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| U.S. Department of the Interior  | height="0.7207020997375329in"}   |
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National Capital Region Network Long-Term Forest Vegetation Monitoring
Protocol

Version 2.0(November, 2008)

Natural Resource Report NPS/NCR/NCRN/NRR---2008/????

**ON THE COVER**

J. Parrish measures the diameter of a tree in Prince William Forest
Park.

Photograph by: Thomas Paradis, NPS.

National Capital Region Network Long-Term Forest Monitoring Protocol **\
**

Version 2.0

Natural Resource Report NPS/NCR/NCRN/NRR---2008/XXX

John Paul Schmit

Geoff Sanders

Mark Lehman

Thomas Paradis

National Park Service

**Center for Urban Ecology**

**4598 MacArthur Blvd., NW**

**Washington DC 2007**

November 2008

U.S. Department of the Interior

National Park Service

National Capital Region Office

Washington, DC

The Natural Resource Publication series addresses natural resource
topics that are of interest and applicability to a broad readership in
the National Park Service and to others in the management of natural
resources, including the scientific community, the public, and the NPS
conservation and environmental constituencies. Manuscripts are
peer-reviewed to ensure that the information is scientifically credible,
technically accurate, appropriately written for the intended audience,
and is designed and published in a professional manner.

Natural Resource Reports are the designated medium for disseminating
high priority, current natural resource management information with
managerial application. The series targets a general, diverse audience,
and may contain NPS policy considerations or address sensitive issues of
management applicability. Examples of the diverse array of reports
published in this series include vital signs monitoring plans; \"how
to\" resource management papers; proceedings of resource management
workshops or conferences; annual reports of resource programs or
divisions of the Natural Resource Program Center; resource action plans;
fact sheets; and regularly-published newsletters.

Views and conclusions in this report are those of the authors and do not
necessarily reflect policies of the National Park Service. Mention of
trade names or commercial products does not constitute endorsement or
recommendation for use by the National Park Service.

Printed copies of reports in these series may be produced in a limited
quantity and they are only available as long as the supply lasts. This
report is also available from the National Capital Region I&M Network
website (<http://www.nature.nps.gov/im/units/ncrn/index.cfm>) on the
internet, or by sending a request to the address on the back cover.

Please cite this publication as:

Schmit, J.P., G. Sanders, M. Lehman and T. Paradis. 2008. National
Capital Region Network Long-Term Forest Monitoring Protocol. Natural
Resource Report NPS/NCRN/NRR---2008/XXX. National Park Service, Fort
Collins, Colorado

NPS D-XXX, November 2008

Contents
========

Page

[Figures ix](#_Toc216757386)

[Tables xi](#_Toc216757387)

[Executive Summary xiii](#executive-summary)

[Acknowledgements xv](#acknowledgements)

[Background and Objectives 1](#background-and-objectives)

[Background and History 1](#background-and-history)

[Rationale for Monitoring this Resource
1](#rationale-for-monitoring-this-resource)

[Measurable Objectives 3](#measurable-objectives)

[Sampling Design 5](#sampling-design)

[Sampling Design Rationale 5](#sampling-design-rationale)

[Site Selection 5](#site-selection)

[Sampling Frequency and Replication
7](#sampling-frequency-and-replication)

[Recommended Number and Location of Sampling Sites and Frequency of
Sampling
7](#recommended-number-and-location-of-sampling-sites-and-frequency-of-sampling)

[Level of Change That Can Be Detected
7](#level-of-change-that-can-be-detected)

[Field Methods 15](#field-methods)

[Field Season Preparations and Equipment Setup
15](#field-season-preparations-and-equipment-setup)

[Field Season Scheduling 15](#field-season-scheduling)

[Measurements and Post-Collection Processing
16](#measurements-and-post-collection-processing)

[End of Season Procedures 16](#end-of-season-procedures)

[Data Handling Analysis and Reporting
17](#data-handling-analysis-and-reporting)

[Metadata Procedures 17](#metadata-procedures)

[Overview of Database Design 17](#overview-of-database-design)

[Data Entry, Verification and Editing
17](#data-entry-verification-and-editing)

[Recommendations for Routine Data Summaries, Tables, Figures and
Statistical Analysis to Detect Change and Trends
17](#recommendations-for-routine-data-summaries-tables-figures-and-statistical-analysis-to-detect-change-and-trends)

[Recommended Reporting Schedule and Format
18](#recommended-reporting-schedule-and-format)

[Recommended Methods for Long-Term Trend Analysis
18](#recommended-methods-for-long-term-trend-analysis)

[Data Archival Procedures 18](#data-archival-procedures)

[Personnel Requirements and Training
19](#personnel-requirements-and-training)

[Roles and Responsibilities 19](#roles-and-responsibilities)

[Training Procedures 19](#training-procedures)

[Operational Requirements 21](#operational-requirements)

[Annual Workload and Field Schedule
21](#annual-workload-and-field-schedule)

[Facility and Equipment Needs 21](#facility-and-equipment-needs)

[Startup Costs and Budget Considerations
21](#startup-costs-and-budget-considerations)

[Revision History 23](#revision-history)

[Version 2.0 (November, 2008) 23](#version-2.0-november-2008)

[Version 1.0 (January 2006) 23](#version-1.0-january-2006)

[Literature Cited 25](#literature-cited)

[SOP 1: Ground-Truthing Potential Monitoring Locations (November, 2008)
27](#sop-1-ground-truthing-potential-monitoring-locations-november-2008)

[Introduction 27](#introduction)

[Preparing for Field Work 27](#preparing-for-field-work)

[Equipment List 27](#equipment-list)

[Field Work 27](#field-work)

[Post-Fieldwork 29](#post-fieldwork)

[Revision History 29](#revision-history-1)

[SOP 2: Plot Location and Establishment (November, 2008)
31](#sop-2-plot-location-and-establishment-november-2008)

[Introduction 31](#introduction-1)

[Preparation 31](#preparation)

[Equipment List 31](#equipment-list-1)

[Plot Location and Marking 32](#plot-location-and-marking)

[Monitoring Plot Layout 33](#monitoring-plot-layout)

[Flow of Work 33](#flow-of-work)

[Marking Transects and Microplots 33](#marking-transects-and-microplots)

[Tagging and Marking Trees 34](#tagging-and-marking-trees)

[Setup of Microplots 36](#setup-of-microplots)

[Note Taking 37](#note-taking)

[Cleanup 37](#cleanup)

[Revision History 37](#revision-history-2)

[SOP 3: Office Preparations Pre- and Post-Monitoring and Field Equipment
(November, 2008)
39](#sop-3-office-preparations-pre--and-post-monitoring-and-field-equipment-november-2008)

[Introduction 39](#introduction-2)

[Preparations before Monitoring 39](#preparations-before-monitoring)

[Field Equipment 39](#field-equipment)

[Post-Monitoring Office Work 40](#post-monitoring-office-work)

[Revision History 40](#revision-history-3)

[SOP 4: Arriving at the Plot and Flow of Work (November, 2008)
41](#sop-4-arriving-at-the-plot-and-flow-of-work-november-2008)

[Introduction 41](#introduction-3)

[Locating the Plot 41](#locating-the-plot)

[Flow of Work 41](#flow-of-work-1)

[Revision History 41](#revision-history-4)

[SOP 5: Photo Points (November, 2008)
43](#sop-5-photo-points-november-2008)

[Introduction 43](#_Toc216757456)

[Photo Points 43](#photo-points)

[Downloading Photos 43](#downloading-photos)

[Renaming Photos 44](#renaming-photos)

[Storing Photos 44](#storing-photos)

[Keyword Metadata Documentation 44](#keyword-metadata-documentation)

[Revision History 44](#revision-history-5)

[SOP 6: Forest Floor Measurements (November, 2008)
47](#sop-6-forest-floor-measurements-november-2008)

[Introduction 47](#_Toc216757464)

[Measurements 47](#measurements)

[Revision History 47](#revision-history-6)

[SOP 7: Tree Measurements (November, 2008)
49](#sop-7-tree-measurements-november-2008)

[Introduction 49](#introduction-4)

[Taking Measurements 50](#taking-measurements)

[Revision History 54](#revision-history-7)

[SOP 8: Sapling and Shrub Measurements (November, 2008)
55](#sop-8-sapling-and-shrub-measurements-november-2008)

[Introduction 55](#introduction-5)

[Sapling and Shrub Measurements 57](#sapling-and-shrub-measurements)

[Revision History 59](#revision-history-8)

[SOP 9: Herbaceous Plant and Seedling Measurements (November, 2008)
61](#sop-9-herbaceous-plant-and-seedling-measurements-november-2008)

[Introduction 61](#introduction-6)

[Herbaceous Plant and Seedling Measures
61](#herbaceous-plant-and-seedling-measures)

[References 64](#references)

[Revision History 64](#revision-history-9)

[SOP 10: Coarse Woody Debris (November, 2008)
65](#sop-10-coarse-woody-debris-november-2008)

[Introduction 65](#introduction-7)

[Measuring Coarse Woody Debris 65](#measuring-coarse-woody-debris)

[Measuring Diameter 65](#measuring-diameter-2)

[References 67](#references-1)

[Revision History 68](#revision-history-10)

[SOP 11: Collection of Unknown Plant Species (November, 2008)
69](#sop-11-collection-of-unknown-plant-species-november-2008)

[Introduction 69](#introduction-8)

[Methods 69](#methods)

[Revision History 70](#revision-history-11)

[SOP 12: Data Entry and Verification (November, 2008)
71](#sop-12-data-entry-and-verification-november-2008)

[Introduction 71](#introduction-9)

[Definitions 71](#definitions)

[Procedures and General Requirements
71](#procedures-and-general-requirements)

[Responsibilities 73](#responsibilities)

[Revision History 74](#revision-history-12)

[SOP 13: Analysis and Reporting (November, 2008)
75](#sop-13-analysis-and-reporting-november-2008)

[Introduction 75](#introduction-10)

[Reporting Schedule 75](#reporting-schedule)

[Annual Report Contents 75](#annual-report-contents)

[Report Formatting 76](#report-formatting)

[Annual Report Peer Review 76](#annual-report-peer-review)

[Automation of Reporting 76](#automation-of-reporting)

[Revision History 77](#revision-history-13)

[SOP 14: Data Management (November, 2008)
79](#sop-14-data-management-november-2008)

[Introduction 79](#introduction-11)

[Procedures and General Requirements
79](#procedures-and-general-requirements-1)

[Responsibilities 80](#responsibilities-1)

[Revision History 81](#revision-history-14)

Figures
=======

Page

[Figure 1. Relationship of forest vital signs 3](#_Toc216757517)

[Figure 2. *Quercus alba* measured basal area vs. fitted values based on
tweedie distribution. 10](#_Toc216757518)

[Figure 3. Layout of forest monitoring plots.
33](file:///T:\I&M\MONITORING\Forest_Vegetation\Protocol\Forest%20Protocol%202%20NRR.docx#_Toc216757519)

[Figure 4. Location of DBH on hills and leaning trees.
35](file:///T:\I&M\MONITORING\Forest_Vegetation\Protocol\Forest%20Protocol%202%20NRR.docx#_Toc216757520)

[Figure 5. Location of DBH on hills and leaning trees.
51](file:///T:\I&M\MONITORING\Forest_Vegetation\Protocol\Forest%20Protocol%202%20NRR.docx#_Toc216757521)

[Figure 6. Illustration of crown classes.
54](file:///T:\I&M\MONITORING\Forest_Vegetation\Protocol\Forest%20Protocol%202%20NRR.docx#_Toc216757522)

[Figure 7. Illustration of cover method based on polygon outline of
plants using a rectangular \"Daubenmire plot\"
63](file:///T:\I&M\MONITORING\Forest_Vegetation\Protocol\Forest%20Protocol%202%20NRR.docx#_Toc216757523)

[Figure 8. Measuring diameter of deformed CWD. 66](#_Toc216757524)

Tables
======

Table 1. Power analysis results for parametric tests. 11

Table 2. Power analysis of occupancy data. 12

Table 3 Startup costs: allocation of existing staff costs to protocol.
21

Table 4. Startup costs: new staff and equipment to implement protocol.
21

Table 5. Order of installation of plot markers. 34

Table 6. Stem sizes for an equivalent diameter ≥10cm. 35

Table 7. List and sequence of photo points. 43

Table 8. Stem sizes for an equivalent diameter ≥10 cm. 49

Table 9. Pests and diseases to monitor. 52

Table 10. List of woody species monitored as shrubs. 56

Table 11. Woody plants that are sometimes considered shrubs but are
monitored in other

categories by the NCRN. 57

Table 12. Herbaceous species monitored in quadrats. 62

Table 13. Decay classes for CWD. 67

Executive Summary 
=================

The vital sign selection process of the NPS Inventory and Monitoring
Program (I&M) identified forest vegetation monitoring as a critical need
for the parks of the National Capital Region Network (NCRN). The data
collected using this protocol will provide much needed baseline
information on the forests in the NCRN, particularly in terms of
community structure and composition. The information will also be used
to determine long term trends in community composition, as well as
trends in the abundance and distribution of individual species.

Additionally, there are several short- and long-term threats to the
forests found in the NCRN parks. There is evidence that the parks are
overpopulated with deer (also the focus of a vital sign), which poses
the risk of unsustainable browsing pressure on forest ecosystems. In
particular, over-browsing can lead to the loss of understory species and
reduce or eliminate regeneration of some tree species. Invasive exotic
plant species are found throughout the network parks and may out-compete
native vegetation. Several tree species are highly susceptible to insect
pests and pathogens. Long-term threats include changes in land use
inside and outside the parks, long-term climate change, pathogens and
air pollution.

This protocol includes monitoring of three related vital signs: forest
vegetation condition, invasive species and forest pests and pathogens.
The protocol is based on the plot design of the US Forest Service Forest
Inventory and Analysis program and the results of a 2004 pilot study.
Thirteen standard operating procedures (SOPs) document the methods used
to collect the relevant data. The protocol was developed in consultation
with other I&M networks in the eastern US so that the data collected
will be compatible with that of other networks to provide a wider
context for trends in the NCRN parks.

Acknowledgements
================

David Chojnacky and Mikaila Milton helped develop and write the previous
version of this protocol. Helpful comments were provided by Pat
Campbell, Shawn Carter, Eric Johnson, Elan Margulies and John Parrish.

Background and Objectives
=========================

Background and History
----------------------

This protocol is designed for monitoring forest vegetation in 11 parks
within the National Park Service's National Capital Region Network
(NCRN) in the Washington, DC, metropolitan area. These parks are
Antietam National Battlefield, Catoctin Mountain Park, Chesapeake and
Ohio Canal National Historical Park, George Washington Memorial Parkway,
Harpers Ferry National Historical Park, Manassas Battlefield Park,
Monocacy National Battlefield, National Capital Parks-East, Prince
William Forest Park, Rock Creek Park, and Wolf Trap National Park for
the Performing Arts. It should be noted that National Capital Parks East
is not an individual park, but rather an administrative unit that
manages a variety of small parks (Greenbelt Park, Anacostia Park,
Piscataway Park, etc.).

Forests are the dominant natural vegetative community in the NCRN parks.
While some parks have individual monitoring programs focused on specific
threats, others have no forest monitoring in place, and there is no
standardization among the existing park programs. The data collected
using this protocol will provide much needed baseline information on the
forests in the NCRN, particularly in terms of community structure and
composition. The information will also be used to determine long term
trends in community composition, as well as trends in the abundance and
distribution of individual species.

Forests in the NCRN parks are currently facing several threats. The most
severe of these include high browsing pressure from deer, invasion by
exotic plant species, decline of tree species such as hemlocks and
dogwoods due to pathogens, and changes in land use. Collectively these
threats have the potential to cause drastic changes in vegetation
structure, species dominance and composition, and resources available to
non-plant species.

Development of forest monitoring field procedures has been a joint
effort between National Capital Region Network Inventory and Monitoring
staff and USDA Forest Service Forest Inventory Research, including
subcontractors. An initial protocol was developed in 2004. In 2005 the
protocol was revised to more closely correspond to FIA standards and to
be consistent with the staffing resources of the NCRN and the needs of
the parks (Schmit et al., 2006). Much of the early development and
protocol writing was performed by **David Chojnacky of the US Forest
Service and Mikaila Milton of the National Park Service.**
Identification of monitoring locations began in 2005. In 2006 protocol
version 1.0 was implemented and 100 plots were monitored. In 2007 and
2008 monitoring continued and 100 new plots were measured each year.
Protocol version 2.0 was written in 2008 with an updated format and
expanded rationale for many of the measurements in the SOPs. No changes
were made to the actual methods in the SOPSs. Data from version 2.0 is
fully compatible with version 1.0. The NCRN is currently evaluating the
benefits of adding one or more soil monitoring SOPs to complement forest
condition monitoring. If soil monitoring is adopted, the protocol will
be updated.

Rationale for Monitoring this Resource
--------------------------------------

Forests are the dominant natural vegetation cover for the parks in the
NCRN and a wide variety of forest communities are found inside park
boundaries. Most of the parks in the NCRN have a specific mandate
related to management of forests in their founding legislation. These
include requirements to preserve natural forests, to preserve or
recreate historic conditions related to Civil War battles, to protect
watersheds, to provide recreation and to protect scenic vistas (National
Park Service, 2005a). As of 2008, no completed vegetation maps of the
parks exist, except for Rock Creek Park, but vegetation mapping is
underway as one of the basic inventories of the I&M program and should
be completed by 2011.

In 2002 The Science Advisory Committee to the NCRN selected the "vital
signs" for the network. The vital signs are indicators that are targets
for long term monitoring. They were selected based on their importance
for documenting and understanding changes in the parks' natural
resources (National Park Service, 2005a). Many of the vital signs are
directly or indirectly related to forest vegetation, including: forest
vegetation condition, invasive plant species, forest pests and
pathogens, changes in land cover and land use, density of white-tailed
deer and forest breeding birds.

Of the six vital signs listed above, forest vegetation condition and
forest breeding birds examine the resources of concern. The other four
vital signs: pests and pathogens, exotic plant species, land cover/land
use, and white-tailed deer density are all threats to the resources that
are expected to persist for the foreseeable future. Although
white-tailed deer are a native species, the concern is overpopulation
and its effects rather than loss of deer. When the data from these
protocols is combined it will help to determine how serious the various
threats are and to what extent they natural resources of the parks are
being impacted (Figure 1).

This protocol describes the methodology for collecting data for the
forest vegetation, exotic plant and forest pest and pathogen vital
signs. Data for these vital signs are collected from randomly placed
monitoring plots. Methods for monitoring white-tailed deer density,
forest birds, and changes in land cover and land use are described in
separate protocols (Bates, 2006; Dawson and Efford, 2006; Townsend et
al., 2006). Monitoring points for forest birds are co-located, when
possible, with the forest vegetation plots described in this protocol.
Deer density and land cover/land use measurements are not co-located
with these plots, but rather collected for each park as a whole.

[]{#_Toc216757517 .anchor}Figure 1. Relationship of forest vital signs.
The four vital signs within the purple box are monitored at the same
locations.

Measurable Objectives
---------------------

The purpose of this protocol is to monitor changes in forest composition
in the NCRN parks. In selecting objectives, emphasis was placed on those
indicators which are likely to respond to known forest threats, which
are important for other species in the forest ecosystem, and which are
likely to be useful in assessing future threats. These selection
criteria have resulted in the following measurable objectives.

The NCRN will document status and long term trends in:

1.  Tree and shrub distribution, composition and richness: Deer browse,
    exotic plants, and pathogens all have the potential to impact some
    plant species more than others. Monitoring species composition will
    allow the NCRN to identify individual species which have a changing
    geographic range throughout the region. This will be an effective
    means of monitoring species which tend not to be very abundant in
    individual plots, but are present in many plots. Locations or forest
    types which are particularly species rich or contain rare species
    can also be identified and may merit special management
    consideration. All tree and shrub species will be monitored.

2.  Tree and shrub basal area and abundance: Basal area is a measure
    related to the total woody biomass of a forest stand. Large declines
    in basal area are indicative of a major disturbance in the forest
    ecosystem. If these declines were widespread and not part of natural
    disturbance processes they could have a significant negative impact
    on all other forest species. Abundance and basal area of individual
    tree and shrub species will allow the NCRN to determine if
    individual species are declining or increasing region-wide. This
    will be particularly useful for species which are found in many
    plots and tend to be abundant in those plots.

3.  Amount of coarse woody debris per plot: Coarse woody debris is an
    important habitat for many animal and microbial species. Declines in
    the amount of coarse woody debris could negatively impact a wide
    variety of other species.

4.  Distribution, abundance and basal area of exotic trees and shrubs:
    This will allow the NCRN to determine if exotic trees and shrubs are
    becoming more common and to determine what changes in forest
    vegetation condition are associated with these exotic species.

5.  Exotic understory plant distribution and cover. Exotic plants may be
    able to out-compete native understory plants. By monitoring the
    distribution of understory plants the NCRN will be able to determine
    which plants are spreading throughout the region. The NCRN will
    monitor the cover of exotic plants to determine how large of an
    impact they are having in the plots where they occur. The NCRN will
    work with the regional Exotic Plant Management Team and the Invasive
    Species Coordinator to determine which plants should be monitored.
    The list is updated annually as new plant species invade network
    parks.

6.  Vines on trees: The NCRN will identify all vine species growing on
    each tree, including exotic vines, and determine which trees have
    vines growing in the crown. This will allow us to determine if
    invasive vines are spreading and if trees that have vines have a
    higher mortality rate that those without vines.

7.  Presence of select forest pests and diseases: The NCRN will record
    the presence of select forest pests and diseases on trees. The NCRN
    will work with the regional Integrated Pest Management Coordinator
    to determine which pests and diseases should be monitored. We will
    focus on those which are particularly destructive. By tracking the
    survival of infected trees, the NCRN will determine if these pests
    and diseases are causing significant tree mortality in network
    parks.

The data from forest monitoring will be examined at both the park-wide
and region-wide scales. As data accumulates, the NCRN plans to compare
results with other I&M networks and with FIA data. This will allow the
NCRN to determine if changes seen in the network are comparable to those
seen elsewhere.

Sampling Design
===============

Sampling Design Rationale
-------------------------

In designing the vegetation monitoring program, it was decided to use
the US Forest Service, Forest Inventory and Analysis program as a model
(FIA, 2004). Other possibilities included developing a custom protocol
for the NCRN or adopting a different standard such as the North Carolina
Vegetation Survey protocol (Peet et al., 1998). It was decided not to
develop a new protocol as adequate protocols already exist. These
protocols cover existing NCRN measurable objectives and have SOPs for
other indicators that the NCRN could choose to use in the future.
Furthermore, adopting a widely-used protocol would allow us to take
advantage of datasets collected from forests near the NCRN parks. The
FIA protocol is used by the Forest Service nationwide and includes an
FIA plot in Catoctin Mountain Park. Furthermore, based on informal
discussion it was clear that the FIA protocol was going to be the basis
for forest vegetation monitoring by other eastern I&M networks.
Therefore, FIA was chosen in order to maximize the benefits of data
sharing.

While FIA is the basis of the NCRN protocol there are some differences.
Not all of the data collected on FIA plots will be collected on NCRN
plots. NCRN plots have the same area, but a different layout than FIA
plots (see SOP 2). Some additional minor changes were made between FIA
measurements and those in the NCRN protocol. These changes are discussed
in the individual SOP's.

Site Selection
--------------

In 2005, the NCRN developed a network-wide, 250 meter square grid across
the network parks. The grid exists as a spatial dataset in the GIS
system. Points which occur at the intersections of the grid are
potential monitoring locations. Those locations which are actually being
monitored are marked in the field as indicated in SOP 2.

The purpose of this grid is to establish a consistent basis for sampling
that will allow the NCRN to co-locate sampling sites and integrate
results from a variety of monitoring protocols. The grid is currently
used in the forest bird monitoring and may be used in additional
protocols or research projects if warranted. Two-hundred and fifty
meters was chosen as a grid size as many NCRN parks have long narrow
forests (e.g., C&O Canal, Baltimore-Washington Parkway, George
Washington Memorial Parkway) that would be missed with a larger grid. A
smaller grid was not used in order to ensure that data collected at one
point on the grid would be independent from data collected at an
adjacent point on the grid. The NCRN forest bird monitoring relies on
audible point count data (i.e. listening for bird calls). Point counts
closer than 250m apart run the risk of counting a single bird in two
listening points, even if the bird stays in the same location. Each
point on the grid on park owned land can be considered a potential
sampling location for forest vegetation monitoring.

A randomized procedure was used to choose which of the grid points would
actually be used for forest monitoring. Sampling locations were selected
by using generalized random-tessellation stratified survey (GRTS:
Stevens and Olsen, 2004). GRTS was chosen over simple random sampling as
GRTS creates a random sample that is spatially balanced -- points are
not clumped in a single part of the study area.

Stratification based on vegetation or landscape features has not been
incorporated. Stratification by forest type has been shown to be
problematic, as vegetation type change quickly. This complicates
analysis and defeats the purpose of the original stratification
(Diefenbach and Mahan, 2002). Furthermore, detailed vegetation maps were
not available for the NCRN parks when monitoring began. An alternative
to stratification by vegetation type would be to stratify based on a
more permanent feature of the landscape such as slope or aspect but this
was rejected. It is not known what responses the current major threats
(deer, exotic invasive plants, diseases) would have to these features,
which would reduce the benefits of stratification and complicate future
analysis. Finally, after the data has been collected it could still be
analyzed to determine if changes in forest structure are related to
landscape features.

Similarly, it was decided that the sampling would not be stratified by
park, that is, there would not be a predetermined number of sites in
each park. Rather the monitoring locations are randomly placed across
the entire network and parks with more forested area have more
monitoring plots. This was chosen as the NCRN parks are not 11 distinct
and compact park units. Parks in the NCRN, particularly in the DC
region, are fragmented and intermingled. Parts of Rock Creek are
contiguous with the C&O Canal, parts of George Washington Memorial
Parkway are surrounded by the C&O Canal and the border between the small
forest fragments managed by Rock Creek and by National Capital Parks
East is an arbitrary line drawn for administrative convenience. Outside
of DC, Harpers Ferry is bisected by the C&O Canal. Additionally, George
Washington Memorial Parkway and the C&O Canal are long linear parks, so
forest conditions at one end of the park may differ markedly from those
at the other end. All of these considerations would reduce the benefits
of stratification by park, as we may wish to analyze the data by a group
of neighboring parks, or break longer parks into smaller regions. These
types of analysis can be done post hoc if we select all of our sampling
sites from a regional design.

GRTS was used to generate a list frame (potential sampling locations)
for forest monitoring that includes all points on the grid that fall
within NCRN parks. The list frame was then used to pick the actual
monitoring locations. Each point in the list frame is numbered in the
order in which they should be considered for monitoring. Prior to plot
setup, potential monitoring points were visited to determine suitability
for forest vegetation monitoring (SOP1). A point was eliminated if it
did not contain forest vegetation (on a road, waterway, maintained
field, etc.), was on a slope greater than 30°, or was otherwise
hazardous, and the next point on the list was considered. Once a
preliminary list of monitoring points was developed it was submitted to
the various parks. The parks could then veto points if there were
concerns about monitoring due to the presence of archeological or
cultural resources, interference with visitors, or any other concern. As
of 2008, only 2 points have been vetoed by a park, in both cases due to
the fact that the monitoring plots would be in very high visitor use
locations.

For panel design (see below) each panel of 100 sites is constructed by
taking the first 100 suitable sites from the list for the first panel,
the second 100 suitable sites for the second panel and so on. If a site
becomes unusable at some point in the future (e.g. land is transferred
out of the park system, forests are felled for visitor facilities etc),
then the next suitable unused point on the GRTS list will be used as a
replacement.

Sampling Frequency and Replication
----------------------------------

Forest monitoring will take place annually but not all plots will be
measured every year. Yearly measurements of plots can cause soil
compaction and trampling of the understory which would bias the
monitoring results. Therefore, plots will be sampled on a rotating panel
design, with four panels. Each year a panel is sampled. Sampling will
take place from May through October, when foliage is fully developed.

Consideration was given to a sampling design with overlapping panels --
one where a small subset of plots would be measured two years in a row.
The advantage of an overlapping panel design is that it can give the
investigator an estimate of trends on a yearly basis rather than waiting
several years until a panel is re-sampled. Despite this advantage, this
type of design was ultimately rejected. It was felt that to detect an
annual change with a small sample size, the change had to be large in
magnitude. Furthermore, annual variation had to be fairly low, as a high
standard deviation would make it difficult to detect any changes. Few if
any of our measures were likely to have both a large trend and small
deviation. Furthermore, given the choice of possibly detecting an annual
trend in some measures vs. establishing a greater number of plots, we
felt that the parks would be better served by a larger sample size
overall. Finally, sampling the same plot in successive years would
increase trampling on the plot.

Recommended Number and Location of Sampling Sites and Frequency of Sampling
---------------------------------------------------------------------------

The NCRN has decided to sample 400 plots in total. The plots are divided
into four panels of 100 plots each. One panel will be sampled per year,
so that each plot is sampled once every four years.

A preliminary power analysis indicated that at least 300 plots should be
monitored, 75 each year. That would allow the NCRN to detect large
changes in moderately abundant species and smaller changes in dominant
species after the first re-measurement of the plots. During the first
year of monitoring NCRN staff determined that at least 100 plots could
be monitored annually. It was decided to increase the sampling size to
400 plots rather than sample 300 plots on a 3 year panel.

Level of Change That Can Be Detected
------------------------------------

The data from the first three years of the monitoring was used for a
power analysis. The analysis is preliminary as it does not have repeated
measures of the same plots, so spatial variation is used as a stand-in
for variation over time. It is likely that the variation over time will
be less than that across space, which makes this a conservative estimate
of the statistical power of this study.

A sample size analysis is used to determine the sample size needed to
determine a set level of change at a particular power and alpha level.
Performing this analysis for the forest monitoring protocols presents
some challenges. Multiple measurements will be taken on each plot, so a
design that provides an adequate sample size for some measurements may
not be adequate for others. Additionally, as the monitoring is expected
to continue indefinitely, more data will be added and the power to
detect change will increase. A design that does not provide adequate
power after the first repetition of the panels may provide adequate
power after several repetitions. For this analysis it was decided that
we would examine the power of the monitoring effort to determine changes
between the first two complete rounds of monitoring.

### Measurable Objective 1 -- Tree and Shrub Distribution

Tree and shrub distribution will be measured as the proportion of plots
that each species occupies. Trends in this proportion will indicate
which species are spreading in the region and which are becoming less
common.

A power analysis for this objective is somewhat difficult. Each plot
will only be visited once per sampling cycle. As we will not have
multiple samples of each plot, we cannot use occupancy estimation
analysis (MacKenzie et al., 2006). A more appropriate test would be the
"McNemar test for significance of changes" (Conover, 1999). The McNemar
test is a variant of the sign test that determines if there was a
significant difference between the number of unoccupied plots that are
colonized and the number of plots occupied by the species that become
vacant. If more unoccupied plots are colonized then the species is
spreading, and if more occupied plots become vacant then the species is
declining. Unfortunately, the power of the test is dependent on the
number of plots which change between occupied and vacant. Without a
reliable estimate of this number, it is not possible to perform a
meaningful power analysis.

For the purposes of this protocol, a power analysis will be performed
assuming that the data will be analyzed as a test for differences in two
proportions. This test compares the proportion of plots occupied by each
species after each complete sampling cycle. This test does not take into
account that plots that are occupied by a species in one sampling cycle
are more likely to be occupied by that species in subsequent rounds of
sampling. Therefore, the power analysis for this objective should be
considered preliminary and will be updated when appropriate data are
available.

In general, the test for a differences between two proportions is valid
when the sample size (*n*) and the proportion of occupied sites (*p*)
meet the criteria that

$$n*p \geq 10$$

and

$$n\left( p - 1 \right) \geq 10.$$

Given the 400 plot sample size at the regional level, this test will be
valid for species which occupy between 2.5% and 97.5% of all plots. For
a difference between two proportions test, differences are most
difficult to detect when one of the proportions is 0.5 (Moore and
McCabe, 1993). When this occurs we will be able to detect differences of
0.098 with power =0.8 and p=0.05 (Table 1).

Park level analysis will be possible in some cases. Fifty eight plots
are required in order to detect a change from 0.5 to 0.25 or 0.75 with a
power = 0.8 and p =0.05. At least two of the parks, Prince William and
the C&O Canal, will have more than 58 plots.

Unlike trees, saplings and shrubs are monitored on 3 microplots in each
plot. This data can be analyzed using occupancy analysis (MacKenzie et
al., 2006). In this analysis, each of the microplots will be treated as
a separate "visit" that samples the plots for each sapling and shrub.
Occupancy analysis determines the proportion of plots that are occupied
by each of the species (ψ) and the detectability of each species. The
detectability is a measure of how likely we are to find a species in our
microplots if it is present in the plot.

Given an estimate of the occupancy and detectability of a species it is
possible to do a power analysis. An analysis was performed on the power
of the design to determine the occupancy of saplings and shrubs that
were present in at least 10% of the 300 plots sampled as of September
2008. Eight species met this criterion. At a minimum, across the entire
400 plots, the design should have a standard error of less than 0.05.
All but one species met this criterion by wide margins (Table 2).

### Measurable Objective 2 -- Tree and Shrub Basal Area and Density

Tree and shrub basal area and density will be analyzed by looking at
plot totals across all species, and by looking at data from individual
species. Regardless of the focus of the analysis, at a minimum, after
one resampling of the plots, the design should have a power of 0.80 to
detect a 50% change in the measurement of interest with an alpha of
0.05.

For data summed across all species, an appropriate test is a matched
t-test that compares density or basal area from one round of sampling to
the next. A power analysis for this test was performed using the power
for a one sample t-test. For overall tree density and basal area, 8
plots are needed to detect a 50% change from current levels. With 400
plots a 5.9% change in basal area and 5.5% change in density can be
detected (Table 1)

For data from individual species, the situation in considerably more
complicated. Each individual species is present in less than half the
plots. As a consequence, the distribution of basal area or density has a
large peak at zero. This type of distribution is a "tweedie
distribution" part of a family of distributions known as "exponential
dispersion models" (Dunn and White, 2005). These models are used in
fitting generalized linear models. Using the tweedie distribution
(available in the R statistical package) generalized linear models can
be used to model changes in density and basal area of trees, shrubs and
saplings over time (Figure 2). Unfortunately, a power analysis is not
readily available for this type of modeling.

[]{#_Toc216757518 .anchor}Figure . *Quercus alba* measured basal area
vs. fitted values based on tweedie distribution. The data from the
monitoring plots shows a large proportion of the plots have no *Quercus
alba*. This can be accounted for by modeling the data as a tweedie
distribution.

### Measurable Objective 3 -- Coarse Woody Debris

The density of coarse woody debris, measured in m^3^/ha, will be
analyzed by determining the values on each plot by combining data from
the three transects. This data in not normally distributed, but a
log~10~ transformation better approximates a normal distribution. A
power analysis was performed on the transformed data using a one sample
t-test as was done for total tree basal area and density in measurable
objective 2. The analysis indicated that 18 plots are needed to detect a
50% change from current levels, and that with 400 plots a 9.8% change in
the log~10~ transformed data can be detected (Table 1). Due to the use
of the logarithmic scale, the amount of change that can be detected in
untransformed values depends upon the amount of CWD present. Smaller
changes can be detected when smaller amounts of CWD are present to begin
with.

### Measurable Objective 4 -- Exotic Tree and Shrub Distribution, Basal Area and Density

Distribution for exotic trees will be analyzed in an identical manner as
that for native trees, as outlined in Measureable Objective 1 above.
Basal area and density of exotic trees will be analyzed as described in
objective 2 above.

Table 1. Power analysis results for parametric tests.

  Measurement                                    Test              Mean      SD        Change Detectable at Power =0.80   \% Change Detectable   Minimum Plots Desired
  ---------------------------------------------- ----------------- --------- --------- ---------------------------------- ---------------------- -----------------------
  Tree/shrub species distribution                2 proportions     0.5       na        0.098                              19.6%                  58
  Total tree basal area per plot (cm^2^/ha)      1 sample t-test   276,000   109,000   15,300                             5.5%                   8
  Total tree density per plot (individuals/ha)   1 sample t-test   386       163       22.9                               5.9%                   8
  Coarse woody debris \[Log~10~(m^3^/ha)\]       1 sample t-test   1.36      0.945     0.133                              9.8%                   18
  Gypsy moth increase in distribution            2 proportions     0.13      na        +0.074                             56.7%                  505
  Gypsy moth decrease in distribution            2 proportions     0.13      na        -0.059                             45.7%                  326

### Measurable Objective 5 -- Exotic Understory Plant Distribution and Cover.

One measure of the impact of exotic understory plants is the
distribution of these plants across the region. As with trees, increases
or decreases in the number of plots occupied can be used to track the
distribution of the species.

Exotic herbaceous plants are measured on 12 quadrats in each plot. Like
the data for shrubs and saplings, the exotic herbaceous data can be
analyzed using occupancy analysis (MacKenzie et al., 2006). In this
analysis, each of the quadrats will be treated as a separate "visit"
that samples the plots for each of the targeted species.

An analysis was performed on the power of the design to determine the
occupancy of exotic species that were present in at least 5% of the 300
sampled plots. Nine species met this criterion. At a minimum, across the
entire 400 plots, the design should have a standard error of less than
0.05. All nine species met this criterion by wide margins (Table 2).

Table . Power analysis of occupancy data.

  Species                   Common Name             Measured as:   Naïve ψ^1^   Detectability^2^   Corrected ψ^3^   SE^4^ w/ 400 plots   Plots needed for 0.05 SE^4^
  ------------------------- ----------------------- -------------- ------------ ------------------ ---------------- -------------------- -----------------------------
  *Acer rubrum*             red maple               sapling        0.31         0.27               0.51             0.058                543
  *Asimina triloba*         pawpaw                  sapling        0.13         0.44               0.16             0.023                82
  *Cornus florida*          flowering dogwood       sapling        0.17         0.25               0.29             0.050                396
  *Fagus grandifolia*       American beech          sapling        0.37         0.61               0.40             0.026                107
  *Ilex opaca*              American holly          sapling        0.18         0.49               0.20             0.023                86
  *Nyssa sylvatica*         blackgum                sapling        0.32         0.39               0.41             0.036                208
  *Kalmia latifolia*        mountain laurel         shrub          0.15         0.51               0.17             0.021                72
  *Lindera benzoin*         northern spicebush      shrub          0.20         0.74               0.20             0.020                66
  *Alliaria petiolata*      garlic mustard          herbaceous     0.29         0.56               0.29             0.023                83
  *Berberis thunbergii*     Japanese barberry       herbaceous     0.087        0.18               0.096            0.015                41
  *Celastrus orbiculatus*   oriental bittersweet    herbaceous     0.087        0.28               0.088            0.014                33
  *Duchesnea indica*        India mock strawberry   herbaceous     0.15         0.33               0.15             0.018                52
  *Glechoma hederacea*      ground ivy              herbaceous     0.07         0.25               0.07             0.013                28
  *Hedera helix*            English ivy             herbaceous     0.063        0.64               0.063            0.012                24
  *Lonicera japonica*       Japanese honeysuckle    herbaceous     0.32         0.45               0.32             0.023                88
  *Microstegium vimineum*   Japanese stiltgrass     herbaceous     0.32         0.44               0.32             0.023                88
  *Rosa multiflora*         multiflora rose         herbaceous     0.13         0.25               0.13             0.017                47

^1^Occupancy based solely on the raw data, not corrected for
detectability

^2^Probability of finding a species in a particular quadrat if it is
present in the plot

^3^Occupancy corrected based on the detectability of the species.

^4^Standard Error

In addition to distribution, the NCRN also measures the percent of each
quadrat covered by each species. While invasive species are widespread
in the region, no individual species has been found on more than one
third of all plots (Table 2). Analyzing the percent cover data will
present the same challenges as analyzing basal area and density of trees
and shrubs. Currently, the NCRN plans to use a generalized linear model
approach to analyze this data as outlined under measurable objective 2
above.

### Measurable Objective 6 -- Exotic Vines on Trees

For this measurable objective there are two analyses to consider, how
common are the exotic vines, and which species of tree are susceptible
to exotic vine species. In the future the NCRN will seek to compare
mortality rates between trees with and without exotic vines, but there
is currently insufficient data for a power analysis.

The distribution of exotic vines on trees can be measured as presence or
absence on plots like that of tree species discussed in measurable
objective 1 above. In that case the results for the power analyses for
trees are equally applicable to vines (Table 1).

The NCRN can also look for trends in the proportion of trees per plot
that have vines. After sampling 300 plots, only 22% of them have any
trees with vines. Therefore, like the basal area and tree density from
measurable objective 1, this data follows a tweedie distribution and
will have to be analyzed using generalized linear models.

### Measurable Objective 7 -- Pests and Pathogens

In principal, the pest and pathogen data can be analyzed in much the
same way as the data from exotic vines on trees. However; in practice,
the analysis may have very low power. Some pathogens, such as hemlock
wooly adelgid are present in the NCRN but can only occur in the
relatively small number of plots where hemlocks occur. After three years
of sapling, hemlocks have only been found in four of the 300 plots. It
is likely that the number of plots with any particular disease will be
so small that the NCRN will have little power to detect trends. So far,
the most commonly encountered insect pest is gypsy moth, which occurred
on 39 of the 300 plots. At 400 plots the NCRN does not have a power of
0.8 to detect a change representing an increase of 50%, but we do have
sufficient power to detect a 50% decrease (Table 2). Note that the
sample design will have more power to detect a decrease in gypsy moth
distribution than an increase. However the monitoring program can play a
vital role in alerting park resource managers to emerging threats in
their parks, even if the data is not used quantitatively.

Field Methods
=============

Field Season Preparations and Equipment Setup
---------------------------------------------

At the beginning of each calendar year NCRN permanent staff will review
permits for monitoring all NCRN parks and submit permit renewal requests
and investigator's annual reports to the parks as necessary. All field
equipment will be inspected by NCRN staff and new equipment or supplies
will be purchased as necessary.

A series of maps will be made or updated to help the field crew locate
the monitoring plots in the field. The field crew will also be provided
with a list of phone numbers and contact procedures for parks that have
special requirements for entering certain areas (e.g. working along the
Baltimore-Washington parkway).

Initial ground-truthing and plot setup can take place year round. Prior
to plot setup, rebar stakes and survey markers must be prepared for each
plot.

Field Season Scheduling
-----------------------

### 

### Initial Ground-Truthing 

Ground-truthing of the plots consists of an initial visit to determine
if the plot is suitable for forest condition monitoring. SOP 1 details
how this assessment is made. Ground-truthing can occur year-round. The
only equipment needed for ground-truthing is a GPS and only a few
minutes are spent at any one point. Typically 7 or more points can be
checked in a single day. Approximately half of all points which are
checked in the region are unsuitable for forest monitoring. As plot
setup requires more staff time and more equipment, it is recommended
that all plots be ground-truthed before setup to avoid wasted trips.

### Plot Setup

Plot setup occurs after a location has been ground-truthed and the park
it occurs in has granted permission for monitoring but before the first
data collection begins. During plot setup permanent marking stakes are
set in the ground and trees are tagged and marked at 1.37m for measuring
the diameter at breast height. Methods for plot setup are discussed in
SOP 2. Plot setup can occur any time of the year, but a plot must be
setup before it can be monitored. On average, two plots can be setup in
a single day by two people, including travel to and from the sites.

During 2006, the first year of monitoring, plot setup took place during
spring and summer. This required two teams in the field, one with two
people doing setup and the other of three people taking the
measurements. After measurements were completed in the summer of 2006,
one field crew continued to setup plots during the fall and early
winter. The remaining plots were setup in spring and early summer of
2007. The 2007 field crew monitored the plots for that year, and then
setup the next year's plots in the fall. This system will continue until
all 400 plots have been installed. After the initial four years of
setup, fewer new plots will be needed, largely to replace those which
must be removed from the monitoring for some reason. This will take
place during the spring or summer, when the need becomes apparent.

### Monitoring

Monitoring can take place between May, when the canopy develops, and
leaf off, which typically takes place in early to mid October. Ideally
field crews will start as early in the season as possible to insure that
all plots are monitored before the end of the field season. In the first
three years of monitoring, measurements have taken approximately 17
weeks to complete. This includes sick and vacation days for the crew,
rain days, holidays etc.

Measurements and Post-Collection Processing
-------------------------------------------

The forest condition monitoring field crew will meet at the I&M office
in Washington DC each day. The crew will collect equipment and travel to
a network park for monitoring. The crew will plan the day to day
schedule themselves and contact the park managers or other personnel as
necessary. A small number of plots are located at the western end of the
C&O Canal near Cumberland, MD. As these are far from the I&M office the
crew will stay in that area overnight so that more time can be spent at
those plots. The crew should decide on a date to do this and work with
the network coordinator to make necessary travel arrangements. When
returning from the field, the crew will download data and digital photos
at the I&M office.

All measurements are described in SOPs 5 to 10. No laboratory processing
is planned, except for plant species identification that cannot be done
in the field. The botanist on the field crew will use appropriate
methodology to collect unknown plants outside the sample plot, if
possible, for later identification (SOP 11).

Official vouchers that have been identified will be stored at the NPS
Museum Resource Center unless otherwise designated by a park. A
temporary field herbarium may be created for training purposes during
the field season. Plants used for a field herbarium do not constitute
official vouchers and will be stored in the I&M office.

End of Season Procedures
------------------------

After measurements have been taken on all plots, the field crew will
meet with the data managers to determine if there are any plots with
missing or incorrect measurements. The crew will then revisit those
plots and verify the correct measurements. This can be combined with
setup of nearby plots for the next year.

Data Handling Analysis and Reporting
====================================

Metadata Procedures
-------------------

Any dataset compiled by the NCRN must be accompanied by Federal
Geographic Data Committee (FGDC) compliant metadata. This includes both
spatial and non-spatial datasets. Certain metadata fields will be
incorporated into the project database but additional metadata
documentation is often required. Specific metadata requirements can be
found in the NCRN Metadata SOP.

Overview of Database Design
---------------------------

The project database is based on the back-end database design of the
Natural Resources Database Template (NRDT). The NCRN deploys field crews
with tablet PCs which run the project database in the field. Crews enter
vegetation data directly into the project database thereby eliminating
the need for paper field forms. The database incorporates many functions
and utilities to help reduce the possibility of data entry errors and
promote data integrity. Entering the data in this manner eliminates the
need to transfer data from paper data forms into a project database
running on a desktop PC. Eliminating this step adds an additional level
of quality control. Paper datasheets are available to the crew in the
field, but only as a backup in case of a computer failure.

Data Entry, Verification and Editing
------------------------------------

As mentioned above, ruggedized tablet PCs are used by field crews to
enter vegetation data directly into the project database. This increases
the integrity of the data by eliminating the step of transferring
information from field forms to the database at a later time. Field
crews are responsible for verifying the data entered into the database
and the crew leader is responsible for ensuring that all datasets
undergo complete QA/QC. Certain QA/QC measures are incorporated into the
data entry forms of the database including pick lists and automatically
populated fields. SOP 12 covers the QA/QC and other data management
performed by the field crews.

Recommendations for Routine Data Summaries, Tables, Figures and Statistical Analysis to Detect Change and Trends
----------------------------------------------------------------------------------------------------------------

After each year of data collection the NCRN will prepare an annual
report. The annual report will focus on the activities of the previous
year and contain data summaries at the regional and park level (SOP 13).
The primary purpose of the report is to inform park managers and other
interested parties of new information that has been generated during the
field season. The annual report with have summary information on density
and basal area of all trees, shrubs and saplings, seedling density,
volume of coarse woody debris, and presence of invasive species and
forest pests. In order to prevent excessively large annual reports, not
every field measurement will be reported. Once plots are being
re-measured, the annual reports should compare the current year's data
to previous measurements on the same set of plots.

Every four years, once all plots have been sampled, the network will
prepare a status and trends report based on the complete dataset. Once
trend data is available, this report will be more focused on trend
detection than the annual reports, and will be more statistical in
nature.

The NCRN quantitative ecologist should work with the data manager to
incorporate routine summaries and analysis directly into the project
database. This will speed the process of producing annual reports and
will keep the reports consistent even when there is staff turnover.

Recommended Reporting Schedule and Format
-----------------------------------------

Annual reports will be prepared in the fall and winter following each
field season. Status and trends reports will be prepared every four
years after each complete sampling of the plots. These reports will be
published in the National Park Service's Natural Resource Technical
Report Series. Formatting will follow current guidelines for that series
(NPS, 2006).

In addition to the regular reports, additional reports will be prepared
when appropriate. These might include specific reports prepared at a
park's request, input into a park planning document or journal
publications.

Recommended Methods for Long-Term Trend Analysis
------------------------------------------------

Methods for trend analysis will change as more data accumulates. In
general trend analysis will focus on comparing measurements from each
plot to measurements of the same plot taken in earlier years. During the
first four years of monitoring, trend analysis will not be performed as
each plot will only have been measured one time.

During the second round of sampling (years 5 through 8), it will be
possible to compare between the first two rounds of sampling. At this
time, tests for differences in means can be used to detect changes. This
may include matched t-tests, generalized linear models or non-parametric
tests, depending on the data.

As more data accumulates, different analyses will become more
appropriate. This could include regression analysis, time series
analysis or life history table analysis depending on the specific
question and the data available.

Data Archival Procedures
------------------------

Data is transferred from the field team(s) to the I&M Data Manager on a
daily basis. The data is maintained on the I&M file server in the proper
project folder and considered "Active" until the completion of the field
season. After each field season, project data from that season is
aggregated and archived in the project folder under the "Archive"
directory. Prior to archiving the data must be verified and validated
through proper QA/QC procedures. Once this has been done, the dataset is
considered certified and can be archived. The archived datasets are
stored under the Archived folder for that project which is formatted as
"Read Only" for everyone except the I&M Data Manager.

In addition to archiving electronic data, any hard copy materials and
vouchers are archived at the regional museum resource center (MARS) at
the end of each field season. For additional information about archiving
procedures see the NCRN Digital Data Storage SOP, Print Media Storage
SOP and the Voucher SOP available in the NCRN Data Management Plan
(National Park Service, 2005b).

Personnel Requirements and Training
===================================

Roles and Responsibilities
--------------------------

### 

### Network Coordinator

The network coordinator oversees all administration of the forest
monitoring. This includes hiring personnel, making purchase and travel
arrangements, managing the budget and any contracts or agreements
relevant to the monitoring. The network coordinator is the official
supervisor of the field crew. The network coordinator also participates
in field crew training and performs field work on an ad hoc basis.

### Quantitative Ecologist

The quantitative ecologist oversees technical aspects of the forest
monitoring. This includes protocol development, site selection, site
setup, data analysis and reporting. The quantitative ecologist acquires
the permits and prepares Investigator's Annual Reports (IAR's). The
quantitative ecologist provides the crew with maps and directions to all
of the plots. The quantitative ecologist also participates in field crew
training and performs field work on an ad hoc basis.

### Data Manager

The data manager is responsible for providing database training to I&M
permanent staff and field crews and ensuring that all those involved in
the project are aware of their data management responsibilities. All
data transfers and data archiving will be facilitated by the data
manager. The I&M data manager will be responsible for providing any
database assistance as well as GIS support when needed. The data manager
will also archive documents and specimens with the regional museum. The
data manger will help with field work on an ad hoc basis. Since 2006,
the NCRN data manager has been aided by a term appointment GIS
specialist.

### Vegetation Crew Leader

The vegetation monitoring crew leader will be responsible for managing
vegetation field crews. The crew leader should be skilled in botany with
a strong knowledge of flora of the mid-Atlantic region. The crew leader
will determine the daily schedule for field work and coordinate with
park staff. The crew leader will make sure all field crews are properly
trained in data collection and use of the database. The field crew
leader will regularly participate in field work.

### Two Field Crew Members

The field crew members carry out the monitoring in the field and make
sure all data is entered in the database.

Training Procedures
-------------------

Field training for correctly executing the SOPs should be decided by the
I&M Network Coordinator.

Operational Requirements
========================

Annual Workload and Field Schedule
----------------------------------

The process of hiring field crews should begin as soon after the
beginning of the fiscal year as possible, due to the length of time it
takes to hire seasonal staff. Investigators annual reports are due early
each calendar year, and permit applications should be submitted in
January or February of each year to make sure that any issues are
resolved before the field season begins. Scheduling for field work is
discussed above.

Work on the annual reports can begin after the field work has been
completed. The annual reports should be finished in the spring after
each field season.

### 

Facility and Equipment Needs
----------------------------

The field crews will be based at the Center for Urban Ecology office in
Washington DC. In addition to the equipment listed in SOP 2 and 3, the
only equipment required will be access to computers and software for
analysis, reporting and archiving. A small amount of additional supplies
may be required to prepare voucher collections of plant species. The
field crew will need to have access to a four wheel drive vehicle for
the entire field season.

Startup Costs and Budget Considerations
---------------------------------------

We have estimated the costs for 2006, the first year of implementation
of the protocol. This has been broken into two components -- costs
associated with existing full time network staff (Table 3), and those
which are specific to this particular protocol (Table 4). Three existing
staff members are expected to be involved in the protocol: the network
coordinator, the quantitative ecologist, and the data manager. The term
GIS specialist also provided considerable help. Full time network staff
will also assist the field crews on an ad-hoc basis, particularly at the
initiation of the field season when crews are undergoing training and to
cover for occasional absences of field crew members.

Table Startup costs: allocation of existing staff costs to protocol.

  Position                         Work Weeks   1^st^ Year Cost (2006)
  -------------------------------- ------------ ------------------------
  Network coordinator (GS-12)      14           \$23,000
  Quantitative ecologist (GS-12)   20           \$34,000
  Data manager (GS-11)             5            \$7000
  GIS specialist (GS-9)            8            \$9000
  Total                                         \$73,000

Table 4. Startup costs: new staff and equipment to implement protocol.

  Position                               Work Weeks   1^st^ Year Cost (2006)
  -------------------------------------- ------------ ------------------------
  Field crew leader (GS-7)               26           \$19,802
  Two field crew members (GS-5)          26           \$31,972
  Miscellaneous equipment and supplies                \$21,000
  Total                                               \$72,774

This specific protocol requires the network to hire three seasonal
employees. These include a field crew leader who will be responsible for
carrying out the protocol in the parks. Additionally, money is allocated
to purchase equipment related to plot setup and measurement. After the
plots are established and basic equipment needs are met, it is
anticipated maintenance cost for plots and equipment will be lower.

Revision History
================

Version 2.0 (November, 2008)
----------------------------

-   Protocol reformatted for publication in NRR report series

-   Updated methods section to reflect the decision to sample 400 plots

-   Updated sections on reporting to match current practice

-   Improved text throughout

Version 1.0 (January 2006)
--------------------------

Version of protocol used from 2006 to 2008.

Literature Cited
================

Bates, S. 2006. White-tailed Deer density monitoring protocol version
1.1: Distance and pellet-group surveys. National Capital Region Network,
Center for Urban Ecology, National Park Service, Washington DC.

Conover, W.J. 1999. Practical Nonparametric Statistics. John Wiley and
Sons Inc., New York.

Dawson, D.K. and M. G. Efford. 2006. Protocol for monitoring
forest-nesting birds in national park service parks. National Capital
Region Network, Center for Urban Ecology, National Park Service,
Washington DC.

Diefenbach, D.R. and C. Mahan. 2002. Setting realistic objectives:
vegetation inventory and monitoring at Shenandoah National Park.
Technical Report NPS/PHSO/NRTR-02/87, National Park Service, Northeast
Region, Philadelphia Support Office, Philadelphia, PA.

Dunn, P.K. and N White. 2005. Power-variance models for modeling
rainfall. In: 20^th^ International Workshop on Statistical Modeling
10-15 July 2005, Sydney, Australia.

Forest Inventory and Analysis \[FIA\]. 2004. Forest Inventory and
Analysis program background. U.S. Department of Agriculture, Forest
Service, Forest Inventory and Analysis program, Washington, DC.
http://fia.fs.fed.us/. \[accessed December 1, 2004\]

MacKenzie, D.I., J.D. Nichols, J.A. Royle, K.H. Pollock, L.L. Bailey and
J.E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Pattern
and Dynamics of Species Occurrence. Academic Press, New York.

Moore, D.S. and G.P. McCabe. 1993. Introduction to the Practice of
Statistics, Second Edition. W.H. Freeman and Company, New York.

National Park Service. 2005a. Long-term Monitoring Plan for Natural
Resources in the National Capital Region Network. Inventory and
Monitoring Program, Center for Urban Ecology. Washington DC.

National Park Service. 2005b. Data Management Plan for Natural Resources
in the

National Capital Region Network. Inventory and Monitoring Program,
Center for Urban Ecology. Washington DC.

National Park Service. 2006. Instruction to authors---Natural Resource
Report and Natural Resource Technical Report. Natural Resource Report
NPS/NRPC/NRR---2006/001. National Park Service, Fort Collins, Colorado.

Peet, R.K., T.R. Wentworth and P.S. White. 1998. A flexible multipurpose
method for recording vegetation composition and structure. Castanea 63:
262-274.

Schmit, J.P., D. Chojnacky and M. Milton. 2006. National Capital Region
Network Long-Term Forest Monitoring Protocol Version 1.0. Inventory and
Monitoring Program, Center for Urban Ecology, Washington D.C.

Stevens, D.L. and A.N. Olsen. 2004. Spatially balanced sampling of
natural resources. Journal of American Statistical Association. 99(465):
262-278.

Townsend, P.A., R.H. Gardner, T.R. Lookingbill and C.C. Kingdon. 2006.
Remote sensing and landscape pattern protocol for long term monitoring
of parks. National Capital Region Network, Center for Urban Ecology,
National Park Service, Washington DC.

SOP 1: Ground-Truthing Potential Monitoring Locations (November, 2008)
======================================================================

Version 1.0

Introduction
------------

This SOP describes how to ground-truth potential monitoring locations
for the NCRN forest condition protocol. This includes visits to the
location, determining if it is suitable, and taking appropriate notes.
Ground-truthing requires one person and can take place at any time of
year.

Preparing for Field Work
------------------------

Before heading out to the field, you must develop a list of locations to
be ground-truthed. The NCRN data manager and quantitative ecologist
maintain the list of potential locations and their GRTS number. Start
with the lowest GRTS number that has not already been used or rejected.
Plot locations are used in order by GRTS number. In practice, about half
of all locations are rejected, so ground-truth at least twice as many
locations as you think you will need.

The first step in the process occurs in the office. Using the GIS,
determine the ownership for every plot location you are considering. If
any location is not owned by the Park Service, it is automatically
rejected. Land owned by the NPS is often referred to as "fed-fee" land
to distinguish it from land which the NPS does not own outright, but
instead has easement rights.

Print out maps of all of the potential locations to ground-truth in each
park.

Before heading out, be sure you are familiar with how to use the GPS and
the TerraSync database on the data logger.

Equipment List
--------------

The following equipment is needed in the field

-   Trimble GPS, including receiver, antenna, data logger, batteries and
    magnetic roof mount

-   Maps to plot and 2 copies of research permits

-   Insect repellent

-   Laser rangefinder or clinometer to measure slope.

-   Lunch, water etc.

Field Work
----------

### 

### Assessing the Location

Using the GPS, navigate to the potential plot location. Usually you can
visit 7 or more points in a park in one day. Typically you can assess
the location if you get to within 2m of the point. However, in cases
where you are near to a road or forest edge, or where the slope is near
the 30% cutoff, you should get to within 1m to assess the point. To
assess the point consider the following:

-   Is the entire potential plot in a forest or land that is reverting
    to forest from some other land use? In the NCRN forest (including
    wooded wetlands) and marsh are the only natural habitats you are
    likely to encounter. Therefore, assume that any canopy opening or
    abandoned farm field will revert to forest. Land that the parks are
    managing to prevent succession -- e.g. mowed fields, is not
    considered potential forest. If any part of the plot is not forest
    or potential forest then the point is rejected.

-   Is any part of the plot mowed or trimmed? In some parks there are
    wooded picnic areas and campgrounds where underbrush is routinely
    trimmed. We do not monitor forest conditions in these areas. Areas
    that are undergoing treatment for exotic plants, but are not
    otherwise mowed are suitable for forest monitoring.

-   How steep is the slope? If the slope is steeper than 30° the
    location is not used due to safety concerns for the crew and
    potential damage to the understory. When assessing this, consider
    what the crew will actually need to walk across. Very small steps or
    steep spots that the crew can easily avoid should not automatically
    disqualify a plot if they will not interfere with monitoring.

-   Is the plot entirely on fed-fee land?

-   Does a larger stream or river run through the plot? Plots are
    monitored in locations with seasonal streams, or small streams with
    forest vegetation in them. Plots which include streams that are
    typically more than 50cm deep and have cleared their channel of
    vegetations are not used. In some locations, such as along the
    Potomac, the edge of the river is a wooded wetland and water can be
    deeper than 50cm at times. As long as the entire plot will be in the
    wooded part, this habitat can be used as a forest monitoring
    location.

-   Is there a road in the plot? Locations with paved or dirt roads are
    not monitored, but locations with foot paths are monitored.

-   Is there any unusual safety hazard for the crew? Dangerous locations
    are not monitored. An example of an unusual safety hazard would be
    an abandoned building which is near the plot and could collapse on
    the crew.

-   Is there any archeological or cultural resource that would be
    disturbed by forest monitoring? The NCRN staff will discuss these
    locations with the park staff, but they will most likely be
    eliminated.

### Data Entry

Once you have arrived, open up the data screen for that point in
TerraSync on the data logger. The logger will display the park name,
plot code and GRTS number; make sure you are entering data for the
correct point. Enter data into each field as follows;

-   Visited: Mark Y if you have visited the plot. Plots which are not on
    fed-fee land can be marked with an N.

-   Forest: Mark Y if this location is suitable for a forest condition
    plot, N if it is not and "?" if you are unsure. Reasons to be unsure
    would be a slope that is difficult to measure alone, poor GPS
    precision in an area that is near to a non-forest habitat, or land
    use that is not immediately clear and input from park staff is
    needed.

-   Habitat: choices include Grass (including crops), Marsh, Water,
    Road, Swamp (wooded wetland), Rec (recreational area such as a ball
    field or yard of a visitor center), Forest and Building.

-   Anderson 2: choose the appropriate Anderson Level 2 habitat
    classification

-   Slope: choices are Flat, Hill and Too Steep (for location with a
    slope \> 30°).

-   Photo: Y or N, if you took a photograph at the location.

-   Notes: Enter anything noteworthy about the location. If you put N in
    the forest field, and the habitat is forest or swamp, be sure to
    indicate why the point was rejected. If you put "?" in the forest
    field, be sure to indicate why you are not sure if the plot is
    suitable or not.

Post-Fieldwork
--------------

After you have returned, download the data from the data logger to the
appropriate place on the server as indicated by the NCRN data manager.
Prior to plot setup, the potential plot locations must be approved by
park natural resource managers. They should be included in the annual
permit application submitted in the park, but if necessary new locations
can be approved between permits.

Revision History
----------------

### Version1.0 (November, 2008)

-   Original version of the protocol, in use since 2005, but formalized
    as an SOP in November, 2008.

SOP 2: Plot Location and Establishment (November, 2008)
=======================================================

Version 2.0

Introduction 
------------

This SOP describes how to establish permanent plots for the NCRN forest
condition protocol. The plot setup will include placing permanent makers
in the ground, tagging trees, marking dbh and determining the distance
and azimuth of each tree relative to plot center. Shrubs and saplings
are also tagged and marked.

Preparation
-----------

Before setup can begin, permanent markers must be prepared. Each
potential plot location has already been assigned a plot code based on
the parks 4 letter acronym and a number. The number is based on the
location of the potential plot in the park, with the northwestern most
point numbered as "1" proceeding to the last numbered plot in the
southeast corner. The NCRN data manager has the plot code for each
location.

The center of each plot is marked by a piece of rebar ¾" × 18" topped
with an aluminum survey cap. The survey cap has "U.S. Dept of Interior",
"Vegetation Plot", "Inventory & Monitoring" and "National Park Service"
stamped on the edges. The center is left blank. Prior to fieldwork, use
a metal die set to punch the plot code into the survey cap. Once the cap
is marked, place it on the rebar and use liberal amounts of plastic
steel putty to fix it in place. The plot center marker should then be
left for several days to dry and cure.

Six smaller rebar stakes, measuring ½" × 12", are used to mark the
centers of the microplots and the ends of each transect. Prior to going
in the field, use the rebar bender to bend about 3" of each of the
smaller stakes at a 90° angle. The long end of the rebar will be driven
into the ground. The smaller bent end will remain above and flush with
the ground. The bent end will present a greater surface to the metal
detector and make it easier to find in subsequent visits.

Finally, the location of the plot must be loaded into a GPS system. For
initial plot setup it is important that the center of the plot be
located as closely as possible to the coordinates from the GIS.
Therefore, take the GPS with the greatest accuracy, such as a Trimble
Pro-XR with an integrated beacon that allows for sub-meter accuracy. The
list of locations is kept by the NCRN data manager.

Equipment List
--------------

The following equipment is needed in the field:

-   Trimble GPS, including receiver, antenna, data logger, batteries and
    magnetic roof mount

-   Maps to plot and 2 copies of research permits

-   Laser rangefinder with built in digital compass

-   Tripod and tripod mount for rangefinder

-   PVC pole with dbh marked

-   Plot center marker

-   Six smaller bent rebar stakes

-   Rubber mallet

-   2.5 lb sledge hammer

-   Claw hammer

-   Board with reflective tape

-   Notebook with water proof paper

-   Pens and pencils

-   Compass

-   Tree tags (about 150 per plot)

-   Aluminum nails

-   6 Chaining pins

-   Leather sheath for chaining pins

-   Flagging tape

-   Tree marking spray paint

-   Pistol grip for spray paint

-   Plastic cable ties

-   Calipers

-   Sonar rangefinder

-   30 m tape measure

-   Dbh tape

-   Leather holster for dbh tape

-   Utility apron

-   Orange safety vest when working along busy roads

-   Extra batteries

-   Insect repellent

-   Calculator

Plot Location and Marking
-------------------------

Drive to a convenient parking spot and leave a copy of the research
permit in the windshield of the car. Carry a second copy of the research
permit with you. Start the GPS and navigate to the plot. Once at the
plot find the plot center to within 1 m. It helps to make a small mark
in the dirt with your boot so that you can locate the point again after
you have removed your pack.

Use the rubber mallet to pound the plot center marker into the ground
until top of the survey cap is flush with the ground. That is, the plot
center marker should not stick up. Do not hit the plot center marker
directly with the sledge as this will damage the aluminum survey cap and
make the plot code hard to read. If you need more force than the mallet
can provide, place the head of the mallet on the survey cap, hold the
mallet handle with one hand, and hold the sledge in the other. Hit the
mallet head with the sledge, thus protecting the survey cap.

If a rock blocks the point at the center of the plot, move the center
marker the shortest distance possible and sink it there. If you need to
move the center more than 1m, than you should make a small mark on the
rock with the tree marking paint and place the plot marker in nearest
possible place. Note the center is marked with paint in the notebook and
give the direction and distance from the plot maker to plot center.
However, do not mark the rock with paint if you are in a location that
has high visitor use or if the obstruction may have archeological or
cultural significance. In that case, don't set up the plot, instead the
NCRN permanent staff will contact resource managers to figure out what
is best to do at that particular site.

Monitoring Plot Layout
----------------------

The layout of the monitoring plots is diagramed in Figure 3, below.
Important features of the plot include:

**Plot** of 15-m radius for live trees 10-cm dbh (diameter at breast
height).

**Microplots** of 3-meter radius for trees 1 to 10 cm dbh and shrubs ≥
1cm drc (diameter root collar). Three microplots are at 60^o^, 180^o^,
and 300^o^ and 10 m from plot center.

**Quadrats** (2×0.5 m) for select herbs and shrub/tree seedlings (\<1 cm
dbh or drc). Located along **3 transects** at 0^o^, 120^o^, and 240^o^
from plot center, where 3 quadrats are placed to right of each transect
with lower corner at 3, 8, 13, meters (3 quads per transect) and in the
center of each microplot (Total of **1**2 quads per plot).

Flow of Work
------------

If two people are setting up the plot, one person should remain at plot
center. That person will operate the laser rangefinder and take all of
the notes. The other person will install the transect and microplot
center markers and paint and tag the trees. Once all trees are tagged,
both field workers will mark, tag and record saplings and shrubs in the
microplots.

If three people are setting up a plot, and the plot is relatively open,
the third person can start tagging and marking the trees while the other
two place the plot markers and measure the distances and the azimuths to
the trees. Alternatively, if the forest is unusually dense and microplot
setup will take a long time, the third person can setup the microplots
while the other two work on plot markers and trees.

Marking Transects and Microplots
--------------------------------

Once the plot center maker has been installed, calibrate and setup the
laser rangefinder. The rangefinder should be directly above plot center.
Using the digital compass setting, one crew member should point the
rangefinder to magnetic north. A second crewmember should take the board
with reflective tape, the bent rebar stakes the chaining pins and the
sledge hammer to install the stake. The first stake is installed at 0°,
15m distance and is the end of one of the transects. The crew member at
plot center should direct the person at the edge of the plot until they
are straight north. Aiming at the board with reflective tape as a
target, use the rangefinder to direct the crew member with the stakes to
15 m out. When measuring the distance be sure to use the horizontal
distance, not the distance along the slope. The laser rangefinder can
provide this distance. You should get to within 20 cm and 1° of azimuth
from the designated location before installing the stake. Pound the long
end of the stake in until the bent portion is flush with the ground.
Insert one of the chaining pins with flagging next to the stake to mark
its location. If a rock blocks the marker, go to the nearest possible
location to insert the marker and place blue paint on a rock to mark the
true location. If the plot is in a highly visible location or has
cultural or archeological significance, don't set up the plot. The order
of stakes to be set up is shown in Table 5.

Table 5. Order of installation of plot markers.

  Azimuth   Distance from Center   Purpose
  --------- ---------------------- -----------
  0°        15m                    Transect
  60°       10m                    Microplot
  120°      15m                    Transect
  180°      10m                    Microplot
  240°      15m                    Transect
  300°      10m                    Microplot

Each stake should be marked with a chaining pin with flagging tape. It
is helpful to use different colors of flagging tape to distinguish
between the transect stakes and the microplot stakes.

Tagging and Marking Trees
-------------------------

### 

### What Is a tree?

For the purposes of this protocol a tree is an individual woody plant
that is not on the list of shrub species (see SOP 8 for this list) and
that has a diameter or equivalent diameter of 10cm at dbh (diameter at
breast height=1.37m).

The equivalent diameter criterion applies only to trees that split into
two or more stems below dbh. In general, we wish to include split trees
that have the same or greater total basal area as a tree with a single
trunk with a dbh of 10 cm. This is a departure from FIA methodology,
which only includes trees where at least one stem has a dbh ≥10cm.

If any of the stems have a dbh ≥ 10cm, then the individual is included
as a tree. If all of the stems are individually less than 10cm dbh, then
the equivalent must be calculated. To calculate equivalent diameter, use
the following equation:

$$Equivalent\ Diameter = 2\ \left( \sqrt{\left( \frac{Diameter\ of\ stem\ 1}{2} \right)^{2} + \left( \frac{Diameter\ of\ stem\ 2}{2} \right)^{2} + \left( \frac{Diameter\ of\ stem\ 3}{2} \right)^{2}}\ldots\ldots etc \right)$$

For simplicity Table 6 can be used as a guide to situations commonly
encountered when a tree splits into two stems. Note that for trees with
two stems, if both stems are ≤ 7cm, then the tree is always too small.
If for some reason you are unsure if you should include a tree or not,
include the tree as it will removed later during QA/QC if it is too
small.

Table 6. Stem sizes for an equivalent diameter ≥10cm.

  Dbh of Largest Stem   Requirement for dbh of Smaller Stem
  --------------------- -------------------------------------
  9.9 cm                ≥1.41 cm
  9.5 cm                ≥3.12 cm
  9.0 cm                ≥4.36 cm
  8.0 cm                ≥6.00 cm
  7.07 cm               ≥7.07 cm

### Measuring Diameter

The diameter measurement is not recorded when the plot is established.
However, in order to determine which individuals are trees and to mark
the trees, the setup crew needs to understand how diameter is measured.

Dbh is measured to 0.1 cm at 1.37 m from the ground. Trees on a hill
should be measured on the uphill side of the tree. Leaning trees should
be measured on the short side (Figure 4).

![](media/image5.png)

If there is an abnormality at dbh, take the measurement just below the
abnormality if possible, marking the tree at the measurement point. If
the abnormality extends far below dbh, then take the measurement just
above dbh.

If the tree forks, measure each stem of the tree. Always record the dbh
of all separate stems before performing the calculation needed to derive
the equivalent diameter. If the forking influences the diameter of the
stems at the dbh, then treat the forking as an abnormality as explained
above. If a tree appears to fork beneath the ground, but the trunks are
not visibly connected at the surface, mark and tag them as two separate
trees.

### Tagging Trees

The NCRN uses aluminum tree tags engraved with "U.S. National Park
Service, Forest Monitoring, Do Not Remove" and then a unique identifying
number. Each tree, sapling and shrub is given a tag, seedlings are not.
When a tree splits into two or more stems, the entire tree gets a single
tag, do not tag each individual stem. Do not worry about putting all of
the tags in any particular numerical pattern or order. As existing trees
die and new trees grow, any order will be lost.

In general tags should be placed so that they are facing the plot center
as this will help field workers to locate the center marker. However,
when the plot is near a road, trail or other high traffic area, the plot
should be as inconspicuous as possible. Place the tags so that they are
facing away from high public use areas.

There are two methods used for tagging trees. In most cases you should
attach the tag to the tree using an 2 ¼˝ aluminum nail. The tag should
be placed at shin height, as this will be less conspicuous. Hammer the
nail about 1/3^rd^ of the way in, angling downward. This will allow the
tag to hang away from the tree and not be swallowed up as the tree
increases in diameter.

The other option for tagging trees is to attach the tag using plastic
cable ties. In practice you will need to string two or more ties
together in order to reach around a tree. Make sure there is plenty of
slack in the tie so that the tree has room to grow. The tag and ties
should rest on the ground.

### Marking Trees

In order to accurately re-measure dbh at the same point on successive
visits, each tree is marked at dbh. Use a PVC poll with a mark at 1.37m
to determine where the measurement should be taken on the tree. Then
paint a horizontal line on the tree using the tree marking paint. Try to
make the line as thin as possible. In general, the line should be made
facing plot center. However, as with the tags, the line should not be
visible areas with high visitor traffic, such as trails and roads.

### Measuring Distance and Azimuth

Measure the distance to 0.1m and the azimuth to 1° of each tree with
respect to the center of the plot. In general this can be accomplished
using the digital compass and rangefinder along with the reflective tape
target. Occasionally, dense underbrush can make it difficult to measure
the distance with the rangefinder. In these instances the sonar
measuring device will work. In the unlikely event that neither of these
works, use the 30m tape measure. In all cases measure the horizontal
distance, not the distance along the slope.

Setup of Microplots
-------------------

Each plot has three circular microplots, each with a 3m radius. The
centers of the microplots are 10m from plot center, at azimuths of 60°,
180° and 300°. Use the sonar measurer or the tape measure to determine
which shrubs and saplings are in the plot and tag them. When determining
which saplings and shrubs are in the plot, be sure to use the
horizontal, not the slope distance.

Saplings are non-shrub woody plants with a dbh ≥1cm and \<10cm. Dbh for
saplings is measured in an identical fashion as it is for trees. The one
exception is that the equivalent diameter method is not used for
saplings. Instead, for a sapling to be tagged at least one stem must
measure ≥ 1cm at dbh. Sapling are painted at dbh in the same way that
trees are.

Shrubs are woody plant species on the list of shrubs (SOP 8). Shrubs are
tagged if their drc (diameter at root crown) is ≥ 1cm. Shrubs are not
painted at plot setup.

All tags and dbh marking should be placed so that they face the center
of the microplot, not the plot. As with all other tags and marks, do not
place them so they are visible to high visitor use areas.

Note Taking
-----------

One crew members should act as the note taker during setup. Be sure to
note the following:

-   The plot code assigned to the plot

-   Date

-   Crew members who set up the plot

-   The tag number, distance and azimuth of every tree

-   The microplot and tag number of each sapling and shrub

-   Record if any microplot has no trees or shrubs at setup

-   A brief description of where to park and how to get to the plot.

-   Any problems or other comments

Cleanup 
-------

After setting up the plot be sure to remove the chaining pins from the
transects and microplots. Do not use flagging to mark the route to the
plots or the plots themselves.

Revision History
----------------

### 

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Expanded explanation of equivalent diameter.

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 3: Office Preparations Pre- and Post-Monitoring and Field Equipment (November, 2008)
========================================================================================

Version 1.0

Introduction
------------

This SOP describes the steps that are taken each day before and after
monitoring the plots and contains a list of equipment that is needed for
fieldwork.

Preparations before Monitoring
------------------------------

Before heading to the field, verify that you have the maps and field
work permits for the correct park with you. You may need to make special
arrangements to work in some areas of the parks (e.g. the Baltimore-
Washington Parkway, lands adjoining Quantico Marine Base), plan ahead
accordingly. Check the field computers and the GPS to make sure that
they have the plot data and the locations for the planned plots. If any
of the data is missing, the data management staff can provide it. Make
sure that someone at the office knows which park you are working in.

Field Equipment
---------------

The following equipment should be taken with you for collecting the
monitoring data:

-   Plot and the park maps

-   Street atlas or vehicle based GPS unit

-   Permits

-   Hand held GPS

-   Metal detector

-   2 Tablet computers

-   Packing tape (for protection against tics)

-   Insect repellent

-   Copy of protocol

-   Blank paper data sheets

-   2 Metal clipboards

-   All weather paper

-   3 Back packs

-   PVC quadrat frame

-   4 30m measuring tapes

-   2 compasses

-   Spare tree tags

-   Black zip ties

-   Aluminum tree nails

-   Hammer

-   Forestry spray paint

-   Pistol grip for spray paint

-   DBH pole

-   Binoculars

-   2 DBH tapes

-   Pencils and pencil sharpener

-   Spare batteries

-   4 Chaining pins

-   3 Pink marker flags

-   Leather sheath for pins and flags

-   Hand lens

-   Digital camera

-   2 Meter folding rulers

-   12˝ Ruler

-   Throw rope (for obtaining plant specimens which are out of reach)

-   Plant presses

-   Whistle

-   Field Guides

-   Lunch, water, personal items

Post-Monitoring Office Work
---------------------------

After you return to the office, you should ensure that the day's data is
properly archived. The data should be backed up to a USB key and passed
on to the data manager. The data manager will provide training on this
procedure (see SOP 12). The data manger will integrate this data with
the main forest monitoring database on the I&M server.

The data manger will also provide hardcopies of the monitoring data for
each plot after it has been monitored. Every crew member should review
the data to make sure that it is accurate or complete. Indicate any
problems on the data sheet and return it to the data manager. If data is
missing the plot can be revisited to fill in any gaps.

Make sure that the tablet batteries are left to recharge overnight. Once
a week, connect the tablets to their docking stations, and the internet
and leave them on overnight. This will allow them to receive security
updates and software upgrades.

Once a weak download the plot photos and obtain a blank data card for
the camera (SOP5)

Be sure to report any equipment problems to the data manager or I&M
coordinator.

Revision History
----------------

### 

### Version1.0 (November, 2008)

Original version of the protocol, in use since 2005, but formalized as
an SOP in November, 2008.

SOP 4: Arriving at the Plot and Flow of Work (November, 2008)
=============================================================

Version 1.0

Introduction
------------

This protocol describes how to find the plots and the general flow of
work during monitoring.

Locating the Plot
-----------------

You will be provided with a map and general directions to each plot.
Drive to a convenient parking spot and leave a copy of the research
permit in the windshield of the car. Carry a second copy of the research
permit with you. Start the GPS and navigate to the plot. As you get near
the plot you will usually spot trees which have been marked with
forestry paint and tree tags.

To minimize the effects of trampling, leave the backpacks with equipment
outside of the plot. Use the metal detector to find the plot center
marker. It is helpful to remember that in most cases the tags and
marking paint should point in towards the center stake. Once you locate
the center stake, mark it with a chaining pin.

Flow of Work
------------

Once the plot has been located, use a compass and the metal detector to
locate the six bent pieces of rebar marking the ends of the transects
and the center of the microplots. Mark the microplots with one of the
marking flags. Mark the ends of the transects with chaining pins. Lay
out the 30m tapes along the transects, using the chaining pins as anchor
points.

Once the plot is completely marked, one crew member should take the
photos (SOP 5) while the others boot up the tablets and start the
databases. Generally monitoring works best if two crew members cooperate
on taking the forest floor (SOP 6), tree (SOP 7) and microplot (SOP 8)
measurements. The third crewmember should take the quadrat (SOP 9) and
coarse woody debris (SOP 10) measures. While taking measurements be
careful to minimize trampling of the vegetation, particularly in the
quadrats.

Once the measurements have been taken, remove all pins, tapes and flags
and pack up the equipment. Check the area to make sure nothing has been
left behind.

Revision History
----------------

### 

### Version1.0 (November, 2008)

Original version of the protocol, in use since 2005, but formalized as
an SOP in November, 2008.

SOP 5: Photo Points (November, 2008)
====================================

Version 2.0

[]{#_Toc216757456 .anchor}***Introduction***

This SOP describes how to take a standardized series of photographs,
called photo points, at each plot. The purpose of the photographs is to
document the overall look of the plot. This will allow us to visually
demonstrate the changes to the plots over time.

Photo Points
------------

Photo points should be the first measurements. Thirteen photos (Table 7)
will be taken in the following standardized sequence with the camera
focal length set to its widest angle. First, a close-up of the plot
marker, then six (horizontal and vertical at each azimuth) from plot
center facing the 10-meter mark at 060, 180, and 300 degrees, and six at
15 m taken towards plot center at 360, 120, and 240 degrees. The
horizontal images should record a wide view of the forest floor and
understory, the vertical should record the forest floor and what tree
height can be included in the frame without tilting the camera up
towards the canopy. The photographer should attempt to exclude the field
crew from the monitoring photos.

Table 7. List and sequence of photo points.

  Photo   Angle   Orientation   Distance
  ------- ------- ------------- ----------------------
  1       none    down          Plot marker close-up
  2       060°    horizontal    Center facing out
  3       060°    vertical      Center facing out
  4       180°    horizontal    Center facing out
  5       180°    vertical      Center facing out
  6       300°    horizontal    Center facing out
  7       300°    vertical      Center facing out
  8       360°    horizontal    15m facing in
  9       360°    vertical      15m facing in
  10      120°    horizontal    15m facing in
  11      120°    vertical      15m facing in
  12      240°    horizontal    15m facing in
  13      240°    vertical      15m facing in

Downloading Photos 
------------------

At least once a week the memory card from the camera should be exchanged
for a blank memory card. The used memory card should be presented to
NCRN data management staff, the Visual Information Specialist, or a
designated field crew member for transfer to the NCRN file server. As
these photos will require additional processing and quality assurance
they should not yet be stored with the verified monitoring photographs,
but rather in a folder named \~Inbox, in a subfolder named with the date
the photos were taken. For example:

T:\\I&M\\MONITORING\\Forest\_Vegetation\\Photos\\\~Inbox\\2008-08-11

Note that this dated subfolder may include photographs from multiple
plots which will need to be segregated by examining the photo sequence
and center stake photos during the renaming process. While it is always
advantageous to do as much of the photo data management when memories of
the event are still fresh, it is critical that the newly transferred
photo sets are at least examined for completeness and to identify any
camera malfunctions during this weekly data transfer.

Renaming Photos
---------------

Once photos have been copied from the camera to the NCRN file server
they should be renamed using the following standard:
PlotID\_YYMMDD\_Angle/Orientation or Description, with the three
elements of the name separated by underscores. The photograph of the
center stake should use a suffix of "plotcenter" instead of an
angle/orientation, and any anecdotal photos should include a suffix that
describes the item of interest in the photo.

Example: CHOH-0026 061002 Gypsy Moth

Example: MANA-0106\_070612\_plotcenter.jpg

Example: CATO-0275\_070829\_060h.jpg

Note that the leading zeros should always be included for the plot
number, the date and the 060°Angle/Orientation.

For folders which contain photos from multiple events, the Plot ID will
be identified by sorting the photos by the time-date stamp and looking
for the center stake photo.

Storing Photos
--------------

The verified and renamed photos should be moved from the Inbox location
to a permanent storage folder named for the plot where they were taken -
for example *Forest\_Vegetation\\Photos\\HAFE-0154 -* and should be
subject to NCRN standard archiving procedures. When this plot is
revisited a second set of photos will be added to this folder, with the
date portion of the file name distinguishing the two sets.

Keyword Metadata Documentation 
------------------------------

At the close of each field season the verified, permanently stored
photos should be tagged with embedded keywords in accordance with the
NCRN photo documentation standards including, at a minimum, the
embedding of keywords for Park Code, and "Forest Vegetation Monitoring".
This documentation must be accomplished with metadata editing software
that embeds the keywords permanently into the image/jpg file.

Revision History
----------------

### 

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 6: Forest Floor Measurements (November, 2008)
=================================================

Version 2.0

[]{#_Toc216757464 .anchor}***Introduction***

This SOP describes how to record information about the forest floor.
This information is used to get a general idea of the ground cover of
the plots.

Measurements
------------

The three measurements taken as part of this SOP are meant to be
estimates, do not attempt to measure them exactly. The measurements are:

Rock cover -- This is the % of the plot that is covered by large rocks.
In most cases this will be low, but in some of the parks large rocks are
a dominant feature of the landscape.

Bare Soil -- this is the % of the plot that is covered by bare soil or
by dead leaves (not living vegetation).

Trampled -- this is the % of the plot that is trampled by a hiking trail
or similar feature.

Each of these measurements is recorded by indicating which of the
following broad classes it fits in: \<1%, 1-5%, 6-25%, 26-50%, 51-75%,
76-100%.

Revision History
----------------

### 

### Version1.0 (November, 2008)

Original version of the protocol, in use since 2005, but formalized as
an SOP in November, 2008

SOP 7: Tree Measurements (November, 2008)
=========================================

Version 2.0

Introduction
------------

This SOP describes procedures for taking data on trees which have a dbh
\>10 cm and are found in the monitoring plots.

### What Is a Tree? 

For the purposes of this protocol a tree is an individual living woody
plant that is not on the list of shrub species (see SOP 8 for this list)
and that has a diameter or equivalent diameter of 10cm at dbh (diameter
at breast height=1.37m). A tree is considered to be living if it has
living tissue (e.g. leaves) above dbh.

The equivalent diameter criterion applies only to trees that split into
two or more stems below dbh. In general, we wish to include split trees
that have the same or greater total basal area as a tree with a single
trunk with a dbh of 10 cm. This is a departure from FIA methodology,
which only includes trees where at least one stem has a dbh ≥10cm.

If any of the stems have a dbh ≥ 10cm, then the individual is included
as a tree, and all of its stems are measured at dbh. If all of the stems
are less than 10cm dbh, then the equivalent must be calculated. To
calculate equivalent diameter, use the following equation:

$$\text{Equivalent}\ D\text{iameter} = 2\ \left( \sqrt{\left( \frac{\text{Diameter}\ \text{of}\ \text{stem}\ 1}{2} \right)^{2} + \left( \frac{\text{Diameter}\ \text{of}\ \text{stem}\ 2}{2} \right)^{2} + \left( \frac{\text{Diameter}\ \text{of}\ \text{stem}\ 3}{2} \right)^{2}}\ldots\ldots\text{etc} \right)$$

For simplicity Table 8 can be used as a guide to situations commonly
encountered when a tree splits into two stems. Note that if a tree has
two stems and both stems are ≤ 7cm, then the tree is always too small.
If for some reason you are unsure if you should include a tree or not,
include the tree as it will removed later during QA/QC.

Table 8. Stem sizes for an equivalent diameter ≥10 cm.

  Dbh of Largest Stem   Requirement for dbh of Smaller Stem
  --------------------- -------------------------------------
  9.9 cm                ≥1.41 cm
  9.5 cm                ≥3.12 cm
  9.0 cm                ≥4.36 cm
  8.0 cm                ≥6.00 cm
  7.07 cm               ≥7.07 cm

Taking Measurements
-------------------

### 

### Tag Number

First locate the tag that is attached to the tree. Select the
corresponding tree in the database, or note down the tree number on the
datasheet.

Occasionally you will encounter a tree which does not already have a
tag. This may be because the tag has been lost, the tree appeared dead
when the plot was initially set up, the tree has grown since plot setup
or the tree may have simply been missed. Record the distance and azimuth
from plot center and place a new tag on the tree. If it appears that the
tree was previously marked but has lost its tag, note the new tag number
under the old tag number if you can determine it.

### Tree Identification

We are recording the species of each tree so that we can relate species
to habitat types and so we can determine if there are long term trends
in the populations of individual tree species.

Record the scientific name of the tree. If the tree has already been
identified, confirm the identification. If you find that it was
identified incorrectly, note down the old ID, the new ID, your name, the
date, and any notes that may be useful. If you cannot identify the tree,
take a sample to identify as indicated in SOP 11.

### Measuring Diameter

Dbh is used to calculate the basal area of each tree. Basal area is an
approximation of the area of the cross section of each tree at breast
height. Basal area is used as a measure of the amount of living woody
biomass in the forests and as a measure of importance of the various
tree species. Measuring dbh will allow us to track trends in the basal
area of the forests as a whole and of individual tree species.

Dbh is measured to 0.1 cm at 1.37 m from the ground. In most cases the
tree will already be marked at dbh and the measurement should be taken
at the marking. If the marking is off, take dbh at the mark. The only
exception is if this is the first measurement of the tree and the mark
is grossly in error. In that case remark the tree correctly and make
note explaining the correction.

Trees on a hill should be measured on the uphill side of the tree.
Leaning trees should be measured on the short side (Figure 5).

![](media/image5.png)

If there is an abnormality at dbh, take the measurement just below the
abnormality if possible, marking the tree at the measurement point. It
is best to mark the tree first and take the measurement second. If the
abnormality extends far below dbh, then take the measurement just above
dbh, again marking the tree at the measurement site before taking the
measurement.

If the tree forks, measure each stem of the tree. Always record the dbh
of all separate stems before performing the calculation needed to derive
the equivalent diameter. If the forking influences the diameter of the
stems at the dbh, then treat the forking as an abnormality as explained
above. If a tree appears to fork beneath the ground, but the trunks are
not visibly connected at the surface, measure them as two separate
trees.

### Vines on the Tree

Vines, including exotic vines, are found on trees throughout the NCRN.
We are recording the scientific name of each vine found on each tree so
that we can determine how common each species is and track change in
abundance and distribution over time. If an individual vine is growing
on more than one tree it is recorded for each tree. We are not taking
additional measurements of individual vines, such as counting the number
of individual vines in the plot or taking a dbh-like measurement, as the
growth form of vines makes them difficult to monitor using these
techniques.

Record the scientific name of any vines growing on the tree. If you
cannot identify the vine, take a sample to identify as indicated in SOP
11. If more than one vine species grows on a tree, record all species
found. If no vines are growing on the tree, note that you completed this
so that it is clear there are no vines and you did not just forget to
take the data.

### Tree Conditions

A "tree condition" is any of a number of factors that might be expected
to increase the mortality rates of trees. These conditions are recorded
simply as being present or absent as it is too difficult to accurately
quantify them. More than one condition can be recorded for each tree.
The conditions are:

-   Absent: No conditions are present

-   Advanced Decay: Large portions of the tree are undergoing decay
    (e.g. heart-rot), but the tree is still alive.

-   Broken: Main trunk of the tree is broken off. In the case of trees
    which split, if any main trunk is broken use this condition and make
    a note of the circumstances.

-   Large Dead Branches: large branches on the tree are dead

-   Open wound: large open wound, such as from where a branch fell off.

-   Vines in the crown: record if any vines on the tree grow into the
    crown. This is not recorded separately for each vine species as it
    can be difficult to identify vines that are high above the ground.

-   Visible Damage: Any other damage that you feel could increase the
    mortality risk of the tree that is not covered here (note that wind
    and lightning damage is covered separately below). Record in the
    notes what the damage is.

Tree pests and diseases are also recorded in this section (see below).

### Tree Pests and Diseases

Tree pests and diseases are one of the vital signs of the NCRN. These
organisms can cause extensive mortality of native trees. The presence of
these organisms is being recorded in order to understand their
importance in NCRN forests.

Record the presence of each pest or disease found from the list below
(Table 9). The list is not meant to be exhaustive. Rather it is a list
of tree pests and diseases which are known to be devastating to natural
populations and that can be found in the area covered by the NCRN. Some
diseases, such as Dutch elm disease, can kill individual trees, but are
not a threat to wild populations, so they are not included. This list
will be reviewed annually and updated as necessary.

Table 9. Pests and diseases to monitor.

  Pest or Disease                   Year Monitoring Began
  --------------------------------- -----------------------
  Beech bark disease                2006
  Butternut canker                  2006
  Dogwood anthracnose               2008
  Gypsy moth                        2006
  Hemlock scale                     2008
  Hemlock wooly adelgid             2006
  Spruce budworm                    2006
  Other significant insect damage   2006

### Foliar Conditions

A "foliar condition" is any of a number of factors that might be
expected to increase the mortality rates of trees and specifically
affects the leaves. These are being noted in an attempt to see if there
is in fact a relationship between these factors and tree mortality.

Unlike the tree conditions above, foliar conditions are recorded and an
estimate is made of the percentage of the leaves which are affected.
More than one foliar condition can be recorded for each tree. The
conditions are:

-   Absent: no foliar condition present

-   Chlorosis: this is a loss of chlorophyll in the leaves which will be
    evidenced by an unseasonal loss of their green color.

-   Holes: Small holes found in leaves, usually from insect damage

-   Necrosis: leaves are dying

-   Small leaves: some leaves are unusually small, usually due to damage
    during leaf development

-   Wilting: leaves are wilted, usually due to water stress or damage to
    branches

```{=html}
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```
-   Other: Any other damage or conditions to the leaves that you feel
    could increase the mortality risk of the tree that is not covered
    here. Record in the notes what the damage is.

### Tree Status

Tree status indicates if the tree is alive, dead, or no longer part of
the study and if it is still standing. This information will be used to
help understand causes of mortality and to track the reasons why trees
are removed from the study. The tree status options are:

-   Alive Standing: Tree is alive and is standing upright.

-   Alive Leaning: Tree is leaning at more than 30° from vertical.

-   Alive Broken: The main stem of the tree is broken off.

-   Alive Fallen: The main stem is perpendicular to the ground.

-   Dead: Tree has died since last measurement. If this is the first
    time a tree has been measured do not record it as dead, as it should
    not be part of the study. Rather just mark it as removed from study
    and note that it died before it could be measured for the first
    time.

-   Missing: You cannot find this tree at all.

-   Removed from Study: Tree is no longer part of study. If a tree is on
    the edge of the plot it may have been wrongly included during setup
    (outside of plot) and this is discovered during measurement.

### Crown Class

Crown class refers to the position and height of the canopy compared to
its neighbors and how much sunlight it receives (Figure 6). This
information can be helpful in understanding growth rates and tree
mortality. The crown classes are:

-   *1. Open-grown*: crown has received full sunlight from above and all
    sides through most of its life, particularly during early
    development.

-   *2. Dominant:* crown extends above canopy, receiving full light from
    above and some light from sides. Taller than the average tree in
    stand and has well-developed crown.

-   *3. Co-dominant:* crown at the general level of the canopy,
    receiving full light from above but little direct light from sides.
    Typically, co-dominant trees have medium-sized crowns and are
    crowded on the sides; in dense stands, co-dominant trees have small
    crowns.

-   *4. Intermediate:* tree is shorter than co-dominant trees but with a
    crown that extends into the general canopy. Crown receives little
    direct light from above and none from the side; tree has small crown
    and is very crowded from the sides.

-   *5. Overtopped:* crowns is entirely below the general level of the
    canopy and receives no direct sunlight.

-   

### ![](media/image7.wmf){width="5.996527777777778in" height="2.2916666666666665in"} 

### Wind or Lightning Damage

Wind and lightning damage allows us to determine the extent of damage to
trees due to storm events in the NCRN. In some locations, particularly
in Catoctin Mountain Park, wind damage from storms can knock down stands
of dozens of trees. Lightning damage occurs throughout the parks. You
should indicate wind or lightning damage only if you are sure this kind
of damage has occurred.

### Comments

Make any notes as directed in this SOP. Also, record any other
observations of the tree that are unusual and may help explain mortality
or other changes in the forest community. Do not attempt to write
comments about each individual tree, only unusual observations should be
noted.

Revision History
----------------

### 

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Expanded explanation of equivalent diameter

-   Matched sections in SOP with fields in database

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 8: Sapling and Shrub Measurements (November, 2008)
======================================================

Version 2.0

Introduction
------------

This SOP describes how to take measurements on saplings and shrubs.
Saplings and shrubs are covered in the same SOP as they are both
monitored only in the three microplots and nearly identical data is
taken for each.

In order to distinguish between the three microplots they have been
given names based on their azimuth: 60°, 180° and 300°.

### What Is a Sapling?

A sapling is any tree with a dbh ≥ 1cm, but \< 10 cm. Trees with a dbh
≥10 cm are monitored as trees, whereas those \<1cm are monitored as
seedlings. A tree can be originally monitored as a sapling, but later be
monitored as a tree once it has a larger dbh.

### What Is a Shrub?

A shrub is a woody plant species with a diameter at root crown ≥1cm and
that typically has a growth form with many stems at breast height. In
practice, a shrub is any woody species on the list of shrubs (Table 10),
even if that particular individual has only a single main branch.
Occasionally, as new species are found in the NCRN monitoring plots,
additions are made to the list of shrubs.

Table 10. List of woody species monitored as shrubs.

  Latin Name                       Common Name                Year added
  -------------------------------- -------------------------- ------------
  *Clethra* spp.                   sweet pepper bush          2006
  *Elaeagnus umbellata*            autumn olive               2006
  *Euonymus alatus*                winged burning bush        2006
  *Euonymus americana*             bursting-heart             2007
  *Euonymus atropurpureus*         burning bush               2007
  *Hamamelis virginiana*           American witch-hazel       2006
  *Ilex verticillata*              common winterberry         2006
  *Kalmia latifolia*               mountain laurel            2006
  *Ligustrum obtusifolia*          border privet              2006
  *Lindera benzoin*                northern spicebush         2006
  *Lonicera mackii*                amur honeysuckle           2006
  *Lyonia ligustrina*              maleberry                  2007
  *Rhododendron periclymenoides*   pink azalea                2007
  *Rhus* spp.                      sumac                      2006
  *Rubus argutus*                  sawtooth blackberry        2007
  *Sambucus pubens*                red elderberry             2007
  *Staphylea trifolia*             American bladdernut        2006
  *Symphoricarpos orbiculatus*     coralberry                 2006
  *Vaccinium corymbosum*           highbush blueberry         2006
  *Vaccinium fuscatum*             black highbush blueberry   2007
  *Vaccinium stamineum*            deerberry                  2006
  *Viburnum acerifolium*           mapleleaf viburnum         2006
  *Viburnum dentatum*              southern arrowwood         2006
  *Viburnum dilatatum*             linden arrowwood           2008
  *Viburnum plicatum*              Japanese snowball          2007
  *Viburnum sieboldii*             Siebold's arrowwood        2007

Small woody plant species that could be confused with shrubs but are
monitored as trees are listed in Table 11. Additionally, some small
woody plant species that would commonly be called a shrub are monitored
like a herbaceous plant in the quadrats (Table 11). These include shrubs
which tend to be small and numerous, such as some *Vaccinium* species,
that would often be missed in the microplots due to their small
diameter. Also, shrubs that are vine-like and thorny, such as *Smilax*
species, are monitored like herbaceous species as searching for the
location where they root can result in trampling and can be painful for
the monitoring crew.

Table 11. Woody plants that are sometimes considered shrubs but are
monitored in other categories by the NCRN.

  Latin Name                                 Common Name    Monitoring Category
  ------------------------------------------ -------------- ---------------------
  *Amelanchier* spp.                         serviceberry   tree
  *Asimina triloba*                          pawpaw         tree
  *Berberis* spp.                            barberry       herbaceous cover
  *Gaylussacia* spp.                         huckleberry    herbaceous cover
  *Lonicera* (not *maackii* or *japonica*)   honeysuckle    herbaceous cover
  *Morus rubra*                              red mulberry   tree
  *Rosa* spp.                                rose           herbaceous cover
  *Smilax* spp.                              greenbrier     herbaceous cover
  *Vaccinium* (not listed above)             blueberry      herbaceous cover

### What if You Don't Know What It Is?

The monitoring crew may run into a situation where either they are
unsure of the species identification of a plant or they are able to
identify it but that species has not been monitored before. In those
cases it may not be clear if the plant should be monitored as a sapling
or a shrub. The crew should take data for the plant as both a sapling
and as a shrub and a determination will be made later.

Sapling and Shrub Measurements
------------------------------

### 

### Tag Number

First locate the tag that is attached to the sapling or shrub. Select
the corresponding plant in the database, or note down the tag number on
the datasheet.

Occasionally you will encounter a sapling or shrub which does not
already have a tag. This may be because the tag has been lost, the plant
appeared dead when the plot was initially set up, the plant has grown
since plot setup or the plant may have simply been missed. Record which
microplot the plant occurs in and new tag on the plant. If it appears
that the plant was previously marked but has lost its tag, note the new
tag number under the old tag number if you can determine it.

### Sapling/Shrub Identification

We are recording the species of each sapling and shrub so that we can
relate species to habitat types and so we can determine if there are
long term trends in the populations of individual plant species.

Record the scientific name of the plant. If the plant has already been
identified, confirm the identification. If you find that it was
identified incorrectly, note down the old ID, the new ID, your name, the
date, and any notes that may be useful. If you cannot identify the
plant, take a sample to identify as indicated in SOP 11.

### Sapling Diameter at Breast Height

Dbh is used to calculate the basal area of each sapling. Basal area is
an approximation of the area of the cross section of each tree at breast
height. Basal area is used as a measure of the amount of living woody
biomass in the forests and as a measure of importance of the various
tree species. Measuring dbh will allow us to track trends in the basal
area of the forests as a whole and of individual tree species.

Dbh is measured to 0.1 cm at 1.37 m from the ground. In most cases the
tree will already by marked at dbh and the measurement should be taken
at the marking. Dbh is measured in the same way as tree diameter is (see
SOP 6). The only differences is that stems less than 1 cm diameter are
not measured and are not used to determine equivalent diameter. These
narrow stems are too difficult to measure accurately and make a very
small contribution to basal area.

### Shrub Diameter at Root Crown

Diameter at root crown (drc) is used to measure the basal area of the
shrub, much like dbh is used for trees and saplings. The NCRN has
tentative plans to use basal area calculated from drc as a measure of
the amount of living woody biomass in the forests and as a measure of
importance of the various shrub species. Measuring drc will allow us to
track trends in the basal area of the forests as a whole and of
individual shrub species.

The NCRN originally considered using dbh for shrubs, and a small amount
of data was collected using dbh in 2006. However, it was decided that
dbh was not a useful measure for shrubs. In many cases the bulk of the
biomass of the shrub is below dbh and we were measuring just the tips of
the branches. It is not clear what the relationship between dbh and
biomass would be for some shrub species. Also, for species which tend to
branch repeatedly low to the ground, collecting dbh on every branch was
too time consuming.

Drc is measured to 0.1 cm just above the roots of the shrub. Otherwise,
follow the same procedures as for dbh.

### Status

Status indicates if the plant is alive, dead, or no longer part of the
study and if it still standing. This information will be used to help
understand causes of mortality and to track the reasons why plants are
removed from the study. The status options are:

-   Alive Standing: Tree is alive and is standing upright.

-   Alive Leaning: Tree is leaning at more than 30° from vertical.

-   Alive Broken: The main stem of the tree is broken off.

-   Alive Fallen: The main stem is perpendicular to the ground.

-   Dead: Tree has died since last measurement. If this is the first
    time a tree has been measured do not record it as dead, as it should
    not be part of the study. Rather just mark it as removed from study
    and note that it died before it could be measured for the first
    time.

-   Missing: You cannot find this tree at all.

-   Upgraded to Tree: Sapling has grown large enough that it is now
    monitored as a tree.

-   Removed from Study: Sapling is no longer part of study If a sapling
    I on the edge of the microplot it may have been wrongly included
    during setup (outside of plot) and this is discovered during
    measurement.

### Deer Browse

Record whether there is any evidence of deer browsing on the shrub or
sapling. Stem tips that have been newly browsed by white-tailed deer
typically have a dark brown band at the browse point and acuminate tips.
Do not count numbers of browsed stem tips.

### Comments

Make any notes as directed in this SOP. Also, record any other
observations of the plant that are unusual and may help explain
mortality or other changes in the forest community. Do not attempt to
write comments about each individual plant, only unusual observations be
noted.

Revision History
----------------

### 

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Matched sections in SOP with fields in database

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 9: Herbaceous Plant and Seedling Measurements (November, 2008)
==================================================================

Version 2.0

Introduction
------------

This SOP describes measurements of some herbaceous plant species and
shrubs that are measured in the same manner as herbaceous plants, and
seedlings of trees and shrubs.

### Quadrat Location and Name

The herbaceous layer and seedlings are measured using twelve 2 × 0.5 m
quadrats. Nine of the quadrats are laid out perpendicular to the three
transects at 0°, 120°, and 240°. Three quadrats are placed along each
transect, 20 cm to right when facing away from plot center. The lower
corners of the quadrats should be at 3, 8, and 13 meters from plot
center. The remaining three quadrats are placed in the center of the
microplots used for measuring shrubs. The center of the quadrat should
coincide with the microplot center, with the long axis of the quadrat
pointing towards the plot center.

Each quadrat is given a name based on its locations. For quadrats along
the transects, the name consists of the azimuth of the transect and the
distance the quadrat is from plot center. For example, the quadrat that
starts at 8 m along the 120° transect is referred to as 120°-8m. The
quadrats that are in the microplots are named based solely on the
microplot (e. g. 300°), without any reference to the distance.

### PVC Quadrat Frame

To aid in taking measurements, the field crew will take a quadrat frame
with them in the field. Quadrat frames are constructed out of ½ inch
PVC. Each 2 × 0.5 m^2^ quadrat frame is calibrated (painted in 10 cm
sections) to make cover estimates easier. The quadrat is kept as
separate poles for each side and then constructed around the vegetation
in the field.

Level the quadrat if necessary by propping up the corners. When a
quadrat is located on a steep slope the field crew should be positioned
downhill from the quadrat to prevent sliding or falling into the
quadrat.

Herbaceous Plant and Seedling Measures
--------------------------------------

### 

### Measuring Herbaceous Plants

Cover of select "herbaceous" species (Table 12) is measured in each
quadrat. Some of the plant species measured under this portion of the
monitoring program are actually woody shrubs, but they are measured in
the same manner as the true herbaceous species. Additionally, some vines
are measured under this SOP when they occur on the ground, and are also
tallied when they grow on trees (SOP 7).

The NCRN does not monitor all herbaceous plant species, but rather a
select group of species. Many of these species are exotic plants that
are known to be invasive in the NCRN. There are many exotic species in
the network that are not monitored as they are not invasive enough to be
a concern. New exotic invasives are added to the list as conditions
warrant.

Table 12. Herbaceous species monitored in quadrats.

  Latin Name                      Common Name              Reason to monitor   Year Added
  ------------------------------- ------------------------ ------------------- ------------
  *Akebia quinata*                chocolate vine           exotic invasive     2006
  *Alliaria petiolata*            garlic mustard           exotic invasive     2006
  *Ampelopsis brevipedunculata*   porcelain berry          exotic invasive     2006
  *Berberis thunbergii*           Japanese barberry        exotic invasive     2006
  *Celastrus orbiculatus*         oriental bittersweet     exotic invasive     2006
  *Centaurea biebersteinii*       spotted knapweed         exotic invasive     2006
  *Cirsium arvense*               Canada thistle           exotic invasive     2006
  *Clematis terniflora*           sweet autumn             exotic invasive     2006
  *Duchesnea indica*              Indian mock strawberry   exotic invasive     2006
  *Euonymus fortunei*             winter creeper           exotic invasive     2006
  *Glechoma hederacea*            ground ivy               exotic invasive     2006
  *Hedera helix*                  English ivy              exotic invasive     2006
  *Hemerocallis fulva*            orange day lily          exotic invasive     2006
  *Lespedeza cuneata*             Chinese lespedeza        exotic invasive     2006
  Liliaceae (family)              lily family              preferred by deer   2006
  *Lonicera japonica*             Japanese honeysuckle     exotic invasive     2006
  *Lonicera* spp.                 honeysuckle              exotic invasive     2006
  *Lysimachia nummularia*         Creeping jenny           exotic invasive     2008
  *Microstegium vimineum*         Japanese stiltgrass      exotic invasive     2006
  Orchidaceae (family)            orchids                  preferred by deer   2008
  *Podophyllum peltatum*          may apple                preferred by deer   2006
  *Polygonum caespitosum*         bristled knotweed        exotic invasive     2008
  *Polygonum cuspidaum*           Japanese knotweed        exotic invasive     2006
  *Polygonum perfoliatum*         mile-a-minute            exotic invasive     2006
  *Polygonum persicaria*          Asiatic tearthumb        exotic invasive     2008
  *Pueraria montana*              kudzu                    exotic invasive     2006
  *Ranunculus ficaria*            fig buttercup            exotic invasive     2006
  *Rosa multiflora*               multiflora rose          exotic invasive     2006
  *Rubus phoenicolasius*          wineberry                exotic invasive     2006
  *Smilax glauca*                 cat greenbrier           preferred by deer   2008
  *Smilax rotundifolia*           common greenbrier        preferred by deer   2008
  *Smilax tamnoides*              bristly greenbrier       preferred by deer   2008
  *Toxicodendron radicans*        poison ivy               determine extent    2006
  *Vaccinium* spp.                blueberries              preferred by deer   2006
  *Viburnum dilatatum*            Linden arrowwood         exotic invasive     2006
  *Vinca minor*                   common periwinkle        exotic invasive     2006
  *Wisteria sinensis*             Chinese wisteria         exotic invasive     2006

We are also monitoring herbaceous plants that are generally considered
to be highly sought after by deer (Table 10). This data will be used to
help assess deer impact on the parks. Some species (e.g. Orchidaceae)
are monitored as a group rather than as individual species as they are
rare in general. If possible, indicate which specific species were found
in the "Comments" If you cannot identify the species indicate that as
well. In 2006 and 2007 "*Smilax* spp." were monitored as a group. In
2008, "*Smilax* spp.' was removed from the list and replaced with the
three individual species as they were fairly easy to separate. Poison
ivy is also monitored in the quadrats in order to determine how common
it is across the parks and to warn future field crews which plots are
heavily infested.

Only estimate foliar cover on plants or portions of plants that fall
inside the quadrat frame and less than 2 m above the ground. For each
plant, cover is based on a vertically-projected polygon described by the
outline of each plant, ignoring any normal spaces occurring between the
leaves of a plant (Figure 7, Daubenmire, 1959). This best reflects the
plant's above-ground zone of dominance. The only **exception** is for
species represented by **plants that are rooted in the quadrat, but have
canopies that do not cover the quadrat or that are more than 2m above
the ground; estimate cover for these species based on their basal
area**. Base percent cover estimates on the current years\' growth, by
including living, damaged, and dead material from the current year.
Record the percent cover present at the time of the plot visit. Do not
adjust the percent for the time of year during which the visit was made
(i.e., for immature or wilted plants). Sparse plants can be difficult to
assess, but follow the polygon rule unless it is obvious that the
plant(s) have been trampled or otherwise recently disturbed and would
naturally stand more upright.

![](media/image8.emf){width="3.876388888888889in" height="2.5in"}Overlap
of plants of the same species is ignored. Visually group the plants in a
species together into a percent cover. Familiarize yourself with what
certain cover estimates (e.g., 1%, 10%, 15%, etc.) look like and use
them as reference sizes. There will often be overlap of plants of
different species. Therefore, your total cover for a quadrat may exceed
100%.

### Measuring Seedlings

In each quadrat, record the scientific name of each tree and shrub
seedling found . Tree seedlings are woody plants \<1 cm dbh and ≥15 cm
tall. If the seedling is less than 15cm tall do not count it. Only count
seedlings rooted in the quadrat.

### Plot Conditions

"Plot conditions" are anything that can occupy part of a quadrat and may
explain why herbaceous vegetation does not occur there. The categories
are: trees, rocks, CWD (coarse woody debris) and "other". Estimate the %
of the quadrat that each of these conditions covers to either the
nearest 1% if the cover is less than 10%, or to the nearest 5% if the
cover is over 10%.

The "trees" category includes the area covered by the stem/trunk of
woody plants and does not include cover of the canopy. CWD includes any
wood laying on the soil with a diameter ≥ 7.5 cm. "Other" can include
any other object (such as trash). If you the cover of other is greater
than

0, note in the comments section what object is being measured.

### Vegetation Categories

"Vegetation categories" are types of vegetation that can occur in the
quadrat. This data is monitored to help determine if there are trends in
understory cover of these groups over time.

These categories are: grasses, sedges, herbs, ferns and bryophytes.
Estimate the % of the quadrat that each of these conditions covers to
either the nearest 1% if the cover is less than 10%, or to the nearest
5% if the cover is over 10%.

### Comments

#### Record anything unusual about the plants or measurements.

References
----------

Daubenmire, R.F. 1959. A canopy-coverage method. Northwest Science
33:43-64.

Forest Inventory and Analysis \[FIA\]. 2004. Forest Inventory and
Analysis program background. U.S. Department of Agriculture, Forest
Service, Forest Inventory and Analysis program, Washington, DC.
http://fia.fs.fed.us/. \[accessed December 1, 2004\]

Revision History
----------------

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Matched sections in SOP with fields in database

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 10: Coarse Woody Debris (November, 2008)
============================================

Version 2.0

Introduction
------------

This SOP describes the methods to measure coarse woody debris on the
plots along the three transects. Coarse woody debris (CWD) is an
important habitat for many animal and microbial species, and a net loss
of coarse woody debris can result in a reduction of biodiversity.

### What is Coarse Woody Debris?

Coarse woody debris is large pieces of dead wood. The dead wood can be
from any woody plant and can be from a branch or a main stem. For the
purposes of this protocol, we are defining it as dead wood which is
lying on the ground and has a diameter ≥7.5 cm and a length ≥1m. Dead
trees that are still standing are not counted. If a tree is leaning more
than 45° from vertical, it is counted as CWD. To qualify as CWD, a piece
must retain some structural integrity. Very decomposed logs that are
slightly elevated 'humps' on the ground are not tallied as CWD.

### What is done with the measurements?

As described below you will measure the diameter of coarse woody debris
along the transects. This data is used to calculate the volume of CWD at
the plot in m^3^/ha. This is calculated with the following formula:

$$\text{Volume\ }\left( \frac{m^{3}}{\text{ha}} \right) = \frac{\pi^{2}\sum_{i = 1}^{n}d_{i}^{2}}{8L}$$

where *d* is the diameter in cm, *n* is the number of intersections, and
*L* is the total length of the transects (van Wagner, 1968). In the
NCRN, the total length of the transects is 45m, so the equation reduces
to:

$$\text{Volume\ }\left( \frac{m^{3}}{\text{ha}} \right) = 0.02742\left( \sum_{i = 1}^{n}d_{i}^{2} \right)$$

Measuring Coarse Woody Debris
-----------------------------

### 

### Transects

CWD is measured along the three transects that are at azimuths 120°,
240° and 360°. Each transect is 15m long. Occasionally you will find
that the marker at the end of the transect is slightly closer or farther
than 15m. In these cases you should measure CWD for 15m regardless of
where the transect marker is. Unlike plot setup, the 15m is measured
along the slope rather than horizontal distance. If the azimuth of the
transect marker is wrong, note it down in the comments section, but
measure the CWD along the azimuth of the marker.

Measuring Diameter
------------------

Most CWD will be laying on the ground. To be tallied by this protocol,
the point of intersection between the transect and the central
longitudinal axis of the piece must occur above the ground, and the
piece must be ≥ 1 m long. The piece must also meet the ≥7.5 cm diameter
requirement where it intersects the transect. If the piece is \<7.5 cm
diameter at the transect but has a large enough diameter elsewhere, it
does not count.

Occasionally a piece intersects a transect line more than once or
intersects two transect lines. In these cases tally the piece each time
it intersects. The estimate for CWD is based on the number and size of
the intercepts of the transect with CWD, not on a count of pieces of
CWD.

In the event that a piece of wood is at the exact center of the plot
where the three transects meet, tally that piece only once, on the 0°
transect.

The diameter of each piece is measured to the nearest 0.1 cm where the
transect intersects the longitudinal center of the piece. Measure the
diameter perpendicular to the length of the piece, not along the
transect. Diameter of CWD is typically measured by using a dbh tape, or
by holding a steel tape or ruler above the log or by using calipers.
Chose whichever method works best given the situation, but try to avoid
disturbing the log too much. Do not lift up large pieces of wood in
order to put a dbh tape around them.

For pieces that are not round in cross-section because of missing chunks
or \"settling\" due to decay, measure the diameter in two directions and
average, if this is possible. Estimate the longest and shortest axis of
the cross-section (Figure 8) and record the average value.

![](media/image9.wmf){width="2.9916666666666667in"
height="1.3194444444444444in"}

[]{#_Toc216757524 .anchor}Figure . Measuring diameter of deformed CWD.

### Decay Class

Record the decay class of each piece on a five point scale (Table 13).
The scale was originally developed for Douglas-fir in the Pacific
Northwest but it is widely used. In practice a single piece of wood can
exhibit a variety of decay classes along its length. Record the decay
class that best fits the point where the wood intersects the transect.

Table 13. Decay classes for CWD.

  ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
  Class   Structural\                                                                            Texture of\                                                                                Color\                             Invading\      Branches\
          Integrity                                                                              Rotten Portions                                                                            of Wood                            Roots          and Twigs
  ------- -------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------ ---------------------------------- -------------- ----------------------------------------------------------------------------------------------
  1       Sound, freshly fallen, intact logs                                                     Intact, no rot; conks of stem decay absent                                                 Original color                     Absent         If branches are present, fine twigs are still attached and have tight bark

  2       Sound                                                                                  Mostly intact; sapwood partly soft (starting to decay) but can't be pulled apart by hand   Original color                     Absent         If branches are present, many fine twigs are gone and remaining fine twigs have peeling bark

  3       Heartwood sound; **piece supports its own weight**                                     Hard, large pieces; sapwood can be pulled apart by hand or sapwood absent                  Reddish- brown or original color   Sapwood only   Branch stubs will not pull out

  4       Heartwood rotten; piece **does not** support its own weight, but maintains its shape   Soft, small blocky pieces; **a metal pin can be pushed into heartwood**                    Reddish or light brown             Through-out    Branch stubs pull out

  5       None, piece **no longer** maintains its shape, it spreads out on ground                Soft; powdery when dry                                                                     Red-brown to dark brown            Through-out    Branch stubs and pitch pockets have usually rotted down
  ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

### Species

If you know what species or genus the wood was when it was alive record
it. In general well decayed wood will be difficult to identity, but
newly fallen branches may have leaves or bark that can be identified.
Occasionally trees that were being monitored will fall and be tallied as
CWD. In that case record the tree species and in the comments note the
tag number from the tree. Do not remove the tag.

### Hollow 

Record if the piece is hollow. A piece is considered hollow if a cavity
extends at least 0.5 m along the central longitudinal axis of the piece,
and the cavity entrance is at least 1/4 the diameter of the piece.

### Comments

Record in the comments any unusual observations.

References
----------

Van Wagner, C.E. 1968. The line intersect method in forest fuel
sampling. Forest Science 14:20-26

Revision History
----------------

### 

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Matched sections in SOP with fields in database

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 11: Collection of Unknown Plant Species (November, 2008)
============================================================

Version 2.0

Introduction
------------

This Standard Operating Procedure (SOP) describes the procedure for
collecting, pressing, storing, and processing unknown plants. For the
procedure used for the collection of voucher specimens, refer to the
data management plan SOP on vouchers.

### What Should be collected?

Specimens of all plants that cannot be confidently identified to species
should be collected off the plot, if possible, labeled, pressed and
dried for subsequent identification by the field botanist or a
cooperating herbarium.

Methods
-------

When you encounter a plant you do not recognize and you cannot identify
it quickly using field guides, collect it. Find a specimen to collect
that is off the plot, if possible. Make sure the collection is as
representative as possible, including leaves, flowers, fruits, etc.

Plants can be stored and carried from plots in paper bags, and kept cool
for later keying. Crispy plants can be re-hydrated in a zip-lock bag. If
a plant cannot be identified within a few hours of returning from the
field, they must be pressed and dried with an identifying label.

### Pressing Plants

Collected plants will be pressed and stored in a plant press until they
can be identified. Plant presses contain blotters (thick blotting paper)
and ventilators (corrugated cardboard) and newspaper. Begin to fill your
press on one side, laying a single ventilator on one of the press frame
pieces. Lay a single blotter on top of the ventilator, and then open a
single fold of newsprint and place one side on the blotter. Put only one
plant in the folded newsprint. Bend the stem in a v-, z- or
w-arrangement to fit it on a single newsprint page. Larger specimens may
need several sheets, but usually you can fit all essential plant parts
in a single folded section. Plants can be trimmed to reduce bulk, as
long as the diagnostic parts are included, such as stem sections,
petioles, and branch bases. Arrange the specimens so some upper and some
lower surfaces are exposed. Flower parts should be visible as well,
including stamens, pistils, sepals and petals. You can tear or cut small
strips of newsprint and wet them with water to use to hold leaves and
flowers in place. This will add drying time, but the quality of the
pressed specimen is well worth it. Before you close the newsprint fold,
be sure to add the label.

The usual arrangement in the press is ventilator-blotter-newsprint (with
plant)-blotter-ventilator-blotter-newsprint (and next plant)-blotter,
and so on. If you have large or succulent plants, they may be sectioned
to reduce bulk.

When you have finished placing your specimens in the press, place the
second part of the frame on top of your last ventilator and tighten the
straps firmly. It works best if the straps are fastened from opposing
directions. To help expedite the drying of plants, keep in mind that
water vapor rises. If you prop the press so that the "tubes" of the
corrugated cardboard run up and down, the plants will dry faster.

### Notes

Include the following notes with your plant collection:

-   Plot Code

-   Date

-   Family or genus, if known

-   Names of field crew

-   Any useful information about the plant, such as habitat or
    observations of leaves or other parts that were too high to reach.

Revision History
----------------

### 

### Version 2.0 (November,2008)

-   SOP reformatted for publication in NRR report series

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2008.

SOP 12: Data Entry and Verification (November, 2008)
====================================================

Version 2.0

Introduction
------------

The purpose of this SOP is to outline the processes that should be
followed when entering data into the forest vegetation monitoring
database. Also described are the steps that should be taken to verify
and validate data once it is in the database.

Definitions
-----------

Verification -- Pertains mainly to data that are entered from paper data
sheets. It involves ensuring that the information entered into the
database is the same as the data on the field data sheets.

Validation -- Pertains to field data collected on paper field forms as
well as data collected electronically on field computers. Validation
involves checking to make sure that the data make sense. For example, if
a dbh of -9000cm is entered it is fairly apparent that that value is
incorrect.

Procedures and General Requirements
-----------------------------------

The primary method of data collection for forest vegetation monitoring
data will be through the use of tablet PCs deployed with the full MS
Access version of the forest vegetation monitoring database. Field crews
are required to carry paper field forms with them as a contingency in
case the field computers are not functioning. Therefore, this document
will provide guidance for transferring data from field computers and
enter raw data from data sheets.

### Entering Data on Field Computers

#### Data Entry: When using field computers data is entered directly into a project database while it is being collected in the field. The advantages to this are numerous and include:

-   #### The database can be designed to require the entry of essential information such as date and location.

-   #### Validation rules can be incorporated directly into the database that will alert field crews if an inappropriate value is entered (e.g. a negative dbh).

-   #### The availability of defined pick lists for the user to choose from ensuring that only certain, pre-defined parameters can be entered. The use of such lists also eliminates the possibility of typos and misspellings.

-   #### The data entry step that would normally take place when using paper field forms is eliminated. All data entry takes place in the field making the use of field computers a much more efficient means of collecting data. Also, eliminating the data entry step from paper to computer reduces the chances of data entry errors into the database.

If two field computers are used then one field computer is dedicated to
the crew member collecting data from the herbaceous quadrats and from
the coarse woody debris transects. This computer should not be used to
collect data from any other section of the plot unless absolutely
necessary and should be designated as "Tablet \#2 (secondary)". The
other field computer should be used by the remaining crew member(s) to
collect data from the remaining parts of the plot and should be
designated as "Tablet \#1 (primary)".

#### Data Verification: The data verification is process is much less of an issue when field computers are used for collecting data as there are no paper data sheets to compare with data in a database. Even though these devices help reduce the chance for errors, it is still possible to enter erroneous data (e.g. selecting the wrong species from the drop down list). Accordingly, there are certain verification steps that should be taken to ensure proper data entry. 

Prior to leaving a field site following data collection, field crews
should review the data collected on the field computer(s) to try and
catch any data entry errors. Someone other than the person entering the
data in the field should check the data.

**Data Transfer:** The field crew, upon returning to the office, will
work with the data manager to transfer the data from the tablets to the
NCRN file server. The database file(s) containing the new field data
should be renamed and tagged with a specific date identifier referring
to when the data was collected. If one field computer is used, the data
file should be tagged with a suffix of "single". If two field computers
are used, the data files should be tagged with a suffix of "primary" or
"secondary" designating which tablet the data was collected on.

For example, a file name could be "NCRN\_Forest\_Veg\_DB\_be 2007-06-0
Primary.mdb", where the first portion of the name indicated the protocol
database name, followed by the date and finally the tablet function. The
renamed file(s) should be transferred to a folder on a dedicated flash
drive named "Field Data YYYY-MM-DD", where YYYY-MM-DD identifies the
date that the data was collected. The renamed file(s) should then be
transferred to the file server and placed in the forest vegetation
monitoring folder under Database\\Field Data. No data should be stored
on the field computers for more than the length of a field trip. The
NCRN data manager will help you with renaming and moving the files.

The data manager will make sure the field data are incorporated into the
monitoring database. using the importing and appending utilities. These
utilities will ensure that the proper data from each tablet dataset are
imported and appended to the proper data tables in the main working data
file.

After importing and appending new data to the master forest monitoring
database data management staff review the database for any obvious
import errors. Data management staff produce event summary reports from
the database that all members of the field crew must review for accuracy
and initial once completed.

Once successful data import has been confirmed, the field database(s)
copied from the field computers should be moved to the "Field Data
Import Complete" folder. It is important to maintain these "field" data
sets as they are the raw field data (akin to a paper field data sheet).

### Entering Data from Paper Field Forms

**Data Entry:** Upon returning from the field with paper data sheets,
all data sheets are to be copied and the copies placed in the proper
folder in the fire-proof cabinet. Originals are taken back to the
offices where the data are entered.

Data collected on paper data sheets should be entered into the project
database within one week of collection. This will allow information
about the sampling trip to remain fresh in the minds of the field crew
in case of a question. Data should be entered by someone on the crew
that collected it. Ideally, more than one member of the field crew
should be involved during data entry. This will allow for proper
interpretation of notes on the data sheet as well as increase the
possibility that errors on the data sheet will be caught during data
entry. If any mistakes are discovered on the data sheets the data should
be entered into the database correctly and a notation made on the data
sheet. If any questions arise during data entry, the data entry
personnel should make a note of any uncertainties on the data sheet as
well as in the database record.

Upon the completion of data entry, personnel should indicate who entered
the data and the date it was entered in the database. The data sheets
should also be dated and initialed by the person(s) entering the data.

**Data Verification:** Once the data for a specific sampling event has
been entered, the data must be verified. Someone other than the
person(s) who entered the data should review the data that was entered
and compare it to the data sheets. Ideally this should be someone on the
field crew but does not have to be. If errors are found, the record
should be corrected and a notation made in the database as well as on
the data sheet as to who updated the record and when it was updated. The
verifier should indicate in the database as well as on the data sheets
that they verified the data and the date on which the data were
verified.

Upon completing the data verification steps, the data sheets should be
stored in a safe location off-site. Data sheets will be permanently
archived at the Regional Museum Resource Center after five years. Copies
will still be maintained in the fire-proof storage cabinet.

### Data Validation

Regardless of whether field data are collected on paper data sheets or
on field computers, all data must be validated. Data validation involves
making sure that the data collected makes sense. Many of these checks
can be incorporated into project database regardless of whether they are
deployed on field computers or sit on desktop computers. The benefit of
having validation checks incorporated into field databases in the field
is that questionable data can immediately be flagged, checked and if
need be corrected. It is important to remember that simply because data
seem unusual or are identified as outliers does not make them incorrect.
Before deleting or changing any such errors always double check to be
sure that the information is incorrect.

Responsibilities
----------------

### 

### Data Manager

-   Ensure that all members of the field crew are aware of the
    procedures outlining how data should be entered into project
    database, verified and validated.

-   Make sure that field crews enter/upload the field data in a timely
    fashion.

-   Ensure that data undergo the proper QA/QC procedures.

-   Provide training and/or assistance with project databases.

-   Develop database tools to assist with data entry and data QA/QC
    procedures.

-   Archive data sheets and field data sheets

### Field Crews

-   Follow all data collection procedures.

-   Enter/upload data into project databases in a timely fashion.

-   Conduct data verification and validation checks.

Revision History
----------------

### 

### Version 2.0 (November, 2008)

-   SOP reformatted for publication in NRR report series

-   Improved text throughout

### Version 1.1(July 2007)

Updated data transfer procedures.

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2007.

SOP 13: Analysis and Reporting (November, 2008)
===============================================

Version 1.0

Introduction
------------

The purpose of this SOP is to describe the procedures used for analysis
and reporting. It is anticipated that the analysis and reporting will
change significantly as multiple measurements of the plots are made.
This SOP will focus solely on the analysis and reporting already taking
place and does not describe future plans that require more data than
currently available.

Reporting Schedule
------------------

Annual reports will be prepared in the fall and winter after each field
season. Preparation of the reports can begin after all data has been
collected, verified and validated. Occasionally the field crew may need
to revisit a plot to collect data that was missed on the first visit, do
not prepare the report until this has been completed.

In addition to the annual report, a longer report will be prepared after
each 4 year panel. The longer report will summarize the results from all
plots being monitored.

Annual Report Contents
----------------------

The purpose of the annual report will be to summarize the findings for
each field season. As only 25% of the plots are sampled each year,
statistical analysis will be very limited, at least for the initial
years. The report will contain summaries of the data both at the
regional and the park scale. The report will include all three of the
vital signs covered in this protocol. Reports that have been prepared in
previous years should be used as a guide to prepare future reports.

### Locations of Plots

Each year a map should be provided that indicates the plot locations in
each park. Locations that were considered and ultimately rejected should
also be shown. The exact coordinates of each plot should not be included
as the reports are public information. The plot locations are provided
in the annual permit requests to the parks, and are also available to
the parks upon request.

### Summary Data: Forest Communities

The report will provide summary data at both the regional and park
levels. The report should include the following information at the
network, park and plot levels:

-   Tree density, basal area/ha and species richness.

-   Sapling density, basal area/ha and species richness.

-   Tree seedling density.

-   Shrub density, basal area/ha and species richness.

-   Shrub seedling density.

-   Volume of coarse woody debris per hectare (at regional and park
    levels only).

The following information should be summarized on a per species basis at
the network and park levels:

-   Tree species identification, number of individuals and basal area.

-   Sapling species identification, number of individuals and basal
    area.

-   Tree seedling species identification and number of individuals.

-   Shrub species identification, number of individuals and basal area.

-   Shrub seedling species identification, number of individuals.

### Summary Data: Forest Pests and Diseases

Forest pest and disease information will be summarized both regionally
and by park. Summary information should include which pests or disease
were found, where they were found, and which tree species were affected.

### Summary Data: Exotic Plant Species

Data on exotic trees and shrubs will be summarized as part of the forest
community summaries outlined above.

The following information should be presented for vines on trees:

-   Number of trees with vines, and number of trees with vines in the
    crown at the network, park and plot level.

-   Vine identification, number of trees it is found on and number of
    times it is found on a tree with vines in the crown at the network
    and park level.

-   For each tree species, the number of individuals with vines and the
    number with vines in their crowns at the network and park level.

The following information should be presented for exotic herbaceous
species on trees:

-   The number of plots with exotic herbaceous species and the number of
    quadrats with exotics at the network and park levels.

-   The identification of exotic herbaceous species, the number of plots
    they occur on and the mean % cover they have on plots where they
    occur at the network and park levels.

Report Formatting 
-----------------

Annual reports will be published in the National Park Service's Natural
Resource Technical Report Series. Formatting will follow current
guidelines for that series.

Annual Report Peer Review
-------------------------

The Regional Inventory and Monitoring Coordinator for the NCRN will
determine the level of peer review needed for annual reports. In general
it is anticipated that routine data summaries will not require external
peer review, but more intensive analysis may merit outside review.

Automation of Reporting
-----------------------

When possible, preparation of the data for the annual reports should be
automated in the forest monitoring database. Automating summaries which
will be prepared annually will speed up the process of preparing the
reports and will reduce the opportunities for human error when the data
is exported and summarized in a different software package. Automating
the summaries will also help to make the reports more consistent year to
year, even when there is turnover in the staff.

Revision History
----------------

### 

### Version1.0 (November, 2008)

Original version of the protocol, in use since 2005, but formalized as
an SOP in November, 2008

SOP 14: Data Management (November, 2008)
========================================

Version 2.0

Introduction
------------

The purpose of this SOP is to define the data management guidelines and
procedures that apply to the forest vegetation monitoring protocol. This
document focuses primarily on the procedures involved with the storage
and documenting of data collected for the Forest Vegetation Monitoring
vital sign.

Procedures and General Requirements
-----------------------------------

The I&M Program strives to provide accurate data that will be useful to
park managers and the scientific community to help inform management
decisions both now and far into the future. In order to ensure that the
data collected and information products produced achieve this goal, data
and products must be reviewed for accuracy, documented completely, and
stored securely.

### Reviewing Data (QA/QC)

Refer to SOP 12: Data Entry and Verification

### Data Documentation (Metadata)

Data documentation is a critical step toward ensuring that data sets are
usable for their intended purposes well into the future. This involves
the development of metadata, which is defined as structured information
about the content, quality, condition, and other characteristics of a
data set. Basically speaking, the 'who', 'what', 'when', 'where', 'why'
and 'how' of the data set. In addition, metadata include information
about data format, collection and analysis methods, access/use
constraints, and distribution. Metadata provide the means to catalog
data sets, within intranet and internet systems, making their associated
data sets available to a broad range of potential users.

Requirements: Metadata should be generated/updated for all electronic
data files produced for the vegetation monitoring protocol. This
includes spatial and non-spatial data. If products include both a GIS
layer and a database file, each product needs an XML metadata file
associated with it.

Metadata should be updated annually once the field season has been
completed and data sets have been certified as accurate and complete. It
is important to update:

-   Personnel involved (i.e. members of the field crew)

-   Time frame of the project

-   Does the data set contain sensitive information? (e.g. was an
    endangered plant species found at a plot during the surveys?)

-   Did methodologies or protocols change during the field season? (e.g.
    did the protocol for measuring shrubs or saplings change?)

    -   If protocols did change, make sure to cross-reference the
        correct version of the protocol document.

-   Did any of the data analysis procedures change?

#### Tools for Metadata Generation: A number of tools exist to facilitate the generation of metadata. Project staff members are encouraged to use tools such as the NPS Metadata Tools and Editor which is an application developed by the national I&M Program to assist with creating and editing NPS metadata files. This tool can function as a stand-alone application or as part of ESRI's ArcCatalog application. A metadata template for this project already exists and has been populated with much of the basic project information. If project staff choose to use the Metadata Editor the data manager can provide training and support.

For those not comfortable using the Metadata Editor a metadata
questionnaire will be provided to staff for completion. Once the
metadata questionnaire is complete, data management staff will update
the XML metadata template. A copy of the questionnaire can be obtained
by contacting the data manager.

Note: No annual data set will be considered final unless it associated
with updated (current) metadata.

For more detailed information about generating metadata and network
metadata requirements please refer to the Network's Metadata SOP.
(<http://science.nature.nps.gov/im/units/ncrn/products/guideline_docs/SOP-Metadata_Ver_2.0.pdf>)

### Network Data Storage and Archiving

All protocol materials are maintained on the NCRN data server under the
following directory:

T:\\I&M\\MONITORING\\Forest\_Vegetation\\

#### Protocol and SOPs: All currently active protocols and SOPs will be maintained in the 'Protocol' directory. Copies of the currently active protocol and SOPs will also be stored under the appropriate 'ARCHIVE' folder in case the 'Active' file is inadvertently altered or deleted. 

#### Field Data: All field data will remain under the 'MONITORING' data folder until the field season has been completed and data have been certified and documented at which time the data manager will archive the annual data products. Archived products can be found here:

T:\\I&M\\Archive\\Monitoring\_ARCHIVE\\Forest\_Vegetation

Responsibilities
----------------

### 

### Data Manager

-   Ensure that all members of the field crew are aware of the
    procedures outlining how data should be entered into project
    database, verified and validated.

-   Ensure that data undergo the proper QA/QC procedures.

-   Make sure that all data sets are associated with updated metadata.

-   Archive data sheets and field data sheets.

### Field Crews

-   Conduct data verification and validation checks.

-   Update annual metadata files.

Revision History
----------------

### 

### Version 2.0 (November 2008)

-   SOP reformatted for publication in NRR report series

-   Improved text throughout

### Version 1.0 (January 2006)

Version of protocol used from 2006 to 2007.

The U.S. Department of the Interior (DOI) is the nation\'s principal
conservation agency, charged with the mission \"to protect and provide
access to our Nation\'s natural and cultural heritage and honor our
trust responsibilities to Indian tribes and our commitments to island
communities.\" More specifically, Interior protects America's treasures
for future generations, provides access to our nation's natural and
cultural heritage, offers recreation opportunities, honors its trust
responsibilities to American Indians and Alaska Natives and its
responsibilities to island communities, conducts scientific research,
provides wise stewardship of energy and mineral resources, fosters sound
use of land and water resources, and conserves and protects fish and
wildlife. The work that we do affects the lives of millions of people;
from the family taking a vacation in one of our national parks to the
children studying in one of our Indian schools.

NPS D-XXX, November 2008

+---------------------------------+-----------------------------------+
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|                                 | edia/image1.png){width="0.5625in" |
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+---------------------------------+-----------------------------------+

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