.8 -2.9 1.6 5.4 8.7 9.1 6.7 1.1 -2.8 -3.1 0.8

Average Precipitation (cm)

Total 2.9 1.4 2.7 1.6 1.9 2.9 4.7 4.4 5.1 4.1 3.9 4.3 40.1

2.1.3 Visitation Statistics

Annual visitation to the park is low; the visitation count was 10, 14, and 62 people in 2008, 2009, and 

2010, respectively (NPS 2010a). This is due to the remoteness of the monument. The main means of 

transportation to ANIA are floatplanes or amphibious vehicles. Most visitors fly from King Salmon 

to Surprise Lake (located in Aniakchak Caldera) (NPS 1986). 

There are several reasons for visiting ANIA, which include fishing, hunting, trapping, hiking, 

camping, and rafting. Subsistence fishing, hunting, and trapping by local residents are permitted in 

the monument and preserve. Sport fishing is also allowed in both the preserve and monument. 

However, sport hunting and trapping are only allowed in the preserve (NPS 1986). Moose (Alces 

alces) and brown bear (Ursus arctos) are two of the primary species of game in the park (NPS 

2010c). 

Hiking, backpacking, and camping occur in ANIA. In order to preserve the ecological condition of 

the monument and preserve, hiking trails and campgrounds were not developed. Most visitors find 

the hiking conditions to be excellent on the caldera floor (NPS 2010c). Many visitors can access the 

caldera floor through “The Gates” of the caldera (break in the caldera wall) which also allows the 

Aniakchak River to flow from the caldera to the sea (APG 1973, p. 11). Some hikers may find 

themselves using game and other animal trails; information regarding wildlife encounters can be 

found at ANIA headquarters in King Salmon (NPS 1986). When camping, visitors are required to 

leave little to no evidence of their presence after leaving the camp site.

Another activity that brings visitors to ANIA is rafting. The high gradient of the Aniakchak River 

makes rafting challenging. The first 24 km (15 mi) of the river drops greater than 305 m (1,000 ft); 

the last 19 km (12 mi) of the river are a slightly smoother trip through the open tundra (NPS 2010b). 

Rafting this river from the beginning to end requires expert/advanced rafting skills, and visitors are 

recommended to bring extra equipment in case there is damage due to the river’s composition (large 

boulders, sharp bends) and rapidly changing conditions, which can be severe or life-threatening (NPS 

2010c). 
8 

2.2 Natural Resources

2.2.1 Ecological Units and Watersheds

ANIA is a part of Environmental Protection Agency’s (EPA) Pacific Northwest Region 10. This 

region provides support for Alaska, Idaho, Oregon, Washington, and 271 Native Tribes (EPA 2011). 

The monument and preserve is found in the Alaska Peninsula Mountains Ecoregion. 

The Alaska Peninsula Mountains ecoregion includes a portion of the Kodiak Islands and runs down 

the eastern side of the Aleutian Islands. This region’s climate is considered marine with high annual 

rates of precipitation (Griffith 2010). The vegetation composition found throughout this region 

includes dwarf shrubs, willow, birch and alder. The Aleutian mountains give this region a large 

elevation range (sea level to 2,600 m) and have sporadically placed volcanoes (Griffith 2010). The 

volcanic activity has affected the soil because many soils in the region have “formed in deposits of 

volcanic ash and cinder” (Griffith 2010, p. 19). 

ANIA belongs to the Aniakchak River watershed. The watershed begins in the Aniakchak Caldera 

(Surprise Lake) and runs east into Aniakchak Bay. This watershed is approximately 43 km2

 (16 mi2) 

including the entire Aniakchak Caldera, Aniakchak River, and the river’s tributaries (Nagorski et al. 

2007). This watershed does not contain any dams; it is a naturally free- flowing river watershed (NPS 

1986). The caldera was said to have been a large snow-fed reservoir for the watershed, but over the 

years a leak in the caldera wall caused most of the caldera to drain, forming the National Wild 

Aniakchak River (NPS 1986). 

2.2.2 Resource Descriptions

ANIA encompasses many unique biomes. The Alaska Planning Group (1973) has classified four 

vegetative types in ANIA: alpine tundra, wet tundra, moist tundra, and shrub. The alpine tundra is 

located on the eastern slopes of the mountain. On the western slopes of the caldera and in the Cinder 

River Valley, moist tundra is present. The wet tundra occupies much of the coastal plains near Bristol 

Bay. The shrub vegetative type inhabits most of the river valleys (e.g., Meshik, Cinder, and 

Aniakchak) (APG 1973). According to Lenz et al. (2002), there are roughly 472 plant species in the 

national monument and preserve. Regrowth of vegetation in the caldera has been occurring since the 

last eruption in 1931. 

 ANIA provides habitat for 28 species of mammals, 

including three semi-aquatic species and three marine 

species (NPS 2013). Common species include brown 

bear, moose, and caribou (Rangifer tarandus; Photo 3). 

The moderate climate in the unit permits brown bears to 

be active longer throughout the year; ANIA bears have 

held off hibernation until December in some years. Brown 

bears are often found in areas of ANIA where the salmon 

availability is highest, which includes the caldera when 

salmon reach Surprise Lake (NPS 2003). Bears also prey 

on moose and caribou at different times over the course of Photo 3. A caribou in Aniakchak 

Caldera (NPS photo).
9 

the year. The moose in ANIA exceeded their carrying capacity around 1960 in the Aleutian Range, 

which caused a population decline. Brown bear predation also keeps moose density down. Moose 

have been observed in the northern region of the preserve by the Cinder River, where there is higher 

quality wintering habitat (NPS 2003). Some species that are present, but observed less frequently, 

include wolves (Canis lupus), lynx (Lynx canadensis), wolverines (Gulo gulo), and porcupines 

(Erethizon dorsatum) (NPS 2003). 

There are 134 documented bird species in 

ANIA; there are approximately 54 landbird 

species, 33 inland waterfowl species, and 47 

seabird species (NPS 2013). Some of the more 

common species include harlequin ducks 

(Histrionicus histrionicus), mergansers (Mergus 

spp.), bald eagles (Haliaeetus leucocephalus), 

rough-legged hawks (Buteo lagopus), American 

pipit (Anthus rubescens), black oystercatchers 

(Haematopus bachmani), Kittlitz’s murrelets 

(Brachyramphus brevirostris), and horned 

puffins (Fratercula corniculata; Photo 4) 

(Stroud and Fuller 1983, Manski et al. 1987, Meyer 1987, Sowl 1988, Starr and Starr 1988, Savage 

1993, as cited by NPS 2003). Bald eagles can be found from the coast to the caldera in ANIA; they 

are commonly found and have been observed building nests along the rivers and lakes (NPS 1986). 

ANIA supports a number of fish from freshwater to marine species According to NPS (2013), there 

are 18 species of fish in ANIA waters. Some species found in the freshwater streams include Dolly 

Varden (Salvelinus malma), arctic char (S. alpinus), and rainbow trout (Oncorhynchus mykiss) (NPS 

1986). The anadromous fish include several species of salmon (e.g., coho, chum, king, sockeye, and 

pink) (Oncorhynchus spp.), which are harvested to benefit both commercial and subsistence 

fishermen. Marine fish that are found on the coast of ANIA include halibut (Hippoglossus spp.), cod 

(Gadus spp.), herring (Clupea spp.), and flounder (Platichthys spp.), which are also very important to 

commercial and subsistence fishermen (NPS 1986). 

2.2.3. Resource Issues Overview

ANIA is largely protected from human impacts by its remoteness; it is the most remote NPS unit in 

the nation with the lowest amount of annual visitors (Nagorski et al. 2007). However, several issues 

or events have altered or threaten multiple resources within the monument and preserve. Aniakchak

was devastated by the Exxon Valdez oil spill in 1989; approximately two-thirds of the eastern 

coastline was contaminated with oil (Nagorski et al. 2007). The run-aground tanker spilled roughly 

11 million gallons of oil. ANIA is located 756 km (470 mi) from the wreck and it only took 56 days 

for oil to reach this unit (Nagorski et al. 2007). Marine wildlife, including mammals, fish, and 

seabirds, were most adversely affected by the spill. A restoration plan was created in 1994 by the 

Exxon Valdez Oil Spill Committee to restore the resources lost or damaged in the area. The plan 

contains actions to rehabilitate the environment by replanting intertidal plant species to prespill 

Photo 4. Horned puffins (USFWS photo).
10 

conditions, and limiting human use in the park and surrounding areas until populations stabilize 

(EVOS Council 1994). 

Climate change has begun to alter ANIA resources, but the extent of future impact is uncertain. The 

average temperatures have risen 2.2°C (4°F) since the 1950s and are predicted to continue to increase 

by 2.8-10°C (5–18°F) by 2100 (Nagorski et al. 2007). A warming climate will most seriously impact

water resources, especially at high altitudes (Hall 1988, Serreze et al. 2000), by affecting snow cover, 

glaciers, and sea/lake ice cover (Nagorski et al. 2007). Warmer winters will cause the snowpack to 

decrease while increasing rain events (Nagorski et al. 2007). This will result in a drier spring 

environment. Drier conditions may then cause an increase in the fire regime (SNAP et al. 2009). 

There is a slight risk of exotic fish species entering ANIA. Anadromous fish that escape fish farms or 

aquaculture may make their way up ANIA rivers (Nagorski et al. 2007). One example of an exotic 

fish species that is already present in Alaskan waters is the northern pike (Esox lucius); it may alter 

native fish species composition because it is a competitive fish species (ADF&G 2002). The Alaska 

Department of Fish and Game (ADF&G) created a management plan to reduce invasive species 

spread into Alaskan waters. The Alaska Aquatic Nuisance Species Management Plan was finished in 

2002; it is used to prevent the invasion of those species that are considered the highest threat

(ADF&G 2002). 

Exotic plant species do not seem to be a major problem, as long as the monument controls off-road 

vehicles and annual visitor counts remain low. Fewer visitors traveling in and out of the park will 

most likely mean a low risk of exotic invasions. According to a survey by Lipkin (2005), no 

introduced plant species were observed in the monument and preserve. 

2.3 Resource Stewardship

2.3.1 Management Directives and Planning Guidance

ANIA’s Master Plan (APG 1973) outlined the monument’s purpose, before the development of the 

general management plan in 1986, by setting out objectives to protect the monument and preserve. 

These general management objectives are as follows: 

• Recognize the management requirements for the Natural Area Category of the National Park 

System and the National Wild and Scenic Rivers System and apply them accordingly to 

Aniakchak Caldera and the Aniakchak National Wild River. 

• Manage Aniakchak as a unit of the Alaska State Office of the NPS with direct supervision by 

an area superintendent. 

• Offer ANIA visitors yearly services that are seasonally appropriate. 

• Work cooperatively with others (e.g., private enterprises) to develop an appropriate mode of 

transportation for visitors that is both efficient and energy efficient to benefit the monument 

and preserve as well as the region (APG 1973). 

The ANIA General Management Plan (NPS 1986) has several management objectives for natural 

resources, cultural resources, visitor use and interpretation and commercial operation purposes. 

These objectives are as follows:
11 

Natural resources:

• Ensure the continuation of the monument’s ecological processes and systems by maintaining 

the natural resources. 

• Encourage the natural growth of vegetation and wildlife in the monument and emphasize the 

importance of the caldera and its features as resources that need protection. 

• Develop a program to permit sport hunting in the preserve and subsistence hunting and 

fishing throughout the unit to balance the wildlife populations and ensure the health of their 

habitat. 

• Cooperate with organizations such as Alaska Department of Fish and Game and Public 

Safety, as well as the local government, native corporations and private interests to create a 

suitable monitoring system for the area natural resources. 

• Work with private interests to ensure that high environmental standards are met when 

considering future exploration and potential development inside or near the monument and 

preserve. 

Cultural resources:

• Recognize and follow the legislative and executive requirements and policies of the National 

Park Service when assessing the unit’s resources (historical, archeological, and cultural). 

• Collect cultural resources information (oral and written) relevant to the unit and use that 

information to create fun and educational materials and programs for visitors. 

• Encourage and assist local people, groups, and native corporations to perpetuate the cultural 

heritage of the region. 

Visitor use and interpretations: 

• Develop a baseline inventory of recreational resources to provide visitors the necessary 

services and means of accessing the monument to minimize unauthorized travel and negative 

impacts in the monument and preserve.

• Encourage and provide information and technical assistance to private enterprise to provide 

appropriate visitor services, preferably with bases of operation outside the boundaries of the 

monument and preserve. 

• Create informative programs to educate potential visitors and the public of the monument and 

preserve’s key resources, environmental factors, weather, and visitor activities that may 

influence their decision to visit the unit.

Commercial operations: 

• Identify appropriate levels and types of commercial services feasible for providing visitor 

services and issue permits and commercial use licenses as appropriate to meet the needs of 

visitors and to perpetuate resources (NPS 1986). 
12 

2.3.2 Status of Supporting Science

The Southwest Alaska Network Inventory and Monitoring Network (SWAN) identifies key resources 

network-wide and for each of its parks that can be used to determine the overall health of the parks. 

These key resources are called Vital Signs. In 2006, the SWAN completed and released a Vital Signs 

monitoring plan (Bennett et al. 2006). Table 2 shows the network Vital Signs selected for monitoring 

in ANIA.

Table 2. SWAN Vital Signs selected for monitoring in ANIA (adapted from Bennett et al. 2006). Those in 

bold are Vital Signs that the SWAN is working independently or jointly with a network park, federal, state, 

or private partner to develop and implement monitoring protocols using funding from the Vital Signs or 

water quality monitoring programs while those in italics Vital Signs that are monitored independently of 

SWAN by a Network park, another NPS program, or another federal, state, or private agency.

Category ANIA Vital Signs

Air and Climate Visibility and particulate matter

Geology and Soils Volcanic and earthquake activity

Water Surface hydrology, freshwater chemistry

Biological Integrity

Invasive/exotic species, resident lake fish, salmon, bald eagle, 

brown bear, wolf, wolverine, moose, caribou, vegetation composition 

and structure, sensitive vegetation communities

Human Use Resource harvest for subsistence and sport, visitor use

Landscapes (Ecosystem Pattern and 

Processes) Land cover/land use, landscape processes

The coastal areas of ANIA have been inventoried and digitally mapped through a project funded by 

NOAA. This process produced a series of Environmental Sensitivity Index (ESI) maps that 

summarized sensitive natural and human-use resources for prevention planning and accident 

response. While produced primarily for oil and chemical spill planning and response these maps can 

provide a base for other natural resource planning as well. 

Sensitive shoreline habitat, sensitive biological resources and human-use resources are all indicated 

on these maps. Shoreline type (substrate, grain size, origin, elevation), exposure to wave energy, 

biological productivity and sensitivity and ease of cleanup (in response to a spill) are all factors that 

determine the sensitivity of a shoreline. Biological resources identified on the maps include six major 

categories; terrestrial mammals, marine mammals, birds, fish, invertebrates, and benthic marine 

habitats and are the resources most likely to be impacted by an oil spill. Finally, human-use resources 

such as airports, wildlife refuges, critical habitat, and national park lands are also identified in these 

data.

The ESI series of maps (and associated attribute data) along with other sources such as the NSM data 

are available to ANIA for planning and response purposes. 
13 

2.4 Landcover and Landscape Processes

Exisiting landcover datasets do not lend themselves to assessment due to their variability in defining 

landcover classes from one data set year to the next. However, some general observations between 

data set years can be made, as well as statements regarding the importance of how natural processes 

shape the ANIA landscape. 

2.4.1. ANIA Landcover 

Landcover datasets for ANIA were created in both 1983 and 2008. The 1983 dataset was created in 

fulfillment of the Bristol Bay landcover mapping project initiated by the Alaska Department of 

Natural Resources (ADNR) and U.S. Geological Survey (USGS) using satellite imagery (Plate 2). 

This landcover mapping ground condition survey was completed and published by the USGS Earth 

Resources Observation and Science Center (EROS). Data are raster format with a 50-meter cell size. 

A total of 15 landcover types are included (Table 3). The most prevalent landcover type identified 

was barren, covering 59,511 hectares or 24% of the total park area. 

The 2008 landcover dataset of ANIA was completed in an effort to continue mapping the Alaskan 

Peninsula by the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM)-

Alaska, and Ducks Unlimited (DU). Data are raster format with a 30-meter cell size. The data set 

presented in this publication is a compilation of four Landsat TM satellite scenes: Path 71 Row 20 

(acquired 13 August 2002) Path 72 Row 19 and 20 (acquired 13 August 2002) and Path 72 Rows 19 

and 20 (acquired 28 August 1999, 15 September 2000 and 17 June 2002 (Plate 3). A total of 36 

landcover classes were included (Table 4). The most prevalent landcover type identified was upland 

dwarf shrubs, covering 53,365 hectares or 21% of the total park area. 

Table 3. 1983 landcover classes and coverage areas in ANIA (USGS/EROS 1989).

Landcover Class Hectares % Landcover

Barren 59,511 24

Snow/Cloud/Light Barren 45,714 19

Closed Shrub Graminoid 39,713 16

No Data 35,664 15

Open Low Shrub Gramin./Mesic Bog/Gramin. 

Lichen Shrub TundraShrub Tundra 27,187 11

Open Low Shrub Eric./Conifer 

Woodland/Mes.Bog/Eric.Shrub Tundra 14,832 6

Miscellaneous Deciduous (Open Alder, 

Cottonwood, Birch, Willow) 12,671 5

Wet Bog/Wet Meadow' 5,245 2

Marsh/Very Wet Bog 2,066 1

Deep Clear Water 403 0
14 

Table 3 (continued). 1983 landcover classes and coverage areas in ANIA (USGS/EROS 1989).

Landcover Class Hectares % Landcover

Shallow/Sedimented Water 367 0

Shallow/Sedimented Water - Offshore 337 0

Deep Clear Water - Offshore 293 0

Mountain Shadow 217 0

Lichen Shrub Tundra 12 0

Total Area 244,232 100

Table 4. 2008 landcover classes and coverage areas in ANIA (DU 2009).

Landcover Class Hectares % Landcover

Dwarf Shrub - Upland 53,365 21

Rock/Gravel 34,105 14

Tall Shrub - Alder 31,343 12

Low Shrub - Willow 17,604 7

Tall Shrub - Willow 17,520 7

Dwarf Shrub - Other 15,233 6

Tall Shrub - Other 9,498 3

Dwarf Shrub - Lichen 8,381 3

Snow 8,187 3

Tall Shrub - Alder/Willow 8,002 3

Sparse Vegetation 7,476 3

Low Shrub - Other 5,755 2

Dwarf Shrub - Lush 5,712 2

Mesic/Dry Forb 4,746 1

Mesic/Dry Grass Meadow 2,739 1

Cloud 2,593 1

Low Shrub - Alder 2,375 1

Dwarf Shrub - Wet 1,699 0

Low Shrub - Alder/Willow 1,535 0

Non-Vegetated Soil 1,394 0

Clear Water 987 0

Mesic/Dry Sedge Meadow 850 0

Wet Graminoid 770 0

Turbid/Shallow Water 606 0

Emergent 604 0

Wet Sedge 513 0

Ocean Water 260 0
15 

Table 4 (continued). 2008 landcover classes and coverage areas in ANIA (DU 2009).

Landcover Class Hectares % Landcover

Bryoid Moss/Dwarf Shrub - Lichen 150 0

Other Crypto-Biotic Soil 144 0

Mesic/Dry Graminoid 38 0

Floating Algea 14 0

Closed Poplar 6 0

Moss 4 0

Cloud Shadow 1 0

Wet Forb 0 0

Total Area 244,223 100

2.4.2. Dominant Landscape Processes 

Volcanic Activity

Hasselbach (1995) reports that vegetation communities in ANIA in general and specifically within 

the caldera have been affected by significant volcanic disturbances such as the 1931 eruption. 

Volcanic eruptions alter the previous landscape and vegetation by burying large areas with lava flows 

and ash fallout, providing the opportunity for successional processes.

Succession Patterns 

Landscape-changing events such as earthquakes, wild fires, and volcanic eruptions can create large 

areas of barren ground. These barren areas are common locations for vegetation succession to take 

place. The plant life that first establishes an area, along with the successors, is largely dependent on 

the previous flora of the area and the current conditions of the succession site (e.g., substrate type, 

steepness of slope, or abundance of nitrogen-fixing taxa) (Hasselbach 1995). Re-establishment of 

plant life is generally accelerated in sites affected by fires compared to those made barren from a 

volcanic eruption where the acidity level, ash coverings, and rocky terrain slow succession rates 

(Hasselbach 1995). Hasselbach (1995) describes the vegetative succession patterns in the caldera 

area of ANIA to be slow since the damage from the1931 eruption. 

2.5 Literature Cited

Alaska Department of Fish and Game (ADF&G). 2002. Alaska aquatic nuisance management plan. 

Alaska Department of Fish and Game, Juneau, Alaska.

Alaska Planning Group (APG). 1973. Aniakchak Caldera National Monument master plan. National 

Park Service, Washington, D.C. 

Bennett, A. J., W. L Thompson, and D. C. Mortenson. 2006. Vital Signs monitoring plan Southwest 

Alaska Network. National Park Service, Anchorage, Alaska 

Ducks Unlimited, Inc. (DU). 2009. Landcover ANIA 2008. Ducks Unlimited, Inc., Memphis, 

Tennessee. 
16 

Environmental Protection Agency (EPA). 2011. EPA region 10 (Pacific Northwest). 

http://www.epa.gov/aboutepa/region10.html (accessed 20 December 2011). 

Exxon Valdez Oil Spill Trustee Council (EVOS). 1994. The Exxon Valdez oil spill restoration plan. 

Exxon Valdez Oil Spill Trustee Council, Anchorage, Alaska 

Griffith, G. 2010. Level III North American terrestrial ecoregions: United States descriptions. North 

American Commission for Environmental Cooperation, Montreal, Quebec. 

Hall, D. K. 1988. Assessment of polar climate change using satellite technology. Reviews of 

Geophysics 26(1):26-39. 

Hasselbach, L. M. 1995. Vascular and nonvascular vegetation of Aniakchak Caldera, Alaska. Forest 

and Rangeland Ecosystem Science Center, Oregon State University, Corvallis, Oregon.

Lenz, J., T. Gotthardt, R. Lipkin, and M. Kelly. 2002. Compilation of existing species data in 

Alaska’s National Parks. University of Alaska, Anchorage, Alaska. 

Lipkin, R. 2005. Aniakchak National Monument and Preserve, vascular plant inventory, final 

technical report. NPS/AKR/SWAN/NRTR-2005/06. National Park Service, Southwest Alaska 

Network, Anchorage, Alaska. 

Manski, D., M. Schroeder, and K. Bosworth. 1987. Annotated bird list, Pacific Coast, Aniakchak

National Monument and Preserve, 17 August-3 September 1987. National Park Service, King 

Salmon, Alaska. 

Meyer, K. 1987. 1987 bird surveys of Aniakchak Caldera. National Park Service unpublished report, 

King Salmon, Alaska. 

Nagorski, S., G. Eckert, E. Hood, and S. Pyare. 2007. Assessment of coastal water resources and 

watershed conditions at Aniakchak National Monument and Preserve (Alaska). National 

Resource Technical Report NPS/NRWRD/NRTR-2007/371. National Park Service, Fort Collins, 

Colorado. 

National Park Service (NPS). 1986. Aniakchak National Monument and Preserve general 

management plan, land protection plan, wilderness suitability review. National Park Service, 

Denver Service Center, Denver, Colorado. 

National Park Service (NPS). 2003. Fauna monitoring – scoping meeting. National Park Service, 

Southwest Alaska Network Vital Signs Monitoring Program, Anchorage, Alaska. 

National Park System (NPS). 2008. Strategic plan for Katmai National Park and Preserve, Aniakchak 

National Monument and Preserve, and Alagnak Wild River. National Park Service, King Salmon, 

Alaska. 
17 

National Park Service (NPS). 2010a. Aniakchak National Monument and Preserve: monthly and 

annual visitation statistics. National Park Service Public Use Statistics Office Online. 

http://www.nature.nps.gov/stats/park.cfm (accessed 2 January 2012). 

National Park Service (NPS). 2010b. Aniakchak National Monument and Preserve: nature and 

science. http://www.nps.gov/ania/naturescience/index.htm (accessed 4 January 2012). 

National Park Service (NPS). 2010c. Aniakchak National Monument and Preserve: outdoor 

activities. http://www.nps.gov/ania/planyourvisit/outdooractivities.htm (accessed 2 January 

2012). 

National Park Service (NPS). 2013. NPSpecies online database. 

https://irma.nps.gov/App/Species/Search (accessed 16 September 2012). 

Savage, S. 1993. Annotated bird list, Aniakchak Caldera and surrounds, field season 1993. 

Aniakchak National Monument and Preserve, King Salmon, Alaska. 

Scenarios Network for Alaska Planning (SNAP), The Wilderness Society, and National Park Service 

(NPS). 2009. Projected climate change scenarios for Aniakchak National Monument and 

Preserve. University of Alaska, Fairbanks, Alaska. 

Serreze, M. C., J. E. Walsh, F. S. Chapin III, T. Osterkamp, M. Dyurgerov, V. Romanovsky, W. C. 

Oechel, J. Morison, T. Zhang, and R. G. Barry. 2000. Observational evidence of recent change in 

the northern high-latitude environment. Climate Change 46:159-207. 

Sowl, K. 1988. Investigations of the flora and fauna inside Aniakchak Caldera, June to September 

1988. Aniakchak National Monument and Preserve, King Salmon, Alaska. 

Starr, F., and P. Starr. 1988. Annotated bird observations, Aniakchak coast, June 17 – August 30, 

1988. Aniakchak National Monument and Preserve, King Salmon, Alaska. 

Stroud, G., and L. Fuller. 1983. End of season report, Aniakchak National Monument and Preserve, 

September 1983. National Park Service, King Salmon, Alaska. 

U.S. Census. 2010. 2010 Census data: Alaska state population. U.S. Census Data Online. 

http://2010.census.gov/2010census/data/ (accessed 2 January 2012). 

U.S. Geological Survey, Earth Resources Observation and Science Center (USGS EROS). 1989. 

Landcover – ANIA 1983 group. Raster digital data. USGS/EROS Alaska Field Office,

Anchorage, Alaska. 

 Western Regional Climate Center (WRCC). 2011. Port Heiden, Alaska: Period of record monthly 

climate summary. http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?ak7700 (accessed 2 January 

2012). 
18

Plate 1. Aniakchak Park Map (NPS).
19

Plate 2. Landcover classes and coverage area for ANIA in 1983. Landcover classes combined from original data for display purposes 

(USGS/EROS 1989).
20

Plate 3. Landcover classes and coverage area for ANIA in 2008. Landcover classes combined from original data for display purposes (DU 2009).
Chapter 3. Study Scoping and Design

This NRCA is a collaborative project between the NPS and Saint Mary’s University of Minnesota 

Geospatial Services (SMUMN GSS). Project stakeholders include the ANIA resource management 

team and SWAN staff. Before embarking on the project, it was necessary to identify the specific 

roles of the NPS and SMUMN GSS. Preliminary scoping meetings were held, and a task agreement 

and a scope of work document were created cooperatively between the NPS and SMUMN GSS.

3.1 Preliminary scoping

A preliminary scoping meeting was held during November 2011. At this meeting, SMUMN GSS and 

NPS staff confirmed that the purpose of the ANIA NRCA was to evaluate and report on current 

conditions, critical data and knowledge gaps, and selected existing and emerging resource condition 

influences of concern to park managers. Certain constraints were placed on this NRCA, including the 

following: 

• Condition assessments are conducted using existing data and information.

• Identification of data needs and gaps is driven by the project framework categories. 

• The analysis of natural resource conditions includes a strong geospatial component. 

• Resource focus and priorities are primarily driven by the park resource management.

This condition assessment provides a “snapshot-in-time” evaluation of the condition of a select set of 

park natural resources that were identified and agreed upon by the project team. Project findings will 

aid ANIA resource managers in the following objectives:

• Develop near-term management priorities (how to allocate limited staff and funding 

resources); 

• Engage in watershed or landscape scale partnership and education efforts; 

• Consider new park planning goals and take steps to further these;

• Report program performance (e.g., Department of Interior Strategic Plan “land health” goals, 

Government Performance and Results Act [GPRA]). 

Specific project expectations and outcomes included the following: 

• For key natural resource components, consolidate available data, reports, and spatial 

information from appropriate sources including: park resource staff, the NPS Integrated 

Resource Management Application (IRMA) website, Inventory and Monitoring Vital Signs, 

and available third-party sources. The NRCA report will provide a resource assessment and 

summary of pertinent data evaluated through this project. 

• When appropriate, define a reference condition so that statements of current condition may 

be developed. The statements will describe the current state of a particular resource with 

respect to an agreed upon reference point. 

• Clearly identify “management critical” data (i.e., those data relevant to the key resources).

This will drive the data mining and gap definition process.
22 

• Where applicable, develop GIS products that provide spatial representation of resource data, 

ecological processes, resource stressors, trends, or other valuable information that can be 

better interpreted visually. 

• Utilize “gray literature” and reports from third party research to the extent practicable.

3.2 Study Design

3.2.1 Indicator Framework, Focal Study Resources and Indicators

Selection of Resources and Measures 

As defined by SMUMN GSS in the NRCA process, a “framework” is developed for a park or 

preserve. This framework is a way of organizing, in a hierarchical fashion, bio-geophysical resource 

topics considered important in park management efforts. The primary features in the framework are 

key resource components, measures, stressors, and reference conditions. 

“Components” in this process are defined as natural resources (e.g., birds), ecological processes or 

patterns (e.g., natural fire regime), or specific natural features or values (e.g., geological formations) 

that are considered important to current park management. Each key resource component has one or 

more “measures” that best define the current condition of a component being assessed in the NRCA. 

Measures are defined as those values or characterizations that evaluate and quantify the state of 

ecological health or integrity of a component. In addition to measures, current condition of 

components may be influenced by certain “stressors,” which are also considered during assessment. 

A “stressor” is defined as any agent that imposes adverse changes upon a component. These typically 

refer to anthropogenic factors that adversely affect natural ecosystems, but may also include natural 

processes or disturbances such as floods, fires, or predation (adapted from GLEI 2010). 

During the NRCA scoping process, key resource components were identified by NPS staff and are 

represented as “components” in the NRCA framework. While this list of components is not a 

comprehensive list of all the resources in the park, it includes resources and processes that are unique 

to the park in some way, or are of greatest concern or highest management priority in ANIA. Several 

measures for each component, as well as known or potential stressors, were also identified in 

collaboration with NPS resource staff. 

Selection of Reference Conditions 

A “reference condition” is a benchmark to which current values of a given component’s measures 

can be compared to determine the condition of that component. A reference condition may be a 

historical condition (e.g., flood frequency prior to dam construction on a river), an established 

ecological threshold (e.g., EPA standards for air quality), or a targeted management goal/objective 

(e.g., a bison herd of at least 200 individuals) (adapted from Stoddard et al. 2006). 

Reference conditions in this project were identified during the scoping process using input from NPS 

resource staff. In some cases, reference conditions represent a historical reference before human 

activity and disturbance was a major driver of ecological populations and processes, such as "pre-fire 

suppression.” In other cases, peer-reviewed literature and ecological thresholds helped to define 

appropriate reference conditions. 
23 

Finalizing the Framework 

An initial framework was adapted from the organizational framework outlined by the H. John Heinz 

III Center for Science’s “State of Our Nation’s Ecosystems 2008” (Heinz Center 2008). This initial 

framework was presented to park resource staff to stimulate meaningful dialogue about key resources 

that should be assessed. Significant collaboration between SMUMN GSS analysts and NPS staff was 

needed to focus the scope of the NRCA project and finalize the framework of key resources to be 

assessed. 

The NRCA framework was finalized in May 2012 following acceptance from NPS resource staff. It 

contains a total of 13 components (Table 5) and was used to drive analysis in this NRCA. Two 

components (near shore sensitivity index, landcover/landscape processes) were subsequently 

removed from the framework and the concerns around these components were incorporated into 

Chapter 2 of this document. This framework outlines the components (resources), most appropriate 

measures, known or perceived stressors and threats to the resources, and the reference conditions for 

each component for comparison to current conditions. 
24

Table 5. ANIA natural resource condition assessment framework. 

 

 ANIA National Park – Scoping Meeting

Natural Resource Condition Assessment Framework

Componen

t Experts Data Sources

Measures or Specific 

Analysis Stressors Reference Condition

Biotic Composition 

Ecological Communities 

 

Landcover/Lan

dscape 

Processes 

(Chapter 2 

discussion) 

Parker Martin, 

Amy Miller

Two landcover datasets 

available in ThemeManager: 

Landcover - ANIA Group 

(1981 - ADNR); Landcover 

ANIA 2008 - early 2000s DU)

Discussion of the dominant 

landscape processes - successional 

patterns, fire, insect outbreak effects, 

permafrost change. References to 

invasives section for that information.

climate change (precipitation, 

temp, etc.)

Team agreed that this component does 

not lend itself to a condition 

graphic/scoring.

Mammals 

 Moose Sherri 

Anderson

Moose data being compiled 

by the park over the winter. 

ADF&G moose management 

report provides limited 

survey information.

Metrics defined in ADF&G moose 

summary documents: population 

density, bull:cow ratio

Brown bear predation on 

neonatal moose. 

Overbrowsing resulting in 

poor calf survival.

ADF&G defined management goals

 Bear Sherri 

Anderson

Bear data being compiled by 

the park over the winter. 

ADF&G bear management 

report indicates little data are 

available for GMU 9E

Population Density Identify during component 

development.

Need to define // all we will have is harvest 

records - this is not compiled

 Caribou

Troy Hamon, 

Dominic 

Watts

ADF&G Caribou Reports 

(complete herd and 

composition estimates for 

many years)

North Alaska Peninsula Herd size, 

Herd compostion

Identify during component 

development.

Troy and Dominic will work to define 

reference condition.

Birds 

 Passerines

Sherri 

Anderson, 

Susan 

Savage 

(USFWS)

A few dated literature 

sources provided by park 

staff, nothing recent.

Species abundance, Species 

richness and diversity

not clear what may actually 

be causing stress on birds 

overall, most are likely not 

from in-park issues

Team agreed that this component does 

not lend itself to a condition 

graphic/scoring.

Fish 

 Salmon Troy Hamon Salmon escapement data 

provided by Troy.

Escapement, Percent Harvest, Run 

Timing

harvest (which is already a 

measure). 

Talk with Troy about escapement data - 

aerial state surveys - a lot of data but not 

related to condition assessment.

 

Native Fish 

(nonanadromous)Troy Hamon

Data are limited to three 

documents: Meshik corridor 

survey, freshwater fish 

inventory of the caldera, FW 

fish inventory from I&M (use 

to establish baseline)

Specific Analysis: Compile existing 

data and information from the defined 

literature sources and provide to the 

park for future use and updating. 

Develop a concise summary of the 

information for Chapter 4 and provide 

a statement of condition according to 

conversations with Troy.

Identify during component 

development.

Team agreed that this component does 

not lend itself to a condition 

graphic/scoring. Once data are compiled, 

we might be able to infer condition from 

trends.
25

Table 5 (continued). ANIA natural resource condition assessment framework.

Component Experts Data Sources Measures or Specific Analysis Stressors Reference Condition

Environmental Quality

 Human Activity

Kyler Smith, 

Michael 

Shephard

most visitor use is 

reported by 

consessionares, as it is 

primarily guided hunting

Specific Analysis: Use available datasets to provide an 

overview of visitor use (distribution and primary activity) in 

the park with close attention to use during hunting 

seasons, as this is when most conflicts occur. Identify the 

areas most prone to user conflict based on findings 

(spatial and non-spatial). Explain the level of subsistence 

use in the park based on community survey data and park 

staff knowledge.

Identify during 

component 

development.

Due to the lack of visitation, 

human use is minimal. Need 

to determine how to frame 

this in respect to condition (if 

at all).

 Water Quality Claudette 

Moore

Claudette will provide 

data during midNovember.

Specific Analysis: Examine the available data and 

information and georeference that data when possible to 

enable future GIS data display and storage. If enough data 

exist for individual lakes or rivers, present these data and 

describe condition accordingly. Provide a brief synopsis of 

the SWAN temp profile data that are being collected 

currently.

diesel fuel spills, other 

sources? 

Team agreed that this 

component does not lend 

itself to a condition 

graphic/scoring

Physical Characteristics 

Seismic 

Activity

USGS and 

AVO - John 

Paskievitch 

Alaska Volcano 

Observatory Data

Specific Analysis: Provide a summary of the recorded 

seismic history of the park, both background levels of 

activity and major events.

consult Paskievitch

Team agreed that this 

component does not lend 

itself to a condition 

graphic/scoring

Climate Chuck 

Lindsey PRISM Data Summarize PRISM and other available data. human activity

Team agreed that this 

component does not lend 

itself to a condition 

graphic/scoring

 Glacier Extent 

Bruce Giffen, 

Chuck 

Lindsey

Identify with component 

experts

Extent, terminus retreat, volumetric estimates (mass 

balance)

Identify during 

component 

development.

Rely on Bruce for developing 

this component - minimal 

data.
26 

3.2.2 General Approach and Methods

This study involved gathering and reviewing existing literature and data relevant to each of the key 

resource components included in the framework. No new data were collected for this study; however, 

where appropriate, existing data were further analyzed to provide summaries of resource condition or 

to create new spatial representations. After all data and literature relevant to the measures of each 

component were reviewed and considered, a qualitative statement of overall current condition was 

created and compared to the reference condition when possible.

Data Mining

The data mining process (acquiring as much relevant data about key resources as possible) began at 

the initial scoping meeting, at which time ANIA staff provided data and literature in multiple forms, 

including: NPS reports and monitoring plans, reports from various state and federal agencies, 

published and unpublished research documents, databases, tabular data, and charts. GIS data were 

provided by NPS staff. Additional data and literature were also acquired through online bibliographic 

literature searches and inquiries on various state and federal government websites. Data and literature 

acquired throughout the data mining process were inventoried and analyzed for thoroughness, 

relevancy, and quality regarding the resource components identified at the scoping meeting. 

Data Development and Analysis

Data development and analysis was highly specific to each component in the framework and 

depended largely on the amount of information and data available for the component and 

recommendations from NPS reviewers and sources of expertise including NPS staff from ANIA and 

the SWAN. Specific approaches to data development and analysis can be found within the respective 

component assessment sections located in Chapter 4 of this report. 

Preparation and Review of Component Draft Assessments

The preparation of draft assessments for each component was a highly cooperative process among 

SMUMN GSS analysts and park staff. Though SMUMN GSS analysts rely heavily on peer-reviewed

literature and existing data in conducting the assessment, the expertise of NPS resource staff also 

plays a significant and invaluable role in providing insights into the appropriate direction for analysis 

and assessment of each component. This step is especially important when data or literature are 

limited for a resource component. 

The process of developing draft documents for each component began with a detailed phone or 

conference call with an individual or multiple individuals considered local experts on the resource 

components under examination. These conversations were a way for analysts to verify the most 

relevant data and literature sources that should be used and also to formulate ideas about current 

condition with respect to the NPS staff opinions. Upon completion, draft assessments were forwarded 

to component experts for initial review and comments. 

Development and Review of Final Component Assessments 

Following review of the component draft assessments, analysts used the review feedback from 

resource experts to compile the final component assessments. As a result of this process, and based 

on the recommendations and insights provided by park resource staff and other experts, the final 
27 

component assessments represent, the most relevant and current data available for each component 

and the sentiments of park resource staff and resource experts. 

Format of Component Assessment Documents 

All resource component assessments are presented in a standard format. The format and structure of 

these assessments is described below.

Description

This section describes the relevance of the resource component to the park and the context within 

which it occurs in the park setting. For example, a component may represent a unique feature of the 

park, it may be a key process or resource in park ecology, or it may be a resource that is of high 

management priority in the park. Also emphasized are interrelationships that occur among a given 

component and other resource components included in the broader assessment. 

Measures 

Resource component measures were defined in the scoping process and refined through dialogue 

with resource experts. Those measures deemed most appropriate for assessing the current condition 

of a component are listed in this section, typically as bulleted items.

Reference Conditions/Values

This section explains the reference condition determined for each resource component as it is defined 

in the framework. Explanation is provided as to why specific reference conditions are appropriate or 

logical to use. Also included in this section is a discussion of any available data and literature that 

explain and elaborate on the designated reference conditions. If these conditions or values originated 

with the NPS experts or SMUMN GSS analysts, an explanation of how they were developed is 

provided. 

Data and Methods 

This section includes a discussion of the data sets used to evaluate the component and if or how these 

data sets were adjusted or processed as a lead-up to analysis. If adjustment or processing of data 

involved an extensive or highly technical process, these descriptions are included in an appendix for 

the reader or a GIS metadata file. Also discussed is how the data were evaluated and analyzed to 

determine current condition (and trend when appropriate). 

Current Condition and Trend 

This section presents and discusses in-depth key findings regarding the current condition of the 

resource component and trends (when available). The information is presented primarily with text 

but is often accompanied by detailed maps or plates that display different analyses, as well as graphs, 

charts, and/or tables that summarize relevant data or show interesting relationships. All relevant data 

and information for a component is presented and interpreted in this section. 

Threats and Stressor Factors 

This section provides a summary of the threats and stressors that may impact the resource and 

influence to varying degrees the current condition of a resource component. Relevant stressors were 

described in the scoping process and are outlined in the NRCA framework. However, these are 
28 

elaborated on in this section to create a summary of threats and stressor based on a combination of 

available data and literature, and discussions with resource experts and NPS natural resources staff. 

Data Needs/Gaps 

This section outlines critical data needs or gaps for the resource component. Specifically, what is 

discussed is how these data needs/gaps, if addressed, would provide further insight in determining 

the current condition or trend of a given component in future assessments. In some cases, the data 

needs/gaps are significant enough to make it inappropriate or impossible to determine condition of 

the resource component. In these cases, stating the data needs/gaps is useful to natural resources staff 

who wishes to prioritize monitoring or data gathering efforts. 

Overall Condition 

This section provides a qualitative summary statement of the current condition that was determined 

for the resource component using the WCS method. Condition is determined after thoughtful review 

of available literature, data, and any insights from NPS staff and experts, which are presented in the 

Current Condition and Trend section. The Overall Condition section summarizes the key findings 

and highlights the key elements used in determining and justifying the level of concern, if any, that 

analysts attribute to the condition of the resource component. Also included in this section are the 

graphics used to represent the component condition. 

Sources of Expertise

This is a listing of the individuals (including their title and affiliation with offices or programs) who 

had a primary role in providing expertise, insight, and interpretation to determine current condition 

(and trend when appropriate) for each resource component. 

Literature Cited

This is a list of formal citations for literature or datasets used in the analysis and assessment of 

condition for the resource component. Note, citations used in appendices and plates referenced in 

each section (component) of Chapter 4 are listed in that section’s “Literature Cited” section.

3.3 Literature Cited

Great Lakes Environmental Indicators Project (GLEI). 2010. Glossary, Stressor. 

http://glei.nrri.umn.edu/default/glossary.htm (accessed 16 March 2015). 

The H. John Heinz III Center for Science, Economics, and the Environment. 2008. The state of the 

nation’s ecosystems 2008: Measuring the land, waters, and living resources of the United States. 

Island Press, Washington, D.C.

Stoddard. J. L., D. P. Larsen, C. P. Hawkins, R. K. Johnson, and R. J. Norris. 2006. Setting 

expectations for the ecological condition of streams: the concept of reference condition. 

Ecological Applications 16(4):1267-127
29 

Chapter 4 Natural Resource Conditions 

This chapter presents the background, analysis, and condition summaries for the 11 key resource 

components in the project framework. The following sections discuss the key resources and their 

measures, stressors, and reference conditions. The summary for each component is arranged around 

the following sections: 

1. Description 

2. Measures 

3. Reference Condition 

4. Data and Methods 

5. Current Condition and Trend (including threats and stressor factors, data needs/gaps, and overall 

condition) 

6. Sources of Expertise 

7. Literature Cited

The order of components is as follows: 

4.1 Moose

4.2 Bear 

4.3 Caribou 

4.4 Passerines 

4.5 Salmon 

4.6 Native Fish 

4.7 Seismic Activity

4.8 Climate 

4.9 Human Activity 

4.10 Glacial Extent 

4.11 Water Quality 
30 

4.1 Moose

4.1.1 Description

Moose (Alces alces) (Photo 5) are ubiquitous in 

the ANIA biotic community, present 

throughout the inland, river and lake riparian 

zones, and coastal areas of the park (NPS 

2003). Moose are normally associated with 

northern forests and subarctic climates typical 

of southwestern Alaska. They are solitary 

mammals that rarely gather in groups except 

during the mating season. Females weigh in 

excess of 363 kg (800 lbs), while males can 

weigh up to 725 kg (1,600 lbs) and exceed 1.83 

m (6 ft) in height (Rausch et al. 2008). Antlers 

develop on males within the first year of life and generally grow larger each subsequent summer until 

the animal health decreases with the onset of old age. Antlers typically develop in three to five 

months beginning in the spring, and are shed after the mating season. The average moose life span is 

16 years, although 25-year-old individuals have been reported (Rausch et al. 2008). 

Moose are herbivorous, feeding primarily on willow (Salix spp.), aspen (Populus spp.), aquatic 

vegetation, and a variety of grasses (Rausch et al. 2008). Moose are most often associated with open 

low or mixed shrub vegetation classifications near riparian zones. Sexual maturity and breeding 

occur at about 28 months. Calves are born in the spring, with females typically producing one or two

calves per year. During the mating season, sparring between bulls occurs in order to secure mates; 

injuries are common but rarely serious. Adult moose are generally calm and subdued, although 

aggressive behavior is frequently displayed by cows with calves when they become startled, angered, 

or when offspring are threatened, as well as by bulls during the breeding period (Rausch et al. 2008). 

Natural predators in ANIA include wolves and brown bears. Predation on yearlings or adults 

weakened by disease or injury is most common (Butler 2010). Moose populations are protected from 

sport hunting within the 55,432-ha (137,000-ac) Aniakchak National Monument (ANM). However, 

subsistence hunting is legal within ANM but is considered to be quite rare. Limited sport hunting is 

permitted in the Aniakchak National Preserve (ANP), which comprises 188,179 ha (465,000 ac). 

Concession contracts are issued for sport hunting services within ANIA to manage wildlife 

populations and protect subsistence uses (NPS 2003). Game Management Units (GMUs) were 

established to give residents and visitors fair and equal hunting rights throughout the state of Alaska. 

The Alaska Department of Fish and Game (ADF&G) tracks parameters such as population density, 

population composition, habitat, and harvest for selected species in each GMU. ADF&G establishes 

individualized management objectives for moose in each GMU and in many cases for each subunit. 

ANIA is located within GMU 9, which covers the entire southwestern Alaskan Peninsula. GMU 9 

has multiple subunits; ANIA is in GMU 9E (Plate 4).

Photo 5. Cow moose grazing with two calves 

(USFWS photo by K. O’Reilly Doyle).
31

4.1.2 Measures

• Population size

• Population composition (bull:cow ratio)

4.1.3 Reference Conditions/Values

According to the NPS’s enabling legislation, ANIA, like all other NPS managed lands, is to manage 

animal species in a manner consistent with maintaining a natural and healthy population. NPS 

policies that support the naturally occurring and healthy population are found in sections 4.4.1 and 

4.4.3 of the NPS Management Policies (2006) which state that;

The NPS will maintain as parts of the natural ecosystem of parks all plants and animals 

native to park ecosystems...

...preserving and restoring the natural abundances, diversities, dynamics, distributions, 

habitats, and behaviors of native plant and animal populations and the communities and 

ecosystems in which they occur...

...minimizing human impacts on native plants, animals, populations, communities, and 

ecosystems, and the processes that sustain them.

...the Service (NPS) does not engage in activities to reduce the numbers of native species for 

the purposes of increasing the numbers of harvested species (i.e., predator control), nor does 

the Service permit others to do so on lands managed by the National Park Service

Management of the moose population in ANIA is intended to be implemented through the 

cooperative efforts of the NPS and the ADF&G . However, when the species in question is a 

harvested or game species, it should be noted that the NPS management policies may not be 

congruent with local or state wildlife management policies due to differing management objectives.

Currently, quantitative moose population metrics have not been established by the NPS that would 

define a set of moose population reference conditions (i.e., ranges of natural variability that embody 

natural and healthy populations). In lieu of NPS established moose population reference conditions, 

the following section reports population metrics according to ADF&G defined management goals. 

While the ADF&G defined management goals are discussed below, it is important to recognize that 

the NPS goals may differ and that management objectives of the ADF&G do not necessarily 

represent the management objectives of the NPS.

Two reference conditions were outlined in the ADF&G moose management report for GMU 9 

(Butler 2006). The reference condition used in this assessment is the ADF&G-determined population 

goal for each GMU. The first reference condition, population size, is the maintenance of existing 

moose densities in areas where the current population density is considered moderate (0.5-1.5 

moose/mi2 or 0.19-0.58 moose/km2

), assuming non-limiting habitat conditions (Butler 2010). The

second reference condition, population composition (bull: cow ratio), is the maintenance of sex ratios 

of at least 25 bulls:100 cows in areas where the current population is density is considered moderate 

(0.5-1.5 moose/mi2 or 0.19-0.58 moose/km2

) (Butler 2010). GMU 9E, which includes ANIA, had a 
32

1983 survey result of 1,148 moose within a 1,314 mi2 (3,403 km2

) study area and would be a 

moderate density moose population (Butler 2010).

4.1.4 Data and Methods

ADF&G management reports (Butler 2006, 2008, 2010) provide information on defined management 

goals. ADF&G conducts annual sex and age composition surveys from November through early 

December, assuming adequate snow cover, for all GMU 9 subunits (Butler 2010). Harvest rates and 

other sources of mortality are also reported (Butler 2010). ADF&G reports establish moose 

population and composition objectives, as well as monitor temporal trends in population size and 

composition.

ADF&G surveys of moose within ANIA recorded population, density, and composition information 

from trend areas surveyed by airplane transects along the trend area boundaries (Plate 5). ADF&G 

trend areas for ANIA are outlined as the Meshik and Cinder River Valleys, and the head of Amber 

Bay. Trend areas around the Cinder River in northern ANIA and coastal habitat of southeast ANIA 

are classified as moderate- to high-quality moose wintering habitat. A new trend area in the 

southwest preserve has been surveyed once and is defined as another ANIA wintering habitat area.

Observations and counts were documented and geographic locations recorded using GPS units (NPS 

2003).

4.1.5 Current Condition and Trend

Population Size

In the absence of quantitative moose population metrics from the NPS the following section reports 

population metrics according to ADF&G defined management goals. While the ADF&G defined 

management goals are discussed below, it is important to recognize that the NPS goals may differ 

and that management objectives of the ADF&G do not necessarily represent the management 

objectives of the NPS.

Butler (2006) noted that moose were present but scarce on the Alaskan Peninsula prior to 1900 and 

spread throughout the southwest in the 1950s and 1960s. Cahalane (1956) noted that Alaska moose

were numerous in the area throughout the early 1950s with populations peaking in the late 1960s 

(Butler 2010). Implementation of liberal hunting regulations resulted in slowed moose population 

growth and recovery of willow stands that were depleted from over browsing. The population then 

declined, most notably in unit 9E even after 1973 when hunting restrictions were enforced. Despite 

improved range conditions, moose densities in the early 1980s were 60% below peak levels observed 

in the 1960s (Butler 2010). Unit 9E was considered in 1999 to be “important for providing high 

levels of human consumptive use” by the Alaska Board of Game (Butler 2010, p. 116). Currently, 

moose population densities in Unit 9E are generally considered moderate (0.8-0.9 moose/mi2 or 0.31-

0.35 moose/km2

) (Butler 2010).

The 2005 ADF&G fall sex and age composition survey of ANIA moose indicated slight declines for 

Unit 9E. However, Butler (2008, 2010) reported that, overall, Unit 9 moose populations (a much 

larger area) were relatively stable over the past 30 years. In 1983, ADF&G conducted a survey 

resulting in a rough estimate of 2,500 moose in unit 9E, according to data extrapolated from a 2114 
33 

km2

 (1,314 mi2) survey of the center portion of Unit 9E. That survey identified 1,148 moose (90% 

CI ± 16%) (Butler 2010). Unit 9 moose surveys are frequently limited by poor weather conditions 

and inadequate snowfall. 

Population Composition (bull:cow ratio) 

In the absence of quantitative moose population metrics from the NPS the following section reports 

population metrics according to ADF&G defined management goals. While the ADF&G defined 

management goals are discussed below, it is important to recognize that the NPS goals may differ 

and that management objectives of the ADF&G do not necessarily represent the management 

objectives of the NPS. It is noted that in 2008, Young and Bortell reported that in lightly hunted and 

remote areas of Alaska 60-80 bulls: 100 cows were observed. 

Historically, bull:cow ratios varied across unit 9 (Butler 2010). A recent survey of unit 9E was not 

sufficient to define population composition at the subunit scale. However, bull:cow ratios are 

generally above the 25:100 ratio set as a management goal by ADF&G in unit 9E. Past ADF&G 

surveys from 1999, 2002, 2003, and 2005 confirm a bull:cow ratio well above the standard of 25:100 

for most years (Table 6). The 2005 survey represents the only year that bull:cow ratios were not well 

above ADF&G parameters. Since 2000, unit 9 has shown stable bull:cow ratios, and a ratio in 2010 

well above the established 25:100 parameter (Butler 2010). Considering historic variation and small 

sample size, the population of unit 9E appears stable and the bull:cow ratio is not being affected by 

harvest (Butler 2010). 

Table 6. Moose population composition in Unit 9E, 1999, 2002-2005. Table compiled from ADF&G report

(Butler 2010).

Year

Males:100 

females

Yearling 

males:100 

females Calves:100 females Calf % Adults

Total 

Moose Moose/hour

19992 60 10.77 3 1.89 104 106 27

20021 74 27 20 11 87 97 47

20031 46 10 10 6 131 140 18

2004 * * * * * * *

20051 25 5 22 15 81 95 19

* Not surveyed due to weather factors 

1 Includes some data from the U.S Fish and Wildlife Service

2 Survey in 1999 conducted in Aniakchak 

Threats and Stressor Factors 

Stressors identified by NPS staff include moose harvest rates and brown bear predation on neonatal 

moose. From the mid-1960s to early 1970s, relaxed hunting regulations led to slowed population 

growth and decreased populations in order to rehabilitate willow stands within Unit 9 (Butler 2006, 

2010). Moose population declines in the 1970s were attributed to low calf recruitment rates, liberal 

hunting regulations, and range damage (Butler 2006, 2008, 2010). Reported/unreported moose 

harvest in GMU 9 has been estimated at 200-280 moose per year since 2000 (Table 7). Even 
34 

considering unreported harvest, unit 9 remains within sustainable harvest limits established by the 

ADF&G (Butler 2010). Butler (2010) suggested that moose harvested within Unit 9 are often not 

reported by hunters. Closed season hunting and cow moose harvest likely represent a significant 

percentage of the unreported harvest. Butler (2010) suggests that illegal harvest will only cease with 

increased community support and law enforcement efforts, which may not be cost-effective. 

Reported annual moose harvest rates declined between 1998 and 2008 (Table 7). 

Table 7. Annual moose harvest in Unit 9, 1998-2008. An additional 100 moose are estimated as 

harvested but unreported annually. Table compiled from Butler (2006, 2010).

Year Male Female Unknown Reported Total Estimated Total

1998 198 2 0 200 300

1999 238 8 7 253 353

2000 176 2 2 180 280

2001 167 8 0 175 275

2002 171 6 2 179 279

2003 177 0 0 177 277

2004 158 3 0 161 261

2005 158 0 2 160 260

2006 124 1 0 125 225

2007 147 0 0 147 247

2008 107 0 0 107 207

Butler (2006, 2010) suggested that recent declines in harvest rates are associated with a decrease in 

the number of hunters rather than changes in the moose population. Unit 9E moose are hunted from 

10-20 September by non-resident hunters. A bag limit of one bull with three brow tines on one antler 

side or a 50-in (127-cm) minimum spread is permitted. Resident and subsistence hunting is permitted 

in Unit 9E for 81 days from 20 August to 20 September and 1 December to 30 January. Resident 

hunters must follow the bull take restrictions of non-resident hunters but are also permitted to take a 

spike or fork bull. Subsistence hunters are allowed any antlered bull with no antler restrictions. Cow 

harvest is prohibited in unit 9E. An estimated 100 unreported moose, many of which are assumed to 

be cows, are harvested each year in Unit 9 (Butler 2010). However, Butler (2010) noted that while 

current illegal practices likely do not greatly influence overall moose populations in Unit 9, illegal 

harvest of cows may play some role in limiting moose densities (Butler 2006). Concession hunts are 

also permitted in ANIA, although the harvest of 58 bulls from 2005-2011 is likely not a stress on the 

population (Table 8). 

Table 8. Concession harvest of moose in ANIA from 2005 to 2010 (Sherri Anderson, KATM Wildlife 

Biologist, pers. comm., 2012). 

Moose Harvest 2005 2006 2007 2008 2009 2010 2011 Total Harvest

Total for Year 6 8 13 7 10 6 8 58
35 

The primary limiting factor of moose populations in Unit 9 was brown bear predation on neonatal 

moose (Butler 2006, 2010). Predation on calves caused moose density in Unit 9 to decline, even after 

range conditions improved from relieved browsing pressure in the 1950s and 1960s (Sellers 1990). 

Neonatal and young of the year moose are exceptionally vulnerable to predators such as bears and 

wolves, particularly in late winter months when snow hinders a moose’s movements. Ballard et al. 

(1981) found that moose predation by brown bears accounted for 79% of mortalities of collared 

moose calves. Butler (2010) stated that while conditions have improved since the 1960s and 1970s, 

recruitment remains low in Unit 9. According to Butler (2010, p. 119), “bear:moose ratios in Unit 9 

ranged from >1:1 to 1:10,” and in order to achieve significant improvements in calf survival, major 

reductions in bear densities need to occur. However, this suggestion would run contrary to NPS 

management policy and, as the authors suggest, this would likely be opposed by the general public. 

Extremely low calf:cow ratios reported in the 2000s suggest that recruitment may be a further 

limiting factor of moose densities. Calf:cow ratios were low in GMU 9 even during years of peak 

population (Butler 2006). 

Data Needs/Gaps

The 2012 ADF&G moose management report is not yet available. Therefore, the most current 

available information from older ADF&G reports was utilized for this assessment. Butler (2008, 

2010) and Anderson (pers. comm., 2012) noted that inadequate snow cover, aircraft availability, and 

poor weather conditions often limit moose population composition surveys in Unit 9, which results in 

infrequent or incomplete surveys. Moose movements also add variability to population estimates and 

survey results (Butler 2008, 2010). Butler (2010) noted that sampling variation was introduced into 

surveys in 2007 and 2008 due to changes in technique. This likely introduced slight variability into 

the bull:cow ratio estimate. 

Moose surveys have not been conducted in ANIA within the past 13 years (NPS 2012). Sherri 

Anderson (pers. comm., 2012), KATM wildlife biologist, noted that ANIA often cannot be surveyed 

because of its limited accessibility and frequent poor weather conditions. Future surveys for these 

locales may provide adequate data for comparison and trend analyses. However, Anderson (pers. 

comm., 2012) suggested that in order to have successful aerial surveys, weather and flying conditions 

need to be very good to excellent. Furthermore, snow depth and snow cover must also be at ideal 

conditions. Marginal conditions in the past, due to inadequate snow depth and lack of snow cover, 

likely resulted in underreported moose populations. 
36 

Overall Condition 

Population Size 

Limited quantitative data exist that describe the moose population density within ANIA. Therefore, 

an accurate statement regarding condition cannot be made. However, Butler (2010) indicates that the 

population density is generally within the ADF&G management goal. Furthermore, the remoteness 

of the park limits susceptibility to threats and stressors related to human activities.

Population Composition (bull:cow ratio) 

Moose density and composition monitoring in Unit 9E suggest that the bull:cow ratio was above the 

desired range in recent years (25 bulls:100 cows). Moose population composition in unit 9E has 

remained relatively stable, with slight variations between years. ANIA bull:cow ratio is estimated to 

be within defined parameters. However, ANIA preserve and monument moose surveys should be 

conducted to more accurately define moose composition within ANIA park boundaries.

Summary 

Reports indicate that moose populations are stable in ANIA and Unit 9E, although they may be 

trending slightly downward based on recent NPS and ADF&G population reports (Butler 2006, 2008, 

2010; NPS 2012). Moose population composition (bull:cow ratio) has been consistently above the 

recommended level of 25 bulls:100 cows established by the ADF&G, with slight seasonal and annual 

variability (Butler 2006, 2008, 2010; NPS 2012). Even though human activity is low in ANIA, 

moose hunting is a primary reason for visitor use in the park. Without current data regarding moose 

densities within ANIA and the impact that recreational and subsistence hunting has on moose in 

ANIA, a conclusive statement assessing condition cannot be made. 

4.1.6 Sources of Expertise

Sherri Anderson, KATM Wildlife Biologist 

4.1.7 Literature Cited

Ballard, W. B., T. H. Spraker, and K. P. Taylor. 1981. Causes of neonatal moose calf mortality in 

south central Alaska. Journal of Wildlife Management 45(2):335-342. 

Butler, L. G. 2006. Unit 9 moose management report. Pages 107-115 in P. Harper, editor. Moose 

management report of survey and inventory activities 1 July 2003 – 30 June 2005. Project 1.0. 

Alaska Department of Fish and Game, Juneau, Alaska. 

Butler, L. G. 2008. Unit 9 moose management report. Pages 116-124 in P. Harper, editor. Moose 

management report of survey and inventory activities 1 July 2005 – 30 June 2007. Project 1.0. 

Alaska Department of Fish and Game, Juneau, Alaska. 

Butler, L. G. 2010. Unit 9 moose management report. Pages 116-123 in P. Harper, editor. Moose 

management report of survey and inventory activities 1 July 2007 – 30 June 2009. Project 1.0. 

Alaska Department of Fish and Game, Juneau, Alaska. 

Cahalane, V. H. 1956. Katmai – America’s largest nature reserve. Oryx 3:172-179. 
37 

National Park Service (NPS). 2003. Fauna monitoring – Scoping meeting Vital Signs monitoring 

program Southwest Alaska Network 17 April, 2003. National Park Service, Southwest Alaska 

Network, Anchorage, Alaska. 

National Park Service (NPS). 2012. Moose population survey data. Microsoft Excel spreadsheets. 

Received 22 May 2012 from Sherri Anderson, KATM. 

Rausch, R. A., B. Gasaway, and C. Schwartz. 2008. Moose. Revised by J. Crouse and S. Crouse. 

http://www.adfg.alaska.gov/static/education/wns/moose.pdf (accessed 25 June 2012).

Sellers, R. A. 1990. Annual report of survey-inventory activities - moose. Federal Aid in Wildlife 

Restoration Program Report W-23-2, Study 3.0. Alaska Department of Fish and Game, Juneau, 

Alaska.

Young, D. D., and R. D. Boertje. 2008. Recovery of low bull:cow ratios of moose in interior Alaska. 

Alces, Volume 44:65-71 (2008).
38

Plate 4. Alaska GMUs and subunits. Subunit 9E contains all of the Aniakchak National Monument and Preserve.
39

Plate 5. Trend area survey boundaries. 
40 

4.2 Bear

4.2.1 Description 

Brown bears (Ursus arctos) are a prominent 

mammal species in ANIA (Photo 6). The 

species is found in ANIA and the surrounding 

area, with larger concentrations in coastal and 

lake ecosystems. Brown bears utilize ANIA 

resources year-round but the population 

gravitates towards rivers and lakes with 

available salmon (Sowl 1988). 

Alaskan Peninsula brown bear males average 

357 kg (787 lbs) and females average 226 kg 

(498 lbs) (Miller and Sellers 1992). Brown 

bears primarily feed on salmon from July 

through September; sedges, berries, and clams 

comprise some of their diet in spring/early summer. ANIA brown bears will also consume caribou

and moose; juveniles of both species are predominantly targeted (Eide and Miller 2008). 

NPS (2003) reports that brown bears den in ANIA on caldera slopes and on the east side of the 

Aleutian Range. Typically all bears have entered dens by December and most emerge by early May; 

moderate weather in ANIA facilitates later den entrance and earlier emergence than is typical for its 

latitude (NPS 2003). Mating generally occurs from May to mid-July, and one to four cubs are 

typically born in the mid-winter months. Litter intervals for sows are usually three years, and cubs 

remain with their mother for their first two years (Eide and Miller 2008). 

Brown bear populations are protected from sport hunting within the 55,432-ha (137,000-ac) ANM. 

However, subsistence hunting is legal within ANM. Sport hunting is permitted in the ANP, which 

comprises 188,179 ha (465,000 ac). Sport hunting is permitted in the spring during even-numbered 

years, and the fall during odd-numbered years. Alternating seasons established in the 1980s were 

implemented to stimulate population recovery. Fall brown bear harvest is generally greater than 

spring harvest; alternating seasons lowers bear harvest, stimulating population growth (Loveless et 

al. in review). 

4.2.2 Measures

• Population density 

4.2.3 Reference Conditions/Values

A reference condition for brown bear in ANIA does not exist. Unlike nearby Katmai National Park 

and Preserve (KATM), where the park’s enabling legislation allows for interpretation of a reference 

condition, the enabling legislation of ANIA does not provide enough information to define a 

quantitative reference condition. In addition, the lack of survey data limits the ability to define 

current condition quantitatively and to derive reference conditions. 

Photo 6. An Alaskan brown bear sow with three 

cubs (NPS photo).
41 

4.2.4 Data and Methods

Butler (2009) is the primary source of information for this component. Butler (2009) provided data 

from surveys at Black Lake, approximately 50 km (30 mi) southwest of ANIA, for the years 1990-

2002. In addition, Butler (2009) provides accounts of population density and harvest for all of GMU 

9E, which encompasses ANIA. 

4.2.5 Current Condition and Trend

Population Density 

Quantitative data on the density of brown bears within ANIA do not exist. Overall, little is known 

about the density of brown bear in GMU 9E (Plate 6). Butler (2009) provides survey data for the 

Black Lake area of GMU 9E from 1990-2002. Individual surveys at Black Lake from 1999-2002 

indicated that the population at Black Lake is stable (Butler 2009). Habitat similar to Black Lake is 

found in ANIA, with Aniakchak River and Surprise Lake supporting salmon runs and those runs 

coinciding with observations of brown bear at Surprise Lake (Sowl 1988). 

Threats and Stressor Factors 

The Alaska National Interest Lands Conservation Act (ANILCA) enables brown bear subsistence 

hunting opportunities in the preserve and monument portion of ANIA; sport hunting is permitted 

only in the preserve portion. Proposals have been submitted to the Board of Game requesting that 

units 9C and 9E increase brown bear harvest (Butler 2009). Local residents cite the Northern Alaska 

Peninsula caribou herd (NAPCH) decline, a decline caused by brown bear predation of neonatal and 

young of the year caribou according to caribou mortality studies, as the major reason to increase 

brown bear harvest (Butler 2009). In ANIA, concession contracts are issued for three different guide 

areas which have resulted in 94 brown bear harvested from 2005 to 2010 (NPS 2003, Anderson, pers. 

comm., 2012 ) (Table 9). 

Table 9. Concession harvest of brown bears in ANIA from 2005 to 2010 (Anderson, pers. comm., 2012).

Brown Bear Harvest 2005 2006 2007 2008 2009 2010 2011 Total Harvest

Male 12 14 8 12 9 5 10 70

Female 3 3 3 2 7 2 4 24

Total for Year 15 17 11 14 16 7 14 94

Data Needs/Gaps

Research to assess the brown bear population in ANIA has never been conducted. Therefore, no data 

exist for population density or any other population parameters. 

Overall Condition 

Population Density 

Reference condition and quantitative data that enable explicit conclusions regarding condition do not 

exist for this component. Within GMU 9E, surveys at Black Lake in the late 1990s and early 2000s 

indicate stable populations, but the survey area is approximately 50 km (30 mi) from the park. Fuller 

(1983) and Sowl (1988) document that brown bear are present in ANIA year round, and that bears 
42 

congregate near Surprise Lake and other streams and lakes during the fall salmon run, similar to the 

Black Lake area. 

Summary 

ANIA brown bears reside year-round in a remote section of the Alaskan Peninsula rarely visited by 

humans. Therefore, a conjecture can be made that the stressors caused by human interaction affect 

ANIA brown bears less than other thriving brown bear populations in heavily visited Alaskan parks. 

However, a primary reason for visitor use of ANIA is for the sport and concession hunting of brown 

bears. Until more current brown bear population surveys are conducted and assessment of the impact 

that sport and concession hunting have on the brown bear population is completed, an accurate 

statement regarding the condition of brown bears in ANIA cannot be made. 

4.2.6 Sources of Expertise

Sherri Anderson, ANIA Wildlife Biologist 

Troy Hamon, KATM/ANIA Chief of Resources 

4.2.7 Literature Cited

Butler, L. B. 2009. Unit 9 brown bear management report. Pages 113-124 in P. Harper, editor. Brown 

bear management report of survey and inventory activities 1 July 2006-30 June 2008. Alaska 

Department of Fish and Game, Juneau, Alaska. 

Eide, S., and S. Miller. 2008. Brown bear. Revised by Larry Van Daele. 

http://www.adfg.alaska.gov/static/education/wns/brown_bear.pdf (accessed 25 June 2012). 

Fuller, L. 1983. Brown bear observations, Aniakchak National Monument and Preserve. Original 

notes 1-24. National Park Service Unpublished Report, Aniakchak National Monument and 

Preserve, Alaska. 

Loveless, K., T. Olson, and T. Hamon. In review. Population assessment of brown bears in Katmai 

National Preserve. Ursus. 

Miller, S. D., and R. A. Sellars. 1992. Brown bear density on the Alaska Peninsula at Black Lake, 

Alaska. Final report on completion of density estimation objectives of cooperative interagency 

brown bear studies on the Alaska Peninsula. Alaska Department of Fish and Game, Juneau, 

Alaska. 

National Park Service (NPS). 2003. Fauna monitoring – scoping meeting vital signs monitoring 

program, Southwest Alaska Network. National Park Service, Southwest Alaska Network, 

Anchorage, Alaska. 

Sowl, K. 1988. Investigations of the flora and fauna inside Aniakchak Caldera. National Park 

Service, Aniakchak National Monument and Preserve, Alaska. 
43

Plate 6. Alaska game management units and subunits. Subunit 9E contains all of the ANIA National Monument and Preserve. 
44 

4.3 Caribou

4.3.1 Description

Caribou (Rangifer tarandus; Photo 7) are a 

prominent mammal species in ANIA. An 

Alaskan adult bull caribou can weigh up to 318 

kg (700 lbs), but averages between 160-180 kg 

(350-400 lbs); adult cows weigh on average 80-

120 kg (175-225 lbs) (Rausch et al. 2008). 

Caribou bulls can grow massive antlers. Cows 

also grow antlers but they are much shorter and 

smaller. Antlers grow each spring and remain 

covered in velvet until late August when the 

antler hardens. Caribou are herbivores, eating 

willow leaves, sedges, flowering tundra plants 

and mushrooms in the summer (May-September) and then supplementing their diet with dried 

sedges, small shrubs, and lichens during the winter (Rausch et al. 2008). 

Cows in exceptional condition may breed at 16 months but generally reach sexual maturity at 28 

months of age (Rausch et al. 2008). The breeding season or rut starts in early September and peaks 

towards the end of the month. Fighting between bulls is common but generally brief; occasionally 

serious bouts unfold and result in injury or death. Cows give birth to a single calf (twins are rare) 

around early June. Shortly after calving, “post calving aggregations” form which provide protection 

from predators and insects. Caribou disperse in August to feed heavily before migrating. Caribou 

herds spend much of the year traveling between summer calving grounds and wintering areas. 

Migration is thought to be triggered by changing weather patterns, as caribou migrations generally 

precede cold fronts and snowstorms. Caribou often travel 80 km (50 mi) a day during peak migration 

times (Rausch et al. 2008).

ANIA caribou are part of the NAPCH, one of the 32 designated herds in Alaska. Herds may intermix 

at wintering grounds, but calving grounds are separate and historically remain in the same general 

area; wintering grounds and migration routes have been seen to change suddenly from historic 

locations to routes and areas with more food (Rausch et al. 2008). Mountainous areas and treeless 

tundra are preferred caribou habitat year-round, with preference to open coastal areas and mountains 

for calving areas and boreal forests as wintering grounds (Rausch et al. 2008). Traditional calving 

grounds of the NAPCH have been between the Bear River and Cinder River that runs through ANIA, 

and on the Bering Sea Flats. These traditional grounds have been used sparingly since 2004 and 

calving is now widely dispersed in mountainous terrain between the Meshik River and Katmai 

National Park. 

4.3.2 Measures

• North Alaska Peninsula Herd size 

Photo 7. Alaskan caribou bulls in early fall (NPS 

photo).
45 

• North Alaska Peninsula Herd composition 

4.3.3 Reference Conditions/Values

According to the NPS’s enabling legislation, ANIA, like all other NPS managed lands, is to manage 

animal species in a manner consistent with maintaining a natural and healthy population. NPS 

policies that support the naturally occurring and healthy population are found in sections 4.4.1 and 

4.4.3 of the NPS Management Policies (2006) which state that;

The NPS will maintain as parts of the natural ecosystem of parks all plants and animals 

native to park ecosystems...

...preserving and restoring the natural abundances, diversities, dynamics, distributions, 

habitats, and behaviors of native plant and animal populations and the communities and 

ecosystems in which they occur...

...minimizing human impacts on native plants, animals, populations, communities, and 

ecosystems, and the processes that sustain them.

...the Service (NPS) does not engage in activities to reduce the numbers of native species for 

the purposes of increasing the numbers of harvested species (i.e., predator control), nor does 

the Service permit others to do so on lands managed by the National Park Service

Management of the caribou population in ANIA is intended to be implemented through the 

cooperative efforts of the NPS and the ADF&G . However, when the species in question is a 

harvested or game species, it should be noted that the NPS management policies may not be 

congruent with local or state wildlife management policies due to differing management objectives.

Currently, quantitative caribou population metrics have not been established by the NPS that would 

define a set of caribou population reference conditions (i.e., ranges of natural variability that embody 

natural and healthy populations). In lieu of NPS established caribou population reference conditions, 

the following section reports population metrics according to ADF&G defined management goals. 

While the ADF&G defined management goals are discussed below, it is important to recognize that 

the NPS goals may differ and that management objectives of the ADF&G do not necessarily 

represent the management objectives of the NPS.

Two management goals were outlined in the ADF&G caribou management report for GMU 9C and 

9E (Plate 7). Management goals are set by the ADF&G for each Alaskan GMU and individual 

caribou herd. The management goal for population size of the NAPCH is set at 12,000-15,000 

caribou (Butler 2009). The management goal for the population composition is the maintenance of 

October sex ratios of at least 25 bulls:100 cows (Butler 2009). 

4.3.4 Data and Methods

ADF&G caribou management reports (Butler 2005, 2007, 2009) provide information on defined 

management goals. ADF&G conducts population size, age structure, and sex ratio surveys with the 

aid of radio telemetry, helicopters, and fixed winged aircraft for game management units 9C and 9E. 
46 

ADF&G reports also outline other sources of mortality, establish caribou population and composition 

objectives, and monitor temporal trends in population size and composition (Butler 2005, 2007, 

2009). 

ADF&G conducts aerial population surveys in late June over post-calving concentrations of caribou, 

and USFWS surveys the Aleutian Mountains and Pacific Coast. Establishment of bull:cow ratios; 

percentage of young, medium, and large bulls; and age composition surveys are done in October 

between the Naknek River and Port Moller (Butler 2009). Parturition surveys occur in early June on 

the calving grounds to establish pregnancy rates; cows equipped with radio collars are also surveyed 

at this time to determine age-specific pregnancy rates. The ADF&G and USFWS intend to establish 

and maintain 25-30 radio collars on caribou in the NAPCH and deploy satellite collars to track 

caribou migrations (Butler 2009). Wide angle 35-mm still photos were taken from aircraft over areas 

with large numbers of caribou and later counted to increase accuracy of population, calf:cow ratio, 

and sex ratio estimates (Butler 2005, 2007, 2009). 

4.3.5 Current Condition and Trend

North Alaska Peninsula Herd Size 

In the absence of quantitative caribou population metrics from the NPS the following section reports 

population metrics according to ADF&G defined management goals. While the ADF&G defined 

management goals are discussed below, it is important to recognize that the NPS goals may differ 

and that management objectives of the ADF&G do not necessarily represent the management 

objectives of the NPS. 

Butler (2009) notes that the NAPCH fluctuates in population size; peaks were reached at the turn of 

the century and in the early 1940s with the herd reaching 20,000 caribou. The NAPCH then 

plummeted to 2,000 caribou by the late 1940s, but again recovered to over 10,000 caribou in 1963 

(Skoog 1968). The first population survey aided by radio telemetry occurred in 1981 and estimated 

the NAPCH at 16,000. A survey in 1984 found the NAPCH had again risen to 20,000 caribou (Butler 

2009, Table 10). Traditional wintering grounds south of the Naknek River began to show depletion in 

lichen availability from over browsing, resulting in a decline of caribou use. Several members of the 

NAPCH began to cross the Naknek River, assumedly in search of sustainable overwintering habitat, 

settling between the Naknek River and Lake Iliamna. Butler (2009) found that this new wintering 

area contained excellent forage able to sustain the NAPCH at its 1986 ADF&G management goal of 

15,000 to 20,000 individuals. The NAPCH was managed at the lower end of the management goal 

(15,000) during the late 1980s, because an estimated 50,000 Mulchatna caribou began utilizing the 

same wintering grounds between Lake Iliamna and the Naknek River. This caused concern that 

winter forage in the area would be over browsed (Butler 2009). The NAPCH experienced a slow 

decline throughout the 1990s. The largest population decrease occurred between 1993 and 1994, 

when high natural mortality and a record harvest reduced the population size from 16,000 to 12,500 

animals (Butler 2007). The NAPCH again began wintering in traditional grounds south of the 

Naknek River, as only one radio-collared caribou has crossed the river since 2000. Efforts were made 

to reduce harvest rates with hunting restrictions implemented in 1994, but the NAPCH continued to 
47 

decline over the next several years. The most recent estimate in 2008 indicates that the herd consists 

of approximately 2,000 individuals (Butler 2009). 

The NAPCH continues to winter south of the Naknek River between Port Heiden and King Salmon, 

with very few animals observed to cross the Naknek (Troy Hamon, KATM/ANIA Chief of 

Resources, pers. comm., 2013). Traditional wintering grounds have not been re-established and no 

defined area for wintering exists within this geographic region. Caribou roam the region in winter, 

utilizing and congregating based on weather conditions and areas with quality forage during that year 

(Hamon, pers. comm., 2013). 
48

Table 10. Population size and composition of the NAPCH, 1984, 1990-2008 (reproduced from Butler 2009).

Year

Total bulls: 

100 cows

Calves: 100 

cows Calves % Cows%

Small 

bulls(% of 

bulls

Medium bulls 

(% of bulls)

Large 

bulls (% 

of bulls)

Total 

bulls 

(%)

Sample 

size

Estimate of 

herd size

1984 39 39 22 56 67 16 17 22 1,087 20,000

1990 41 29 17 59 * * * 24 1,484 17,000

1991 42 47 25 53 54 34 12 22 1,639 17,000

1992 40 44 24 54 44 38 19 22 2,766 17,500

1993 44 39 21 55 52 29 19 24 3,021 16,000

1994 34 34 20 59 58 28 14 20 1,857 12500

1995 41 24 15 60 49 29 22 25 2,907 12,000

1996 48 38 19 54 71 19 10 26 2,572 12,000

1997 47 27 16 57 54 31 14 27 1,064 10,000

1998 31 30 19 62 57 28 15 19 1,342 9,200

1999 40 21 13 62 58 30 12 25 2,567 8,600

2000 38 18 12 64 59 24 18 24 1,083 7,200

2001 49 28 16 57 61 24 15 28 2,392 6,300

2002 46 24 14 59 57 19 24 27 1,007 6,600

2003 36 11 8 68 46 30 24 24 2,776 *

2004 34 7 5 71 40 34 25 24 1,355 3,400

2005 23 7 6 77 37 41 22 18 1,914 * 

2006 26 14 10 72 26 43 31 18 1,725 *

2007 27 7 5 75 29 38 33 20 1,719 *

2008 19 10 8 77 33 25 43 15 1,841 2,000

* Data were not included in Butler (2009).
49 

North Alaska Peninsula Herd Composition 

In the absence of quantitative caribou population metrics from the NPS the following section reports 

population metrics according to ADF&G defined management goals. While the ADF&G defined 

management goals are discussed below, it is important to recognize that the NPS goals may differ 

and that management objectives of the ADF&G do not necessarily represent the management 

objectives of the NPS. 

The ADF&G management goal for the NAPCH composition is 25 bulls:100 cows. Butler (2009) 

states that this ratio is lower than several other Alaskan herds and should be switched to a bull: cow 

ratio of at least 35:100. The NAPCH maintained a bull:cow ratio of over 35:100 from 1990-2004 

when the average ratio was 41 bulls:100 cows. NAPCH bull:cow ratios fell below the ADF&G 

management goal from 2005-2008. Butler (2009) indicated that poor calf recruitment and the shorter 

lifespan of bulls compared to cows were primary causes for the decline of the ratio (Table 10). Butler 

(2009) suggests that managing towards a bull:cow ratio of 35:100 will be a more achievable goal 

now that the NAPCH is small (2,000 caribou). 

ADF&G fall estimates of cow:calf ratios provide insight into changes in population size and help 

explain trends in bull:cow ratios. During the NAPCH herds steady growth years, from 1970 to 1980, 

the calf:cow ratio was on average 50:100. When the population size was stable from 1981-1994, 

calf:cow ratios averaged 39:100. While the herd declined from 1995 to 2002, the average ratio was 

26 calves:100 cows (Butler 2009). Since 2003, yearly calf:cow ratios average 9:100; this ratio is a 

record low for the NAPCH herd according to available data (Butler 2009). 

Threats and Stressor Factors 

The population size of the NAPCH has been steadily decreasing since 1984, with nutritional stress 

and habitat condition being cited as possible setbacks (Butler 2009). ADF&G compiled data on the 

weights of neonatal, young of the year, and adult female caribou from the NAPCH for most years 

from 1990-1998 (Butler 2009). In comparison to other Alaskan herds, adult, neonatal, and young of 

the year cows displayed intermediate body size. However, an ADF&G study of NAPCH cow 

productivity from 1997-2000 concluded that moderate nutritional stress was evident in the herd 

(Butler 2009). A sample of 32 age-two cows and 18 age-three cows resulted in 33% (six cows) and 

0% pregnancy rates, respectively (Butler 2009). 

Cow and calf mortality rates have been at all-time highs for the NAPCH, according to an ongoing 

ADF&G study using telemetry flights to monitor these rates. Since 1998, an average cow mortality 

rate of 21% has been observed; cow mortality rates from 1980 to 1984 were 7% (Butler 2009). 

Predation on caribou from wolves and brown bears could also be a contributor to the NAPCH decline 

and lack of recovery. Brown bear and wolf predation was cited as the likely cause of death for 60% 

of collared neonatal calves (2 weeks and younger) from 2005 to 2007 (Butler 2009). Although the 

cause of the mortalities was undocumented, calves between 2 weeks and 4 months of age also 

continued to show a high mortality rate, at 66% over the same years. 

Hunting of the NAPCH is not permitted at this time, but is predicted to reopen again with a bull-only 

harvest; no specific date for the reinstatement of hunting has been set and will not be set until the 
50 

herd begins to recover (Butler 2009). Butler (2009, p. 36 ) reports that a “2005 herd health 

assessment identified heavy parasite loads, the presence of bovine respiratory disease complex, poor 

immune response, low levels of micronutrients, and chronic dehydration” in caribou examined from 

the NAPCH. 

Data Needs/Gaps

Butler (2009) suggests that assessment of the NAPCH wintering grounds should be completed, with 

an aim to define if nutritional limitations are still stressing the herd. This assessment would aid in 

defining future management goals for the NAPCH and determine if the herd has a chance to recover 

from a poor health assessment in 2005 (Butler 2009). 

Overall Condition 

The NAPCH has shown small improvements from 2001 to 2008. Pregnancy rates of cows over 2 

years of age have been slowly improving from 2005-2008 with rates of 57%, 63%, 74%, and 78% 

during those years. However, calf survival remains at an all-time low and the herd has continued to 

decline. ADF&G Biologists examined the NAPCH from 1999 through the 2000s to define intensive 

management options and concluded “no viable solutions exist to alter the status of this herd” (Butler 

2009, p. 37). 

4.3.6 Sources of Expertise

Troy Hamon, KATM/ANIA Chief of Resources 

4.3.7 Literature Cited

Butler, L. 2005. Units 9C &9E caribou management report. Pages 38-48 in C. Brown, editor. 

Caribou management report of survey inventory activities 1 July 2002-30 June 2004. Alaska 

Department of Fish and Game, Juneau, Alaska. 

Butler, L. 2007. Units 9C &9E caribou management report. Pages 33-42 in P. Harper, editor. Caribou 

management report of survey inventory activities 1 July 2004-30 June 2006. Alaska Department 

of Fish and Game, Juneau, Alaska. 

Butler, L. 2009. Units 9C & 9E caribou management report. Pages 32-42 in P. Harper, editor. 

Caribou management report of survey and inventory activities 1 July 2006-30 June 2008. Alaska 

Department of Fish and Game, Juneau, Alaska. 

Rausch, R. A., B. Gasaway, and C. Schwartz. 2008. Moose. Revised by Steve Arthur. 

http://www.adfg.alaska.gov/static/education/wns/caribou.pdf (accessed 25 June 2012).

Skoog, R. O. 1968. Ecology of caribou in Alaska. Ph.D. thesis. University of California, Berkeley, 

California.
51

Plate 7. Alaska game management units and subunits. Subunits 9E and 9C include the area utilized by the NAPCH.
52 

4.4 Passerines

4.4.1 Description

Passerines are birds that belong to the Order 

Passeriformes, commonly referred to as 

“perching birds”. Bird populations often act as 

excellent indicators of an ecosystem’s health 

(Morrison 1986, Hutto 1998, NABCI 2009). 

Birds are typically easy to observe and identify, 

and bird communities often reflect the 

abundance and distribution of other organisms 

with which they co-exist (Blakesley et al. 

2010). When SWAN began conducting 

biological inventories of vertebrates and 

vascular plants in the network parks in the early 

2000s, land birds were identified as one of the 

top eight priority groups for study (KedzieWebb 2001, as cited in Ruthrauff and Tibbits 2009). 

ANIA provides a wide range of habitats, from coastal to montane, that support a variety of 

passerines. Forty-four passerine species have been documented in the park, including several species 

of conservation concern, such as the snow bunting (Plectrophenax nivalis, Photo 8) (Rich et al. 2004, 

NPS 2013). 

4.4.2 Measures

• Species richness and diversity

• Species abundance 

4.4.3 Data and Methods

The earliest available observations of bird populations in ANIA are from Manski et al. (1987) and 

Meyer (1987). Manski et al. (1987) documented bird species along the Pacific coast of ANIA in 

August and September of 1987, while Meyer (1987) reported on birds in the Aniakchak Caldera 

during July 1987. In the summer of 1988, Starr and Starr (1988) reported bird observations along the 

ANIA coast, and Sowl (1988) documented species in the caldera. Several years later, Savage (1992, 

1993) documented bird species in the park during two summer field seasons. 

The most thorough survey of ANIA bird populations, including passerines, occurred during May and 

June of 2009 (Ruthrauff and Tibbits 2009). The survey utilized stratified random sampling according 

to land cover type. Crews conducted surveys at 136 points within eight plots; more in-depth surveys 

took place at six locations with unique habitats or landforms within the park (Ruthrauff and Tibbits 

2009; Plate 8). 

Photo 8. A male snow bunting in ANIA (NPS photo 

by Bill Thompson).
53 

4.4.4 Current Condition and Trend

Species Richness and Diversity 

According to the NPS Certified Species List 

(NPS 2013), 44 passerine species are present or 

probably present within ANIA (Table 11). This 

includes birds that are year-round or seasonal 

residents as well as species that pass through 

during migration. Ruthrauff and Tibbits (2009) 

documented 28 passerine species during a 

summer landbird survey in 2009, including two 

species new to the park: the horned lark 

(Eremophila alpestris, Photo 9) and the hoary 

redpoll (Carduelis hornemanni). During the 

1992-93 field seasons, Savage (1992, 1993) 

observed 18 passerine species. Observers 

during the summers of 1987 and 1988 recorded 

between nine and 16 species (Table 11). 

However, some of these observations were 

limited in geographical scope. For example, 

Manski et al. (1987) and Starr and Starr (1988) 

visited only the park’s coast, while Meyer (1987) and Sowl (1988) documented birds in Aniakchak 

Caldera. 

Photo 9. Horned lark (USFWS photo by Tim 

Bowman).
54

Table 11. Passerines present or possibly present in ANIA (species in bold are of conservation concern). Abundances are from the NPS Certified 

Species List (NPS 2013), for those species confirmed present in the park. For other sources that recorded abundance, A = abundant, C = 

common, FC = fairly common, U = uncommon, O = occasional, R = rare, VR = very rare.

Scientific Name Common Name Abundance

Ruthrauff & 

Tibbits 2009

Savage 

1992-93

Starr & 

Starr 1988

Sowl 

1988

Meyer 

1987

Manski et 

al. 1987

Alauda arvensis sky lark Occasional x x

Eremophila alpestris horned lark x

Cinclus mexicanus American dipper Uncommon x x U U

Corvus corax common raven Common x x C FC C A

Pica hudsonia black-billed magpie Uncommon x x C C

Calcarius lapponicus2 lapland longspur Common x x FC A

Junco hyemalis dark-eyed junco

Melospiza lincolnii Lincoln's sparrow

Melospiza melodia song sparrow U

Passerculus sandwichensis savannah sparrow Common x x C C A A

Passerella iliaca fox sparrow Uncommon x x O

Plectrophenax hyperboreus McKay's bunting

Plectrophenax nivalis2 snow bunting Uncommon x x A A

Spizella arborea American tree sparrow Uncommon x

Spizella passerina chipping sparrow

1 Landbird Conservation Plan for Alaska (Boreal Partners in Flight Working Group 1999) 

2 NALCP = North American Landbird Conservation Plan (Rich et al. 2004) 

* formerly known as the water pipit, Anthus spinoletta.
55

Table 12 (continued). Passerines present or possibly present in ANIA (species in bold are of conservation concern). Abundances are from the 

NPS Certified Species List (NPS 2013), for those species confirmed present in the park. For other sources that recorded abundance, A = 

abundant, C = common, FC = fairly common, U = uncommon, O = occasional, R = rare, VR = very rare.

Scientific Name Common Name Abundance

Ruthrauff & 

Tibbits 2009

Savage 

1992-93

Starr & 

Starr 1988

Sowl 

1988

Meyer 

1987

Manski et 

al. 1987

Zonotrichia atricapilla1 golden-crowned sparrow Abundant x x C C A A

Zonotrichia leucophrys white-crowned sparrow Rare x x R

Carduelis flammea common redpoll Common x x U FC A

Carduelis hornemanni1,2 hoary redpoll x

Carduelis pinus pine siskin

Fringilla montifringilla brambling

Leucosticte tephrocotis gray-crowned rosy-finch Uncommon x x FC C R

Pinicola enucleator pine grosbeak

Riparia riparia bank swallow Uncommon x x A C C U

Tachycineta bicolor tree swallow Rare x O

Tachycineta thalassina violet-green swallow

Lanius excubitor northern shrike Rare x O C U

Anthus hodgsoni olive-backed pipit

Anthus rubescens* American pipit Common x U A A A

Motacilla tschutschensis eastern yellow wagtail

Poecile atricapillus black-capped chickadee Rare x x O U

1 Landbird Conservation Plan for Alaska (Boreal Partners in Flight Working Group 1999) 

2 NALCP = North American Landbird Conservation Plan (Rich et al. 2004) 

* formerly known as the water pipit, Anthus spinoletta.
56

Table 13 (continued). Passerines present or possibly present in ANIA (species in bold are of conservation concern). Abundances are from the 

NPS Certified Species List (NPS 2013), for those species confirmed present in the park. For other sources that recorded abundance, A = 

abundant, C = common, FC = fairly common, U = uncommon, O = occasional, R = rare, VR = very rare.

Scientific Name Common Name Abundance

Ruthrauff & 

Tibbits 2009

Savage 

1992-93

Starr & 

Starr 1988

Sowl 

1988

Meyer 

1987

Manski et 

al. 1987

Dendroica petechia yellow warbler Rare x x O

Vermivora celata orange-crowned warbler Rare x x VR

Vermivora peregrina Tennessee warbler

Wilsonia pusilla Wilson's warbler Uncommon x x U R R

Regulus calendula ruby-crowned kinglet

Regulus satrapa golden-crowned kinglet Unknown x

Troglodytes troglodytes winter wren Occasional x O

Catharus guttatus hermit thrush Abundant x C

Catharus minimus1 gray-cheeked thrush Rare x x O

Ixoreus naevius varied thrush

Turdus migratorius American robin Unknown x

Contopus sordidulus western wood-pewee

Empidonax alnorum alder flycatcher

Total species 28 18 16 12 14 9

1 Landbird Conservation Plan for Alaska (Boreal Partners in Flight Working Group 1999) 

2 NALCP = North American Landbird Conservation Plan (Rich et al. 2004) 

* formerly known as the water pipit, Anthus spinoletta.
57 

 

Photo 10. Orange-crowned warbler (Vermivora celata), black-billed magpie (Pica hudsonia) (USFWS 

photos), and golden-crowned sparrow (Zonotrichia atricapilla) (NPS photo by Kelly Walton).

Species Abundance 

Abundance information for passerines in ANIA is primarily anecdotal. Several observers have 

classified species into categories such as “common”, “uncommon”, or “rare” (see Table 11). Species 

consistently reported as abundant or common across surveys include the savannah sparrow 

(Passerculus sandwichensis), golden-crowned sparrow, and common raven (Corvus corax). 

During the Ruthrauff and Tibbits (2009) landbird survey, four of the five most commonly detected 

species were passerines: bank swallow (Riparia riparia), golden-crowned sparrow, Wilson’s warbler 

(Wilsonia pusilla), and hermit thrush (Catharus guttatus). However, nearly all the bank swallows 

occurred in a large flock at one location, and the species was not widely distributed across the park 

(Ruthrauff and Tibbits 2009). The total number of each passerine species observed and average 

occurrence (number of individuals/number of points surveyed) in ANIA are presented in Table 12. 

Table 14. Number of individuals of each passerine species documented in ANIA, and average 

occurrence (Ruthrauff and Tibbits 2009). 

Species Individuals

Average 

Occurrence

black-billed magpie 8 0.059

common raven 16 0.118

horned lark 3 0.022

tree swallow 10 0.074

bank swallow * 187 1.375

American dipper 2 0.015

gray-cheeked thrush 6 0.044

hermit thrush * 114 0.838

American robin 10 0.074

American pipit 45 0.331

orange-crowned warbler * 72 0.529

* Species with the five highest average occurrences (also highlighted in gray).
58 

Table 15 (continued). Number of individuals of each passerine species documented in ANIA, and 

average occurrence (Ruthrauff and Tibbits 2009). 

Species Individuals

Average 

Occurrence

yellow warbler 4 0.029

Wilson's warbler * 141 1.037

American tree sparrow 11 0.081

savannah sparrow 45 0.331

fox sparrow 50 0.368

white-crowned sparrow 15 0.110

golden-crowned sparrow * 143 1.051

Lapland longspur 21 0.154

snow bunting 32 0.235

redpoll sp. 10 0.074

* Species with the five highest average occurrences (also highlighted in gray).

Threats and Stressor Factors

Due to limited research, it is unclear if any stressors to passerines are present within the park. 

However, these species are likely threatened by sources outside ANIA boundaries, such as mining or 

the development of off-shore oil and gas exploration. For example, several large developments have 

been proposed in Bristol Bay west of the park, which may influence wildlife in the region (Ruthrauff 

et al. 2007). Climate change is also a threat to birds, particularly those that rely on alpine habitats, as 

these areas are likely to become drier and experience shifts in vegetation (Ruthrauff et al. 2007). 

Additionally, many of the passerines that occur in ANIA are migratory, and face multiple threats 

during migration and while in their winter habitats. 

Data Needs/Gaps

Nearly all of the bird surveys and observations in ANIA have occurred during the summer months. 

While this is likely the time when most passerines are present and active in the parks, surveys during 

other seasons (e.g., spring and fall migrations) would contribute to a more thorough understanding of 

the passerine population (Ruthrauff and Tibbits 2009). Establishment of a regular monitoring 

program would help NPS staff determine if any changes are occurring within the ANIA passerine 

population 

Overall Condition 

It is difficult to assess the overall condition of passerines in ANIA, due to the limited amount of data 

that are available. Historical information is primarily from incidental observations as opposed to 

scientifically designed inventories or surveys. As a result, it is not directly comparable to more recent 

surveys. However, there is no evidence of any cause for concern among the passerine populations, 

particularly given the relatively pristine and undisturbed condition of the park.
59 

4.4.5 Sources of Expertise

Sherri Anderson, KATM Wildlife Biologist

4.4.6 Literature Cited

Blakesley, J. A., D. C. Pavlacky Jr., and D. J. Hanni. 2010. Monitoring bird populations in Wind 

Cave National Park. Technical Report M-WICA09-01. Rocky Mountain Bird Observatory, 

Brighton, Colorado. 

Boreal Partners in Flight Working Group. 1999. Landbird conservation plan for Alaska 

biogeographic regions, Version 1.0. U.S. Fish and Wildlife Service unpublished report, 

Anchorage, Alaska. 

Hutto, R. L. 1998. Using landbirds as an indicator species group. Avian conservation: Research and 

management. Island Press, Washington, D.C. 

Kedzie-Webb, S. 2001. Biological inventory study plan, Southwest Alaska Network. National Park 

Service, Anchorage, Alaska.

Manski, D., M. Schroeder, and K. Bosworth. 1987. Annotated bird list: Pacific coast, Aniakchak 

National Monument and Preserve. National Park Service, King Salmon, Alaska. 

Meyer, K. 1987. 1987 Bird surveys of Aniakchak Caldera. National Park Service unpublished report, 

King Salmon, Alaska. 

Morrison, M. L. 1986. Bird populations as indicators of environmental change. Current Ornithology 

3:429-451. 

National Park Service (NPS). 2013. NPSpecies online database. 

https://irma.nps.gov/App/Species/Search (accessed 4 March 2013). 

North American Bird Conservation Initiative, U.S. Committee (NABCI). 2009. The State of the 

Birds, United States of America, 2009. U.S. Department of the Interior, Washington, D.C. 

Rich, T. D., C. J. Beardmore, H. Berlanga, P. J. Blancher, M. S. W. Bradstreet, G. S. Butcher, D. W. 

Demarest, E. H. Dunn, W. C. Hunter, E. E. Inigo-Elias, and more. 2004. Partners in Flight North 

American landbird conservation plan. Cornell Lab of Ornithology, Ithaca, New York. 

Ruthrauff, D. R., T. L. Tibbitts, R. E. Gill, Jr., and C. M. Handel. 2007. Inventory of montane-nesting 

birds in Katmai and Lake Clark National Parks and Preserves. U.S. Geological Survey, Alaska 

Science Center, Anchorage, Alaska. 

Ruthrauff, D. R., and T. L. Tibbits. 2009. Inventory of breeding birds in Aniakchak National 

Monument and Preserve. Natural Resource Technical Report NPS/SWAN/NRTR—2009/186. 

National Park Service, Fort Collins, Colorado. 

Savage, S. 1992. Trip report: Aniakchak 1992. National Park Service unpublished report, King 

Salmon, Alaska. 
60 

Savage, S. 1993. Annotated bird list: Aniakchak Caldera and surrounds, field season 1993. National 

Park Service unpublished report, King Salmon, Alaska. 

Sowl, K. 1988. Investigations of the flora and fauna inside Aniakchak Caldera. National Park 

Service, King Salmon, Alaska. 

Starr, F., and P. Starr. 1988. Annotated bird observations: Aniakchak coast. National Park Service 

unpublished report, King Salmon, Alaska. 
61 

Plate 8. Breeding bird inventory sites within ANIA (from Ruthrauff and Tibbitts 2009). Sample plot 

boundaries are shown in black and red circles represent point-count survey locations. Areas of special 

interest are outlined in blue with focal-area inventory locations shown by pale yellow circles. 
62 

4.5 Salmon

4.5.1 Description

Sockeye salmon (Oncorhynchus nerka) are 

known to inhabit Surprise Lake within the 

Aniakchak Caldera, where they have 

established spawning populations (Mahoney 

and Sonnevil 1991, Hamon 2000, Hamon et al. 

2004). Other salmon species present within the 

park include Coho (O. kisutch), pink (O.

gorbuscha), chum (O. keta), and Chinook 

salmon (O. tshawytscha). A variety of other 

salmonid species are present within the 

Aniakchak River and its major tributaries, 

including Dolly Varden (Salvelinus malma) and

arctic char (S. alpinus) (Lechner 1969, Buck 

1979, Mahoney and Sonnevil 1991). Sockeye 

salmon are an anadromous species that have 

adapted to adverse conditions within the park, 

including previously uninhabited areas once covered by receding glaciers, and Surprise Lake, a highaltitude lake within the Aniakchak Caldera, formed nearly 3,500 years ago by volcanic eruptions 

(Hamon et al. 2004) (Plate 9). According to Hamon et al. (2004, p. 37), sockeye salmon in Surprise 

Lake are “some of the most recently established natural populations known in southwest Alaska.” 

The Aniakchak Caldera within ANIA contains Surprise Lake, which populated with salmon 

following a break in the caldera wall and subsequent flood between 1,800 and 3,400 years ago 

(Hamon 1999). Salmon species have persisted in Surprise Lake since sometime following the historic 

flood, and have thrived even after another major eruption of the Aniakchak volcano in 1931 

(Mahoney and Sonnevil 1991, Hamon 1999). Following geological events such as volcanic eruptions 

or deglaciation, fish typically colonize new areas or become adapted to this newly available habitat 

(Hamon et al. 2004). Historically, sockeye salmon inhabited roughly one-third of the eastern 

shoreline of Surprise Lake (Lechner 1969); currently, three spawning salmon populations are present 

within ANIA, two within the caldera and one in Albert Johnson Creek, a major tributary of the 

Aniakchak River (Hamon 1999). During annual spawning runs, sockeye salmon swim up the highgradient Aniakchak River to Surprise Lake to lay their eggs before they die. ANIA contains several 

nursery areas for sockeye salmon runs that are considered part of the Bristol Bay and Kodiak/Chignik 

fisheries (Hamon, pers. comm., 2013). 

Hamon (1999) noted that recreational visitor observations, documentation of subsistence use, and 

aerial counts provided evidence of the presence of sockeye salmon within ANIA and its drainages. 

Sport fishing is a common visitor activity, although total visitation in 2010 was only 62 visitors 

(Street 2011). Salmon are frequently harvested by local residents and native tribes for subsistence use 

(Photo 11) (Deur et al. 2007). ANIA is known for frequently bad weather conditions and costly, 

unpredictable access; this often discourages visitation and inhibits scientific investigations in the 

Photo 11. A local fisherman drying salmon on a 

knoll east of the mouth of the Aniakchak River (NPS 

photo by Keith Trexler).
63 

region (Mahoney and Sonnevil 1991, Hamon 1999, 2000). Salmon populations within ANIA have 

not been well-documented (Hamon 2000); therefore, data regarding escapement, harvest rates, and 

run timing are either sporadic or non-existent. 

4.5.2 Measures

• Escapement

• Percent harvest

• Run timing 

4.5.3 Reference Conditions/Values

Management objectives typically correspond to escapements and harvest rates of major salmon 

species. However, a reference condition was not established by park staff for the ANIA salmon 

component. Conclusions were drawn from anadromous fish reports, anecdotal accounts, available 

historical data, and temporal trends. 

4.5.4 Data and Methods

Lechner (1969) provided one of the first investigations on sockeye salmon stocks in the ANIA 

region. Lechner (1969) determined the origin of sockeye salmon stocks harvested in the Cape 

Kumlik fishery at Aniakchak Bay. Numbers of Chignik sockeye salmon harvested at Aniakchak Bay 

were recorded using tagging efforts, which provided a basis for management of the cape fishery. Age 

composition of salmon stocks, time of migration, and the contribution of Aniakchak system sockeye 

salmon to the cape fishery were also investigated in the study (Lechner 1969). 

Mahoney and Sonnevil (1991) conducted the first study investigating the Surprise Lake and 

Aniakchak River fisheries from 1987-1988, which sampled both fisheries to determine age, length, 

and weight of adult sockeye salmon at each location (Mahoney and Sonnevil 1991). The study 

collected various baseline data on fish species composition and distribution (Mahoney and Sonnevil 

1991). 

Baseline data gathered by Hamon (1999) identified spawning locations and total population estimates 

within the Aniakchak River drainage. Genetic sampling and body dimension measurements allowed 

researchers to compare present and historic salmon populations; the study also provided population 

estimates and a baseline for future ANIA salmon studies (Hamon 1999). Hamon (2000) further 

studied sockeye salmon populations within the Aniakchak Caldera and the Aniakchak River 

drainage. The study documented spawning populations, associated habitats, and distribution of 

spawning aggregations within the park (Hamon 2000). 

Hamon et al. (2004) discussed sockeye salmon investigations in ANIA and studied salmon 

adaptation to geologic upheaval and survivability in harsh environments. Hamon et al. (2004) also 

studied salmon colonization efforts following the historic Aniakchak flood, escapement within the 

Chignik and Aniakchak River systems, as well as genetic similarity between three different sockeye 

salmon populations within ANIA. 
64 

4.5.5 Current Condition and Trend

Escapement

Historical accounts (Lechner 1969) reported that sockeye salmon escapement in Albert Johnson 

Creek was approximately 500 to 1,000 annually. Escapement to Surprise Lake was estimated to be 

between 3,000 and 5,000 individuals, except in 1962 when 40,000 spawning sockeye salmon were 

observed (Lechner 1969). The study by Lechner (1969) estimated the spawning population of 

sockeye salmon in Surprise Lake to be approximately 2,000 fish. An additional 200 sockeye were 

found spawning in the Aniakchak River, near the edge of the crater (Lechner 1969). Interviewees in 

the study by Deur et al. (2007, p. 80) noted that “official fish escapement figures represented ‘paper 

numbers’ and that the actual escapement numbers for the local fishery were so low that the salmon 

population was in a steady state of decline.”

As of 2007, Albert Johnson Creek, the outlet of Surprise Lake, and the beaches of Surprise Lake all 

report escapement rates of fewer than 10,000 fish each annually (Pavey et al. 2007). Hamon et al. 

(2004) noted that Surprise Lake experiences between 5,000 and 50,000 spawning salmon annually. 

Black Lake, located southwest of ANIA in the neighboring Chignik River system (Plate 9), has an 

average annual escapement between one and two million fish (Hamon et al. 2004, Pavey et al. 2007). 

Bristol Bay, located on the northwest border of the Alaskan Peninsula, and its associated fishing 

districts experience escapement of approximately 11 million sockeye salmon annually on average 

(Jones et al. 2012). 

Percent Harvest

Sockeye salmon populations within ANIA are affected by commercial harvest pressures outside of 

park boundaries, as well as subsistence harvest within park boundaries (Hamon 1999). The 

commercial fishing industry is active in the waters surrounding ANIA. However, major 

concentrations of harvest vessels are typically found in the nearby Chignik district (Hamon et al. 

2004). Because of small spawning salmon populations in the ANIA region, harvest of sockeye 

salmon is typically minimal (Hamon et al. 2004). Generally, weather conditions and the rate of 

salmon entering Chignik Lagoon were two significant factors that determined harvest rates (Lechner 

1969). Recreational harvest along the ANIA coast is typically minimal because of harsh weather 

conditions. However, fishermen suggest that the shoreline is a “profitable fishing ground” and is 

often sought out due to low density human populations and protection from harsh winds (Deur et al. 

2007). Salmon populations are generally governed by natural processes within ANIA.

Subsistence harvest was present in the area prior to the establishment of ANIA in 1978 (Deur et al. 

2007). Chignik villagers harvest modest amounts of salmon, clams, and waterfowl along the ANIA 

coast (Deur et al. 2007). Historically, harvest occurred in the spring or fall seasons, closely mirroring 

salmon runs (Deur et al. 2007). Fishermen from other regions, Kodiak Island for example, were 

known to harvest salmon in the area although exact numbers are unknown (Tuten 1977). Tuten 

(1977, p. 11, as cited in Deur et al. 2007) suggested that subsistence data for the ANIA coast seem to 

have a relatively high margin of error due to residents’ high sensitivity “to the powerful role of the 

ADF&G which regulates their commercial salmon industry.” 
65 

Run Timing 

Little data exist regarding run timing for ANIA salmon populations and little is known about salmon 

run timing for differing geographic locations within ANIA. Salmon runs occur in the spring and fall 

months, typically beginning in early June and ending in late July to mid-August. According to 

interviewees in a study by Deur et al. (2007), salmon runs occur at irregular pulses depending on 

species and are occasionally delayed by inclement weather.

Threats and Stressor Factors 

Park staff identified harvest rates as a major stressor to salmon populations within ANIA. 

Recreational and subsistence fisheries do not influence the salmon population as significantly as the 

commercial fishery, but often unique salmon stock can be affected. Genetic sampling conducted by 

Hamon et al. (2004) revealed three distinct spawning populations within ANIA water bodies, all tied 

to the ANIA fishing industry. A delicate balance exists between escapement and harvest rates in 

southwest Alaska. For example, historical closings of the Chignik Bay district in order to improve 

system escapement rates of sockeye salmon resulted in harvest increases in the nearby Cape Kumlik 

fishery (near ANIA), approximately 97 km (60 mi) to the east (Plate 9) (Lechner 1969). Typically, 

fisheries are only closed if harvest adversely affects ADF&G escapement goals (Lechner 1969). 

Tensions between subsistence and commercial harvest exist in the region, which have direct effects 

on ANIA such as coincidental commercial and subsistence harvests (Deur et al. 2007). Interviewees 

in the study by Deur et al. (2007, p. 80) expressed concern “that subsistence fishery seasons were not 

providing enough time to meet the needs of the communities before the commercial season began.” 

Others cited the commercial fishery’s preferential catchment of larger fish as a factor contributing to 

smaller salmon caught for subsistence use (Deur et al. 2007). 

Salmon populations in southwestern Alaska are subject to commercial harvest pressures outside of 

the park, while subsistence and recreational harvest pressures exist within park boundaries (Hamon 

1999). Salmon runs within ANIA streams are not as large as other nearby systems, such as those in 

the Bristol Bay or Chignik Bay region (Hamon et al. 2004). For this reason, it is likely that 

commercial harvest efforts will remain concentrated in the Bristol and Chignik Bay areas and not 

dramatically affect smaller runs returning to Surprise Lake and the Aniakchak River through 

Aniakchak Bay (Hamon et al. 2004). However, Deur et al. (2007) noted that significant declines in 

species such as salmon and halibut were observed over the past few decades.

Data Needs/Gaps

Because of its frequent poor weather conditions, inaccessibility, and remoteness, salmon populations 

in and near ANIA have not been well-studied; data regarding escapement, harvest, and run timing are 

either non-existent or severely lacking (Hamon 1999). Although anecdotal accounts exist, very few 

scientific studies investigating escapement, harvest, or run timing have occurred in ANIA. 

Studies investigating run-timing in ANIA streams would help to address the measure. Comparisons 

between various other waterbodies, as well as changes over time within the system, would likely help 

to address temporal shifts in salmon runs; however, complete inventories of anadromous waters 

would likely be difficult and would not be cost effective.
66 

Overall Condition 

Escapement 

The measure of escapement is not currently considered an area of management concern. While 

sockeye salmon escapement within ANIA has not been especially well-documented, populations are 

generally governed by natural processes. However, escapement rates are likely directly affected by 

harvest rates, and vice versa. Escapement for Albert Johnson Creek, the outlet of Surprise Lake, and 

the beaches of Surprise Lake are each estimated at less than 10,000 fish annually (Pavey et al. 2007). 

Surprise Lake escapement is relatively variable, between 5,000 and 50,000 spawning salmon 

annually (Hamon et al. 2004). Sockeye salmon escapement within Surprise Lake, Aniakchak Bay, 

the Aniakchak River, and its tributaries is significantly less than other locations in southwest Alaska 

(Hamon et al. 2004, Jones et al. 2012). 

Percent Harvest

The measure of percent harvest is not currently considered an area of management concern. 

Commercial, recreational, and subsistence harvest all uniquely contribute to the percent harvest of 

sockeye salmon within ANIA. Recreational and subsistence fisheries do not heavily influence salmon 

populations. According to Hamon et al. (2004), it is likely that commercial harvest efforts will 

remain concentrated in the Bristol Bay and Chignik River districts because of larger salmon 

populations. 

Run Timing

The current run timing in ANIA is unknown as data are not available for the park. Because of its 

remoteness and frequent poor weather conditions, ANIA is little affected by human activity and 

generally governed by natural processes (NPS 2009). Future studies examining run timing (e.g., 

mean day of salmon escapement) and the effects of climate change on salmon runs would be helpful 

to determine overall condition for this resource?. 

Summary 

ANIA salmon populations are not well studied. Therefore, significant conclusions cannot be drawn 

from available data, although anecdotal sources note that populations within ANIA are relatively 

small, but apparently healthy. According to Hamon et al. (2004, p. 39), “the populations at ANIA, 

though relatively small, appear to be very healthy and represent adaptations to a unique region.” 

Harvest rates do not currently have significant impacts on the small sockeye salmon populations 

within the park. 

4.5.6 Sources of Expertise

Troy Hamon, KATM/ANIA Chief of Resources 

4.5.7 Literature Cited

Buck, E. H. 1979. Surface resources and environmental values – Alaska peninsula: Becharof Lake to 

Aniakchak area. Arctic Environmental Information and Data Center, University of Alaska, 

Anchorage, Alaska. 
67 

Deur, D., M. Morseth, U. Goggin, and R. Lind. 2007. Aniakchak National Monument and Preserve, 

traditional use and user groups study. National Park Service, Fort Collins, Colorado. 

Hamon, T. 1999. Sockeye salmon population status and local adaptation inventoried at Aniakchak. 

Pages 27-28 in Natural Resource Year in Review - 1999. National Park Service, Natural 

Resource Information Division, Lakewood, Colorado. 

Hamon, T. 2000. Population status, local adaptation, and gene flow in Surprise Lake sockeye salmon: 

an ecological and evolutionary study of colonization and succession in Aniakchak National 

Monument and Preserve. Resource Management Technical Report KATM-NR-01-01. National 

Park Service, King Salmon, Alaska. 

Hamon, T., S. A. Pavey, J. L. Miller, and J. L. Nielsen. 2004. Aniakchak sockeye salmon 

investigation. Alaska Park Science 3(2):34-39. 

Jones, M., T. Sands, S. Morstad, P. Salomone, G. Buck, F. West, T. Baker, and T. Krieg. 2012. 2011 

Bristol Bay area annual management report. Fishery Management Report No. 12-21. Alaska 

Department of Fish and Game, Department of Commercial Fisheries, Anchorage, Alaska. 

Lechner, J. 1969. Identification of red salmon stocks taken in the Cape Kumlik – Aniakchak Bay 

fishery, Chignik Area, 1967. Informational leaflet 133. Alaska Department of Fish and Game, 

Juneau, Alaska. 

Mahoney, B. A., and G. M. Sonnevil. 1991. Surprise Lake and Aniakchak River fishery 

investigation, Aniakchak National Monument and Preserve, Alaska, 1987 and 1988 final report. 

Alaska Fisheries Technical Report Number 12. U.S. Fish and Wildlife Service, King Salmon, 

Alaska.

National Park Service (NPS). 2009. Aniakchak National Monument and Preserve foundation 

statement. National Park Service, Aniakchak National Monument and Preserve, Alaska. 

Pavey, S. A., T. R. Hamon, and J. L. Nielsen. 2007. Revisiting evolutionary dead ends in sockeye 

salmon life history. Canadian Journal of Fisheries and Aquatic Sciences 64:1199-1208. 

Street, B. 2011. Statistical abstract: 2010. Natural Resource Data Series NPS/NRPC/SSD/NRDS2011/117. National Park Service, Fort Collins, Colorado. 

Tuten, M. A. 1977. A preliminary study of subsistence activities of the Pacific coast of the proposed 

Aniakchak Caldera National Monument. Cooperative Park Studies Unit, occasional paper No. 4. 

University of Alaska, Fairbanks, Alaska.
68

Plate 9. Major water bodies in and near ANIA.
69 

4.6 Native Fish 

4.6.1 Description

Twenty-seven anadromous and nonanadromous native fish species are present or 

probably present in ANIA (Table 13, Miller and 

Markis 2004, Jones et al. 2005, NPS 2012). 

Native fish of ANIA have been subjected to 

major geologic upheaval and flooding events 

over the past century. Sockeye salmon, coho 

salmon, and Dolly Varden are the most 

prevalent species in ANIA, showing an ability

to adapt after environment-altering events. 

Hamon et al. (2004) recognizes salmon as an 

important source of nutrients for plant and 

mammal species and a source of subsistence for the native people surrounding ANIA (Krieg et al. 

2004). Brown bears rely on fall salmon runs to supplement their diets before hibernation and native 

fish such as the Dolly Varden (Photo 12) feed heavily on drifting salmon eggs. 

Table 16. NPS certified species list of native fish present or probably present in ANIA (NPS 2012).

Scientific Name Common Name Occurrence Abundance

Catostomus catostomus longnose sucker probably present * 

Dallia pectoralis Alaska blackfish present in park uncommon

Gasterosteus aculeatus three-spined, Alaskan stickleback present in park abundant

Pungitius pungitius ten-spined, nine-spined stickleback present in park abundant

Thaleichthys pacificus eulachon probably present *

Lampetra tridentata Pacific lamprey probably present * 

Lethenteron japonicum Arctic lamprey probably present * 

Platichthys stellatus starry flounder present in park unknown

Oncorhynchus gorbuscha pink salmon present in park abundant

Oncorhynchus keta chum salmon present in park abundant

Oncorhynchus kisutch coho salmon present in park abundant

Oncorhynchus mykiss steelhead, rainbow trout present in park rare 

Oncorhynchus nerka sockeye salmon present in park abundant

Oncorhynchus tshawytscha king salmon, chinook salmon present in park uncommon

Prosopium cylindraceum round whitefish probably present *

Salvelinus malma Dolly Varden present in park abundant

Thymallus arcticus Arctic grayling probably present * 

Cottus aleuticus coastrange sculpin present in park uncommon

Platichthys stellatus starry flounder present in park uncommon

* Indicates that information regarding the abundance of the species is not available. 

Photo 12. An Alaskan Dolly Varden (Photo by Jacob 

Zanon, SMUMN GSS 2011). 
70 

Table 13 (continued). NPS certified species list of native fish present or probably present in ANIA (NPS 

2012).

Scientific Name Common Name Occurrence Abundance

Leptocottus amatus Pacific staghorn sculpin present in park uncommon

Lota lota burbot probably present *

Salvelinus namaycush lake trout probably present *

Esox lucius northern pike probably present *

Artedius fenestralis padded sculpin probably present * 

Hypomesus olidus pond smelt probably present * 

Prosopium cylindraceum round whitefish probably present *

Cottus cognatus slimy sculpin probably present *

* Indicates that information regarding the abundance of the species is not available. 

4.6.2 Analysis

Existing data and literature sources for this component were compiled and reported. Data for this 

component are minimal.

4.6.3 Reference Conditions/Values

Reference condition for this component is not available. 

4.6.4 Data and Methods

Due to the lack of reference conditions for this component, the primary purpose of this portion of the 

NRCA is to provide park management with summarized data and information for future use. To 

fulfill this goal, data and literature provided by SWAN and ANIA staff were compiled and 

summarized.

Mahoney and Sonnevil (1987, 1991) completed a fisheries investigation of Surprise Lake and its 

tributaries, conducting three sampling efforts over two consecutive years (July 1987, AugustSeptember 1988). Fishery sampling efforts were reported in two water body groups: stream sampling 

and lake sampling efforts. Fisheries collection methods included minnow traps, backpack 

electrofishing, gill netting, hook and line, and dip netting. 

Miller and Markis (2004) conducted a fisheries survey of ANIA water bodies with the goal to 

document species classified as probably present in ANIA. Water bodies were sampled in August 

2002 and May-July 2003. Fisheries collection methods included minnow traps, hoop traps, minnow 

seines, beach seines, fyke nets, gill nets, and hook and line (Miller and Markis 2004). Jones et al. 

(2005) surveyed ANIA water bodies with a similar goal: to seek species listed as probably present 

and confirm those already present.

Manski et al. (1988) conducted a brief water quality sampling and fisheries survey of Surprise Lake. 

Methods of fisheries sampling included backpack electrofishing, minnow traps, hook and line, and 

gill nets (Manski et al. 1988).
71 

4.6.5 Current Condition and Trend

Harvest and Angler Pressure Data 

Dolly Varden and sockeye salmon were the only species reported in Surprise Lake (Mahoney and 

Sonnevil 1987, 1991; Table 14). Manski et al. (1988) confirms that only two species are found in 

Surprise Lake, adding that since the last major volcanic eruption in 1931, non-anadromous species 

such as stickleback have not yet been able to re-populate. Dolly Varden ranged from 1-11 years of 

age; several fish sampled over 4 years of age were found to be anadromous (Mahoney and Sonnevil 

1987, 1991). The 1988 study sampled selected streams branching off of the Aniakchak River, 

resulting in more species being reported than the previous year (Plate 9, Table 15). The presence of 

juvenile sockeye salmon indicates that Surprise Lake supports sockeye salmon reproduction 

(Mahoney and Sonnevil 1987, 1991). 

Table 17. Fisheries survey of Surprise Lake and Surprise Lake Tributaries. Table compiled from Mahoney 

and Sonnevil (1987).

ANIA fish survey 

1987

Dolly 

Varden

sockeye 

(juvenile)

sockeye 

(adult)

pink

salmon

chum 

salmon

coho 

salmon

three-spined 

stickleback

Surprise 

Lake/Tributaries 92 175 11 0 0 0 0 

Table 18. 1987 & 1988 fisheries survey of Surprise Lake, Surprise Lake Tributaries, and Aniakchak River 

Tributaries. Table compiled from Mahoney and Sonnevil (1991).

ANIA fish survey 

1988

Dolly 

Varden

sockeye 

(juvenile)

sockeye 

(adult)

pink 

salmon

chum 

salmon

coho 

salmon

three-spined 

stickleback

Surprise Lake 86 175 45 0 0 0 0

Tributary 5 15 0 0 0 0 0 0

Albert Johnson 

Creek 69 2 1 19 2 30 2 

N. Fork ANIA River 9 0 0 A* 0 94 1 

* A - Indicates that pink salmon were observed in large numbers but no effort to gather numerical 

data was made.

Miller and Markis (2004) were successful in documenting three species in ANIA: Alaska blackfish, 

coastrange sculpin, and nine-spined stickleback, all of which were labeled probably present before 

2003. Miller and Markis (2004) confirmed that only two species: sockeye salmon and Dolly Varden, 

were present in Surprise Lake. The Aniakchak River was found to have the highest species diversity 

in the area with nine sampled species (Table 16, Miller and Markis 2004). Jones et al. (2005) 

identified 11 native fish species from ANIA water bodies, with two species confirmed that had 

previously been labeled as probably present. 
72 

Table 19. Species and number of fish sampled (2002 – 2003) in ANIA water bodies. Table compiled from 

Miller and Markis (2004). 

Species

Albert 

Johnson 

Creek

Aniakchak 

River

Surprise 

Lake

Iris 

Creek

Willow 

Creek

Meshik 

Lake

Meshik 

River Total

Expected undocumented species

 Alaska blackfish 0 0 0 0 0 0 1 1

 coastrange 

 sculpin 0 3 0 9 1 0 0 13

 ninespine

 stickleback 56 4 0 0 0 3 2 65

Previously documented species

 coho/silver 

 salmon 700 880 0 148 0 189 408 2,325

 Dolly Varden 63 52 942 572 2 3 67 1,701

 Pacific staghorn 

 sculpin 0 100 0 0 0 0 0 100

 pink salmon 0 1 0 0 0 0 0 0

 rainbow trout/ 

 steelhead 0 0 0 39 0 0 0 39

 sockeye salmon/ 

 red 0 17 1,264 0 0 679 16 1,976

Table 20. Species and number of fish sampled (2002 – 2003) in ANIA water bodies. Table compiled from 

Miller and Markis (2004). 

Species

Albert 

Johnson 

Creek

Aniakchak 

River

Surprise 

Lake

Iris 

Creek

Willow 

Creek

Meshik 

Lake

Meshik 

River Total

starry flounder 0 81 0 1 0 0 0 82

threespine 

stickleback

1 13 0 1 4 756 15 790

Threats and Stressor Factors 

Salmon extirpation or the discontinued use of ANIA water bodies by salmon (especially sockeye 

salmon) would threaten the existence of several native fish species. Salmon supply essential nutrients 

from their eggs and flesh to the native fish of ANIA; without these nutrients many native fish species 

would become stressed. ANIA is also susceptible to another large volcanic eruption or other 

ecological disturbance, which could again alter native fish distribution. 

Data Needs/Gaps 

Unlike nearby KATM, data from ADF&G statewide mail-in surveys and guide logbooks do not exist 

for ANIA. Overall, information regarding native fish studies in ANIA is limited and outdated. Future 

sampling efforts would benefit the ability to describe condition in the future. 
73 

Overall Condition 

Given the remoteness of the Aniakchak River and its tributaries, Surprise Lake, and other water 

bodies in ANIA, natural processes should be the primary driver of fish population dynamics and the 

condition of this resource is assumed to be good. However, without frequent and recent monitoring 

data, condition is only speculative.

4.6.6 Sources of Expertise

Troy Hamon, KATM/ANIA Chief of Resources 

4.6.7 Literature Cited

Hamon, T. R., S. A. Pavey, J. L. Miller, and J. L. Nielsen. 2004. Aniakchak sockeye salmon 

investigations. Alaska Park Science 3(2):34-39. 

Jones, T. M., L. A. Bennett, and T. R. Hamon. 2005. Baseline inventory of freshwater fishes of the 

Southwest Alaska Inventory and Monitoring Network: Alagnak Wild River, Aniakchak National 

Monument and Preserve, Katmai National Park and Preserve, Kenai Fjords National Park, and 

Lake Clark National Park and Preserve. National Park Service, Southwest Alaska Network,

Anchorage, Alaska. 

Krieg, M. T., H. C. Nicholson, and P. C. Kenner. 2004. Traditions, knowledge, and customs of the 

Alaska Peninsula/Becharof National Wildlife Refuge Complex and Aniakchak National 

Monument subsistence fishing communities. Final Report for Study 01-109. U.S. Fish and 

Wildlife Service, Fisheries Resource Monitoring Program, Anchorage, Alaska. 

Mahoney, B. A., and G. M. Sonnevil. 1987. Surprise Lake fishery investigation, Aniakchak National 

Monument and Preserve, Alaska. U.S Fish and Wildlife Service, King Salmon Fishery 

Assistance Office, King Salmon, Alaska.

Mahoney, B. A., and G. M. Sonnevil. 1991. Surprise Lake and Aniakchak River fishery 

investigation, Aniakchak National Monument and Preserve, Alaska, 1987 and 1988 final report. 

Fisheries technical report number 12. U.S. Fish and Wildlife Service, King Salmon, Alaska. 

Manski, D. A., B. Mahoney, and G. Sonnevil. 1988. Fish populations of an Alaskan volcanic lake. 

U.S. Fish and Wildlife Service, Fisheries Assistance Office, King Salmon, Alaska. 

Miller, J. L., and J. Markis. 2004. Freshwater fish inventory of Aniakchak National Monument and 

Preserve, Southwest Alaska Inventory and Monitoring Network. National Park Service,

Southwest Alaska Network, Anchorage, Alaska. 

National Park Service (NPS). 2012. Integrated resource management applications. NPSpecies search. 

Available from https://irma.nps.gov/App/Species/Search (accessed 15 July 2012). 
74

Plate 10. Area waterbodies of interest in Aniakchak National Monument and Preserve.
75 

4.7 Seismic Activity

4.7.1 Description

ANIA is located in the Aleutian volcanic arc, 

one of the most volcanic and seismically active 

regions of the world, due to the northward 

movement of the Pacific Plate in relation to the 

North American plate (Page et al. 1991). The 

Aleutian volcanic arc is geographically 

described as a curving chain of volcanoes from 

the far western end of the Aleutian Islands, 

extending up the southwest Alaskan peninsula, 

and terminating in south-central Alaska (Simkin 

and Siebert 1994). 

The Aniakchak Caldera (Photo 13), deemed a National Natural Landmark, has been the subject of 

several geologic studies because of its unique geologic features, formation history, and volcanic 

characteristics. The caldera is, on average, 10 km (6 mi) wide and over 600 m (2,000 ft) deep, 

making it one of the largest explosive craters in the world (Coombs and Bacon 2012). The caldera 

was formed from the collapse of Aniakchak Volcano after a catastrophic eruption around 3,400 years 

ago in an eruption larger than the Novarupta-Katmai eruption in 1912 (Coombs and Bacon 2012). 

Visits to the caldera are rare and usually involve geologic and fisheries studies or water quality 

sampling. These teams are drawn to Surprise Lake and prime examples of lava flows, cinder cones, 

and explosion pits contained within the interior of the caldera (Brooks 2012). One of the most 

intriguing facets of the caldera, caused by its topography and location, is its ability to generate its 

own weather (Brooks 2012). 

Earthquakes and volcanic eruptions within ANIA are a result of the interaction of the Pacific and 

North American plates along the Aleutian volcanic arc and are capable of drastically changing the 

landscape. Major alterations to the flora and fauna of a region can occur tens of kilometers from an 

epicenter or major eruption (Page et al. 1991). These alterations occur through a variety of 

mechanisms such as uplift or subsidence, tsunamis, mass movements or mass wasting events (e.g., 

snow avalanches, landslides), lava flows, and fallout debris which can cover the landscape with a 

thick layer of ash (Hoyer 1971, Crowell and Mann 1998, and AVO 2001). 

Fierstein (2012, p. 15) states that “understanding the eruptive history of a volcano provides the best 

clues as to when, how, and on what scale that volcano may erupt in the future.” By analyzing the 

juxtaposition of lava flows, ash deposits, and other deposits as well as utilizing radiometric dating, 

estimates can be made regarding the frequency and magnitude of historic volcanic eruptions 

produced by the volcano in question (Fierstein 2012). 

Photo 13. Aerial photograph of Aniakchak Caldera 

with landforms and deposits labeled (Coombs and 

Bacon 2012).
76 

Generally, an increase in seismic activity will accompany 

a volcanic eruption. A seismic swarm of volcano tectonic 

(VT) earthquakes is a common disturbance before an 

eruption occurs (Umakoshi 2001). Low frequency 

earthquakes are thought to be an even more diagnostic 

seismic signal, as their occurrence often indicates the

movement of fluid or gasses (James Dixon, USGS 

Geophysicist, pers. comm., 2013). A large scale volcanic 

eruption can cause massive destruction to landscapes, 

personal property and result in wide-spread casualties. The 

ability to predict if an observed seismic event is the 

precursor for an eruption can provide an opportunity to set 

plans into action to save human lives through the 

evacuation of an area in danger.

The Alaska Volcano Observatory (AVO) operates a 

seismograph station network to monitor seismic activity 

across the Aleutian volcanic arc (Photo 14). AVO 

inherited 22 seismograph stations in 1988 and added the 

majority of the existing seismograph stations between 

1996 and 2006 (AVO 2013). In 2011, the AVO seismic 

monitoring network had expanded to include 205 seismograph stations across 33 AVO seismicallymonitored volcanoes located within the Aleutian volcanic arc (Dixon et al. 2012). 

4.7.2 Measures

• Summary of recorded seismic history

• Summary of major seismic events

4.7.3 Reference Conditions/Values

Long-term trends defining geologic or seismic background for a region are difficult to achieve, as the 

factors that produce the frequency and magnitude of events are many and unpredictable. Regional 

trends could possibly be derived from consistent long-term monitoring of the seismic activity in a 

region with a constant number of functioning seismic stations. Discussion regarding the seismic 

activity of ANIA is limited to the time in which the seismic monitoring system has been operational. 

Due to the fact that a consistent number of seismic monitoring stations have only been operational 

since 2003, an accurate reference condition cannot be determined, as a sample size of a decade is 

extremely short when compared to the time between eruptions or great earthquakes. 

4.7.4 Data and Methods

AVO (2013) monitors and records the daily seismic activity of the 33 volcanoes actively monitored 

by the observatory. Information is also presented regarding the seismic station and volcano latitude 

and longitude locations within ANIA, descriptions of each volcano, recorded seismic histories, and 

recorded volcanic activity.

Photo 14. AVO seismic monitoring 

station in ANIA (Image courtesy of 

AVO/USGS). 
77 

4.7.5 Current Condition and Trend

Summary of Recorded Seismic History 

Within ANIA, the Aniakchak Crater is the only volcano monitored by AVO (Table 17; Plate 11). 

AVO maintains six seismic monitoring stations in the Aniakchak subnetwork in an effort to record 

the daily seismic activity, predict eruptions, and develop historical seismic activity data (Table 18; 

Plate 12; Dixon et al. 2012). The only volcanic activity in the caldera recorded over the past 200 

years is the six-week long eruption of Aniakchak Crater in 1931 (Neal et al. 2001). Scientists have 

worked to unravel the volcanic history of ANIA in an effort to better understand the past eruptions of 

the region. Half Cone, Blocky Cone, and Vent Mountain, all located within the Aniakchak Crater, 

were identified to have erupted explosively about 400 years ago (Coombs and Bacon 2012). 

Table 21. Volcano located in ANIA (AVO 2013).

Name

Latitude 

(DD)

Longitude 

(DD)

Elevation 

(ft)

Seismically 

Monitored Type

Aniakchak Crater 56.906 -158.209 4,400 Yes Stratovolcano with intracaldera 

domes, vents, and cones 

Table 22. Seismic monitoring stations located within ANIA (AVO 2013).

Station Latitude (DD) Longitude (DD) Elevation (ft) Seismometer Open Date

ANNE 56.913 -158.059 214 L4 07/18/1997

ANNW 56.966 -158.215 248 L4 07/18/1997

ANON 56.92 -158.172 135 L22 07/10/2000

ANPB 56.802 -158.281 200 L4 07/18/1997

ANPK 56.842 -158.126 296 L4 07/18/1997

AZAC 56.895 -158.231 322 L4 07/12/2003

Aniakchak Crater was one of only seven AVO monitored volcanoes to show an increase in regional 

seismic activity in 2011 from recorded 2010 levels (Dixon et al. 2012). AVO located 12 earthquakes 

within the Aniakchak volcano subnetwork in 2010 and 55 in 2011. Over the last eight years, AVO 

seismic stations have located, on average, 24 earthquakes/year at Aniakchak. 

Summary of Major Seismic Events 

The 1931 eruption from the new vent within the Aniakchak Caldera produced egg-sized rock 

projectiles observed to travel over 30 km (19 mi) (Coombs and Bacon 2012). The eruption began 1 

May and continued into the middle of June, with the most violent activity reported during the first 10 

days. This eruption was unique in regards to the chemical makeup of the magma emitted, and type of 

projectiles ejected (Coombs and Bacon 2012). Fragments of pumice with estimated diameters of 5 

cm (2 in) landed in Meshik, approximately 25 km (15 mi) away. Ash fallout about the size of a sand 

grain was nearly 10 m (32 ft) deep near the Aniakchak Caldera; however, fallout was observed to be 

only a dusting at distances greater than 100 km (62 mi) (Neal et al. 2001). 
78 

Threats and Stressor Factors 

Threats and stressors regarding the seismic activity of the ANIA region are undefined. 

Data Needs/Gaps

Roman and Cashman (2006) state that VT swarms that are observed but do not result in an eruption 

are largely not understood. This is mainly due to the fact that only VT swarms that result in a 

volcanic eruption are of interest and, therefore, thoroughly studied. Approximately half of observed 

VT swarms occurring on or near a volcanic center lead to an eruption (Benoit and McNutt 1996). 

Dixon and Power (2009) stress the need and importance to study VT swarms that do not result in 

volcanic eruption. A more thorough understanding of these VT swarms is important for the quick and 

decisive assessment of future VT swarms and the probability that they may cause a volcanic 

eruption. 

Overall Condition 

Within ANIA, one volcano is monitored by six seismic monitoring stations maintained by AVO. 

Seismic stations surrounding the Aniakchak Crater have recorded an average of 24 earthquakes/year 

over the past eight years. Aniakchak Crater was one of only seven AVO monitored volcanoes to 

show an increase in regional seismic activity from recorded 2010 levels (Dixon et al. 2012). AVO 

located 12 earthquakes within the Aniakchak volcano subnetwork in 2010 and 55 in 2011, more than 

double the eight-year average for the region. This seismic increase has been attributed to low 

frequency events which occur at depths greater than 10 km (6 mi) and in short activity bursts (Dixon 

et al. 2012). The presence of these low frequency events indicates that an active source underlies the 

Aniakchak Caldera (Dixon, pers. comm., 2013). 

Volcanologists predict, through the piecing together of historic geological evidence, that eruptions of 

the same scale as the 1931 eruption of the Aniakchak Caldera, are to be expected (Neal et al. 2001). 

4.7.6 Sources of Expertise

James Dixon, USGS Geophysicist

4.7.7 Literature Cited

Alaska Volcano Observatory (AVO). 2001. Preliminary volcano-hazard assessment for the Katmai 

Volcanic Cluster, Alaska. Open file report 00-489. U.S. Geological Survey, Anchorage, Alaska. 

Alaska Volcano Observatory (AVO). 2013. Volcano information, seismic station reports, and seismic 

history of the KATM region. https://www.avo.alaska.edu (accessed 25 March 2013). 

Benoit, J. P., and S. R. McNutt. (1996) Global volcanic earthquake swarm database 1979-1989. Open 

file report 96-69. U.S. Geological Survey, Anchorage, Alaska. 

Brooks, M. 2012. Volcanic national natural landmarks in Alaska. Alaska Park Science 11(1):23-27. 

Coombs, M. L., and C. R. Bacon. 2012. Using rocks to reveal the inner workings of magma 

chambers below volcanoes in Alaska’s national parks. Alaska Park Science 11(1):27-33. 
79 

Crowell, A. L., and D. H. Mann. 1998. Archaeology and coastal dynamics of Kenai Fjords National 

Park, Alaska. National Park Service, Anchorage, Alaska. 

Dixon, J. P., and J. A. Power. 2009. The January 2006 volcanic-tectonic earthquake swarm at 

Mount Martin, Alaska. in Studies by the U.S. Geological Survey in Alaska, 2007. Haeussler, 

P.J., and J. P. Galloway (eds.). U.S. Geological Survey, Reston, Virginia.

Dixon, J. P., S. D. Stihler, J. A. Power, and C. K. Searcy. 2012. Catalog of earthquake hypocenters at 

Alaskan Volcanoes: January 1 through December 31, 2011. U.S Geological Survey Data Series,

Reston, Virginia. 

Fierstein, J. 2012. Katmai National Park volcanoes. Alaska Park Science 11(1):15-21. 

Hoyer, M. C. 1971. Puget Peak avalanche. Geological Society of America Bulletin 82:1267-1284. 

Neal, A. C., R. G. McGimsey, T. P. Miller, J. R. Riehle, and C. F. Waythomas. 2001. Preliminary 

volcano-hazard assessment for Aniakchak Volcano, Alaska. U.S. Geological Survey, Alaska 

Volcano Observatory, Anchorage, Alaska. 

Northern California Earthquake Data Center (NCEDC). 2013. Advanced National Seismic System 

catalog. http://www.ncedc.org/anss/anss-detail.html (accessed 3 April 2013). 

Page, R. A., N. N. Biswas, J. C. Lahr, and H. Pulpan. 1991. Seismicity of continental Alaska. In

Neotectonics of North America. D. B. Slemmons, E. R. Engdahl, M. D. Zoback, and D. D. 

Blackwell (eds.). Geological Society of America, Boulder, Colorado. 

Roman, D. C., and K. V. Cashman. 2006. The origin of volcano-tectonic earthquake swarms. 

Geology 34(6):457-460. 

Simkin, T., and L. Siebert. 1994. Volcanoes of the world. Geoscience Press, Tucson, Arizona. 

Umakoshi, K., H. Shimizu, and N. Matsuwo. 2001. Volcano-tectonic seismicity at Unzen Volcano, 

Japan, 1985-1999. Journal of Volcanology and Geothermal Research 112:117-131. 
80

Plate 11. Seismically monitored volcano and seismic stations within ANIA.
81

Plate 12. Distribution and magnitudes of recorded seismic events of the KATM region (NCEDC 2013).
82 

4.8 Climate

4.8.1 Description

Climate is widely recognized as one of the most fundamental drivers of ecological condition and 

ecological change, particularly in Alaska (NPS 2011). As a primary driver of many other ecosystem 

components (vegetation, wildlife, disturbance regime, etc.), climate also has numerous management 

consequences and implications. Climate was selected by the SWAN I&M program as a high-priority 

Vital Sign for southwest Alaska parks (Davey et al. 2007). ANIA’s climate is described as 

“transitional between polar (tundra climate) and maritime (maritime subarctic)” (Lindsay 2013, p. 1). 

Winter temperatures are cold, while summer temperatures are somewhat moderated by nearby open 

water (e.g., Bering Sea and Gulf of Alaska) (Lindsay 2013). 

The climate of ANIA and southwest Alaska as a whole is influenced by its high latitude, varying 

topography, and location near the ocean, as well as atmospheric and oceanic circulation patterns 

(NPS 2011). Two patterns of particular importance are the Aleutian Low and the Pacific Decadal 

Oscillation (PDO) (Lindsay 2013). The Aleutian Low is a “semi-permanent low pressure center” in 

the Gulf of Alaska that influences storm tracks and, therefore, variability in precipitation (Lindsay 

2013, p. 2; Bennet et al. 2006). The PDO, which is related to sea surface temperatures in the northern 

Pacific Ocean, affects atmospheric circulation patterns and alternates between positive and negative 

phases (Wendler and Shulski 2009). A positive phase is associated with a relatively strong low 

pressure center over the Aleutian Islands, which moves warmer air into the region, particularly 

during the winter (Wendler and Shulski 2009). Some of the variation in Alaska’s climate over time 

can be explained by major shifts in the PDO which occurred in 1925 (negative to positive), 1947 

(positive to negative), and 1977 (negative to positive) (Mantua et al. 1997). Hartmann and Wendler 

(2005) found that much of the warming that occurred in Alaska during the last half of the twentieth 

century was influenced by the PDO shift in 1976-77. Temperatures in southwestern Alaska are also 

influenced by the El Niño Southern Oscillation (ENSO) (Lindsay 2013). 

4.8.2 Data and Methods

No weather or climate monitoring stations have ever operated in ANIA (Davey et al. 2007). The 

nearest available climate data is from two Remote Automated Weather Stations (RAWS) 

approximately 21 km (13 mi) northeast of the park. One of the stations (Yantarni Bay) was not 

established until 2010; the other (Mother Goose) operated for several years in the early 2000s and 

was re-established in 2010. Climate data for these stations were obtained through the Western 

Regional Climate Center website (WRCC 2013). In the past, climate conditions in the ANIA region 

were estimated using data from an Automated Weather Observing System (AWOS) monitoring 

station at Port Heiden, approximately 20 km (12.5 mi) west of the park. Temperature data for this 

station from 2008-2011 was provided by the NPS. 

The NPS also provided GIS climate data for Alaska from the Parameter Regression on Independent 

Slopes Model (PRISM). PRISM was developed “to address the extreme spatial and elevation 

gradients exhibited by the climate of the western U.S.” (Davey et al. 2007, p. 20). The model is 

initialized using climatological normals from stations where actual data are available. It incorporates 

the “scale-dependent effects of topography” into estimates of climate metrics (i.e., temperature and 
83 

precipitation) and can be useful in remote areas where little or no climate data has been gathered 

(Davey et al. 2007, p. 20). The available PRISM data provides temperature and precipitation means 

for the period 1971-2000. 

Lindsay (2013) provides weather information for the SWAN region in 2012, comparing it to longer 

term climate patterns in the area. The status of climate patterns (e.g., PDO, ENSO) and their potential 

influence on weather variables are also discussed as well. Lindsay (2013) also raises concerns 

regarding the collection of winter (November - April) precipitation data at RAWS stations. These 

stations utilize unheated tipping buckets to collect precipitation and are only accurate in measuring 

liquid precipitation, not snow or snow water equivalent (Lindsay 2013). Sometimes ice or snow that 

has been stored in the gauge for weeks or even months suddenly melts, resulting in a “delayed” 

report of precipitation. Buckets can also shake during high winds and cause false precipitation 

reports. Lindsay (SWAN Physical Scientist, email communication, 28 March 2013) believes that 

precipitation readings taken when the temperature is below -0.5°C (31.1°F) or when the wind is 

above 126 km/hr (78 mi/hr) are likely not reliable.

4.8.3 Current Condition and Trend

Temperature 

The mean annual temperatures in the ANIA region for the period 1971-2000, according to PRISM 

data, are presented graphically in Plate 13. It is important to remember that these values are based on 

modeling rather than actual ground observations. Mean annual temperatures within the park 

boundary ranged from approximately -3.2°C to 4.4°C. 

Monthly mean temperature data for the AWOS station at Port Heiden and for the two RAWS stations 

near the park are presented in Table 19 - Table 21. An overall mean for each month during the period 

of data collection is also included. The final column of each table shows the monthly mean 

temperatures for each location according to 1971-2000 PRISM data (PRISM 2010). Monthly mean 

temperatures across all stations ranged from -7.5°C at Port Heiden in January to 11.6°C at Yantarni 

Bay in August (WRCC 2013). The coldest temperature recorded during the period of record was -

31.7°C at Mother Goose in January 2012, while the highest temperature (23.3°C) was observed at 

Yantarni Bay in June 2012. The minimum and maximum temperatures for each monitoring station 

during the period of record are shown in Table 22. 
84 

Table 23. Port Heiden monthly mean temperature (°C) by year and the mean from Oct. 2008-Sept. 2011, 

according to AWOS data (NCDC 2010, 2013). The final column shows 1971-2000 monthly means 

according to PRISM data (PRISM 2010). 

Month 2007 2008 2009 2010 2011 2012

Mean

(2007-12)

1971-

2000 

Mean

Jan. -5.1 -9.1 -7.8 -6.2 -3.3 -13.2 -7.5 * -4 

Feb. -1.1 -9.1 -4.2 -3.9 -3 -1.5 -3.8 -4.6

Mar. -11.2 -6.1 -5.8 -7 -3.7 -9.5 -7.2 * -2.3

Apr. 2.6 -1.8 -0.2 -1.4 0.2 0.2 -0.1 0.7

May 4.1 4.1 4.2 3.4 5.6 2.1 3.9 * 5

June 4.5 6.9 8.4 7.5 7.6 5.5 6.7 * 8.6

July 8.5 8.9 11.5 9.6 9.2 8.7 9.4 * 11.1

Aug. 11.5 9.7 10.3 10.4 10.3 10.8 10.5 * 11.7

Sept. 8.1 8.6 8.6 9.4 8.6 7.7 8.5 9.1

Oct. 3.3 1.9 4.8 3.3 4.9 2.9 3.5 3.6

Nov. 0.9 -3.9 -2.8 -0.2 -2.5 -3.4 -2.0 * -0.4

Dec. -1.7 -1.9 -0.4 -7.6 -1.3 -7.3 -3.4 -2.6

* Indicates months where recent AWOS data means are 1° colder than PRISM means (also 

highlighted in dark grey).

Table 24. Yantarni Bay monthly mean temperature (°C) by year and the mean over all years of available 

RAWS data (WRCC 2013). 

Month 2010 2011 2012 2013

Mean

(2010-13)

1971-2000 

Mean

Jan. -- 0.4 -9.3 0.2 -2.9 -2.0

Feb. -- -1.8 -1.0 -0.6 -1.1 1 -2.3

Mar. -- -0.3 -5.9 -- -3.1 * -0.6

Apr. -- 1.3 2.9 -- 2.2 2.7

May -- 5.9 4.8 -- 5.3 6.3

June -- 8.3 9.9 -- 9.1 9.6

July -- 10.3 10.4 -- 10.3 * 12.0

Aug. 11.8 -- 11.5 -- 11.6 12.4

Sept. 9.9 7.2 8.1 -- 8.4 * 9.9

Oct. 4.2 5.2 3.8 -- 4.4 4.9

Nov. 0.7 -2.2 -2.5 -- -1.3 * 1.2

Dec. -4.9 -2.2 -4.2 -- -3.8 * -1.3

* Indicates months where recent AWOS data means are 1° colder than PRISM means (also 

highlighted in dark grey).

1 Indicates months where recent AWOS data means are 1° warmer than PRISM means (also 

highlighted in light grey).
85 

Table 25. Mother Goose monthly mean temperature (°C) by year and the mean, 2010-2013 (WRCC 

2013). 

Month 2010 2011 2012 2013

Mean

(2010-13)

1971-2000 

Mean

Jan. -- -2.3 -16.8 -1.1 -6.7 -7.2

Feb. -- -3.9 -1.7 -2.2 -2.6 1 -6.9

Mar. -- -3.8 -8.5 -- -6.2 * -3.6

Apr. -- 0.2 1.2 -- 0.7 0.3

May -- 6.1 3.8 -- 4.9 * 6.0

June -- 7.8 7.7 -- 7. 7 * 9.3

July 10.5 -- 10.1 -- 10.3 * 12.0

Aug. 11.2 -- 11.4 -- 11.3 12.2

Sept. 9.7 6.4 8.0 -- 8.1 9.1

Oct. 2.9 4.8 2.7 -- 3.5 1 2.1

Nov. -1.0 -4.0 -6.8 -- -3.9 * -1.9

Dec. -10.1 -3.3 -7.6 -- -7.0 * -5.9

* Indicates months where recent AWOS data means are 1° colder than PRISM means (also 

highlighted in dark grey).

1 Indicates months where recent AWOS data means are 1° warmer than PRISM means (also 

highlighted in light grey).

Table 26. Minimum and maximum temperatures (°C) recorded at each of the climate monitoring stations 

near ANIA, along with the month in which they occurred (NCDC 2010, WRCC 2013). 

Port Heiden Yantarni Bay Mother Goose

Minimum -28.9 (Jan 2009) -19.4 (Feb 2012) -31.66 (Jan 2012)

Maximum 22.2 (July 2009) 23.3 (June 2012) 22.2 (June & Aug 2012)

A comparison of recent RAWS and AWOS data from the three stations near ANIA to the modeled 

temperature means from PRISM (1971-2000) shows that monthly means during the RAWS/AWOS 

period of record were often colder than PRISM means (see Table 19 - Table 21). However, it is 

unclear if this is due to actual change in temperatures over time or simply because of differences in 

methodology (i.e., RAWS/AWOS data are actual on-the-ground measurements while PRISM data 

are based on modeling). The amount of data used in calculating means also has an influence; PRISM 

means are for a 30-year period while RAWS/AWOS means in this document are based on just 3-6 

years of data.

According to Lindsay (2011), the SWAN region in 2010 was warmer and slightly drier in 

comparison to climatological normals (1971-2000), perhaps due to El Nino conditions. However, the 

region was then colder than average in 2012. Temperatures at weather stations throughout the region 

were 1.5-2.2°C cooler than the most recent 30-year climatological normals (1981-2010) (Lindsay 

2013). These cooler conditions may be related to a negative phase in the PDO, causing colder sea 
86 

surface temperatures in the Bering Sea and Gulf of Alaska, as well as a weak La Niña event (part of 

the ENSO circulation pattern) in early 2012 (JISAO 2013, NWS Climate Prediction Center 2013). 

Evidence suggests that temperatures in Alaska are typically lower than normal, particularly in the 

winter, during La Niña events (Papineau 2001). Monthly minimum, maximum, and mean 

temperatures at the Port Heiden AWOS station in 2010 and 2012 are presented in Table 23. 

Table 27. Mean minimum, mean maximum, and overall mean monthly temperatures (°C) at Port Heiden 

during the 2010 and 2012 hydrologic years (Oct.-Sept.) (Lindsay 2011, 2013).

Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sept. Year

2010

Min 2.1 -5.8 -1.9 -9.0 -6.4 -10.5 -4.8 1.0 4.3 7.4 8.1 6.2 -0.7

Max 7.4 -0.1 2.7 -3.5 -2.2 -3.6 1.6 6.4 11.0 12.3 13.1 12.4 4.8

Mean 4.9 -2.8 0.2 -6.1 -3.9 -6.9 -1.4 0.7 7.6 9.6 10.4 9.4 2.1

2012

Min 2.0 -5.8 -4.7 -17.2 -4.3 -12.1 -2.6 -0.5 2.8 6.4 8.2 4.6 -1.9

Max 7.4 0.8 0.5 -9.2 0.9 -6.6 3.7 4.7 8.5 11.5 14.1 10.3 3.9

Mean 4.8 -2.5 -1.6 -13.2 -1.9 -9.2 0.3 2.2 5.6 8.8 10.8 7.7 1.0

Precipitation

Mean annual precipitation in the ANIA region for the period 1971-2000, according to PRISM data, 

are presented graphically in Plate 14. Again, it should be noted that these values are based on 

modeling rather than actual ground observations. Mean annual precipitation within the park boundary 

ranged from 475 mm (19 in) to 2,420 mm (95 in) (PRISM 2010). 

Monthly precipitation data for each year available, as well as an overall mean, are presented for the 

RAWS stations in Table 24 - Table 25 (the AWOS station at Port Heiden did not collect precipitation 

data). The final column of each table shows the monthly mean precipitation for these locations 

according to 1971-2000 PRISM data (PRISM 2010). Yantarni Bay was generally wetter than Mother 

Goose, averaging nearly 2,000 mm (78.7 in) of precipitation a year during the period of record, 

compared to Mother Goose’s approximately 1,200 mm (47.2 in) (WRCC 2013). The wettest monthly 

measurement on record was January 2013, when Yantarni Bay received 1,514 mm (59.6 in) of 

precipitation. However, this reading may not be accurate, due to the issues with measuring winter 

precipitation discussed earlier in the data and methods section. 

Substantial differences exist between the monthly precipitation means from recent RAWS data and 

modeled means from PRISM. As with temperature means, it is unclear if this is due to actual changes 

in precipitation over time or differences in methodology (i.e., actual measurements vs. modeling). It 

is also important to keep in mind that winter precipitation data from RAWS stations may also be 

inaccurate, due to their ability to measure only liquids (Lindsay 2013). 
87 

Table 28. Yantarni Bay monthly precipitation (mm) by year and the mean over all years of available 

RAWS data (WRCC 2013). The final column shows 1971-2000 monthly precipitation according to PRISM 

data (PRISM 2010). Annual totals were not calculated for years with missing monthly data.

Month 2010 2011 2012 2013 Mean (2010-13) 1971-2000 Mean

Jan. -- 266.7 51.6 1,514.0 610.8 130.9

Feb. -- 121.7 162.3 172.0 152.0 102.1

Mar. -- 30.7 27.4 -- 29.0 98.9

Apr. -- 218.4 120.9 -- 169.7 80.4

May -- 300.2 122.4 -- 211.3 100.6

June -- 209.0 33.3 -- 121.2 65.7

July -- 6.4 118.6 -- 62.5 72.5

Aug. 9.4 -- 91.2 -- 50.3 101.5

Sept. 222.5 33.8 202.2 -- 152.8 155.8

Oct. 135.9 205.7 92.5 -- 144.7 142.1

Nov. 90.4 113.8 107.9 -- 104.0 169.6

Dec. 52.8 240.5 183.1 -- 158.8 142.4

Annual total -- -- 1,313.4 -- 1,967.1 1,362.6

Table 29. Mother Goose monthly precipitation (mm) by year and the mean over all years of available 

RAWS data (WRCC 2013). The final column shows 1971-2000 monthly precipitation according to PRISM 

data (PRISM 2010). Annual totals were not calculated for years with missing monthly data.

Month 2010 2011 2012 2013

Mean

(2010-13)

1971-2000 

Mean

Jan. -- 223.3 37.3 538 266.2 57.3

Feb. -- 215.6 11.9 58.7 95.4 38.8

Mar. -- 36.8 0 -- 18.4 44.7

Apr. -- 462.0 0 -- 231 40.2

May -- 163.1 0 -- 81.6 47.8

June -- 32.3 0 -- 16.1 52.5

July 2.3 -- 69.9 -- 36.1 57.6

Aug. 0.5 -- 65.5 -- 33.0 68.9

Sept. 60.5 189.7 121.4 -- 123.8 99.5

Oct. 136.1 139.4 19.1 -- 98.2 93.4

Nov. 48.8 101.1 26.9 -- 58.9 70.3

Dec. 50.6 193.0 99.6 -- 114.4 64.4

Annual total -- -- 414.3 -- 1,173.1 735.5
88 

During the 2010 hydrologic year (Oct. 2009-Sept. 2010), the SWAN region was slightly drier than 

normal, receiving 75-97% of the typical annual precipitation (Lindsay 2011). In the 2012 hydrologic 

year (Oct. 2011-Sept. 2012), the southern part of the SWAN region experienced above average 

precipitation, with 126-142% of typical annual precipitation (Lindsay 2013). According to the Alaska 

Climate Research Center (ACRC 2012), much of southern Alaska experienced record-high snowfall 

during the winter of 2011-2012. 

Threats and Stressor Factors 

There is a scientific consensus that human activities, particularly those that produce greenhouse 

gasses (e.g., fossil fuel burning), have contributed to a general warming trend in global climate 

(IPCC 2010). Climate models predict that change will be greatest at higher latitudes, like in Alaska 

(NPS 2011). In the ANIA region, temperatures are projected to increase approximately 1°F (about 

0.6°C) per decade over the next century (SNAP et al. 2009). Winter temperatures may change more 

dramatically, increasing by 10°F (about 6°C) by 2080 (SNAP et al. 2009). Precipitation is predicted 

to increase, yet increased evapotranspiration due to warmer temperatures and a longer growing 

season will likely lead to an overall drier climate (SNAP et al. 2009). Potential impacts of these 

changes in southwest Alaska parks include reduced snowpack and a longer growing season, which 

could affect plant phenology and productivity, wildlife distribution and mating cycles, water 

availability, and recreational and subsistence activities (e.g., hunting, fishing) (SNAP et al. 2009, 

NPS 2011). 

Data Needs/Gaps

No climate data have been collected within ANIA boundaries. Establishing a climate monitoring 

station within the park would provide data that are more reliable and accurate, as opposed to relying 

on data from nearby monitoring stations that may not reflect the specific climate within the park. 

However, if this is not feasible, it will be important to continue gathering data from the two RAWS 

stations just northeast of the park. This information will help identify the range of climate variability 

in the area and if any changes are occurring over time, perhaps in connection with global climate 

change. Further studies may be needed explore how changes in climate will impact other park 

resources (e.g., vegetation and wildlife, water regime, etc.). 

Overall Condition 

Due to a lack of climate data collected within ANIA boundaries it is difficult to assess the current 

condition of climate in the park. Data from just outside the park and the greater region suggest that 

temperatures have been slightly cooler over the last decade in comparison to 30-year normals, 

perhaps due to a negative phase in the PDO. However, climate models predict that Alaska will 

become warmer and drier over the next century, which is a cause for concern regarding the effects on 

resources in the park. 

4.8.4 Sources of Expertise

Chuck Lindsay, SWAN Physical Scientist
89 

4.8.5 Literature Cited

Alaska Climate Research Center (ACRC). 2012. Historical monthly summaries. 

http://akclimate.org/AKCityClimo/AK_Climate_Sum.html (accessed 15 April 2013). 

Bennett, A. J., W. L Thompson, and D. C. Mortenson. 2006. Vital Signs monitoring plan Southwest 

Alaska Network. National Park Service, Anchorage, Alaska 

Davey, C. A., K. T. Redmond, and D. B. Simeral. 2007. Weather and Climate Inventory, National 

Park Service, Southwest Alaska Network. Natural Resource Technical Report 

NPS/SWAN/NRTR—2007/045. National Park Service, Fort Collins, Colorado. 

Hartmann, B., and G. Wendler. 2005. The significance of the 1976 Pacific climate shift in the 

climatology of Alaska. Journal of Climate 18:4824-4839. 

Intergovernmental Panel on Climate Change (IPCC). 2010. Contribution of working groups I, II and 

III to the fourth assessment report of the Intergovernmental Panel on Climate Change. 

http://www.ipcc.ch/publications_and_data/ar4/syr/en/contents.html (accessed 25 March 2013). 

Joint Institute for the Study of the Atmosphere and Ocean (JISAO). 2013. Monthly standardized 

values for the PDO index. http://jisao.washington.edu/pdo/PDO.latest (accessed 15 April 2013). 

Lindsay, C. R. 2011. Climate monitoring in the Southwest Alaska Network: Annual report for the 

2010 hydrologic year. Natural Resource Technical Report NPS/SWAN/NRTR-2011/463. 

National Park Service, Fort Collins, Colorado. 

Lindsay, C. R. 2013. Climate monitoring in the Southwest Alaska Network: Annual report for the 

2012 hydrologic year. Natural Resource Technical Report NPS/SWAN/NRTR-2013/716. 

National Park Service, Fort Collins, Colorado. 

Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis. 1997. A pacific interdecadal 

climate oscillation with impacts on salmon production. Bulletin of the American Meteorological 

Society. 78(6):1069-1079. 

National Climatic Data Center (NCDC). 2010. Climate data for the Port Heiden AWOS monitoring 

station, 2009-2011. Excel spreadsheet received from Chuck Lindsay, September 2012. 

 National Climatic Data Center (NCDC). 2013. http://www.ncdc.noaa.gov/data-access/land-basedstation-data/land-based-datasets/automated-weather-observing-system-awos (accessed 19 June 

2013). 

National Park Service (NPS). 2011. Weather and climate resource brief. National Park Service, 

Southwest Alaska Network, Anchorage, Alaska. 
90 

National Weather Service (NWS) Climate Prediction Center. 2013. Cold and warm episodes by 

season. http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ ensoyears.shtml 

(accessed 15 April 2013). 

Papineau, J. 2001. Wintertime temperature anomalies in Alaska correlated with ENSO and PDO. 

International Journal of Climatology 21:1577-1592. 

PRISM Climate Group, Oregon State University and Alaska Region Inventory and Monitoring 

Program, National Park Service. 2010. Gridded temperature and precipitation data for Alaska for 

the 1971-2000 climatological normal. Received from Chuck Lindsay, September 2012. 

Scenarios Network for Alaska Planning (SNAP), The Wilderness Society, and National Park Service 

(NPS). 2009. Projected climate change scenarios for Aniakchak National Monument and 

Preserve. University of Alaska, Fairbanks, Alaska. 

Wendler, G., and M. Shulski. 2009. A century of climate change for Fairbanks, Alaska. Arctic. 

62(3):295-300. 

Western Regional Climate Center (WRCC). 2013. RAWS USA climate archive: Alaska. 

http://www.raws.dri.edu/akF.html (accessed 5 March 2012). 
91

Plate 13. Mean annual temperatures in the ANIA region, 1971-2000, according to PRISM data (PRISM 2010).
92

Plate 14. Mean annual precipitation in the ANIA region, 1971-2000, according to PRISM data (PRISM 2010).
93 

4.9 Human Activity

4.9.1 Description

ANIA is one of the least visited national parks. 

NPS (2013) reports that on average, less than 

500 individuals visited ANIA each year since 

1989. In the last five years, the average annual 

visitation was less than 40 individuals (NPS 

2013). Low visitation is primarily due to the 

remoteness of the park. Access to the park is 

restricted to aircraft or boat, as there are no 

roads within park boundaries. In addition, NPS 

does not maintain facilities or trails within the 

park. Whitewater rafting from the Aniakchak 

Caldera to the ocean is one of the most common 

activities within the park (Photo 15). 

4.9.2 Specific Analysis

For this component, available datasets were used to provide an overview of visitor use in the park. 

The Commercial Use Authorization (CUA) database was the primary source of information for this 

analysis (NPS 2012). In addition, data available online via the NPS Integrated Resource Management 

Application (IRMA) (NPS 2013) provided general summaries of park usage. 

4.9.3 Data and Methods

Queries were developed to extract data from the CUA database to better understand location of 

human activities within ANIA. Queries were dynamic when possible, to enable future use. Queried 

data were linked to ArcGIS via a SQL Server connection. Data were joined to Visitor Use Location 

GIS data received from SWAN. Using linked data, appropriate maps were developed to display 

visitor use patterns in the park. 

4.9.4 Current Condition and Trend

Yearly Visitation by Park Location 

Visitation in ANIA is extremely limited (Table 26); the park consistently ranks among the five least 

visited sites out of more than 350 NPS units (NPS 2013). To date, NPS (2013) has recorded a 

maximum of 1,638 visitors to ANIA during any year; this occurred during 1992. During multiple 

years, NPS (2013) indicates that no visitors have utilized the park. From 2006-2012, fewer than 100 

visitors used park resources each year. 

SWAN NPS visitor use data include four distinct visitor use areas in ANIA where the CUA database 

identifies visitor use during 2005-2012: Amber Bay, Aniakchak Bay, Aniakchak Caldera, and Cinder 

River (Plate 15). According to the CUA database, the Aniakchak Caldera received the most visitor 

days from 2005-2012, followed by Amber Bay and Aniakchak Bay (Table 27, Plate 16). Of 

identified activities in CUA records, sport fishing was the activity that visitors to the park engaged in 

Photo 15. Rafting the Aniakchak River (NPS photo 

by Troy Hamon).
94 

most, with 95 visitor days from 2005-2012. Unspecified activities was the second most prevalent 

category of visitor use according to the CUA database from 2005-2012 (Table 28). 

Table 30. ANIA yearly visitation, 1989-2011 (NPS 2013).

Year

Number of 

Visitors

1989 853

1990 967

1991 1,469

1992 1,638

1993 1,593

1994 1,193

1995 0

1996 0

1997 0

1998 209

1999 377

2000 251

2001 206

2002 241

2003 154

2004 285

2005 285

2006 60

2007 26

2008 10

2009 14

2010 62

2011 57

2012 19

Table 31. Yearly visitor days, by park location, from SWAN CUA database (NPS 2012).

Location Name 2012 2011 2010 2009 2008 2007 2006 2005

Amber Bay - - - 4 22 39 8 -

Aniakchak Bay - - - 46 - 2 15 -

Aniakchak Caldera - - 22 53 4 7 14 146

Cinder River - - - - - - 7 -

Meshik River - - - - 9 - - -

Other - - - 18 - - 5 -
95 

Table 32. Total visitor days, by activity, from SWAN CUA database, 2005-2012 (NPS 2012).

Location 

Name

Not 

Specified

Sport 

Fishing Photography

Bear 

Viewing

Boating 

Trip

Backpacking/ 

Camping Air Taxi

Amber Bay - 47 - 22 - - 2

Aniakchak 

Bay 12 21 - - - 8 19

Aniakchak 

Caldera 48 20 4 - - 12 40

Cinder River - 7 - - - - -

Other - - - 5 12 - 3

Regarding seasonality of park visitation, the months of June through September are the only months 

with visitation on record, according to the CUA database. Of those, September is the month with the 

highest visitation, totaling 165 visitor days in the park from 2005-2012 (NPS 2012). 

Table 33. ANIA visitor days by month from SWAN CUA Database, 2005-2012 (NPS 2012).

Location Name June July August September

Amber Bay - - - 73

Aniakchak Bay 12 5 25 21

Aniakchak Caldera 18 85 95 48

Cinder River - 4 - 3

Meshik River - - - 9

Other 12 - - 11

Total 42 94 120 165

Threats and Stressor Factors 

Threats and stressors do not apply to this topic. 

Data Needs/Gaps

Data are currently sufficient for this component. 

Overall Condition 

Overall, visitation and human activity are minimal in the park.

4.9.5 Sources of Expertise

Troy Hamon, KATM/ANIA Chief of Resources 

4.9.6 Literature Cited

National Park Service (NPS). 2012. SWAN CUA Database. Received October 2012 from SWAN. 

National Park Service (NPS). 2013. National Park Service visitor use statistics. Available at 

https://irma.nps.gov/Stats/Reports/ReportList (accessed 24 January 2013). 
96

Plate 15. SWAN visitor use monitoring areas. 
97

Plate 16. Total visitor days by park location from SWAN CUA Database, 2005-2012 (NPS 2012). 
98 

4.10 Glaciers

4.10.1 Description

Glaciers are large persistent bodies of ice that 

flow under the influence of gravity (Marshak 

2005). The formation of a glacier requires three 

conditions: abundant snowfall, cool summer 

temperatures, and the gravitational flow of ice 

(NPS 2010). Glaciers occur in ANIA but are 

not considered to be a significant land cover 

type in the park (Giffen and Lindsay 2011). 

Giffen and Lindsay (2011, p.8) describe the 

glaciers in ANIA to be “small hanging/cirque 

glaciers of very limited extent that occur inside 

the Aniakchak crater on the very steep north 

aspect of the southern portion of the crater” 

(Photo 16, Plate 17). Arendt et al. (2012) 

confirms that the ice fields in the Aniakchak Caldera are the only permanent ice fields found in 

ANIA.

Glaciation begins with the accumulation of fresh, loosely packed snow containing 90% air, due to the 

space created by its hexagonal crystals (Marshak 2005). As new layers of snow accumulate on top of 

the old snow, pressure increases from the weight, squeezing out air pockets and, over time, 

transforming the snow into a packed granular material called firn, which contains only 25% air 

(Marshak 2005). As melting occurs, water recrystallizes in the spaces between grains until the firn is 

transformed into a solid mass of glacial ice containing only 20% air (Marshak 2005). 

Glacier mass balance studies determine the difference between the annual accumulation (all 

processes that add to the mass, i.e., snowfall) and ablation (all processes that remove mass, i.e., 

sublimation, melting, and calving) of a glacier during a mass balance year (Veins 1995, NPS 2010, 

Cogley et al. 2011). Mass balance studies can provide information on the stability of glaciers, runoff 

predictions, and a measurement of climatic variation and trends (Muirhead 1978). A mass balance 

year is 12 months long, beginning during the accumulation season and lasting until the end of the 

ablation season (Cogley et al. 2011). A mass balance year is dependent upon elevation and some 

glacial areas in southwest Alaska can experience ablation until late November and accumulation into 

late August; for simplicity a mass balance year is often tied into the water year (Lindsay, pers. 

comm., 2012). If the rate of accumulation is higher than that of ablation, the glacier will thicken, 

advance, or both. However, if the rate of ablation is higher than that of accumulation, the glacier will 

retreat (Marshak 2005). The accumulation zone is the area on a glacier where more mass is gained 

than lost, whereas the area where more mass is lost than gained is known as the ablation zone (Figure 

1, Cogley et al. 2011). The accumulation area ratio (AAR) represents the ratio of the accumulation 

zone to the area of the glacier at the end of a mass balance year (Cogley et al. 2011). 

Photo 16. The Aniakchak Caldera area in ANIA 

(NPS photo).
99 

Figure 1. Illustration of a glacier showing the accumulation zone, ablation zone, and equilibrium line 

(Valentine et al. 2004).

Glacier firn lines define the boundary between the melting ablation zone and the snow-covered 

accumulation zone. Late summer is the end of the ablation season, and during this time, the late 

summer firn line reaches its highest elevation, called the annual firn line. The annual firn line is 

closely related to the equilibrium line, which separates the accumulation zone from the ablation zone 

(Figure 1, Muirhead 1978). The equilibrium line altitude (ELA) is the spatially averaged altitude of 

the equilibrium line at the end of a mass balance year (Cogley et al. 2011). The position of the firn 

line varies depending on the season. During winter, snow covers the entire glacier. As spring thaw 

occurs, the firn line moves up the glacier. The amount of accumulation, combined with the ablation 

rate, determine how far the firn line will move up the glacier before the cycle repeats (Muirhead 

1978). 

4.10.2 Measures

• Area 

• Rate of terminus movement 

4.10.3 Reference Conditions/Values

IKONOS imagery taken in 2005 provides a reference of the glacial areas in ANIA (Robertson 2011). 

4.10.4 Data and Methods

Giffen and Lindsay (2011) provide a general description of the glacial area in ANIA. IKONOS 

imagery was taken over ANIA in 2005 in an effort to define the glacial areas in the park (Giffen and 

Lindsay 2011). 
100 

Loso et al. (2012) provides the first quantitative data for glaciers in ANIA. Interpolation of historic 

map data from 1957 to 1962 provides a benchmark for comparison to the glacial extent data collected 

in fulfillment of this publication. 

4.10.5 Current Condition and Trend

Area 

General glacial areas in ANIA were defined using IKONOS imagery in 2005 (Giffen and Lindsay 

2011). Personal observation from area experts estimate that glacial extent in ANIA does not exceed 2 

km2

 (0.8 mi2)(Bruce Giffen, NPS Alaska Region Geologist, pers. comm., 2012). According to Giffen 

and Lindsay (2011), the only know glaciated area was inside the caldera within the monument 

portion of ANIA. Loso et al. (2012) report the glacial coverage in ANIA to be minimal as well, 

covering approximately 4.4 km2

 (1.7 mi2) (Table 30). Glacial areas continue to be small and located 

on shaded, north-facing slopes of the caldera (Loso et al. 2012). The glaciers within the caldera grew 

or were not mapped originally, based on the most resent glacial extent report for ANIA. Very small 

glacial areas located outside the caldera on the eastern side of ANIA retreated since the 1950s (Loso 

et al. 2012). Imagery from Loso et al. (2012) indicates that no tidewater glaciers are present in ANIA 

and most of the glacial area in ANIA is comprised of a single 3-km2 glacier. 

Table 34. Extent of glaciers located in ANIA (Loso et al. 2012).

Time Period

Number of 

Glaciers

Total Glacier 

Area (km2)

Estimated 

Volume* (km3) 

Historic Map Date 

(1957-1962) 29 4.1 0.5

Modern (post-2000) 19 4.4 1.1

Absolute Change -10 0.3 0.5

Percent Change -34% 8% 106%

* Volumes and volume changes are preliminary and subject to change. They are derived from 

area/volume scaling (Bahr et al. 1997) using coefficient/exponent values of 0.2055/1.375 from Radic 

and Hock (2010).

Glacial recession in ANIA and other SWAN parks on the Southwest Alaskan Peninsula has been 

observed in recent glacial extent reports. Above average yearly temperatures and the predictions that 

these average temperatures will continue to increase in the SWAN parks region is a threat to the 

longevity of the small glaciated areas in ANIA. 

Rate of Terminus Movement 

Study of the rate of terminus movement defines the behavior of the glaciers in a particular region. 

Terminus movement data help quantitatively define the implications of climate change on the 

glaciers of a region. No data regarding rate of terminus movement are available for glaciers in ANIA. 
101 

Threats and Stressor Factors 

Climate Change 

Climate is one of the most important factors influencing ecosystems. In Alaska, climate is constantly 

fluctuating on multiple temporal scales, including several natural cycles. One climate fluctuation of 

particular importance in Alaska is the Pacific Decadal Oscillation (PDO) (Lindsay 2011). Mantua et 

al. (1997) formally identified this pattern of climate variability in a study relating climate oscillation 

to salmon production. The PDO, which is related to sea surface temperatures in the northern Pacific 

Ocean, affects atmospheric circulation patterns and alternates between positive and negative phases 

(Wendler and Shulski 2009). A positive phase is associated with a relatively strong low pressure 

center over the Aleutian Islands, which moves warmer air into the state, particularly during the 

winter (Wendler and Shulski 2009). Some of the variation in Alaska’s climate over time can be 

explained by major shifts in the PDO which occurred in 1925 (negative to positive), 1947 (positive to 

negative), and 1977 (negative to positive) (Mantua et al. 1997). Hartmann and Wendler (2005) found 

that much of the warming that occurred in Alaska during the last half of the twentieth century was 

likely due to the PDO shift in 1976-77.

Over the time period of 1949 to 2008, an increase of summer and winter temperatures was reported 

from two different long-term climate stations located in SWAN park regions (Lindsay 2011). The 

mean annual temperature over this time period has increased by 2.1°C (3.8°F) in King Salmon, 

Alaska and 2.2°C (4.0°F) in Homer, Alaska (Lindsay 2011). The SWAN park region average annual 

temperatures are predicted to continue increasing by about 0.56°C (1.0°F) per decade (SNAP 2008). 

Data Needs/Gaps

Glacier mapping is scheduled to be repeated every 10 years in other SWAN parks on the Southwest 

Alaskan Peninsula to monitor the glacial extent of the region (Arendt et al. 2012). Arendt et al. 

(2012) did not visit the glaciers of ANIA during the previous status and trend assessment of Alaska 

National Park Glaciers; therefore, ANIA glaciers were not studied until the most recent publication 

from Loso et al. (2012). 

Overall Condition 

Given that minimal quantitative data exist regarding the glaciers of ANIA, the condition of this 

component cannot be assessed at this time. An increase in average yearly temperature has been 

identified and is predicted to continue in the SWAN parks region. Since no previous quantitative data 

exist for the glaciers in ANIA, the effects of regional temperature increases cannot be calculated. 

Trends identified by Loso et al. 2012 indicate that the glaciers located on the north-facing slopes of 

the caldera have shown advance since the historic mapping period while glaciers located outside the 

caldera of ANIA have retreated during that time. 

4.10.6 Sources of Expertise

Bruce Giffen, NPS Alaska Regional Office Geologist

Chuck Lindsay, NPS Physical Science Technician
102 

4.10.7 Literature Cited

Arendt, A., C. Larsen, M. Loso, N. Murphy, and J. Rich. 2012. Alaskan National Park glaciers: status 

and trends. Second progress report. Geophysical Institute. University of Alaska-Fairbanks, 

Fairbanks, Alaska. 

Bahr, D. B., M. F. Meier, and S. D. Peckham. 1997. The physical basis of glacier volume-area 

scaling. Journal of Geophysical Research 102:20355-20362. 

Cogley, J. G., R. Hock, L. A. Rasmussen, A. A. Arendt, A. Bauder, R. J. Braithwaite, P. Jansson, G. 

Kaser, M. Möller, L. Nicholson, and M. Zemp. 2011. Glossary of glacier mass balance and 

related terms. IHP-VII Technical Documents in Hydrology No. 86, IACS Contribution No. 2. 

UNESCO International Hydrological Programme, Paris, France. 

Giffen, B. A., and C. R. Lindsay. 2011. Glacier monitoring in the Southwest Alaska Network: 

Volume 1. Natural Resource Report NPS/SWAN/NRR—2011/293. National Park Service, Fort 

Collins, Colorado. 

Hartmann, B., and G. Wendler. 2005. The significance of the 1976 Pacific climate shift in the 

climatology of Alaska. Journal of Climate 18:4824-4839. 

Lindsay, C. 2011. Climate monitoring in the Southwest Alaska Network: Annual report for the 2011 

hydrologic year. National Park Service, Southwest Alaska Network, Anchorage, Alaska. 

Loso, M. 2012. Alaskan National Park glaciers: status and trend. Third progress report. National Park 

Service, Fort Collins, Colorado. 

Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis. 1997. A Pacific interdecadal 

climate oscillation with impacts on salmon production. Bulletin of the American Meteorological 

Society 78(6):1069-1079. 

Marshak, S. 2005. Amazing ice: glaciers and ice ages. Pages 681-718 in Earth: portrait of a planet. 

W. W. Norton & Company, Inc., New York, New York.

Muirhead, B. 1978. Glacier annual firn lines in the Kenai Mountains of Alaska as derived from 

satellite imagery: measurement, evaluation of influencing factors, and some multiple regression 

prediction models. Thesis. University of Maryland, College Park, Maryland. 

National Park Service (NPS). 2010. Glaciers/Glacial Features. Available at 

http://www.nps.gov/kefj/naturescience/glaciers.htm (accessed 11 April 2011). 

Radic, V., and R. Hock. 2010. Regional and global volumes of glaciers derived from statistical 

upscaling of glacier inventory data. Journal of Geophysical Research. 

115:doi:10.1029/2009JF001373 
103 

Robertson, A. 2011. Orthorectification of historic imagery for Kenai Fjords National Park and 

Aniakchak National Monument and Preserve. Natural Resource Technical Report 

NPS/SWAN/NRTR—2011/481. National Park Service, Fort Collins, Colorado. 

Scenarios Network for Alaska Planning (SNAP). 2008. Climate change summary reports: Aniakchak 

National Monument and Preserve, Katmai National Park and Preserve, Kenai Fjords National 

Park and Preserve, and Lake Clark National Park and Preserve. Available from 

http://www.snap.uaf.edu/downloads/climate-change-summary-reports (accessed 15 November 

2009). 

Valentine, V., K. Echelmeyer, S. Campbell, and S. Zirnheld. 2004. Harding Icefield’s clues to 

climate change. Alaska Park Science 3(1):13-17. 

Viens, R. J. 1995. Dynamics and mass balance of temperature tidewater calving glaciers of southern 

Alaska. Thesis. University of Washington, Seattle, Washington. 

Wendler, G., and M. Shulski. 2009. A century of climate change for Fairbanks, Alaska. Arctic 

62(3):295-300. 
104

Plate 17. Glaciated areas of the Aniakchak Caldera in ANIA.
105 

4.11 Water Quality 

4.11.1 Description

Aquatic systems within SWAN units are remote 

and pristine; this results in an opportunity for 

researchers to examine the effects of man-made 

disturbances, namely climate change and 

atmospheric pollutants, on intact systems. 

Currently, water quality data for SWAN units 

such as ANIA are minimal, but a monitoring 

plan exists. Specifically, SWAN intends to 

examine lake water quality parameters (Photo 

17), both physical and chemical, along with 

data regarding other Vital Signs (e.g., surface 

hydrology, lake ice phenology, and glacial 

extent) to develop a more complete 

understanding of watershed dynamics (NPS 

2012). 

Water quality analysis of physical and chemical 

characteristics can be important in understanding the aquatic community of a water body (NPS 

2012). Researchers may use water quality analysis to explain the absence or extirpation of fish 

communities in habitats that appear suitable to sustain productive fish communities. Many ANIA 

fisheries investigations involved water quality data collection as well. Most water quality data for 

ANIA come from sampling efforts at Surprise Lake, and the Meshik Lake/Meshik River Drainages. 

However, the data pool for these areas is sparse and water quality sampling has not been conducted 

in most of the drainages in ANIA. Surprise Lake, located in the Aniakchak Caldera, is 

hydrothermally active, a characteristic also shared by several of its tributaries. The unique nature of 

the Surprise Lake region has contributed to more frequent water quality investigations in this area 

than in other ANIA water bodies. 

Prior to analysis of this component, SWAN aquatic ecologist Claudette Moore (pers. comm. 2012) 

suggested that gathering existing data sources and producing data tables for future use was the most 

useful exercise for the NRCA. Through data and literature searches, past water quality reports for 

ANIA were collected and data were input into tables according to guidance by NPS. Within this 

component section, a summary of data sources and tables are provided for the reader. Because 

recently collected data are minimal, an assessment of condition is not provided for this component. 

4.11.2 Measures

This assessment does not focus on specific metrics for assessing water quality. Rather, literature 

sources for ANIA that include water quality parameters are summarized individually to provide the 

reader with a history of water quality data collection in the park. These results are presented in the 

Data and Methods section. 

Photo 17. Water quality data collection in an 

Alaskan water body (NPS photo).
106 

4.11.3 Data and Methods

Bennett (2004) collected baseline information regarding physical and chemical water quality 

characteristics in ANIA as part of an initiative by the NPS I&M Vital Signs program to collect data 

in areas that have been largely unstudied. Water quality analyses were performed on samples from 

the following areas during a fisheries investigation to help explain the lack of fish production in 

seemingly suitable habitat: Surprise Lake and Aniakchak River and major tributaries (29 May 2003-

13 June 2003); Meshik River, Albert Johnson Creek Headwaters, and Meshik Lake (16 June 2003-24 

June 2003); and coastal streams and the lower Aniakchak River (12 July 2003-21 July 2003). Bennett 

(2004) presents tables and figures for several parameters including temperature, dissolved oxygen, 

specific conductance, pH, alkalinity, nutrients, chlorophyll, major ions and trace elements, discharge, 

and turbidity; parameters were sampled using surface waters and a YSI 6600 multi-parameter sonde 

unit. Discharge and flow measurements were taken with a Marsh McBirney Flo-Mate 2000. 

Parameters for lab analysis included total suspended solids, total dissolved solids, major ions, 

nutrients, alkalinity, and trace metals. Bennett (2004) attempted to re-visit the sample sites defined in 

Cameron and Larson (1992); however, the sites were not georeferenced so sites were re-visited as 

close to the original locations as possible utilizing plotted maps. 

Data presented in Bennett (2004) are not historic (collected before 2000), and are well presented in 

the original document. Therefore, data from Bennett (2004) are not presented in this NRCA. 

Cameron and Larson (1993) present data collected regarding trace element concentrations at stream 

inflow sites around Surprise Lake in July and August of 1988 and 1989 (Table 31, Table 32). Various 

water quality parameters as well as chlorophyll data were also collected in Surprise Lake over these 

sampling dates (Table 33). Field analyses were performed to determine hardness, pH, conductivity, 

and total alkalinity. The values for conductivity and pH were cross-referenced with readings taken in 

the field with a Hydrolab 4000 series. Conductance, dissolved oxygen, and pH readings were 

recorded in Surprise Lake at stations WS1, WS2, RS1 and ML1 over 1-meter depth intervals. 

Cameron and Larson (1992) performed an inventory of the aquatic resources of the monument area 

in ANIA. Surprise Lake (Photo 18) and its inlet streams were sampled to determine if nine chemicals 

were within EPA standards for drinking water (Table 34). Surprise Lake was also sampled to track 

changes in temperature, dissolved oxygen (percent saturation), conductance, pH, and percentage of 

light penetration at depth (Table 34-Table 56). 
107 

Table 35. Late July and August,1988-1989, trace element concentrations of inlet streams and warm 

spring 14 at the point of entry into Surprise Lake. Data presented in minimum–maximum values

(Cameron and Larson 1993). Numbers in parentheses indicate sample size.

Variable Units Inlet 1- 4 (7) Inlet 8 (1) Inlet 9 (1) Inlet 10 (4) Inlet 11 (4) WS 14 (1)

Ca mg/L 2.67-3.54 6.93 7.87 17.23-38.18 42.44-54.48 100.55

Mg mg/L 0.4-1.76 3.67 4.45 8.65-19.47 30.96-41.25 118.07

K mg/L BD-1.43 1.56 1.96 4.04-7.16 10.49-11.56 12.36

Na mg/L 4.86-10.04 14.22 12.29 32.15-64.31 110.18-130.25 207.48

S mg/L .94-1.94 0.75 1.41 3.26-7.48 7.67-10.20 65.05

Si mg/L 3.35-12.83 10.63 13.83 10.92-27.66 8.61-15.8 25.74

Fe μg/L BD BD BD BD 60-166 46

Mn μg/L BD 9 14 54-97 435-534 1249

B mg/L BD-.04 0.06 0.19 .86-1.87 4.25-5.40 2.58

Cu mg/L BD BD BD BD BD BD

Sr μg/L BD-17 15 27 39-140 166-193 309

BD = parameter was below the detection limit

Table 36. Late July and August,1988-1989 trace element concentrations in Surprise Lake at the Warm 

Spring stations (WS1 and WS2), reference station (RS1), and the mid-lake station (ML1 at 1 and 14 m). 

Warm Spring and reference station samples taken at a depth of 1 m. Data presented as minimummaximum values of three samples (Cameron and Larson 1993).

Variable Units WS1 WS2 ML1-1m ML1-14m RS1

Ca mg/L 19.95- 27.27 15.01-21.35 8.80-21.67 12..74- 29.31 14.83- 22.78

Mg mg/L 15.10- 23.64 15.08-19.36 15.04-17.91 14.94 - 26.43 15.46- 18.70

K mg/L 4.14- 6.16 4.03- 4.83 4.11- 4.56 4.16- 5.82 4.13- 4.75

Na mg/L 42.03- 67.05 41.04-51.98 41.26-48.21 40.99- 65.75 42.91- 49.70

S mg/L 7.64- 10.66 7.98- 9.18 8.00- 9.14 7.93- 14.10 6.07- 9.83

Si mg/L 16.21- 24.90 12..11-24.01 17.36-21.25 15.50- 24.97 16.93- 24.97

Fe mg/L BD BD BD BD BD

Mn μg/L 16 -146 33 -76 6-71 16 - 74 26 -101

B mg/L 0.95- 1.82 0.89- 1.34 .90-1.08 0.89- 1.47 0.92- 1.29

Cu mg/L BD BD BD BD BD

Sr μg/L 55 -103 60 -71 39-80 48 -108 59 - 72
108 

Table 37. Water quality and chlorophyll data from Surprise Lake (Cameron and Larson 1992).

Variable Unit Surprise Lake Surprise Lake

Date N/A Aug-31-1988 Jul-30-1989

pH standard 7.3 7.5

Alkalinity mg/L 162 180

Hardness mg/L 126 132

Conductivity μmhos/cm 380 391

Turbidity N/A 2.6 3.2

TP μg/L 24.9 19.2

TFP μg/L 8.5 7.7

FRP μg/L 24.4 6.3

TKN μg/L 44.7 31.2

NH3 + NH4 μg/L N/A 16.4

NO3 + NO2 μg/L N/A N/A

Ca mg/L 16.6 8.8

Mg mg/L 15.1 15.8

K mg/L 4.3 4.1

Na mg/L 41.3 42.9

S μg/L 8 8.2

Si mg/L 17.4 18.6

Fe mg/L <.01 <.01

Cu μg/L <.01 <.01

Mn μg/L 71 6

Chlorophyll μg/L 2.32 1.69

Table 38. Concentrations of chemicals measured in μg/L that exceed drinking water standards developed 

by the U.S. EPA in the inlets of Surprise Lake (Cameron and Larson 1992).

Chemical EPA Standard Cold Inlets

Intermediate 

Inlets Warm Inlets Surprise Lake

Arsenic 50 + + + +

Cadmium 10 + + + +

Chromium 50 + + + +

Iron 300 + + 3,282 436

Lead 50 + + + + 

Manganese 50 + 64 577 62

Nickel 13 + + + +

Nitrate 10,000 + + + +

Zinc 5,000 + + + +
109 

Photo 18. Surprise Lake in the Aniakchak Caldera (NPS photo).

Table 39. Temperature (°C), dissolved oxygen (percent saturation), therapeutic pH (units), and 

conductance (mS/cm at 25° C) measured with a hydrolab in the inlet streams of Surprise Lake, Aniakchak 

National Monument, Alaska (Cameron and Larson 1992).

Date Inlet

Stream 

Section Temperature

Dissolved 

Oxygen pH Conductance

8/13/1988 I1 E fork upper 7.1 98 6.8 141.3

8/13/1988 I1 W fork upper 9.2 96.7 6.7 147.5

8/13/1988 I1 upper 9.5 91.9 6.5 101.9

8/13/1988 I1 middle 15.7 99.3 6.6 85.4

8/13/1988 I1 lower 10.2 79 6.3 90.9

8/13/1988 I1 mouth 8.3 87.9 6.2 97.9

8/13/1988 I2 source 1.8 96.9 7.2 144.7

8/13/1988 I2 middle 6.4 99.1 6.9 117.8

8/13/1988 I2 mouth 7.5 100.7 6.7 112.9

8/13/1988 I3 upper 3.2 98.7 6.7 97.3

8/13/1988 I3 middle 3.7 98.5 6.8 95.7

8/13/1988 I3 lower 4.3 94.4 7 115.4

8/13/1988 I3 mouth 4.7 98.6 7.1 117.7

8/13/1988 I4 source 2.8 98 6.9 127.1

8/13/1988 I4 middle 3.1 99.2 7.1 125.2

8/13/1988 I4 mouth 3.2 98 7.6 123.9

8/13/1988 I5 source 2 98.2 6.9 126.6

8/13/1988 I5 upper 3.1 99.6 6.9 122.6

8/13/1988 I5 middle 4.4 97.5 7 115.1

8/13/1988 I5 mouth 5.2 99.5 7 109.8
110 

Table 35 (continued). Temperature (°C), dissolved oxygen (percent saturation), therapeutic pH (units), 

and conductance (mS/cm at 25° C) measured with a hydrolab in the inlet streams of Surprise Lake, 

Aniakchak National Monument, Alaska (Cameron and Larson 1992).

Date Inlet

Stream 

Section Temperature

Dissolved 

Oxygen pH Conductance

8/18/1988 I8 lower 4.9 98.4 7 261.3

8/18/1988 I9 lower 9.1 97.4 6.9 231.2

8/18/1988 I10 lower 9 90.8 6.3 494

8/18/1988 I11 lower 21.3 13 5.6 1130

8/18/1988 WS4 WP1 23.9 5.1 5.5 1118.5

8/18/1988 WS4 WP2 20.6 4.7 5.5 1118

8/18/1988 WS4 WP3 19.9 5.8 5.5 1101.3

8/13/1988 WS14 source 15.4 10.5 5.8 1468.8

8/13/1988 WS15 source 15.7 7.9 5.8 1501.8

8/13/1988 CS2 source 2.1 97.9 7.1 130.9

8/13/1988 CS2 middle 2.5 100.7 7.1 126.4

8/13/1988 CS2 mouth 3.2 103.1 7.2 124.9

8/13/1988 CS2 marsh 2.9 104.2 7.2 123.4

8/13/1988 CS3 source 2 98.6 7.2 127.2

8/13/1988 CS3 middle 2.4 99.6 6.9 125.5

8/13/1988 CS3 mouth 3.5 103.4 6.9 121.3

8/13/1988 CS3 marsh 2.7 101.2 6.9 121.6

8/13/1988 CS23 mouth 8.4 93.5 6.9 101.1

8/13/1988 CS23 marsh 9.7 98.3 6.2 105.7

8/13/1988 CS24 middle 9.6 82.5 6.5 121.7

8/13/1988 CS24 mouth 9.2 101.2 6.8 120.8

8/13/1988 CS25 middle 7.8 91.3 6.9 101.6

8/13/1988 CS25 mouth 10.1 96 6.5 92.7

8/13/1988 CS26 mouth 11.3 106.4 6.5 109.7

Table 40. Temperature (°C) measured with a Bacharach thermometer in the inlet streams of Surprise 

Lake, Aniakchak National Monument, Alaska (Cameron and Larson 1992).

Date I1 I2 I3 I4 I5 I6 I8 I9 I10 I11 WP1

06/181988 N/A N/A 2.2 7.2 12.2 N/A

7/10/1988 - 7.8 18.1 17.5

7/19/1988 2.8 N/A N/A

7/28/1988 3.3 8.9 22.2 23.9

8/8/1988 - 6.7 11.1 10 21.1 N/A

8/9/1988 3.9 N/A 25.6

8/12/1988 3.9 N/A N/A
111 

Table 36 (continued). Temperature (°C) measured with a Bacharach thermometer in the inlet streams of 

Surprise Lake, Aniakchak National Monument, Alaska (Cameron and Larson 1992).

Date I1 I2 I3 I4 I5 I6 I8 I9 I10 I11 WP1

8/13/1988 8.3 7.5 4.7 3.3 5.4 5.2 8.9 8.9 22.1 N/A

8/18/1988 10 6.7 5 3.3 4.9 9.1 9 21.3 23.9

8/31/1988 3.3 7.5 22.2 24.4

7/30/1989 3.3 8.3 21.1 24.4

8/1/1989 6.7 5.6 6.1 3.3 6.7 6.1 10 8.9 21.1 N/A
112

Table 41. Change in temperature (°C) with depth measured with a hydrolab at Station ML1 Surprise Lake, Aniakchak National Monument, Alaska, 

1988 and 1989 (Cameron and Larson 1992). 

Depth (m) 6/18/1988 7/10/1988 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 9.7 12 13.4 12 11.7 12.9 9.7 11.6

0.5 9.5 11.5 12.8 11.9 11.7 12.7 9.8 11.5

1 9.4 11.4 12.6 11.9 11.7 12.4 9.9 11.5

2 9.3 11.2 12.4 11.8 11.6 11.7 9.9 11.5

3 9.3 11.1 12.3 11.5 11.5 11.6 9.9 11.5

4 9.2 10.8 11.8 11.5 11.4 11.5 9.9 11.5

5 8.8 10.5 11.6 11.4 11.4 11.4 9.9 11.4

6 8.6 10.4 11.1 11.4 11.4 11.4 9.9 11.4

7 8.5 10.4 11.1 11.3 11.3 11.4 9.9 11.4

8 8.3 10.3 10.8 11.2 11.3 11.3 9.9 11.4

9 8.2 10.3 10.6 11.2 11.3 11.3 9.9 11.4

10 8.2 10.2 10.6 11.2 11.3 11.3 9.9 11.4

11 8 10.1 10.5 11.2 11.3 11.3 9.9 11.4

12 8 10.1 10.5 11.2 11.3 11.2 9.9 11.4

13 8 10.1 10.4 11.2 11.3 11.2 9.9 11.4

14 7.9 10 10.4 11.1 11.3 11.1 9.9 11.4

15 7.9 9.9 10.4 11.1 11.3 11.1 9.9 11.4

16 7.8 9.9 10.3 11.1 11.2 11.1 9.9 11.3

17 7.8 9.8 10.3 11 11.1 11 9.9 11.3

18 7.8 9.6 10.2 10.9 11 10.9 9.9 11.2

19 7.7 9.5 10 10.9 11 10.7 9.9 11
113 

Table 42. Change in temperature (°C) with depth measured with a hydrolab at station RS1 Surprise Lake, 

Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 13.8 11.8 11.5 11.2 11.6 11.9

0.5 13.1 11.8 11.4 12.3 11.1 11.7

1 13 11.8 11.4 11.8 11 11.5

2 12.6 11.7 11.4 11.4 10.9 11.4

3 12.3 11.6 11.4 11.3 10.8 11.4

4 12 11.6 11.4 11.3 10.7 11.3

5 11.8 11.6 11.3 11.2 10.2 11.3

6 11.2 11.4 11.3 11.2 10.2 11.3

7 10.9 11.4 11.3 11.2 10.1 11.2

8 10.7 11.4 11.3 11.2 10 11.2

9 10.6 11.4 11.3 11.1 9.9 11.2

10 10.6 11.4 11.2 10.9 9.9 11.2

11 10.5 11.4 11.2 10.9 9.9 N/A

Table 43. Change in temperature (°C) with depth measured with a hydrolab at station WS1 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 15.2 14.7 12.7 14.9 12

0.5 15.2 14.6 12.8 13.2 12

1 14.7 14.6 11.8 12.5 11.9

2 14.1 13.4 11.5 11.7 11.6

3 13.5 12.6 11.5 11.5 11.5

4 12.8 12.1 11.4 11.4 11.5

5 12.1 11.9 11.4 11.4 11.4

6 12 11.8 11.3 11.3 11.3

7 11.7 11.7 11.3 11.3 11.3

8 10.8 11.5 11.2 11.3 11.3

9 10.8 11.4 11.2 11.3 11.3

10 10.6 11.4 11.2 11.2 11.3

11 10.5 11.4 11.2 11.2 11.3

12 N/A N/A N/A N/A 11.2

13 N/A N/A N/A N/A 11.2
114 

Table 44. Change in temperature (°C) with depth measured with a hydrolab at station WS2 Surprise 

Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 14.5 12.5 11.7 14.2 11 12.9

0.5 14.4 12.6 11.8 13 10.9 12

1 14.4 12.6 11.8 12.6 10.9 11.6

2 13.2 12.6 11.8 12.7 10.8 11.5

3 12.8 12.6 11.8 11.5 10.3 11.5

4 12.6 12 11.8 11.5 10.3 11.4

5 12 12 11.7 11.6 10.2 11.4

6 11.8 11.9 11.9 11.4 10.1 11.3

7 11.8 11.7 11.9 11.3 10.1 11.3

8 11.4 11.6 11.6 11.3 10.1 11.3

9 11.3 11.6 11.4 11.3 10.1 11.3

10 11.3 11.6 11.6 11.4 10.3 11.3
115

Table 45. Change in conductance (mS/cm at 25°C) with depth measured with a hydrolab at Surprise Lake station ML1 Aniakchak National

Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 6/18/1988 7/10/1988 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 476.8 465.8 444.4 459.1 454 446.9 475.8 478

0.5 481.7 467.1 452 460.4 454 448.2 477.2 484

1 486.2 466.3 454.3 460.8 452 451.1 477.6 485

2 487.5 469.7 458 462.5 452.6 458.6 477.5 485

3 489.3 469.9 459.3 465 452.1 459.8 477.5 484

4 490 476.8 465 465.6 451.7 461.5 477.5 485

5 494.3 479.1 468 466.3 452.3 462.1 478.1 485

6 497 478.6 473 466.9 452.4 462.7 478.1 485

7 498.4 478.6 472 468.1 452.9 462.7 478.1 485

8 502.3 478.8 474.6 467.6 452.4 463.3 477.5 485

9 504.8 478.8 477.2 468.3 451.9 464.3 477.5 484

10 504.5 480.1 477.2 468.3 451.9 462.3 476.9 484

11 505.5 483.5 477.4 467.7 451.5 462.9 476.9 483

12 505.5 482.4 477.4 467.2 451.5 463.5 476.4 483

13 505.5 480.3 478.6 467.2 450.9 460.4 475.8 482

14 506.3 480.5 477.5 466.8 450.4 461 475.8 482

15 506.5 480.8 477.5 466.3 449.8 460 475.3 482

16 506.6 478.1 477.8 466.9 448.9 459 475.3 482

17 506.6 478.2 476.7 466.9 447.5 458.6 474.8 481

18 506 481.4 476.9 467.6 447.5 459.2 474.8 480

19 505.1 483.7 477.3 467.6 447.1 463.7 475.3 477
116 

Table 46. Change in conductance (mS/cm at 25°C) with depth measured with a hydrolab at Surprise 

Lake station RS1 Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 434.2 459 450.7 451.5 471 475

0.5 439.3 459.5 450.7 451.6 463.7 480

1 438.8 459.5 450.7 458.4 464.9 483

2 443.2 460.7 450.7 462.7 466.2 484

3 447.2 462.8 450.8 462.3 466.8 485

4 453.5 463.4 450.3 462.3 466.5 486

5 459.4 463.4 448.8 463 477.5 486

6 462.5 465 448.3 463.5 477.5 485

7 470.8 465.3 450.4 463 479.4 485

8 472.7 465.3 449.4 463.6 476.2 485

9 475 165.3 449.4 463.7 476.4 484

10 475 464.6 450.5 465 474.7 484

Table 47. Change in conductance (mS/cm at 25°C) with depth measured with a hydrolab at Surprise 

Lake station WS1 Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 503.9 572 428.1 517 610.8 520

0.5 484.7 569.5 477.6 490.1 544.5 521

1 477.5 555.2 469.2 480.2 483.8 520

2 519 506.5 462.5 474.6 460.7 497

3 527.4 477.4 460.4 468.2 471.2 485

4 457 473.2 458 467.9 485 484

5 457 466.5 455.4 466.9 490 481

6 468.3 471.3 455 468.5 484.5 481

7 483.3 477.1 451.9 469.6 479.8 481

8 445.2 465.2 451 469.1 473.3 481

9 451.8 464.2 448.9 471.7 469 481

10 453.9 464.2 447.9 467.2 468.5 482

11 455.1 464.2 448.9 463 468.1 484

12 N/A N/A N/A N/A N/A 481

13 N/A N/A N/A N/A N/A 480
117 

Table 48. Change in conductance (mS/cm at 25°C) with depth measured with a hydrolab at Surprise 

Lake station WS2 Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 436.5 458.3 458.6 467.3 465.9 559

0.5 437.6 458.3 458 471.6 467.1 494

1 441.9 458.3 461 491.3 467.1 488

2 463.4 458.3 460.6 470.4 470 490

3 465 461.3 466.2 471.2 477 490

4 470.3 470.4 470.3 473.9 483.2 488

5 474.5 494.9 470.4 501.6 482.9 491

6 481 501.2 498.7 477.8 482.4 486

7 516 487.4 477.1 477.4 481.4 482

8 496 484.5 480.9 482.5 481.9 482

9 509.1 491.7 471.7 492.4 487.3 482

10 N/A N/A N/A N/A N/A 480
118

Table 49. Change in pH with depth measured with a hydrolab at station ML1 Surprise Lake, Aniakchak National Monument, Alaska,1988 and 

1989 (Cameron and Larson 1992).

Depth (m) 6/18/1988 7/10/1988 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 6.5 6.8 6.3 6.4 6.7 6.7 6 6.2

0.5 6.7 6.9 6.5 6.6 6.8 6.8 6.3 6.5

1 6.7 6.9 6.6 6.7 6.8 6.8 6.5 6.6

2 6.8 7 6.7 6.8 6.9 6.9 6.7 6.7

3 6.9 7.1 6.7 6.8 6.9 6.9 6.7 6.8

4 6.9 7 6.8 6.8 6.9 7 6.8 6.8

5 6.9 7.1 6.8 6.9 6.9 7 6.9 6.9

6 6.9 7 6.8 6.9 7 7 6.9 6.9

7 6.9 7.1 6.8 6.9 7 7 7 6.9

8 6.9 7.1 6.8 6.9 7 7 7 6.9

9 7 7.1 6.8 6.9 7 7.1 7 6.9

10 7 7 6.8 6.9 7 7 7 6.9

11 7 7 6.8 6.9 7 7.1 7 6.9

12 7.1 7 6.8 6.9 6.9 7 7 6.9

13 7.1 7 6.9 6.9 6.9 7 7 6.8

14 7.1 7 6.8 6.9 6.9 7 7 6.8

15 7.1 7 6.8 6.9 6.9 7 7 6.8

16 7 6.9 6.8 6.9 6.9 7 7 6.8

17 7 6.9 6.8 6.9 6.9 7 7 6.8

18 7 6.7 6.7 6.8 6.8 6.8 7 6.7

19 7 6.6 6.7 6.8 6.8 6.8 6.9 6.6
119 

Table 50. Change in pH with depth measured with a hydrolab at station RS1 Surprise Lake, Aniakchak 

National Monument, Alaska,1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 6.2 6.3 6.8 6.9 6.7 6.5

0.5 6.7 6.6 6.8 7 6.8 6.6

1 6.8 6.7 6.9 7 6.9 6.7

2 6.9 6.8 6.9 7 7 6.8

3 6.9 6.8 6.9 7.1 7 6.8

4 6.9 6.9 7 7.1 7.1 6.9

5 7 6.9 7 7.1 7.1 6.9

6 7 6.9 7 7.1 7.1 6.9

7 6.9 6.9 7 7.1 7.2 7

8 6.9 6.9 7.1 7.1 7.1 7

9 7 6.9 7.1 7.1 7.1 7

10 6.9 6.9 7 7 7 6.9

Table 51. Change in pH with depth measured with a hydrolab at station WS1 Surprise Lake, Aniakchak 

National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 6.1 5.9 6.2 6.3 5.8 6

0.5 6.1 6 6.1 6.2 6 6.2

1 6.2 6 6.2 6.3 6.2 6.3

2 6.5 6.2 6.4 6.5 6.4 6.4

3 6.6 6.3 6.5 6.6 6.5 6.6

4 6.6 6.5 6.6 6.7 6.6 6.6

5 6.7 6.6 6.7 6.8 6.6 6.7

6 6.6 6.6 6.7 6.8 6.6 6.7

7 6.6 6.6 6.8 6.8 6.7 6.7

8 6.7 6.7 6.8 6.8 6.7 6.8

9 6.7 6.7 6.9 6.8 6.7 6.8

10 6.7 6.8 6.9 6.8 6.7 6.8

11 6.7 6.8 6.8 6.8 6.8 6.8

12 N/A N/A N/A N/A N/A 6.7

13 N/A N/A N/A N/A N/A 6.7
120 

Table 52. Change in pH with depth measured with a hydrolab at station WS2 Surprise Lake, Aniakchak 

National Monument, Alaska,1988 and 1989 (Cameron and Larson 1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 6.6 6.1 6 6.5 6 6

0.5 6.7 6.4 6.3 6.5 6.4 6.3

1 6.7 6.5 6.4 6.4 6.6 6.3

2 6.6 6.6 6.5 6.6 6.7 6.5

3 6.7 6.7 6.5 6.7 6.8 6.6

4 6.7 6.7 6.5 6.8 6.7 6.7

5 6.7 6.7 6.6 6.7 6.8 6.7

6 6.6 6.6 6.5 6.7 6.8 6.8

7 6.6 6.6 6.5 6.7 6.8 6.9

8 6.5 6.6 6.6 6.7 6.8 6.9

9 6.5 6.6 6.6 6.7 6.8 6.9

10 N/A N/A N/A N/A N/A 6.9
121

Table 53. Change in dissolved oxygen (percent saturation) with depth measured with a hydrolab at station ML1 Surprise Lake, Aniakchak National 

Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992).

Depth (m) 6/18/1988 7/10/1988 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 105.8 104 106 102 98.5 98.9 99.3 95

0.5 101.4 103 106 99 98 97.4 97.7 94

1 97.1 103 107 97 99 96.8 96.4 94

2 95.5 102 105 97 98.4 95.4 95.5 94

3 96.1 97 105 98 97.8 95 95.1 94

4 95.7 96 105 97 96.2 94.8 94.6 93

5 94 95 104 97 95.7 94.7 94.6 93

6 93.1 95 100 97 95.1 94.6 94.2 93

7 92.9 93 98 95 94.9 94.6 93.7 93

8 92.4 92 97 94 95.4 93.5 93.7 93

9 92.2 92 97 94 94.9 93.5 93.7 92

10 92.1 92 97 94 95.4 93 93.2 92

11 91.8 92 97 94 95.3 93.4 93.7 92

12 91.8 91 95 94 94.3 92.8 93.2 92

13 91.8 89 95 91 94.8 92.3 93.2 91

14 91.5 88 95 91 94.3 92.1 93.2 91

15 91.4 88 95 91 94.3 91.6 92.8 91

16 90.9 88 95 91 94.1 92.1 92.8 91

17 90.3 88 94 91 92.9 91.9 92.5 91

18 90 85 93 87 92.4 90.7 92.5 91

19 88.4 85 85 87 91.9 88.5 91.8 90

20 N/A N/A N/A N/A N/A N/A N/A 89
122 

Table 54. Change in dissolved oxygen (percent saturation) with depth measured with a hydrolab at 

station RS1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 

1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 88 83 93 93 80.6 96

0.5 90 80 95.6 92 85 96

1 93 82 95.5 91.5 88 94

2 98 84 93.9 93.3 92.3 94

3 99 95 94.4 95.9 90.6 93

4 99 94 94.7 94.1 89.7 92

5 95 98 94.7 93.6 88.5 92

6 94 90 94.9 93.5 88.2 92

7 89 89 94.9 92.5 88.5 92

8 92 94 94.3 92.4 89 91

9 91 94 94.3 91.5 89 91

10 92 94 94.3 91.3 89 91

11 90 92 93.8 91.3 88.9 N/A

Table 55. Change in dissolved oxygen (percent saturation) with depth measured with a hydrolab at 

station WS1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 

1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 106 103 99.6 101.8 94.6 94

0.5 106 102 98.6 99.6 93.9 93

1 105 101 99.5 96.5 93.8 93

2 102 99 99.5 96 93.5 94

3 104 98 98.4 95.9 92.4 93

4 104 98 99.4 95.3 92.6 93

5 104 98 96.7 95.2 91 93

6 100 98 96.3 94.7 90.5 93

7 99 95 95.3 94.3 88.9 92

8 96 95 95.3 94.1 87.9 92

9 96 97 94.8 92 88.6 92

10 94 97 94.7 91.2 86.9 92

11 N/A N/A N/A N/A N/A 92

12 N/A N/A N/A N/A N/A 91

13 N/A N/A N/A N/A N/A 91
123 

Table 56. Change in dissolved oxygen (percent saturation) with depth measured with a hydrolab at 

station WS2 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 

1992).

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.1 106 110 101.6 95.1 100.5 92

0.5 102 107 102.2 95.1 97.3 96

1 100 105 91.6 93.3 97.3 95

2 95 105 102.2 94.4 94.7 94

3 96 102 99.3 93.9 94.1 94

4 98 98 97.9 93.8 92.1 94

5 95 96 96.3 91.1 91 93

6 92 92 93.9 91.2 90.9 93

7 86 96 94.9 90.6 90.4 93

8 86 96 86.9 90.6 89.9 93

9 86 95 93.6 89.6 90.9 93

10 N/A N/A N/A N/A N/A 93
124

Table 57. Change in light (% of light measured just below the lake surface) with depth measured with a hydrolab at station ML1 Surprise Lake, 

Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron and Larson 1992). 

Depth (m) 6/18/1988 7/10/1988 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.05 100 100 100 100 100 100 100 100

0.5 80 73.3 78.3 63.8 80.4 85.3 79.7 61.1

1 64 55 58.7 39.7 60.7 64.7 59.3 46.7

2 40 30.8 32.6 26.4 33.9 38.2 30.5 25.6

3 24 17.5 18.1 12.6 21.4 20.6 16.8 15.6

4 14.7 10 10.1 8.5 11.4 12.1 9.2 8.8

5 8.8 5.8 5.8 5.2 6.8 7.4 4.9 4.9

6 6.4 3.5 3 2.8 4.1 4.4 3.1 2.7

7 3.5 2 1.6 1.9 2.5 2.6 1.8 2

8 2.1 1.3 0.92 1.2 1.5 1.7 1 1.2

9 1.3 0.76 0.52 0.76 0.95 0.97 0.63 0.6

10 0.84 0.45 0.29 0.38 0.52 0.56 0.39 0.4

11 0.56 0.28 0.2 0.31 0.38 0.38 0.27 0.2

12 0.37 0.18 0.12 0.29 0.23 0.24 0.19 0.1

13 0.24 0.11 0.07 0.14 0.14 0.15 0.13 0.1

14 0.16 0.07 0.05 0.09 0.09 0.1 0.1 0.04

15 0.1 0.04 0.03 0.06 0.05 0.06 0.09 0.02

16 0.07 0.03 0.02 0.04 0.04 0.04 0.08 0.01

17 0.04 0.02 0.01 0.03 0.02 0.03 0.08 0.003

18 0.03 0.01 0.01 0.02 0.02 0.02 0.07 0.001

19 0.02 N/A N/A 0.01 0.01 0.01 0.07 N/A
125 

Table 58. Change in light (% of light measured just below the lake surface) with depth measured with a 

hydrolab at station RS1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron 

and Larson 1992). 

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.05 100 N/A 100 100 100 100

0.5 88.9 N/A 82.9 78.4 81.3 76.7

1 54.2 N/A 62.9 62.7 68.8 56.7

2 36.1 N/A 37.1 37.3 40.6 30

3 19.4 N/A 22.9 21.6 14.4 17

4 11.4 N/A 14 12.6 8.1 9.7

5 6.3 N/A 8.9 7.7 4.3 5.7

6 3.8 N/A 5.7 4.5 2.8 3.2

7 2.2 N/A 3.7 2.9 1.6 1.9

8 1.3 N/A 2.2 1.8 0.94 1.1

9 0.72 N/A 1.3 1.1 0.56 0.63

10 0.43 N/A 1 0.65 0.34 0.35

11 0.28 N/A N/A N/A 0.23 0.22

12 N/A N/A N/A N/A N/A 0.17

Table 59. Change in light (% of light measured just below the lake surface) with depth measured with a 

hydrolab at station WS1 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron 

and Larson 1992). 

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.05 100 N/A 100 100 100 100

0.5 81.5 N/A 77.6 73 81.3 93.8

1 59.3 N/A 55.1 59.5 59.4 53.1

2 32.6 N/A 30.6 29.7 31.3 21.9

3 17 N/A 15.5 15.4 17.5 10.6

4 11.9 N/A 9 8.7 9.7 6.3

5 6.3 N/A 5.3 4.6 4.7 3.1

6 3.3 N/A 2.9 2.7 2.5 1.9

7 1.4 N/A 1.6 1.6 1.3 1

8 0.67 N/A 0.92 0.95 0.72 0.56

9 0.41 N/A 0.55 0.57 0.41 0.32

10 0.33 N/A 0.31 0.27 0.22 0.19

11 0.21 N/A 0.18 0.22 0.13 0.09

12 0.16 N/A 0.14 N/A N/A 0.04
126 

Table 60. Change in light (% of light measured just below the lake surface) with depth measured with a 

hydrolab at station WS2 Surprise Lake, Aniakchak National Monument, Alaska, 1988 and 1989 (Cameron 

and Larson 1992). 

Depth (m) 7/17/1988 7/28/1988 8/5/1988 8/14/1988 8/31/1988 7/30/1989

0.05 100 N/A 100 100 100 100

0.5 83.6 N/A 68.9 82.9 83.3 76

1 64.2 N/A 48.9 68.6 65.2 48

2 35.8 N/A 22 54.3 36.2 21.6

3 17.9 N/A 11.6 20.9 21.2 12

4 8.5 N/A 7.8 11.4 10.2 6.4

5 4.8 N/A 4.7 6.6 5.6 3.8

6 2.2 N/A 2.8 3.7 3.2 2

7 1 N/A 1.7 2.2 1.8 1.1

8 0.46 N/A 1.1 1.2 1 0.64

9 0.24 N/A 0.69 0.63 0.55 0.36

10 0.16 N/A 0.44 0.3 0.2

11 N/A N/A 0.27 N/A 0.17 0.2

12 N/A N/A 0.14 N/A N/A N/A

Mahoney and Sonnevil (1991) performed water quality measurements on Surprise Lake and selected 

tributaries in July of 1987. These data, including a vertical profile of water quality measurements 

taken every 2 m (6.6 ft) in Surprise Lake, and other water quality parameters taken in Surprise Lake 

and some tributaries were compiled and are presented in Table 57-Table 59. 

Stream discharge was measured at selected sites using a Marsh McBirney flow meter, top setting 

wading rod, and meter tape. Conductivity, dissolved oxygen (DO), pH, and temperature were 

measured just below the stream surface at all stream discharge measurement sites. Conductivity 

(μS/cm), DO concentration (mg/L), pH, and temperature (°C) measurements were taken at six 

Surprise Lake locations at depths ranging from 0.9-18.3 m (3.0-60.0 ft) using a hydrolab 4000 series 

instrument. Secchi disk readings were taken in conjunction with the water quality measurements. 
127 

Table 61. Water depth, depth of measurement and water quality parameters for six sampling locations in 

Surprise Lake, Aniakchak National Monument and Preserve, Alaska, 26 July 1987 (Mahoney and 

Sonnevil 1991).

Sample Site A B C D E F

Total depth (m) 13.7 18.6 1.8 1.4 15.9 2

Depth of measurement (m) 10 16 1.4 0.9 10 1.8

Secchi disk depth (m) 2.6 2.9 1.7 1.4 2.3 2

Conductivity (μS/cm) 394 390 789 369 390 386

Dissolved oxygen (mg/l) 10.4 10.1 8.5 9.7 10.2 10.4

pH 6.8 6.8 6.2 6.7 6.8 6.7

Temperature (°C) 10 9.4 12.6 10.1 9.6 11.4
128

Table 62. Calculated stream discharge and water quality measurements of tributaries to Surprise Lake and the Aniakchak River, Aniakchak

National Monument and Preserve, Alaska, 24-26 July 1987 (Mahoney and Sonnevil 1991). 

Tributary

Discharge 

Site 

Discharge

(m3/s)

Stream 

width 

(m)

Mean 

velocity

(m/s)

Maximum 

depth 

(m)

Minimum 

depth 

(m)

Conductivity

(μS/cm)

Dissolved 

oxygen

(mg/L) pH

Temperature

(°C)

Tributary 1 Site 1 * * * * * 101 10.8 6.8 11.4

Site 2 2.54 8.5 1.01 0.9 0.03 289 10.4 6.15 9.8

Site 3 1.95 17.3 0.5 0.5 0.1 288 10.5 6.2 8.9

Tributary 2 Warm Water 

Springs 

0.38 5.7 0.22 0.3 0.1 901 2.5 5.25 19.4

Tributary 3 Tributary 3 0.25 4.5 0.16 0.2 0.1 58 12.7 7.9 4.4

Tributary 4 Waterfall 

Creek 

2.48 7.3 1.41 0.5 0.2 43 13.4 7.45 2.4

Aniakchak 

River

6.71 19.9 1.85 1.2 0.1 N/A N/A N/A N/A

Table 63. Vertical profile of water quality measurements taken at two meter intervals in Surprise Lake, Aniakchak National Monument and 

Preserve, Alaska, 26 July 1987 (Mahoney and Sonnevil 1991). 

Depth

(m)

Conductivity

(μS/cm)

Dissolved 

oxygen

(mg/L) pH

Temperature

(°C)

0.2 387 10.4 6.9 11.1

3 388 10 7 10.9

5 389 10.1 7 10.5

7 390 8.7 7.1 10.3

9 393 10 7.1 9.9

11 393 9.1 7.2 9.8

13 392 9.3 7.2 9.5

15 392 9.2 7.2 9.3

17 392 9.6 7.1 9.2

19 394 8.7 7.1 9.1

130 

4.11.4 Current Condition and Trend

Threats and Stressor Factors 

Nagorski et al. (2007) cites that oil spills, pollutants transferred through the atmosphere and 

biological processes, and climate change have negatively affected ANIA water quality in the past and 

are likely to continue to in the future. Approximately two-thirds of the ANIA coastline was oiled 

after the Exxon Valdez spill in 1989, which still affects water quality and biotic communities of the 

region. Billions of barrels in crude oil are pumped, transported, and processed close enough to the 

park for swift currents to quickly deposit spills of all scales in ANIA waters (Nagorski et al. 2007). 

The ANIA region has been exposed to the recent warming trend identified as beginning in the mid1970s. Climate change can upset the natural balance of snow pack accumulation in the winter, 

resulting in streams with higher winter flow rates and lower summer flow; this could alter the 

number of streams and lakes in ANIA (Nagorski et al. 2007). Natural water quality degradations 

caused by geothermal springs in ANIA have caused the parameters of pH, metals, and temperature to 

measure outside the allowed state and federal water quality standards (Nagorski et al. 2007). 

Data Needs/Gaps

Water quality data do not exist for most drainages in ANIA. The available data collected in ANIA 

include gaps of several years, and are inconsistent with regards to the time of year the sampling was 

conducted. Previous sampling locations have not been revisited again or often enough to develop 

trends and conclusions. Jones et al. (2005) reports that flow and water quality characteristics in many 

SWAN park water bodies including ANIA are completely unknown, making ecological evaluations 

of these water bodies difficult. 

Overall Condition 

Condition is unknown at this time due to lack of reference condition and limited data. 

4.11.5 Sources of Expertise

Claudette Moore, SWAN Aquatic Ecologist 

4.11.6 Literature Cited

Bennett, L. A. 2004. Baseline water quality inventory for the southwest Alaska inventory and 

monitoring network, Aniakchak National Monument and Preserve. Southwest Alaska Inventory 

and Monitoring Network. National Park Service, Anchorage, Alaska.

Cameron, W. A., and G. L. Larsen. 1992. Baseline inventory of the aquatic resources of the 

Aniakchak National Monument, Alaska. Oregon State University, College of Forestry, Corvallis, 

Oregon. 

Cameron, W. A., and G. L. Larsen. 1993. Limnology of a caldera lake influenced by hydrothermal 

processes. Arch. Hydrobiology 128:13-38.

Jones, M. T., L. A. Bennett, and T. R. Hamon. 2005. Baseline inventory of freshwater fishes of the 

Southwest Alaska Inventory and Monitoring Network: Alagnak Wild River, Aniakchak National 

Monument and Preserve, Katmai National Park and Preserve, Kenai Fjords National Park, and 
131 

Lake Clark National Park and Preserve. National Park Service, Southwest Alaska Network, 

Anchorage, Alaska. 

Mahoney, B. A., and G. M. Sonnevil. 1991. Surprise Lake and Aniakchak River fishery 

investigation, Aniakchak National Monument and Preserve, Alaska, 1987 and 1988 final report. 

U.S. Fish and Wildlife Service, King Salmon Fishery Assistance Office, King Salmon, Alaska. 

Nagorski, S., G. Eckert, E. Hood, and S. Pyare. 2007. Assessment of coastal waters resources and 

watershed conditions at Aniakchak National Monument and Preserve National Resources 

Program Center. National Park Service, Water Resources Division, Fort Collins, Colorado. 

National Park Service (NPS). 2012. Freshwater chemistry vital sign resource brief. 

http://science.nature.nps.gov/im/units/swan/Libraries/Resource_Brief/RB_AQ_chemistry_rerevis

i_LR_20120109.pdf (accessed 13 November 2012). 

133 

Chapter 5. Discussion 

Chapter 5 provides an opportunity to summarize assessment findings and discuss the overarching 

themes or common threads that have emerged for the featured components. The data gaps and needs 

identified for each component are summarized and the role these play in the designation of current 

condition is discussed. Also addressed is how condition analysis relates to the overall natural 

resource management issues of the park. 

5.1 Component Data Gaps

The identification of key data and information gaps is an important objective of NRCAs. Data gaps 

or needs are those pieces of information that are currently unavailable, but would help to inform the 

status or overall condition of a key resource component in the park or would allow the park to 

develop a more thorough understanding of the topic in order to inform possible management 

decisions. Data gaps exist for most resource components assessed in this NRCA. Table 60 provides a 

detailed list of the data gaps identified in this assessment by component. Each data gap or need is 

discussed in further detail in the individual component assessments (Chapter 4). 

Table 64. Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Moose Current population and sex survey information available only from 1999 survey data. Data 

variability likely introduced due to differing collection techniques.

Population and sex survey data absent from ANIA.

Bear No quantitative data exists for bears within ANIA. Limited site specific (Black Lake) area 

population survey from 1999-2002.

Caribou Assessment of NAPCH wintering grounds should be conducted to determine if herd has 

recovered from poor health assessment in 2005.

Passerines Bird observation and surveys predominately occur during summer. Surveys during other seasons 

and a regular monitoring program would contribute to a more thorough understanding of

passerines.

Salmon Salmon run data (e.g., escapement, harvest) severely lacking or non-existent.

Studies addressing run timing in ANIA streams would be beneficial.

Native Fish Data very limited and outdated. Future sampling is needed.

Seismic Activity Need to study VT swarms that do not result in volcanic eruption.

Climate Establish a climate monitoring station inside the park if possible.

Continue to gather climate data from stations northeast of the park.

Study how changes in climate will impact other park resources (e.g., vegetation and wildlife, water 

regime, etc.)

Human Activity To allow for future comparison, yearly updates of the CUA database are important for maintaining 

the integrity and quality of the database.
134

Table 60 (continued). Identified data gaps or needs for the featured components.

Component Data Gaps/Needs

Glaciers Decadal glacier mapping for monitoring must continue.

Water Quality Water quality data do not exist for most drainages in ANIA.

Existing data collection methods/times are inconsistent.

Many of the park’s data needs involve the challenge of determining ways to effectively sample and 

monitor biological phenomena in order to increase statistical confidence and to ensure long-term 

monitoring techniques are possible. To increase statistical confidence, sampling techniques of 

existing survey efforts could be strengthened and improved, or in some cases, entirely different 

approaches in terms of long-term data collection could be designed. Some statistical confidence will 

increase by simply repeating the existing surveys consistently to increase the total number of samples 

(e.g., years), as some sampling methods have only been repeated for a few consecutive years. 

The sampling and monitoring efforts in ANIA are complicated given the remote location of the park, 

as well as potentially extreme environmental conditions. Techniques for large mammal surveys 

(aerial) often require ideal weather during the survey period. Moose surveys are frequently impacted 

by a lack of snow cover, inadequate snow depth, and less than optimal flying conditions. Weather 

and sampling conditions also impact other population surveys in ANIA including passerines, salmon, 

and bear. A consistent but opportunistic and flexible approach to population surveys is necessary to 

gather data and improve analyses.

5.2 Park-wide Component Observations 

5.2.1 Biotic Composition

Mammals

Moose

Moose are common within ANIA. Originally scarce on the Alaskan peninsula (prior to 1900), moose 

populations grew exponentially until they peaked in the late 1960s (Butler 2010). Natural predators 

of moose within ANIA include wolves and brown bears. Limited hunting is also allowed within

ANP. While current survey trends in ANIA indicate declining populations, overall, populations are 

considered to have been stable for the past 30 years (Butler 2008, 2010). Consistent moose 

population/sex ratio surveys would aid in obtaining a more complete picture of the moose population 

in ANIA.

Bear

Brown bears are a prominent mammal species in ANIA. The species is found throughout the 

surrounding area, with larger concentrations in coastal and lake ecosystems. Brown bears utilize 

ANIA resources year-round but the population gravitates towards rivers and lakes with available 

salmon (Sowl 1988).

Quantitative data on the density of brown bears within ANIA do not exist. Overall, little is known 

about the density of brown bear in GMU 9E. Sport hunting is permitted in the ANP, which comprises 
135 

188,179 ha (465,000 ac). Sport hunting is permitted in the spring during even-numbered years, and 

the fall during odd-numbered years. 

Caribou 

Caribou are also a prominent species in the park. ANIA caribou are part of the NAPCH, one of the 

32 designated herds in Alaska. Mountainous areas and treeless tundra are preferred caribou habitat 

year-round, with preference to open coastal areas and mountains for calving areas and boreal forests 

as wintering grounds (Rausch et al. 2008). Traditional calving grounds of the NAPCH have been 

between the Bear River and Cinder River that runs through ANIA, and on the Bering Sea Flats. 

The NAPCH population has ranged from a high of 20,000 animals to the current low of 

approximately 2,000 individuals (Butler 2009). Butler (2009) suggests that assessment of the 

NAPCH wintering grounds should be completed, with an aim to define if nutritional limitations are 

still stressing the herd. This assessment would aid in defining future management goals for the 

NAPCH and determine if the herd has a chance to recover from a poor health assessment in 2005 

(Butler 2009). 

Birds 

Passerines

Bird populations can be an important indicator species as they often reflect an ecoystem’s health 

(Morrison 1986, Hutto 1998, NABCI 2009). Forty-four species of passerines have been observed in 

ANIA (NPS 2013a). Abundance information for passerines in ANIA is primarily anecdotal. Several 

observers have classified species into categories such as “common”, “uncommon”, or “rare”. 

Nearly all of the bird surveys and observations at ANIA have been during the summer months. While 

this is the most likely time for passerines to be present and active, surveys during other seasons 

(migratory behavior) would be beneficial in understanding the passerine population. 

Fish

Salmon 

Sockeye salmon are known to inhabit Surprise Lake within the Aniakchak Caldera, where they have 

established spawning populations (Mahoney and Sonnevil 1991, Hamon 2000, Hamon et al. 2004). 

Other salmon species present within the park include Coho, pink, chum, and Chinook salmon. 

Surprise Lake was populated with salmon following a break in the caldera wall and subsequent flood 

between 1,800 and 3,400 years ago (Hamon 1999). Salmon species have persisted in Surprise Lake 

since some time following the historic flood, and have thrived even after another major eruption of 

the Aniakchak volcano in 1931 (Mahoney and Sonnevil 1991, Hamon 1999). 

ANIA salmon populations are not well studied. Therefore, significant conclusions cannot be drawn 

from available data, although anecdotal sources note that populations within ANIA are relatively 

small, but apparently healthy. According to Hamon et al. (2004, p. 39), “the populations at ANIA, 

though relatively small, appear to be very healthy and represent adaptations to a unique region.” 
136 

Harvest rates do not currently have significant impacts on the small sockeye salmon populations 

within the park. Run timing data are also virtually non-existent for ANIA streams. 

Native Fish

Twenty-seven anadromous and non-anadromous native fish species are present or probably present 

in ANIA (Miller and Markis 2004, Jones et al. 2005, NPS 2013a). Unlike nearby KATM, data from 

ADF&G statewide mail-in survey and guide logbooks do not exist for ANIA. Overall, information 

regarding native fish studies in ANIA is limited and outdated. Future sampling efforts would benefit 

the ability to describe condition in the future. 

Given the remoteness of the Aniakchak River and its tributaries, Surprise Lake, and other water 

bodies in ANIA, natural processes are likely the primary driver of native fish population dynamics. 

Hamon et al. (2004) states that even though sockeye salmon populations in ANIA are “relatively 

small they appear to be very healthy and represent adaptations to a unique region.” Given the 

remoteness of the park and lack of stressors, condition of this resource is assumed good. 

5.2.2 Environmental Quality

Human Activity 

ANIA is one of the least visited national parks. NPS (2013b) reports that on average, less than 500 

individuals visited ANIA each year since 1989. Access to the park is restricted to aircraft or boat, as 

there are no roads within park boundaries and the NPS does not maintain facilities or trails within the 

park. Whitewater rafting from the Aniakchak Caldera to the ocean is one of the most common 

activities within the park. To allow for future comparison, yearly updates of the CUA database are 

important for maintaining the integrity and usefulness of the database.

Water Quality

Aquatic systems within SWAN are remote and pristine, providing researchers with an opportunity to 

examine the effects of man-made disturbances such as climate change and atmospheric pollutants on 

intact systems. Currently, water quality data for SWAN NPS units such as ANIA are minimal, but a 

monitoring plan for ANIA exists.

Nagorski et al. (2007) notes that oil spills, pollutants transferred through the atmosphere and 

biological processes, and climate change have negatively affected ANIA water quality in the past and 

are likely to continue to in the future. Water quality data do not exist for most drainages in ANIA. 

The available data collected in ANIA include gaps of several years, and are inconsistent with regards 

to the time of year the sampling was conducted. Previous sampling locations have not been revisited 

again or often enough to develop trends and conclusions. Jones et al. (2005) reports that flow and 

water quality characteristics in many SWAN park water bodies including ANIA are completely 

unknown, making ecological evaluations of these water bodies difficult. 

5.2.3 Physical Characteristics

Seismic Activity

Located in the Aleutian volcanic arc, ANIA has experienced considerable seismic and volcanic 

activity throughout its history. The Aniakchak Caldera, deemed a National Natural Landmark, has 
137 

been the subject of several geologic studies because of its unique geologic features, formation 

history, and volcanic characteristics. The caldera is on average 10 km (6 mi) wide and over 600 m 

(2,000 ft) deep, making it one of the largest explosive craters in the world (Coombs and Bacon 

2012). 

Earthquakes and volcanic eruptions within ANIA are a result of the interaction of the Pacific and 

North American plates along the Aleutian volcanic arc and are capable of drastically changing the 

landscape. Major alterations to the flora and fauna of a region can occur tens of kilometers from an 

epicenter or major eruption (Page et al. 1991). 

Within ANIA, one volcano is monitored by six seismic monitoring stations maintained by AVO. 

Seismic stations surrounding the Aniakchak Crater have located an average of 24 earthquakes/year 

over the past eight years. Aniakchak Crater was one of only seven AVO monitored volcanoes to 

show an increase in regional seismic activity in 2011 from recorded 2010 levels. Volcanologists 

predict, through the piecing together of historic geological evidence, that an eruption of the same 

scale as the 1931 eruption of the Aniakchak Caldera can be expected (Neal et al. 2001). An event that 

large, however, would have an extremely low probability for many centuries to come simply due to 

the rarity of such large events (Neal et al. 2001). 

Climate 

As a primary driver of many other ecosystem components (vegetation, wildlife, disturbance regime, 

etc.), climate has numerous management consequences and implications. Climate was selected by the 

SWAN I&M program as a high-priority Vital Sign for southwest Alaska parks (Davey et al. 2007). 

The ANIA climate is described as “transitional between polar (tundra climate) and maritime 

(maritime subarctic)” (Lindsay 2013, p. 1). Winter temperatures are cold, while summer 

temperatures are somewhat moderated by nearby open water (e.g., Bering Sea and Gulf of Alaska) 

(Lindsay 2013). 

There is a scientific consensus that human activities, particularly those that produce greenhouse 

gasses (e.g., fossil fuel burning), have contributed to a general warming trend in global climate 

(IPCC 2010). Climate models predict that change will be greatest at higher latitudes, indicating that 

Alaska is at high risk (NPS 2011). In the ANIA region, temperatures are projected to increase 

approximately 1°F (about 0.6°C) per decade over the next century (SNAP et al. 2009). 

Glaciers

Glaciers occur in ANIA but are not considered to be a significant land cover type in the park (Giffen 

and Lindsay 2011). Giffen and Lindsay (2011, p. 8) describe the glaciers in ANIA as “small 

hanging/cirque glaciers of very limited extent that occur inside the Aniakchak crater on the very 

steep north aspect of the southern portion of the crater”. Loso et al. (2012) report the glacial coverage 

in ANIA to be minimal, covering approximately 4.4 km2

 (1.7 mi2). 

An increase in average yearly temperature has been identified and predicted to continue in the 

SWAN parks region. Since no previous quantitative data exist for the glaciers in ANIA, the effects of 

regional temperature increases cannot be calculated. Trends identified by Loso et al. (2012) indicate 
138 

that the glaciers located on the north-facing slopes of the caldera have shown advance since historic 

map data while glaciers located outside the caldera of ANIA have retreated during that time. 

5.2.4 Park-wide Threats and Stressors

Several stressors were identified as threatening multiple resources within the park. Anthropogenic 

impacts from tourism to ANIA are extremely low. From 2008-2012, annual park visitation averaged 

less than 35 people (NPS 2013b). Indirect anthropogenic impacts however, are a long-term threat to 

ANIA and include airborne pollutants and climate change. 

Climate change has begun to alter ANIA resources, but the extent of future impacts is uncertain. The 

average temperatures have risen 2.2°C (4°F) since the 1950s and are predicted to continue to increase 

by 2.8-10°C (5–18°F) by 2100 (Nagorski et al. 2007). A warming climate will most seriously impact

water resources, especially at high altitudes (Hall 1988, Serreze et al. 2000), by affecting snow cover, 

glaciers, and sea/lake ice cover (Nagorski et al. 2007). Warmer winters will cause the snowpack to 

decrease while increasing rain events (Nagorski et al. 2007). This will result in a drier spring 

environment. Drier conditions may then cause an increase in the fire regime. 

For biological resources analyzed in this assessment, concerns also stem from climate change 

(warming). Salmon may experience decreased survival of eggs and fry, slowed growth, premature 

smolting, and shifts in onsets of runs (Alderice and Velsen 1978). Other potential impacts of a 

warmer climate include reduced snowpack and a longer growing season, which could affect plant 

phenology and productivity, wildlife distribution and mating cycles, water availability, and 

recreational and subsistence activities (e.g., hunting, fishing) (SNAP et al. 2009, NPS 2011). 

Another threat to resources in ANIA is human-caused disaster such as oil spills. The Exxon Valdez 

oil spill in the spring of 1989 was one of the most environmentally devastating (human-caused) 

events to affect the park (NPS 1990, as cited by Nagorski et al. 2007). The eastern two-thirds of the 

park shoreline was contaminated by the spill (NPS 1990, as cited by Nagorski et al. 2007). Marine 

wildlife, including mammals, fish, and seabirds, were most adversely affected by the spill. A 

restoration plan was created in 1994 by the Exxon Valdez Oil Spill Committee to restore the 

resources lost or damaged in the area. The plan contains actions to rehabilitate the environment by 

replanting intertidal plant species to prespill conditions, and limiting human use in the park and 

surrounding areas until populations stabilize (EVOS Council 1994). 

This assessment serves as a review and summary of available data and literature for featured natural 

resources in the park. Much of the information presented here may serve as a baseline against which 

any changes in condition of components in the future may be compared. Establishing baseline 

information, for many of these resources, can help managers prioritize management objectives and 

better focus conservation strategies to maintain the health and integrity of these ecosystems. 

5.2.5 Literature Cited

Alderice, D. F., and F. P. J. Velsen. 1978. Relation between temperature and incubation time for eggs 

of Chinook salmon (Oncorhynchus tshawytscha). Journal of the Fisheries Research Board of 

Canada 35:69–75. 
139 

Butler, L. G. 2008. Unit 9 moose management report. Pages 116-124 in Moose management report 

of survey and inventory activities 1 July 2005 – 30 June 2007. Project 1.0. Alaska Department of 

Fish and Game, Juneau, Alaska. 

Butler, L. 2009. Units 9C & 9E caribou management report. Pages 32-42 in P. Harper, editor. 

Caribou management report of survey and inventory activities 1 July 2006-30 June 2008. Alaska 

Department of Fish and Game, Juneau, Alaska. 

Butler, L. G. 2010. Unit 9 moose management report. Pages 116-123 in Moose management report 

of survey and inventory activities 1 July 2007 – 30 June 2009. Project 1.0. Alaska Department of 

Fish and Game, Juneau, Alaska. 

Coombs, M. L., and C. R. Bacon. 2012. Using rocks to reveal the inner workings of magma 

chambers below volcanoes in Alaska’s national parks. Alaska Park Science 11:1:27-33. 

Davey, C. A., K. T. Redmond, and D. B. Simeral. 2007. Weather and Climate Inventory, National 

Park Service, Southwest Alaska Network. Natural Resource Technical Report 

NPS/SWAN/NRTR—2007/045. National Park Service, Fort Collins, Colorado. 

Exxon Valdez Oil Spill Trustee Council (EVOS). 1994. The Exxon Valdez oil spill restoration plan. 

Exxon Valdez Oil Spill Trustee Council, Anchorage, Alaska 

Giffen, B. A., and C. R. Lindsay. 2011. Glacier monitoring in the Southwest Alaska Network: 

Volume 1. Natural Resource Report NPS/SWAN/NRR—2011/293. National Park Service, Fort 

Collins, Colorado. 

Hall, D. K. 1988. Assessment of polar climate change using satellite technology. Reviews of 

Geophysics 26(1):26-39. 

Hamon, T. 1999. Sockeye salmon population status and local adaptation inventoried at Aniakchak.

Pages 27-28 in Natural Resource Year in Review - 1999. National Park Service, Natural 

Resource Information Division, Lakewood, Colorado. 

Hamon, T. 2000. Population status, local adaptation, and gene flow in Surprise Lake sockeye salmon: 

an ecological and evolutionary study of colonization and succession in Aniakchak National 

Monument and Preserve. Resource Management Technical Report KATM-NR-01-01. National 

Park Service, King Salmon, Alaska. 

Hamon, T. R., S. A. Pavey, J. L. Miller, and J. L. Nielsen. 2004. Aniakchak sockeye salmon 

investigations. Alaska Park Science 3(2):34-39. 
140 

Hutto, R. L. 1998. Using landbirds as an indicator species group. Avian conservation: Research and 

management. Island Press, Washington, D.C. 

Intergovernmental Panel on Climate Change (IPCC). 2010. Contribution of working groups I, II and 

III to the fourth assessment report of the Intergovernmental Panel on Climate Change. 

http://www.ipcc.ch/publications_and_data/ar4/syr/en/contents.html (accessed 25 March 2013). 

Jones, T. M., L. A. Bennett, and T. R. Hamon. 2005. Baseline inventory of freshwater fishes of the 

Southwest Alaska Inventory and Monitoring Network: Alagnak Wild River, Aniakchak National 

Monument and Preserve, Katmai National Park and Preserve, Kenai Fjords National Park, and 

Lake Clark National Park and Preserve. National Park Service, Southwest Alaska Network, 

Anchorage, Alaska. 

Lindsay, C. R. 2013. Climate monitoring in the Southwest Alaska Network: Annual report for the 

2012 hydrologic year. Natural Resource Technical Report NPS/SWAN/NRTR-2013/716. 

National Park Service, Fort Collins, Colorado. 

Loso, M. 2012. Alaskan National Park glaciers: status and trend. Third progress report. National Park 

Service, Fort Collins, Colorado. 

Mahoney, B. A., and G. M. Sonnevil. 1991. Surprise Lake and Aniakchak River fishery 

investigation, Aniakchak National Monument and Preserve, Alaska, 1987 and 1988 final report. 

Alaska Fisheries Technical Report Number 12. U.S. Fish and Wildlife Service, King Salmon, 

Alaska.

Miller, J. L., and J. Markis. 2004. Freshwater fish inventory of Aniakchak National Monument and 

Preserve, Southwest Alaska Inventory and Monitoring Network. National Park Service, 

Southwest Alaska Network, Anchorage, Alaska. 

Morrison, M. L. 1986. Bird populations as indicators of environmental change. Current Ornithology 

3:429-451. 

Nagorski, S., G. Eckert, E. Hood, and S. Pyare. 2007. Assessment of coastal waters resources and 

watershed conditions at Aniakchak National Park and Preserve (Alaska). National Park Service, 

Water Resources Division, Fort Collins, Colorado. 

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The Department of the Interior protects and manages the nation’s natural resources and cultural heritage; provides scientific 

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affiliated Island Communities.

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