Mid-Atlantic Network Forest Vegetation 

Monitoring Protocol 

Natural Resource Report NPS/MIDN/NRR—2009/119

Natural Resource Program Center

National Park Service

U.S. Department of the Interior
ON THE COVER

Forest vegetation crew establish a monitoring plot using a laser rangefinder. Photograph by J. Comiskey
Mid-Atlantic Network Forest Vegetation 

Monitoring Protocol

Natural Resource Report NPS/MIDN/NRR—2009/119

James A. Comiskey 

Mid-Atlantic Network

National Park Service

120 Chatham Lane

Fredericksburg, VA 22405

John Paul Schmit

National Park Service

Center for Urban Ecology

4598 MacArthur Blvd., NW

Washington DC 2007

and

Geri Tierney

Department of Environmental & Forest Biology

SUNY College of Environmental Science & Forestry

Syracuse, NY 13210

July 2009

U.S. Department of the Interior

National Park Service

Natural Resource Program Center

Fort Collins, Colorado
ii National Park Service

Mid-Atlantic Network

The National Park Service, Natural Resource Program Center publishes a range of reports that 

address natural resource topics of interest and applicability to a broad audience in the National 

Park Service and others in natural resource management, including scientists, conservation and 

environmental constituencies, and the public.

The Natural Resource Report Series is used to disseminate high-priority, current natural resource 

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audience, and may contain NPS policy considerations or address sensitive issues of management 

applicability.

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

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Views, statements, findings, conclusions, recommendations, and data in this report are those of 

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Department of the Interior. Mention of trade names or commercial products does not constitute 

endorsement or recommendation for use by the National Park Service.

This report is available from the Mid-Atlantic Network (http://science.nature.nps.gov/im/units/

midn/Reports.cfm) and the Natural Resource Publications Management website (http://www.

nature.nps.gov/publications/NRPM). 

Please cite this publication as: 

Comiskey, J. A., J. P. Schmit, and G. Tierney. 2009. Mid-Atlantic Network forest vegetation 

monitoring protocol. Natural Resource Report NPS/MIDN/NRR—2009/119. National Park 

Service, Fort Collins, Colorado.

NPS 956/100130, July 2009
Forest Vegetation Monitoring Protocol

2009 iii

Contents

Figures ...............................................................................................................................v

Tables ...............................................................................................................................vii

Acronyms..........................................................................................................................ix

Executive Summary ................................................................................. xi

Acknowledgements ............................................................................... xiii

1 Background and Objectives.................................................................. 1

1.1 Background and History ..........................................................................................1

1.2 Rationale for Monitoring Forest Vegetation..........................................................2

1.3 Measurable Objectives.............................................................................................2

2 Sampling Design ................................................................................... 3

2.1 Sampling Design Rationale......................................................................................3

2.2 Target Population.....................................................................................................3

2.3 Site Selection ............................................................................................................3

2.4 Sampling Frequency and Replication......................................................................4

2.5 Recommended Number and Location of Sampling Sites ......................................4

2.6 Level of Change that can be Detected....................................................................4

2.6.1 Trees..................................................................................................................5

2.6.2 Saplings and shrubs .........................................................................................6

2.6.3 Seedling regeneration.....................................................................................6

3 Field Methods........................................................................................ 7

3.1 Safety ........................................................................................................................7

3.2 Field Season Preparations and Equipment Setup..................................................7

3.3 Field Season Scheduling ..........................................................................................7

3.4 Technician Training...................................................................................................7

3.5 Details of Taking Measurements, and Post-Collection Processing........................8

3.5.1 Plot location.....................................................................................................8

3.5.2 Plot establishment ...........................................................................................9

3.5.3 Stand and site measurements.........................................................................9

3.5.4 Plot photopoints..............................................................................................9

3.5.5 Field measurements.........................................................................................9

3.6 QA/QC .......................................................................................................................9

4 Data Handling, Analysis, and Reporting............................................. 9

4.1 Metadata Procedures ...............................................................................................9

4.2 Overview of Database Design.................................................................................9

4.3 Data Entry, Verification, and Editing ....................................................................10

4.4 Data Analysis..........................................................................................................10

4.5 Data Archival Procedures.......................................................................................10

4.6 Reporting Schedule and Format............................................................................10

5 Personnel Requirements and Training............................................... 10

5.1 Roles, Responsibilities, and Qualifications ..........................................................10

5.1.1 Vegetation Ecologist (Network Coordinator) ..............................................10

5.1.2 Data Manager................................................................................................10

5.1.3 Vegetation Crew Leader................................................................................10
iv National Park Service

Mid-Atlantic Network

5.1.4 Vegetation Crew Technicians........................................................................11

5.1.5 Botanist ..........................................................................................................11

5.2 Training Procedures................................................................................................11

6 Operational Requirements ................................................................. 11

6.1 Annual Workload and Field Schedule...................................................................11

6.2 Facility and Equipment Needs...............................................................................11

6.3 Startup Costs and Budget Considerations............................................................11

7 Literature Cited ................................................................................... 12

Appendix .............................................................................................. A-1

1.1 Introduction.......................................................................................................... A-1

1.2 Objective............................................................................................................... A-1

1.3 Methods................................................................................................................ A-1

1.4 Results................................................................................................................... A-2

1.4.1 All parks........................................................................................................ A-2

1.4.2 Manassas NBP............................................................................................... A-2

1.4.3 Catoctin MP.................................................................................................. A-2

1.4.4 Species across network ................................................................................ A-3

1.4.5 Changes in species density .......................................................................... A-3

1.4.6 Loss of species .............................................................................................. A-3

1.5 Discussion ............................................................................................................. A-3

1.6 Conclusion............................................................................................................. A-4

1.7 Literature Cited..................................................................................................... A-4
2009 v

Forest Vegetation Monitoring Protocol Contents

Figures

Figures

Figure 1. Map of the parks in the Mid-Atlantic Network. Three parks from the 

Northeast Coastal and Barrier Network are also shown and are included 

in this monitoring protocol. Shenandoah National Park has its own 

protocol for monitoring forest vegetation. .............................................1

Figure 2. Example of sampling frame at Valley Forge National Historical Park. ..........3

Figure 3. Layout of Mid-Atlantic Network forest vegetation monitoring 

plot consisting of one 20 x 20 m plot, three 3-m diameter 

microplots, 12 2 m x 0.5 m quadrats, and three 15-m transects. ............9

Figure A. 1. Percent detectable change using different size and number of plots 

throughout the National Capital Region Network. Analyses are 

based on trees ≥ 10 cm dbh collected in circular NCRN plots and 

sub-sampled to smaller square plots .................................................... A-2

Figure A. 2. Percent detectable change using different size and number of plots 

at Manassas National Battlefield Park, VA. Analyses are based on 

trees ≥ 10 cm dbh collected in circular NCRN plots and sub-sampled 

to smaller square plots .......................................................................... A-3

Figure A. 3. Percent detectable change using different size and number of plots 

at Catoctin Mountain Park, MD. Analyses are based on trees 

≥ 10 cm dbh collected in circular NCRN plots and sub-sampled to 

smaller square plots............................................................................... A-4

Figure A. 4. Percent detectable change using different size and number of plots 

in the National Capital Region Network. Analyses are based on 

trees ≥ 10 cm dbh collected in circular NCRN plots and sub-sampled 

to smaller square plots .......................................................................... A-5
Mid-Atlantic Network
2009 vii

Forest Vegetation Monitoring Protocol Contents

Tables

Tables

Table 1. Allocation of plots at Mid-Atlantic and Northeast Coastal and Barrier 

Network parks in relation to forested area. ...............................................5

Table 2. Level of change in trees based on pilot data collected in 75 Mid-Atlantic 

Network forest vegetation monitoring plots in 2007 .................................6

Table 3. Level of change in saplings and shrubs based on pilot data collected in 75 

Mid-Atlantic Network forest vegetation monitoring plots in 2007. ..........7

Table 4. List of Standard Operating Procedures shared between the MIDN and the 

NETN. SOPs are available in Tierney et al. (2009). One NCRN SOP is also 

referenced in this table and is available in Schmit et al. (2009). ................8

Table 5. Criteria for rejecting plot locations....................................................................8

Table 6. Annual budget for implementing the MIDN Forest Vegetation Monitoring 

Protocol. Figures are based on expenses incurred during the 2008 field 

season...........................................................................................................11

Table A. 1. Percent change in basal area and density of trees ≥ 10 DBH occurring in 

NCRN plots in 2006. .................................................................................. A-2

Table A. 2. Percent change in density for species occurring in NCRN plots in 2006. The 

NCRN plot consists of a 15-m radius circular plot. .................................. A-6

Table A. 3. Species lost from study or individual parks when a smaller plot 

is used......................................................................................................... A-7
Mid-Atlantic Network
Forest Vegetation Monitoring Protocol

2009 ix

Acronyms

APCO: Appomattox Court House National 

Historical Park

BOWA: Booker T. Washington National 

Monument

DBH: Diameter at breast height

DOI: U.S. Department of the Interior

EISE: Eisenhower National Historic Site

ERMN: Eastern Rivers and Mountains 

Network

FGDC: Federal Geographic Data Committee

FHM: Forest Health Monitoring

FIA: Forest Inventory and Analysis Program of 

USFS 

FRSP: Fredericksburg and Spotsylvania 

National Military Park

GETT: Gettysburg National Military Park

GLKN: Great Lakes Network

GPS: Global Positioning System

GRTS: Generalized Random Tessellation 

Stratified Design

HOFU: Hopewell Furnace National Historic 

Site

I&M: Inventory and Monitoring Program

MDC: Minimum Detectable Change

MIDN: Mid-Atlantic Network

NB: National Battlefield

NBP: National Battlefield Park

NCBN: Northeast Coastal and Barrier 

Network

NCRN: National Capital Region Network

NER: NPS Northeast Region

NETN: Northeast Temperate Network

NHP: National Historical Park

NHS: National Historic Site

NMP: National Military Park

NP: National Park 

NPS: National Park Service

NRDT: Natural Resource Database Template

NRPC: Natural Resource Program Center

PETE: Petersburg National Battlefield

RICH: Richmond National Battlefield Park

SHEN: Shenandoah National Park

VAFO: Valley Forge National Historical Park

WASO: Washington-Area Service Office
Mid-Atlantic Network
2009 xi

Executive Summary

The Inventory and Monitoring Program’s 

Mid-Atlantic Network has identified forest 

vegetation and several associated vital signs as 

high priority for long-term monitoring. In collaboration with other networks, a protocol has 

been developed and pilot tested in nine parks 

of Virginia and Pennsylvania. The forest vegetation monitoring protocol assesses the status 

and trends of forest plant communities, and the 

impacts of stressors such as white-tailed deer, 

invasive exotic plants, exotic plant diseases 

and pathogens, and native forest pests, as well 

as the effect of acid deposition on forest soils. 

Evaluation of snags and downed woody debris 

provides information on additional important 

habitat for wildlife. A set of Standard Operating Procedures are shared with the Northeast 

Temperate Network’s forest vegetation monitoring protocol. The current protocol has been 

designed to sample 300 plots in forested areas 

of Mid-Atlantic Network and 24 plots in three 

Northeast Coastal and Barrier Network parks. 

Plot locations are randomly chosen from a 

250-m sampling grid using a spatially balanced 

design (generalized random-tessellation stratified). Each plot consists of a 20 x 20 m square 

where all trees and shrubs with a diameter 

at breast height (dbh) ≥ 10 cm are identified, 

measured, tagged, marked, mapped, and their 

condition assessed. Trees and shrubs with a 

dbh ≥ 1 cm are identified, measured, marked, 

and tagged in each of three microplots. Number and height of tree seedlings and cover of a 

select group of native and invasive herbaceous 

plants are recorded in twelve quadrats. Coarse 

woody debris is measured along three transects. Additional metrics will likely be incorporated in future protocol versions including soil 

sampling and landscape context.
Mid-Atlantic Network
Acknowledgments

2009 xiii

We would like to thank members of the National Park Service’s Forest Vegetation Working Group who have spent the last three years 

collaboratively developing the monitoring protocols for networks in the Northeast, National 

Capital, Midwest, and Southeast Regions. In 

particular we are indebted to the staff of the 

National Capital Region Network and Northeast Temperate Network whose protocols form 

a significant basis for the Mid-Atlantic Network protocol. Our thanks are also extended 

to Wendy Cass, Shenandoah National Park, for 

providing a wealth of valuable experience and 

insights into the development and maintenance 

of a long term vegetation monitoring program. 

Kristina Callahan and Sarah Wakamiya have 

provided invaluable data management and field 

support, and we are very grateful to our field 

crews over the last three years including, James 

Burka, Carolyn Davis, Sophia DeMaio, Erika 

Gorczyca, Nichole Lightle, Lindsey Sloat, Andrew Vincello, Katherine Wilkin, and Elizabeth 

Wright. We would also like to thank Elizabeth 

Johnson, Regional I&M Program Manager, and 

John Karish, NER Chief Scientist, as well as the 

park resource managers, including Kristen Allen, Steve Ambrose, Tim Blumenschine, Zachary Bolitho, Brian Eick, Kristina Heister, Gregg 

Kneipp, Dave Shockley, and Timbo Sims for 

their continued support for the implementation of all Mid-Atlantic Network inventory and 

monitoring activities. We are also very grateful to our three reviewers, Mike Jenkins, Will 

McWilliams, and Chip Scott for their valuable 

input and feedback. Penelope Pooler provided 

additional feedback on statistical analyses. Jason Bennett provided guidance and templates 

for the document layout. 
Mid-Atlantic Network
Forest Vegetation Monitoring Protocol

2009 1

1 Background and Objectives

1.1 Background and History

The forest vegetation monitoring protocol 

is designed to inventory and monitor forest 

vegetation in nine parks of the National Park 

Service (NPS) Mid-Atlantic Network (MIDN) 

and three parks of the Northeast Coastal 

and Barrier Network (NCBN) as part of the 

Inventory and Monitoring Program (I&M). 

Since 2004, several I&M parks and networks 

are collaborating to ensure that protocols for 

tracking forest health allow compatibility with 

one another and with the United States Forest Service (USFS) Forest Inventory Analysis 

(FIA) and Forest Health Monitoring (FHM) 

programs. This protocol is based primarily on 

protocols developed by the National Capital 

Region Network (NCRN) (Schmit et al. 2009) 

and NETN (Northeast Temperate Network) 

(Tierney et al. 2009), with additional components from Shenandoah National Park (Cass 

2007), Great Lakes Network (GLKN) (Sanders 

et al. 2008) and the Eastern Rivers and Mountains Network (ERMN)(Perles et al. In press). 

The standard operating procedures (SOPs) are 

shared with the NETN. 

The Mid-Atlantic Network consists of ten 

parks distributed from southern Pennsylvania 

to southern Virginia, and extending from the 

Piedmont to the Coastal Plain (Figure 1). The 

parks range from the predominantly small, 

cultural parks with a limited history of natural 

resource monitoring, to the comparatively large 

Shenandoah National Park that was designated 

as one of the prototype monitoring park upon 

which the I&M vital signs program was developed. All the Mid-Atlantic Network parks are 

located in eastern deciduous forest that is characterized by pronounced seasons, and strong 

annual cycles of temperature and precipitation. 

Richmond National Battlefield Park and the 

Eastern Front of Petersburg National Battlefield fall within the Coastal Plain which is composed primarily of unconsolidated sand, silt 

and clay that has been cleared extensively. The 

Coastal Plain gives way to the Piedmont at the 

loosely defined fall zone, and it is in this transition zone that Fredericksburg and Spotsylvania 

National Military Park is located. All other 

MIDN parks are located within the Piedmont, 

except for Shenandoah NP that is found exclusively in the Blue Ridge Mountains. Forests of 

the Blue Ridge vary along altitudinal gradients 

but are primarily Appalachian Oak Forests. The 

southern Piedmont and Coastal Plain forests 

are Southern Mixed forests composed of pines 

and hardwoods. The Pennsylvania parks are 

primarily broadleaf forests that form a lowland northerly expression of the Appalachian 

Oak Forest. In addition, three NCBN parks 

are included in this monitoring protocol; two 

are located in the coastal plain (Thomas Stone 

National Historic Site and George Washington 

Birthplace National Monument), and the third 

in the Lower New England ecoregion in Long 

Island (Sagamore Hill National Historic Site). 

Figure 1. Map of the 

parks in the Mid-Atlantic 

Network. Three parks from 

the Northeast Coastal and 

Barrier Network are also 

shown and are included in 

this monitoring protocol. 

Shenandoah National Park 

has its own protocol for 

monitoring forest vegetation 

(Cass 2007).
2 National Park Service

Mid-Atlantic Network 

All MIDN have completed vegetation maps 

with some parks having additional vegetation 

inventory work. Reports are available for Appomattox Court House National Historical 

Park (Patterson 2008a), Booker T. Washington National Monument (Patterson 2008b), 

Fredericksburg and Spotsylvania National 

Military Park (Taverna and Patterson 2008), 

Gettysburg National Military Park and Eisenhower National Historic Site (Kunsman 2006, 

Perles et al. 2006), Hopewell Furnace National 

Historic Site (Storm et al. 1994, Podniesinski et 

al. 2005a), Petersburg National Battlefield (Patterson 2008d), Richmond National Battlefield 

Park (Hayden and Johnson 1986, Hayden et al. 

1988, Haskins et al. 1989, Patterson 2008e), and 

Valley Forge National Historical Park (Podniesinski et al. 2005b). For the NCBN parks, a report has been published for George Washington Birthplace National Monument (Patterson 

2008c). Some parks have ongoing monitoring 

activities led by park staff, for example, historic 

woodlots at Gettysburg NMP (Bowersox et al. 

2002, Larrick et al. 2003, Bowersox et al. 2004, 

Niewinski et al. 2006), and Valley Forge NHP 

(Bowersox and Larrick 1999, Diefenbach et 

al. 2008), while several parks have had vegetation monitoring in the past including Fredericksburg and Spotsylvania NMP (Orwig and 

Abrams 1994), and Petersburg NB (Rantis and 

Johnson 1995, 2002).

1.2 Rationale for Monitoring Forest 

Vegetation

The Mid-Atlantic region is primarily a forested 

ecoregion and all MIDN parks have forests 

that form an essential part of the landscape 

and provide habitat for a diversity of wildlife. 

For this reason, the vital signs selection process 

highlighted forest vegetation and several associated indicators as being a high priority for 

monitoring (Comiskey and Callahan 2008).

The forest vegetation monitoring protocol assesses the status and trends of forest plant communities, and the impacts of stressors such as 

white-tailed deer, invasive exotic plants, exotic 

plant diseases and pathogens, and native forest 

pests, as well as the effect of acid deposition on 

forest soils. Evaluation of snags and downed 

woody debris provides information on additional important habitat for wildlife.

Forest structure, composition, and dynamics 

are important measures of forest condition and 

health (Yahner 2000). Changes in these metrics 

can be indicative of stressors that may result 

in alterations in the future ecological integrity 

of the forest communities and the species that 

depend on them (Rutters et al. 1992, Keddy 

and Drummond 1996). For example, high 

mortality rates among canopy trees may signal 

a change in the dominant forest species (Orwig 

and Abrams 1994, Abrams and Black 2000); 

declines in seedling and sapling densities could 

indicate a reduced capacity of the forest to regenerate (McWilliams et al. 2005); or, increases 

in invasive exotic plant cover could result in 

the competitive exclusion of other herbaceous 

plants in the forest understory (Simberloff et al. 

2005). Other anthropogenic stressors may have 

a long-term effect on the forest communities, 

including acid deposition which can alter soil 

chemistry, disrupting nutrient cycles (Fowler 

et al. 1999). Increased habitat fragmentation 

surrounding parks can weaken the ecological 

integrity of the forests, increasing their susceptibility to exotic plant and pest invasions 

(Collinge 1996).

Information from this monitoring protocol 

will assist parks in managing their natural resources. For example, at Valley Forge National 

Historical Park in Pennsylvania, deer densities 

that exceed 200 per square mile have caused a 

drastic reduction in forest regeneration and the 

diversity and abundance of herbaceous understory plants. The park hopes to implement deer 

management efforts, and will use the forest vegetation monitoring data to determine whether 

future deer densities support healthy regeneration. Likewise, parks where deer densities are 

on the rise will look to the forest vegetation 

monitoring data to determine when deer management should be implemented. In addition, 

information and data will be made available to 

other agencies and interested parties.

1.3 Measurable Objectives

The overarching goal of the vegetation monitoring program is to provide a framework 

for monitoring long-term change over broad 

spatial scales of the Mid-Atlantic Network forests1

. Specific monitoring objectives include:

1. Determine the status and trends in forest 

structure, composition, and dynamics of 

canopy and understory woody species.

2. Determine the status and trends in the 

density and composition of tree seedlings 

and selected herbaceous species that are 

indicators of deer browse.

1

 All statements of MIDN in this protocol also 

include the three NCBN parks.
2009 3

Forest Vegetation Monitoring Protocol

3. Detect and monitor the presence of invasive 

exotic plants, exotic plant diseases and 

pathogens, and forest pests.

4. Determine the status and trends in forest 

coarse woody debris and the availability of 

snags.

5. Determine the status and trends in soil 

Ca:Al and C:N ratios to asses the extent of 

base cation depletion, increased aluminum 

availability and/or nitrogen saturation 

impacting MIDN forest soils.

Inferences will be made on a park, network, 

and regional basis. For some MIDN parks that 

are divided into several units, inferences will be 

made to individual units (Fredericksburg and 

Spotsylvania NMP and Petersburg NB). The 

standardized approach will facilitate comparisons across networks and with other agencies 

(for example, the USFS-FIA Program).

2 Sampling Design

2.1 Sampling Design Rationale

As the first I&M networks initiated protocol 

development for forest vegetation, an important objective was to have methodologies compatible with approaches used by other agencies 

and institutions. The Forest Service’s FIA Program was seen as a potential model to follow as 

it has been in use nationwide for over 70 years 

(McRoberts 2005, USFS 2007). A forest monitoring working group was formed to ensure 

protocols developed by the networks consisted 

of standardized metrics and field methods to 

assure that data sharing is possible. The MIDN 

actively participated in the working group and 

has therefore been able to draw heavily from 

the first networks to develop their protocols, 

primarily the NETN (Tierney et al. 2009) and 

the NCRN (Schmit et al. 2009). The resulting 

protocols, including this one, are based on the 

FIA approach, but have been modified to meet 

network objectives and funding constraints.

2.2 Target Population

Forest vegetation monitoring is conducted 

in all MIDN parks (except Shenandoah NP 

where a separate protocol is used [Cass 2007]) 

and three NCBN parks. The target population 

is restricted to forested areas within each park. 

Park resource managers actively participated 

in defining the population to be sampled, with 

some areas being excluded from the sampling 

area. For some parks (Fredericksburg and 

Spotsylvania NMP and Petersburg NB), it 

was determined that inferences on individual 

units or groups of units was desirable; for the 

remaining parks, inferences will be made at a 

park level. 

2.3 Site Selection

Sampling design is based on a 250-m grid developed for the entire network (sampling frame). 

All points that do not fall within the sampling 

frame of the target population were discarded. 

The points within the sampling frame were 

used as potential sampling locations (Figure 

2). Generalized random-tessellation stratified 

(GRTS), a method that produces a random, 

spatially balanced sample (Stevens and Olsen 

2004), was used to order all potential sampling 

points for each park or unit. Sampling points 

are then selected in the order they occur on 

the list. Sampling locations that do not meet 

predefined criteria, for example for safety reasons or because the plot was located on a road 

or trail, can be rejected and the next point on 

the list selected for sampling. The design provided by GRTS also allows points to be added 

or subtracted without a loss of spatial balance.

Stratification based on vegetation or landscape 

Figure 2. Example of sampling 

frame at Valley Forge 

National Historical Park. 
4 National Park Service

Mid-Atlantic Network 

features has not been incorporated. Stratification by forest type is known to be problematic, as vegetation types change quickly. This 

complicates analysis and defeats the purpose 

of the original stratification (Diefenbach and 

Mahan 2002). 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. 

However, inferences on the forest communities 

at a park, and in some instances by units within 

a park, are required. Therefore, individual 

GRTS draws were conducted for the various 

parks/units, with a minimum number of samples being selected based on the extent of forest 

(sampled population area).

2.4 Sampling Frequency and Replication

Vegetation monitoring will be conducted each 

year, but any one plot will only be visited every four years. Yearly plot measurements can 

cause soil compaction and trampling of the 

understory which would bias the monitoring 

data (Urquhart et al. 1998). Additionally, yearly 

changes in trees and soil are likely to be sufficiently small as to warrant a longer sampling 

return interval (Urquhart and Kincaid 1999). A 

four-panel sampling design will be used, where 

each panel consists of 75 plots in the MIDN and 

six plots in the NCBN, which will be revisited 

every fourth year [1-3]. This level of temporal 

resolution was deemed important for monitoring several of the vital signs in this protocol, 

namely deer herbivory, invasive exotic plants, 

native forest pests, and exotic diseases / pathogens – plants. There is no overlap in the panels 

to evaluate inter-annual changes, but dramatic 

events (e.g. drought or insect infestations) will 

be observed for a subset of the plots, events 

that may be missed if all the plots are visited at 

the same time every fourth years. Sampling will 

be conducted between May and October.

2.5 Recommended Number and 

Location of Sampling Sites

The response design and sample size were determined based on an initial evaluation of data 

collected by the neighboring National Capital 

Region Network (NCRN). The MIDN shares 

many similarities with NCRN in geographic 

location, park management priorities, and natural resource threats. The MIDN conducted 

power analysis on data from 100 NCRN plots 

using various plot and sample sizes (Appendix 

A). We estimated that MIDN would be able to 

implement a maximum of 300 plots throughout the network given our funding and staffing 

level. An additional twenty-four plots were included in 2008 for the three NCBN parks. Plots 

were allocated to each sampling frame based 

on total forested area (Table 1). Our preliminary analysis of the NCRN data suggest that 

a minimum of eight plots would be needed to 

make inferences, and this is confirmed by our 

own pilot data (see below). Thus, eight plots 

are the smallest number allocated to any park 

or unit.

2.6 Level of Change that can be 

Detected

Preliminary analysis was conducted using data 

from the first year of pilot testing and implementation (2007). Because no temporal data 

is available, spatial variability is used as a proxy 

for variation over time. Temporal variation is 

likely to be less than that across space, which 

makes this a conservative estimate of the statistical power of this study(Schmit et al. 2009).

Sample size analysis was used to determine the 

level of change and sample sizes at a power of 

0.8 and an alpha level of 0.1 (Elzinga et al. 1998): 

n

s MDC

2 2 + βα ) Z Z()( =

Where, Minimum Detectable Change (MDC) 

is the smallest level of change that can be detected; s is the standard deviation calculated for 

all 75 plots; Zα is the z-coefficient using α for 

the false-change (Type I) error rate of 0.1; Zβ

is the Z-coefficient for the missed-change (Type 

II) error rate of 0.2 (power 1-β = 0.8); and, n is 

the number of plots in the sample (75).

% x 100

mean

MDC Change =

Where % Change (or % effect size) is the percent change that can be detected; and, mean 

is the average values in the sample (including 

plots with no values).
2009 5

Forest Vegetation Monitoring Protocol

As a minimum, we want to detect a 50% change 

after one repeated measure. Because multiple 

measurements will be taken at each plot, we 

expect that the power to detect change will 

increase over time; hence, metrics that have 

low power in the first recensus could improve 

as plots are revisited over the years. We assume 

that data will be analyzed as a paired t-test 

between the two sampling intervals. In the current analysis, data are multiplied by four to account for the four year design — once all plots 

have been installed, our sample size will be 

four times the number of plots than those we 

used in these initial analyses. In all cases, power 

analysis is conducted for all plots. For power 

analysis of species data, plots with no data for 

a species are included. 

2.6.1	 Trees

For tree basal area and density at the network 

level we expect to detect a 6% and 7% change 

respectively with a power of 0.8 and alpha level 

of 0.1. A minimum of four plots are needed to 

detect a 50% change in tree basal area, and six 

plots for detecting the same level of change in 

tree density (Table 2). Therefore, in order to 

make inferences regarding tree populations in a 

park or unit, we need at least six plots. Because 

the analysis is based on one quarter of the plots, 

we are taking a more conservative approach 

and estimating that we will need a minimum 

of eight plots, and this is the minimum number 

allocated to any park or unit.

For individual species across the network, the 

detectable level of change varies considerably, 

Park Park unit Code Plots Forested Area (ha) ha/plot

Mid-Atlantic Network Parks

Appomattox Court House 

NHP APCO 28 442.0 15.8

Booker T. Washington NM BOWA 8 62.4 7.8

Fredericksburg and 

Spotsylvania NMP

Fredericksburg FRSP-F 28 459.6 16.4

Spotsylvania 

Court House FRSP-S 28 430.0 15.4

Wilderness and 

Chancellorsville

FRSPWC 48 1397.9 29.1

Gettysburg NMP GETT 32 587.7 18.4

Hopewell Furnace NHS HOFU 16 269.5 16.8

Petersburg NB

Eastern and 

Western Front

PETEWE 28 525.3 18.8

Five Forks PETE-FF 24 397.4 16.6

Richmond NBP RICH 32 564.1 17.6

Valley Forge NHP VAFO 28 427.3 15.3

Northeast Coastal and Barrier Network 

Thomas Stone NHS THST 8 89.0 11.1

George Washington 

Birthplace NM GEWA 8 86.6 10.8

Sagamore Hill NHS SAHI 81 16.6 2.1

Total 324 5755.6

1

 It may not be possible to sample eight randomly located plots at SAHI due to the limited area of forest in the park

Table 1. Allocation of plots at Mid-Atlantic and Northeast Coastal and Barrier Network parks in relation to forested area. 
6 National Park Service

Mid-Atlantic Network 

with only 18 of the most common species allowing us to detect at least a 50% change in 

basal area or density given our current sample 

sizes (Table 2). Where the detectable level of 

change is above 50%, the primary cause is that 

species occur in only a few plots or there is high 

variability in density or basal area across plots. 

As more plots are added to our sample, there 

will be a likely reduction in the variability, as 

will sampling the same plots over time.

2.6.2	 Saplings and shrubs

A challenge in sampling multiple metrics in 

the same plots is that power to detect change 

will likely vary depending on what is being 

measured. In the case of saplings and shrubs, 

the power to detect change was generally lower 

than with trees, primarily due to the lower 

number of individuals measured. Our pilot 

data indicated that we would be able to detect 

a 12% change in the basal area and 14% change 

in density of saplings and shrubs (Table 3). With 

this estimated level of change, we will need at 

least 18 plots to detect a 50% change in basal 

area, and 24 plots to detect the same change in 

tree density. 

As was seen with the tree data, for most individual species of saplings and shrubs across the 

network, our power to detect change was low. 

Only for the most common understory species 

was is it possible to detect a 50% change in density or basal area (Table 3). Addition of plots in 

the next few years will provide better estimates.

2.6.3	 Seedling regeneration

Forest regeneration is seriously impacted by 

deer grazing in some of the network parks. We 

will be evaluating stocking rate using metrics 

developed by McWilliams (2005) for Pennsylvania. Tree seedlings are assigned a score based 

on their height class. Healthy stocking rates 

are achieved when an average of two seedling 

scores are registered per 1 m2

. We conducted 

a sample size analysis on our pilot data and 

found that on average there were 5.1 seedlings / 

m2 across the network, and we would be able to 

Basal area (cm2) Density

Species Plots1 Mean2 SD3 MDC4 % Change5 Mean2 SD3 MDC4 % Change5

Acer rubrum 33 828 2086 300 36% 1.63 2.96 0.43 26%

Carya glabra 12 162 650 94 58% 0.28 0.80 0.11 41%

Carya tomentosa 20 266 687 99 37% 0.55 1.48 0.21 39%

Cornus florida 15 49 131 19 38% 0.36 0.85 0.12 34%

Fagus grandifolia 10 262 1167 168 64% 0.39 1.29 0.19 48%

Ilex opaca 15 97 266 38 40% 0.60 1.66 0.24 40%

Juniperus virginiana 17 85 286 41 48% 0.35 0.83 0.12 34%

Liquidambar styraciflua 31 1190 3311 477 40% 1.92 3.27 0.47 25%

Liriodendron tulipifera 40 2087 4088 588 28% 2.33 5.57 0.80 34%

Nyssa sylvatica 26 619 2044 294 48% 1.51 3.19 0.46 30%

Pinus taeda 15 1399 3513 506 36% 2.93 8.20 1.18 40%

Pinus virginiana 16 797 2449 353 44% 1.53 4.68 0.67 44%

Prunus serotina 9 50 162 23 47% 0.16 0.47 0.07 42%

Quercus alba 40 1911 3019 435 23% 2.35 3.81 0.55 23%

Quercus coccinea 12 257 951 137 53% 0.29 0.87 0.12 43%

Quercus falcata 9 88 290 42 47% 0.16 0.49 0.07 44%

Quercus rubra 31 744 1573 226 30% 0.88 1.68 0.24 27%

Quercus velutina 20 455 1094 157 35% 0.59 1.32 0.19 32%

Total 75 13295 5103 734 6% 22.56 10.37 1.492 7%

1

 Number of plots that a species occurs in

2

 Mean basal area or density calculated for all 75 plots 

3

 Standard deviation of the basal area or density calculated for all 75 plots

4

 Minimum Detectable Change, the smallest level of change that can be detected at α = 0.1 and Power (1-β) = 0.8

5

 MDC expressed as a percentage of the mean

Table 2. Level of change in trees based on pilot data collected in 75 Mid-Atlantic Network forest vegetation monitoring plots 

in 2Table 3. Level of change in saplings and shrubs based on pilot data collected in 75 Mid-Atlantic Network forest vegetation 
2009 7

Forest Vegetation Monitoring Protocol

detect 10.4% change in the seedling score with 

a power of 0.8 and alpha level of 0.1. At the individual park level, such as at Gettysburg NMP, 

our detectable level of change is 21.4%, while at 

Valley Forge NHP the rate is 57.8%. 

3 Field Methods

Detailed methods and field procedures are 

outlined in the Standard Operating Procedures (SOPs) for the protocol. These SOPs are 

maintained and shared with the NETN. Table 4 

provides a summary of SOPs their content.

3.1 Safety

The Northeast Temperate Network (NETN) 

and the Mid-Atlantic Network (MIDN) consider the occupational health and safety of 

their employees, cooperators, and volunteers 

to be of utmost importance, and are committed 

to ensuring that all seasonal field technicians 

receive adequate training on National Park 

Service (NPS) safety procedures, incident reporting, and emergency response prior to field 

work. Emergency procedures and contacts, 

incident reporting, field preparation, safe field 

procedures, vehicle safety, and workers compensation procedures are outlined in SOP 1 

(Safety procedures).

3.2 Field Season Preparations and 

Equipment Setup

Prior to the field season, all equipment should 

be reviewed against the equipment list, and 

tested to ensure proper functioning. Any consumable items (tags, nails, paint etc.) should be 

ordered if sufficient quantities are not in stock. 

Plot markers should be stamped and affixed to 

rebar. Necessary permits should be obtained 

and park housing reserved. Maps of plot locations are prepared and sample points uploaded 

to the GPS. Additional details and a full list of 

equipment is provided in SOP 2 (Preparation 

and equipment list).

3.3 Field Season Scheduling

Field work is conducted between May and October. In 2008, the MIDN tested a combined 

field team approach with the NETN. The field 

crew, consisting of two teams working independently, conducted field work in the NETN 

parks between May and July, with August to 

October dedicated to the MIDN parks. 

3.4 Technician Training

A one-week training session is conducted each 

year at the beginning of the field season. Training for the combined MIDN/NETN field team 

took place at Acadia National Park in 2008 and 

at Valley Forge National Historical Park in 2009. 

Basal area (cm2) Density

Species Plots1 Mean2 SD3 MDC4 % Change5 Mean2 SD3 MDC4 % Change5

Acer rubrum 31 20.1 39.4 5.7 28% 1.23 2.25 0.32 26%

Carpinus caroliniana 12 12.0 46.9 6.8 56% 0.75 2.45 0.35 47%

Carya tomentosa 9 2.1 7.6 1.1 52% 0.25 0.82 0.12 47%

Cornus florida 24 22.6 47.4 6.8 30% 1.44 3.37 0.49 34%

Fraxinus americana 9 2.7 17.6 2.5 93% 0.17 0.58 0.08 48%

Ilex opaca 27 14.4 35.8 5.2 36% 0.99 1.72 0.25 25%

Liquidambar styraciflua 18 12.5 36.1 5.2 42% 0.59 1.51 0.22 37%

Nyssa sylvatica 29 18.2 40.0 5.8 32% 1.28 2.17 0.31 24%

Quercus alba 21 19.9 56.5 8.1 41% 0.89 2.28 0.33 37%

Quercus velutina 9 5.8 30.1 4.3 75% 0.24 0.79 0.11 47%

Sassafras albidum 8 4.4 17.3 2.5 56% 0.17 0.58 0.08 48%

Total 75 227.3 193.1 27.8 12% 14.59 14.31 2.06 14%

1

 Number of plots that a species occurs in

2

 Mean basal area or density calculated for all 75 plots 

3

 Standard deviation of the basal area or density calculated for all 75 plots

4

 Minimum Detectable Change, the smallest level of change that can be detected at α = 0.1 and Power (1-β) = 0.8

5

 MDC expressed as a percentage of the mean

monitoring plots in 2007.
8 National Park Service

Mid-Atlantic Network 

A training manual is currently under development and will be included as an additional SOP. 

In addition, the project leads spend a second 

week, subsequent to the training, with the field 

crew as they implement the protocol, and again 

sporadically throughout the season. The field 

crew are instructed to address any questions 

and uncertainties while still at the plot — each 

team has at least one cell phone available. 

3.5 Details of Taking Measurements, and 

Post-Collection Processing

3.5.1	 Plot location

Field teams navigate to the plot locations that 

have previously been uploaded to the GPS 

(SOP 3: Using the Global Positioning System 

–Garmin 60CSX). Sampling locations that 

do not meet predefined criteria (Table 5), for 

example are not forested or fall on a road or 

SOP # and title SOP #

Safety procedures 1

Preparation and equipment list 2

Using the Global Positioning System –Garmin 60CSX 3

Using the Laser Rangefinder (LAR) 4

Data management and quality assurance/quality control 5

Site selection and plot establishment 6

Photopoint 7

Stand and site measurements 8

Tree measurements 9

Unknown plant collection NCRN SOP 11

Microplot measurements 10

Coarse woody debris 11

Soil measurements and sampling 12

Quadrat measurements 13

Landscape context 14

Analyzing and reporting ecological integrity 15

Deviations, differences, and summary of major changes 16

Category Criteria

Safety

>30° slope

Hazardous access

Biological

<25% forest cover in an area not designated for forest regeneration, e.g. early 

successional stand

Any portion of the plot overlaps a large trail, road, or river. Small trails and 

streams that pass through the plot are acceptable

Cultural Establishment would disturb sensitive cultural resources, e.g. earthworks

Table 4. List of Standard Operating Procedures shared between the MIDN and the NETN. SOPs are 

available in Tierney et al. (2009). One NCRN SOP is also referenced in this table and is available in Schmit 

et al. (2009).

Table 5. Criteria for rejecting 

plot locations
2009 9

Forest Vegetation Monitoring Protocol

trail, are rejected and the next point on the list 

selected for sampling. A GPS measurement is 

recorded for the plot center using a minimum 

of 100 averaged points (SOP 3).

3.5.2	 Plot establishment

Once the site has been verified, the plot is established using the procedures outlined in SOP 

6 (Site selection and plot establishment). The 

plot consists of a 20 m x 20 m square with three 

nested microplots and 12 quadrats (Figure 3). 

A laser rangefinder is used to establish the plot 

boundaries (SOP 4: Using the Laser Rangefinder). PVC posts are used to mark the plot 

corners and the microplots; a survey marker 

attached to rebar is placed at the plot center.

3.5.3	 Stand and site measurements

Information is recorded that describes the site, 

including, slope, aspect, physiographic class, 

stand structure and height, crown closure, 

ground cover and disturbance, microtopography, and presence of water (SOP 8: Stand and 

site measurements). 

3.5.4	 Plot photopoints

A series of digital photographs are taken from 

the plot center (SOP 7: Photopoint). The camera date and time feature is verified to ensure 

the resulting file will have the correct date 

stamp.

3.5.5	 Field measurements

All trees and shrubs with a diameter at breast 

height (dbh) ≥ 10 cm in the main plot are identified, measured, tagged, marked, their location 

mapped using the laser rangefinder, and their 

condition assessed (SOP 9: Tree measurements). Trees and shrubs with a dbh ≥ 1 cm are 

identified, measured, marked, and tagged in 

each of the three microplots (SOP 10: Microplot measurements). Number and height of tree 

seedlings and cover of a select group of native 

and invasive herbaceous plants are measured in 

the quadrats (SOP 13: Quadrat measurements). 

Coarse woody debris is measured along the 

transects (SOP 11: Coarse woody debris). Any 

plant species that cannot be identified in the 

field are collected (NCRN SOP 11: Unknown 

plant collection).

Additional field measurements will be added 

in the future including those currently in use 

by the NETN such as soil sampling (SOP 12: 

Soil measurements and sampling), landscape 

context (SOP 14: Landscape context). Differences between the networks and major changes 

to SOPs are documented (SOP 16: Deviations, 

differences, and summary of major changes). 

Any new measurements will be documented as 

SOPs.

3.6 QA/QC

Approximately 5% of sampled plots will be 

resampled annually to determine reliability of 

data collection. Additional methods for quality control and quality assurance are specified 

within Data management and QA/QC (SOP 5).

4 Data Handling, Analysis, and 

Reporting

4.1 Metadata Procedures

Data compiled by the MIDN must be accompanied by FGDC compliant metadata. This 

includes both spatial and non-spatial datasets. 

Specific metadata requirements are outlined in 

the NER Biological Metadata Tools SOP.

4.2 Overview of Database Design

The project database is based on the back-end 

database design of the Natural Resources Database Template (NRDT). The original database 

2 m

5 m

8 m

14.14 m

135° 

14.14 m

45° 

14.14 m

225° 

14.14 m

315° 

7 m, 45° 

7 m, 180° 

Plot 

10 m

0° 

20 m 

3 m 

7 m, 315° 

Microplot 

Quadrat 

Transect

Figure 3. Layout of Mid-Atlantic 

Network forest vegetation 

monitoring plot consisting of 

one 20 x 20 m plot, three 3-m 

diameter microplots, 12 2 m x 

0.5 m quadrats, and three 15-m 

transects.
10 National Park Service

Mid-Atlantic Network 

was developed by the ERMN and is currently 

being adapted as a combined MIDN/NETN 

database. The database incorporates many 

functions and utilities to help reduce the possibility of data entry errors and promote data 

integrity.

4.3 Data Entry, Verification, and Editing

Our original intent was to enter data in the field 

using a tablet PC. Given the range of measurements and the small team size (2 people), data 

entry in the field was not practical and risked 

jeopardizing the quality of the measurements 

collected. Therefore, during the first four years 

of plot establishment, data is being entered on 

field datasheets and transferred to the database 

once a week. Once recensus of plots is initiated, 

field computers running the Access database 

will be used to record information. At that 

time, the crew will not be installing new plots 

and therefore the team has fewer tasks and 

more time to record data in a field computer. 

This will reduce data entry errors and provide 

additional quality control in the field.

4.4 Data Analysis

The MIDN will follow the ecological integrity metrics developed by the NETN, which 

includes calculation of a range of forest metrics 

(SOP 15: Analyzing and reporting ecological integrity). As outlined in the NETN forest 

monitoring protocol (Tierney et al. 2009), the 

MIDN will estimate status and trends over 

time of specific measures in forested systems of 

each sampled park. Analyses will be based on 

a general linear model which partitions spatial 

and temporal variability to allow assessment of 

change over time, as is done by the USFS FIA 

program (Woodall and Monleon 2008). 

4.5 Data Archival Procedures

Where data is collected on field forms, these 

will be scanned and stored in electronic format. Data entered into computers, either in 

the field or in the office, will be backed up on 

a daily basis to an external hard drive which 

will be uploaded to the MIDN server weekly. 

Long term archival is conducted through a cooperative agreement with North Carolina State 

University.

4.6 Reporting Schedule and Format

The MIDN will produce annual data summary 

reports on each year’s field work and results of 

the ecological integrity metrics. Upon completion of each panel (every four years), a more 

detailed report will provide information on 

the status and trends in forest metrics at each 

of the parks and the network as whole. Ad-hoc 

reports and scientific papers will be published 

as appropriate.

5 Personnel Requirements and 

Training

5.1 Roles, Responsibilities, and 

Qualifications 

This forest monitoring protocol is implemented 

by a crew leader and technician in addition to 

contract botanists as needed. If two teams are 

hired, the crew leader will alternate working 

with each team.

5.1.1	 Vegetation Ecologist (Network

Coordinator)

The Vegetation Ecologist operates as the project manager to oversee the implementation of 

the monitoring program including:

• Permits, scheduling, hiring, purchasing, and 

contracting

• Maintain and update forest vegetation 

monitoring protocol

• Conduct training and participate in field 

work as needed

• Oversee field crew, providing logistical, 

administrative, and technical support

• Ensure QA/QC standards are met

• Analyze data and prepare reports

5.1.2	 Data Manager

The MIDN Data Manager provides oversight 

for all data related aspects of the project including:

• Provide database training to crew

• Maintain forest monitoring database

• Prepare maps of sample point locations

• Ensure data management practices are 

met, including data backup, transfer, and 

archiving

• Conduct training and participate in field 

work as needed

5.1.3	 Vegetation Crew Leader

The Crew Leader is responsible for managing 

the vegetation crew and must have a strong 

knowledge of the flora of the mid-Atlantic region. Tasks include:
2009 11

Forest Vegetation Monitoring Protocol

• Coordinate daily field activities and ensure 

equipment is in working order

• Coordinate directly with park resource 

managers when conducting field work

• Ensure that all field crew members 

are following proper data collection 

procedures

• Identify plants accurately and/or process 

unknown plants for later identification

• Conduct data verification if data from paper 

field sheets were entered into database

• Ensure that all data undergoes the proper 

QA/QC procedures

• Maintain crew time sheets

5.1.4	 Vegetation Crew Technicians

The Crew Technicians are responsible for data 

collection and must have a working knowledge 

of the flora of the mid-Atlantic region. Tasks 

include:

• Collect field data accurately as described in 

the SOPs

• Identify plants accurately and/or process 

unknown plants for later identification

• Enter data accurately into the project 

database either in the field or from paper 

data sheets

• Ensure all necessary equipment is 

assembled, clean and functional prior to 

each trip

5.1.5	 Botanist

A botanist will be contracted as needed to either work with the teams during the training 

session or to revisit plots established by the 

crews to verify identifications. The Botanist 

should have an expert knowledge of the midAtlantic region flora.

5.2 Training Procedures

A one-week training session is conducted in 

mid-May to review SOPs and practice establishment of forest monitoring plots (SOP 1: 

Preparation and equipment). Training should 

address health and safety concerns and emergency procedures. We also recommend that the 

network ecologist or data manager work with 

the field crew during the first full week following training.

Category Expense ($)

Seasonal staff 25,000

Travel 10,000

Vehicle 4,000

Equipment 5,000

Supplies 1,000

Total 45,000

Table 6. Annual budget for 

implementing the MIDN 

Forest Vegetation Monitoring 

Protocol. Figures are based on 

expenses incurred during the 

2008 field season.

007. 

6 Operational Requirements

6.1 Annual Workload and Field 

Schedule

Field work is conducted between mid-May and 

the end of September. If the field crew is hired 

with the NETN where two teams (crew leader 

and three technicians) implement the field 

work, then the first half of the season (mid-May 

to the end of July) will be spent in NETN parks, 

and the remaining two months is spent in the 

MIDN parks. 

6.2 Facility and Equipment Needs

The field crew is based at Fredericksburg and 

Spotsylvania NMP in Virginia. Whenever possible while traveling to the parks, the crew will 

stay in park housing. Where park housing is not 

available, the field crew will stay at hotels. All 

equipment needed to conduct the field work is 

in listed in SOP 1 (Preparation and equipment 

list). The crew leader is responsible for ensuring that all equipment is in working order and 

coordinating with the network staff to replenish supplies as needed.

6.3 Startup Costs and Budget 

Considerations

The startup costs are based on the costs associated with plot establishment in 2008. Costs 

include personnel, supplies, and travel. Additional costs will be incurred to replace or repair 

equipment including computers, GPS units, 

cameras, and the Laser Ace Rangefinder. These 

equipment costs are estimated over a five year 

replacement cycle.
12 National Park Service

Mid-Atlantic Network 

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Report NPS/NER/NRTR—2005/028, National 

Park Service, Philadelphia, PA.

Rantis, P. A. and J. E. Johnson. 1995. Forest management and the restoration of historic scenes. 

Technical report NPS/MARPPNBP/NRTR— 

95, National Park Service, Philadelphia, PA.

Rantis, P. A. and J. E. Johnson. 2002. Understory 

development in canopy gaps of pine and pinehardwood forests of the upper Coastal Plain of 

Virginia. Plant Ecology 159(1):103-115.

Rutters, K. H., B. E. Law, R. C. Kucera, A. L. Gallant, R. L. DeVelice, and C. J. Palmer. 1992. 

A selection of forest condition indicators for 

monitoring. Environmental Monitoring and Assessment 20(1):21-33.

Sanders, S., S. E. Johnson, and D. M. Waller. 2008. 

Vegetation monitoring protocol: Great Lakes 

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National Park Service, Fort Collins, CO.

Schmit, J. P., G. Sanders, M. Lehman, and T. 

Paradis. 2009. National Capital Region Network 

long-term forest monitoring protocol. Natural 

Resource Report NPS/NCRN/NRR—2009/113, 

National Park Service, Fort Collins, CO.

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Introduced species policy, management, and 

future research needs. Frontiers in Ecology and 

the Environment 3(1):12-20.

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99(465):262.

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Classification and Mapping at Fredericksburg 
14 National Park Service

Mid-Atlantic Network 

and Spotsylvania National Military Park. Technical Report NPS/NER/NRTR—2008/126, 

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A. Kozlowski, and D. Faber-Langendoen. 2009. 

Long-term forest monitoring protocol and SOPs 

for the Northeast Temperate Network. Natural 

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National Park Service, Fort Collins, CO.

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forest: Ecology and wildlife conservation. 2nd 

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Appendix A

2009 A-1

1.1 Introduction

In developing the Mid-Atlantic Network 

(MIDN) Forest Monitoring Protocol, our first 

step was to determine the optimal number and 

size of plots given the limited resources available to the network. In particular, we realized 

that in order to establish plots in all network 

parks and be able to make inferences regarding 

the vegetation communities in each park would 

require a large number of plots – at least 300 

plots throughout the network. Thus in order 

to increase our number of sample plots we 

would likely need to sacrifice the size of each 

plot. Our major concern was whether smaller 

plots would allow us to detect meaningful levels of change among trees ≥ 10 cm in diameter 

(DBH).

The National Capital Region Network (NCRN) 

had completed one year of implementation 

(Schmit and Campbell 2007). Like the MIDN, 

many of the NCRN parks are small, cultural 

landscapes located in rapidly urbanizing environments of the Coastal Plain and Piedmont. 

National Capital Region Network staff provided MIDN with data from 100 forest plots. 

All trees with a DBH ≥ 10 cm in a 15-m radius 

circle were identified, measured, mapped, and 

tagged. 

1.2 Objective

For the pilot data analysis, MIDN wanted to 

evaluate how varying the number and size 

of plots affected the level of power to detect 

change. Our objectives were to: • Determine the optimal plot size • Determine the number of plots 

1.3 Methods

We used NCRN data collected in 2006 as part 

of the Forest Monitoring program’s first year 

of sampling (Schmit and Campbell 2007). Our 

major assumption was that the forest composition and structure in NCRN would be similar 

to that found in MIDN parks. The NCRN 

plots are circular with a 15-m radius (707 m

2

). 

MIDN was considering using 20 x 20 m square 

plots (400 m

2

) – 57% smaller area. In addition, 

NCRN would be implementing a total of 400 

plots over four years, while MIDN was considering implementing only 300 plots over four 

years.

The questions addressed • What is the potential decline in the effect 

size or minimum detectable change (MDC) 

for smaller plots compared to the NCRN 

circles?

•How does the MDC vary depending on 

the final number of plots established by 

MIDN?

•

How does MDC vary for tree density and 

basal area for the network and individual 

parks?

•

What species are lost from the study when 

smaller plots are used?

Because the trees in the 15-m circular plots 

were mapped, it was possible to isolate and 

analyze the data of those trees that occurred 

in a virtual 20 x 20 m area. Power curves were 

generated to determine the percent detectable 

change at different power levels with an alpha (α) level of 0.1, for each of the following total 

sample sizes: • 400 NCRN plots (15-m circular) • 400 square plots (20 x 20 m) – x 1 the 

number of NCRN plots

• 300 square plots (20 x 20 m) – x 0.75 the 

number of NCRN plots

• 200 square plots (20 x 20 m) – x 0.5 the 

number of NCRN plots

An evaluation of National Capital Region Network 

data to assist in developing the 

Mid-Atlantic Network sampling strategy 

James A. Comiskey

Ecologist, Mid-Atlantic Network 
A-2 National Park Service

Mid-Atlantic Network

1.4 Results

1.4.1	 All parks

The NCRN approach (400 circular plots) had 

more power than the smaller plots (20 x 20 m 

plots). The power to detect the same level of 

change declined as the sample size decreased 

from 400 to 200 square plots (Figure A. 1). Nevertheless, while the NCRN plots were able to 

detect a 4.9% change in tree basal area with a 

power of 0.8, the 300 square plots could detect 

a 6.0% change at the same power (Table A. 1). 

Likewise, NCRN plots could detect a 5.0% 

change in tree density compared to a 6.1% 

change with 300 square plots. 

1.4.2	 Manassas NBP

As the total number of plots sampled decreased, the level of change detected with a 

power of 0.8 declined. We analyzed the results 

for Manassas NBP (MANA), a park that presents many similarities to the MIDN parks. Six 

plots were sampled by NCRN in the first year, 

and our analyses assume the same number of 

plots would be sampled each year for a total of 

24 plots. The analyses for the square plots were 

conducted based on 24 plots, 18 plots (threequarters of the total) or 12 plots (half the total). 

Again, the smaller size and decreasing total 

number of plots resulted in a decline in the detectable effect size (Figure A. 2). For basal area 

at a power of 0.8, NCRN plots would detect 

17.4% change while 18 square plots would only 

detect a 30.1% change (Figure A. 2). Likewise, 

NCRN plots would detect a 23.6% change in 

tree density while the 18 square plots would 

detect a 31.5% change.

1.4.3	 Catoctin MP

Interestingly, the lower number of smaller 

plots did not always result in a lower power 

to detect change, as was observed in Catoctin 

MP (CATO) (Figure A. 3). Both for basal area 

Basal Area Density

Square Plot Square Plot

NCRN x 1 x 0.75 x 0.50 NCRN x 1 x 0.75 x 0.50

All Parks 4.9% 5.2% 6.0% 7.3% 5.0% 5.3% 6.1% 7.5%

Manassas NB 17.4% 25.8% 30.1% 37.9% 23.6% 27.0% 31.5% 39.6%

Catoctin MP 14.9% 11.4% 13.3% 16.6% 15.7% 13.9% 16.2% 20.3%

Species 28.8% 28.0% 32.3% 39.7% 24.1% 23.5% 27.2% 33.4%

All Parks - Basal Area

α = 0.1

% Effect Size

0 2 4 6 8 10 12

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

All parks - Density

α = 0.1

% Effect Size

0 2 4 6 8 10 12

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

NCRN x 400 plots

 x 400 plots

 x 300 plots

 x 200 plots

NCRN x 400 plots

 x 400 plots

 x 300 plots

 x 200 plots

Table A. 1. Percent change in basal area and density of trees ≥ 10 DBH occurring in NCRN plots in 2006. The NCRN plot 

consists of a 15-m radius circular plot. The square plots are 20 x 20 m in size. Results for square plots are based on the 

same number as the NCRN or a multiple of that number (indicated in the column header).

Figure A. 1. Percent detectable 

change using different size and 

number of plots throughout the 

National Capital Region Network. 

Analyses are based on trees ≥ 10 

cm dbh collected in circular NCRN 

plots and sub-sampled to smaller 

square plots (1x, 0.75x, and 0.5x 

the NCRN plots). α = 0.1.
2009 A-3

Forest Vegetation Monitoring Protocol

and density, the same number of smaller plots 

were more effective at detecting change than 

the NCBN plots (basal area change of 11.4% 

for square versus 14.9% for NCBN at a power 

of 0.8; density change of 13.9% versus 15.7% 

respectively) (Figure A. 3). In fact for basal 

area, 21 square plots had more power than 28 

NCRN plots (13.3% versus 14.9%). A closer 

evaluation of the data revealed that the larger 

NCRN plots were detecting higher variability 

than the smaller plots. Though the ecological 

and cultural setting of CATO is not directly 

comparable to the MIDN parks, it does illustrate that the variability can vary significantly 

from one park to the next even at small spatial 

scales.

1.4.4	 Species across network

A similar analysis was conducted to evaluate 

the power to detect changes in species density 

and basal area. The same number of NCRN 

plots and the smaller square plots had similar 

abilities to detect change at the same power (α

= 0.1. Figure A. 4). For basal area, NCRN plots 

detected a 28.8% change while the smaller 

plots detected 28.0% (Figure A. 4). For tree 

density the change detected was 24.1% and 

23.5% respectively.

1.4.5	 Changes in species density

The power the detect changes in density of 

individual species was generally low, and decreased with plot size and number (Table A. 2). 

Only among the most common species such 

as Quercus alba, Quercus rubra, Liriodendron 

tulipifera, Nyssa sylvatica, Acer rubrum, Fagus 

grandifolia, and Carya tomentosa were detectable levels below 25% for the NCRN plots. 

1.4.6	 Loss of species

One area of concern when using smaller plots 

is what would be missed. In particular, are 

there any species sampled in the larger NCRN 

plot that would have been lost if only a 20 x 20 

m square plot had been sampled. In fact, this 

was the case, with five species being lost entirely from the network, including Amelanchier 

arborea, Amelanchier canadensis, Broussonetia 

papyrifera, Ulmus americana, and Viburnum 

prunifolium. An additional 17 species were lost 

from individual parks (Table A. 3).

1.5 Discussion

The analyses were conducted with the less 

conservative α level of 0.1, primarily to increase 

our power to detect a lower level of change and 

reduce the size and number of plots needed. 

Manassas - Basal Area

α = 0.1

% Effect Size

0 10 20 30 40 50 60 70

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

NCRN x 24 plots

 x 24 plots

 x 18 plots

 x 12 plots

Manassas - Density

α = 0.1

% Effect Size

0 10 20 30 40 50 60 70

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

NCRN x 24 plots

 x 18 plots

 x 12 plots

 x 24 plots

The higher α does increase our chance of detecting a change when none occurred (Type I 

or false change error), but does err on the side 

of caution – we are less likely to miss a change 

when one really did occur. In addition, the 

analyses were based on spatial variability which 

is likely to be greater than temporal variability, 

and therefore the results may be conservative.

In general, the larger NCRN plots detected 

lower levels of change than the equivalent 

number of smaller square plots. Decreasing the 

total number of square plots from 400 to 300 

and 200 further decreased their ability to detect 

change. However, for the same number of plots, 

the decrease in plot size by 57% accounted for 

decline in the detectable change in the density 

and basal area of trees of between 1 and 8%. In 

fact, in some instances (at CATO) the smaller 

plots had a greater power to detect change due 

to lower variability in the data. 

Detecting change in the number of individuals of a given species across the network was 

generally low. Only the most common species 

provided the ability to detect changes of beFigure A. 2. Percent 

detectable change using 

different size and number of 

plots at Manassas National 

Battlefield Park, VA. Analyses 

are based on trees ≥ 10 cm 

dbh collected in circular 

NCRN plots and sub-sampled 

to smaller square plots (1x, 

0.75x, and 0.5x the NCRN 

plots). α = 0.1.
A-4 National Park Service

Mid-Atlantic Network

tween 10 and 25% for the NCRN plots. The 

level detected for smalller and fewer plots was 

generally higher. Given the small sample sizes, 

detecting changes in species densities in any 

given park is unlikely to be possible with a high 

degree of confidence.

1.6 Conclusion

Based on these results, the MIDN has decided 

to establish smaller plots, 20 x 20 m plots and to 

also establish a smaller number across the network (300). Clearly this will reduce the power 

to detect change, but is based on the networks 

current staffing and funding level. Once all 300 

plots have been established, recensus of these 

plots will be initiated. At that time it may be 

possible to increase the number of plots by 

establishing new ones, and thus increasing the 

protocols power. 

% Effect Size

0 5 10 15 20 25 30

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Catoctin - Basal Area

α = 0.1

% Effect Size

0 5 10 15 20 25 30 35

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Catoctin - Density

α = 0.1

NCRN x 28 plots

 x 28 plots

 x 21 plots

 x 14 plots

 x 14 plots

NCRN x 28 plots

 x 28 plots

 x 21 plots

Figure A. 3. Percent detectable 

change using different size 

and number of plots at 

Catoctin Mountain Park, MD. 

Analyses are based on trees ≥ 

10 cm dbh collected in circular 

NCRN plots and sub-sampled 

to smaller square plots (1x, 

0.75x, and 0.5x the NCRN 

plots). α = 0.1.

1.7 Literature Cited

Schmit, J. and P. Campbell. 2007. National Capital Region Network 2006 Forest Vegetation 

Monitoring Report. Natural Resource Report 

NPS/NCRN/NRTR—2007/046. National Park 

Service, Fort Collins, Colorado. 
2009 A-5

Forest Vegetation Monitoring Protocol

Species - Density

α = 0.1

% Effect Size

0 10 20 30 40 50 60

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Species - Basal Area

α = 0.1

% Effect Size

0 10 20 30 40 50 60 70

Power

0.0

0.2

0.4

0.6

0.8

1.0

1.2

NCRN x 400 plots

 x 400 plots

 x 300 plots

 x 200 plots

NCRN x 400 plots

 x 400 plots

 x 300 plots

 x 200 plots

Figure A. 4. Percent 

detectable change using 

different size and number of 

plots in the National Capital 

Region Network. Analyses 

are based on trees ≥ 10 cm 

dbh collected in circular 

NCRN plots and sub-sampled 

to smaller square plots (1x, 

0.75x, and 0.5x the NCRN 

plots). α = 0.1.
A-6 National Park Service

Mid-Atlantic Network

Table A. 2. Percent change in density for species occurring in NCRN plots in 2006. The NCRN plot 

consists of a 15-m radius circular plot. The square plots are 20 x 20 m in size. Results for square plots 

are based on the same number as the NCRN or a multiple of that number.

Square Plot

Species NCRN x1 x 0.75 x 0.50

Acer negundo 36.7% 35.7% 41.2% 50.6%

Acer rubrum 21.4% 24.2% 27.9% 34.2%

Acer saccharinum 50.2% 57.8% 66.8% 81.9%

Acer saccharum 73.8% 69.6% 80.5% 98.7%

Ailanthus altissima 47.0% 45.6% 52.7% 64.6%

Carya glabra 30.2% 28.7% 33.2% 40.7%

Carya tomentosa 22.2% 25.5% 29.4% 36.1%

Celtis occidentalis 45.1% 47.2% 54.6% 66.9%

Cornus florida 50.6% 71.2% 82.2% 100.9%

Fagus grandifolia 23.7% 24.3% 28.1% 34.5%

Fraxinus americana 41.1% 37.4% 43.2% 52.9%

Fraxinus pennsylvanica 43.1% 47.7% 55.2% 67.7%

Ilex opaca 29.5% 31.8% 36.8% 45.1%

Juglans nigra 43.7% 52.1% 60.2% 73.9%

Juniperus virginiana 53.2% 50.6% 58.5% 71.7%

Liquidambar styraciflua 45.1% 46.5% 53.8% 65.9%

Liriodendron tulipifera 17.7% 19.1% 22.1% 27.1%

Nyssa sylvatica 19.3% 22.0% 25.4% 31.1%

Pinus taeda 71.2% 87.6% 101.2% 124.2%

Pinus virginiana 32.3% 31.3% 36.1% 44.3%

Prunus serotina 47.3% 48.6% 56.2% 68.9%

Quercus alba 19.5% 22.6% 26.1% 32.0%

Quercus coccinea 29.2% 28.5% 32.9% 40.4%

Quercus montana 36.7% 37.6% 43.4% 53.2%

Quercus rubra 24.5% 25.3% 29.2% 35.8%

Quercus stellata 50.0% 61.3% 70.9% 86.9%

Ulmus rubra 32.5% 33.8% 39.1% 48.0%
2009 A-7

Forest Vegetation Monitoring Protocol

Species lost from Study ANTI 

(1)

CATO 

(7)

CHOH 

(23)

GWMP 

(6)

HAFE 

(7)

MANA 

(6)

MONO 

(6)

NACE 

(9)

PRWI 

(35)

ROCR 

(3)

WOTR 

(1)

Amelanchier arborea     x              

Amelanchier canadensis       x            

Broussonetia papyrifera         x          

Ulmus americana                   x

Viburnum prunifolium           x        

Species lost from park ANTI 

(1)

CATO 

(7)

CHOH 

(23)

GWMP 

(6)

HAFE 

(7)

MANA 

(6)

MONO 

(6)

NACE 

(9)

PRWI 

(35)

ROCR 

(3)

WOTR 

(1)

Acer saccharinum               x    

Acer saccharum                 x  

Ailanthus altissima             x      

Amelanchier laevis                   x

Betula lenta     x              

Cercis canadensis         x          

Cornus florida                   x

Fagus grandifolia         x          

Fraxinus pennsylvanica       x            

Pinus virginiana         x          

Platanus occidentalis         x          

Platanus occidentalis           x        

Quercus alba               x    

Quercus palustris         x          

Quercus stellata         x     x    

Tilia americana     x   x          

Ulmus rubra       x            

1

 Parks sampled:

ANTI Antietam National Battlefield

CATO Catoctin Mountain Park

CHOH Chesapeake & Ohio Canal National Historical Park

GWMP George Washington Memorial Parkway 

HAFE Harpers Ferry National Historical Park

MANA Manassas National Battlefield Park

MONO Monocacy National Battlefield

NACE National Capital Parks-East

PRWI Prince William Forest Park 

ROCR Rock Creek Park 

WOTR Wolf Trap National Park for the Performing Arts

Table A. 3. Species lost from study or individual parks when a smaller plot is used. Columns show parks1

 where species are lost, with the total 

number of plots sampled in parentheses.
Mid-Atlantic Network
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