- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Volume 2012 (2012), Article ID 384892, 13 pages
A Habitat-Based Framework for Communicating Natural Resource Condition
1Integration and Application Network, University of Maryland Center for Environmental Science, P.O. Box 775, Cambridge, MD 21613, USA
2US Geological Survey, National Climate Change & Wildlife Science Center, Reston, VA 20192, USA
3Department of Geography and the Environment, University of Richmond, 28 Westhampton Way, Richmond, VA 23173, USA
Received 8 December 2011; Accepted 7 January 2012
Academic Editors: D. Gerten and D. Sánchez-Fernández
Copyright © 2012 Tim J. B. Carruthers et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Progress in achieving desired environmental outcomes needs to be rigorously measured and reported for effective environmental management. Two major challenges in achieving this are, firstly, how to synthesize monitoring data in a meaningful way at appropriate temporal and spatial scales and, secondly, how to present results in a framework that allows for effective communication to resource managers and scientists as well as a broader general audience. This paper presents a habitat framework, developed to assess the natural resource condition of the urban Rock Creek Park (Washington, DC, USA), providing insight on how to improve future assessments. Vegetation and stream GIS layers were used to classify three dominant habitat types, Forest, Wetland, and Artificial-terrestrial. Within Rock Creek Park, Forest habitats were assessed as being in good condition (67% threshold attainment of desired condition), Wetland habitats to be in fair condition (49% attainment), and Artificial-terrestrial habitats to be in degraded condition (26% attainment), resulting in an assessed fair/good condition (60% attainment; weighted by habitat area) for all natural resources in Rock Creek Park. This approach has potential to provide assessment of resource condition for diverse ecosystems and provides a basis for addressing management questions across multiple spatial scales.
One of the key challenges of large-scale monitoring programs is to develop integrated and synthetic data products that can translate a multitude of diverse data into a format that can be readily communicated to decision-makers, policy developers, and the public [1–3]. Such timely syntheses of ecosystem condition can provide feedback to managers and stakeholders, so that the effectiveness of management actions as well as future management goals can be determined at multiple scales .
1.1. Integrative Indices and Report Cards
One approach to synthesizing data has been the development of multimetric indices to summarize the status of a community, such as stream fish, and then draw inferences on the status of the supporting ecosystem . Metrics such as the fish index of biotic integrity (FIBI) and the benthic IBI have been widely applied, both internationally and regionally (e.g., streams in Maryland, USA). IBI metrics are seen as providing greater insight into ecosystem condition than physical measurements (e.g., water quality) alone, as biological communities provide an integrated summary of ecosystem condition over time [6–8]. However, in the absence of a rigorous process for integrating data on diverse biotic communities and other ecosystem components and for communicating results to decision-makers, these indices and bioindicators have had limited effectiveness in improving ecosystem management .
Environmental score cards or report cards are seen as an important tool for this type of integrated assessment, to move beyond simply identifying ecosystem change and on to applying monitoring data to ecosystem management [10, 11]. In some cases, assessments of multiple metrics using threshold-based environmental report cards have been used to compare estuaries at broad spatial scales [12–15]. At the local level, however, most environmental assessments still tend to focus on a few, specific resources rather than providing an integrated overview of site conditions.
1.2. Consideration of Scale in Integrated Assessments
An important consideration in determining the appropriate spatial and temporal scale of an integrated assessment is identifying the characteristic scales of variability in the ecological resources, as well as in the potential stressors to those resources.
Environmental processes typically show a direct relationship between temporal and spatial scales, with fine-scale spatial processes happening rapidly and broad-scale processes happening slowly [16, 17]. Many stressors also follow this pattern, with local impacts such as point-source inputs being short term and concentrated in small areas while global impacts such as climate change occur slowly over large spatial scales  (Figure 1). Less intuitive, and more difficult to measure, are shifting baselines such as nutrient increases, where gradual changes occur at even small spatial scales  and extreme events such as hurricanes where stressors can impact large areas in a very short period of time (Figure 1). In some cases, the aggregation of multiple small-scale stressors can also produce larger-scale impacts (Figure 1). Time versus space plots (Stommel diagrams) have been used extensively [17, 20] to illustrate these scaling relationships for different organisms and processes in oceanic  and terrestrial  environments.
1.3. Monitoring Data Collected at Multiple Scales
Integrative monitoring programs typically collect data on different variables at a variety of spatial and temporal scales. The spatial scale of measurement is important to consider for effectively combining metrics into integrated assessments of resource condition. A large number of metrics can be measured over small spatial scales for relatively little expense (e.g., biodiversity and water quality), so it is often useful to aggregate these metrics to get a more stable measure of condition (Figure 2). Aggregation can be accomplished by the mathematical combination of multiple metrics, for example, into a water quality index [22, 23] or the benthic index of biotic integrity (BIBI) . Metrics providing information at very large spatial scales are often considered individually within an integrated assessment because they are typically more difficult or costly to obtain or represent one number for a large area such as percent impervious surface  (Figure 2).
The temporal scale of metric measurement is also important to consider for data synthesis. Metrics that change over short temporal scales can be measured at high frequency, although interpreting the high data variance can be challenging; in one example, rolling averages have been developed for ozone . For metrics related to long-term trends, measures of central tendency are often suitable; long-term monitoring of land cover change often relies on key spatial pattern indices such as mean patch size, for example . Matching the scale of observation to the scale of environmental change remains a central challenge in ecology . Not only careful metric selection but also a strong framework to integrate diverse metrics, collected at different spatial and temporal scales, can assist in the interpretation of trends in natural resource condition and explanation of linkages between condition and diverse stressors.
The aim of this study was to integrate a series of available monitoring metrics to assess the current resource condition of habitats within Rock Creek Park and to identify ways to improve future assessments of resource condition.
2.1. Study Site
Rock Creek Park is located on approximately 710 hectares in the District of Columbia, USA, at the downstream end of a highly urban and continually developing Piedmont river valley . The Park was established in 1890 at a significant time in the development of what would later become the National Park System. As a result, the protective prescription for the Park called for regulations to “provide for the preservation from injury or spoliation (plundering) of all timber, animals, or curiosities within said park, and their retention in their natural condition, as nearly as possible” [30, 31]. Therefore, determination of key habitats and assessment of resource condition is particularly relevant to the management of Rock Creek Park, a unit within the National Park Service.
2.2. Determination of Assessment Scale
The first step in the assessment process was to identify the spatial and temporal scale for assessment. Relevant scales for integrated assessments of natural resource condition may vary from 100s of meters, for example, within a managed land such as a national park or between subwatersheds, to 1000s of kilometers, for regional or even global-scale comparisons. Different data and approaches have been applied at these different scales [22, 32, 33]. In consultation with Park management staff, the assessment scales were determined based on potential management questions and interpretation as well as data availability. The spatial extent for the assessment was established as the current Park boundary (classified as the Fee Boundary) and the temporal extent is an eight-year period from 2000 to 2008.
2.3. Identification of Habitats
Many ecological classification systems exist, based on such features as vegetation communities [34, 35] or land cover . In the current assessment, a classification defined by the International Union for the Conservation of Nature (IUCN) was used, to facilitate potential comparisons to other ecological systems . The IUCN habitat classification includes 16 habitat types at the highest level, including both terrestrial and aquatic habitats, desert, forest, and subterranean cave habitats.
To determine the habitat types present within Rock Creek Park, a classified vegetation base map, from the National Capital Region (NCR) Inventory and Monitoring Program (I&M), was aggregated into general habitat types: beach/mixed oak, beach/tulip poplar, beach/white oak, chestnut oak, loblolly pine/mixed oak, tulip poplar, Virginia pine/oak, and sycamore/green ash were classified as “Forest habitat”; streams, seeps, and springs were classified as “Wetland (inland) habitat”; and canopy gap, meadow, mowed lawn, and mowed lawn with trees and shrubs were classified as “Artificial-terrestrial habitat”. Although discussions with resource managers originally determined a longer list of habitats (e.g., multiple forest types), available data density did not allow assessment at this level of precision, so the higher level habitat classification (three habitats) was used for condition assessment calculations.
2.4. Selection of Metrics
Within the habitat assessment framework, metrics were chosen to establish a definition of the conceptual range of habitat condition, from desired to degraded, which were applicable to management goals and objectives (Figure 3). Data were obtained from multiple sources: National Park Service (NPS) Inventory and Monitoring (I&M) Program, Montgomery County (Maryland, USA), US Environmental Protection Agency, and the National Atmospheric Deposition Program (Table 1). All metrics are used within the NPS I&M program and hence have been through a stringent process of protocol development as well as careful assessment for responsiveness to ecosystem changes . Seven metrics were used to assess each habitat and two metrics (deer population and percentage of impervious surface) were used in the assessment of both Forest and Artificial-terrestrial habitats, resulting in a total of 19 separate data sets. Data used for the assessment of Rock Creek Park were collected between 2000 and 2008, with data density ranging from one park-level value at one time (e.g., impervious surface, critical connectivity) to 241 total measurements (e.g., dissolved oxygen, monthly measures from 13 sites) (Table 2).
Five of the indicators used to assess ecosystem condition of Forest habitats were measures of biodiversity, with two indicators of ecosystem processes (Figures 2 and 3). Of the seven indicators, three are relevant to the measurement of the quality of a resource within Forest habitats (presence of forest interior dwelling birds, native seedling regeneration, connectivity), while the remaining four (exotic tree/shrub density, presence of pest species, deer density, impervious surface) measure stressors that are likely to directly impact Forest habitats.
Six of the seven indicators used to assess condition of Wetlands habitats were water quality indicators: three indicators of stressors (total phosphorus, salinity, aqueous nitrate) and three indicators of habitat quality for aquatic fauna (dissolved oxygen, benthic IBI, physical habitat index). The remaining indicator (proportion of area occupied by adult amphibians) is a measure of biodiversity and provides information regarding the ecosystem resource value of the habitat. Assessment of Artificial-terrestrial habitat condition was based on indicators in three categories: biodiversity (deer density), ecosystem processes (impervious surface), and air quality (soot, ozone, sulfate deposition, nitrate deposition, mercury deposition) (Figure 2, Table 2).
Recognizing that air quality indicators could be used for any habitat, particularly any terrestrial habitat, they were considered particularly appropriate for use in the predominantly mowed grass characterizing Artificial-terrestrial habitat within Rock Creek Park (Figure 2, Table 2). These open vistas rely most heavily on the resource of high visibility and are likely to be more directly impacted in terms of plant health by high ozone, due to plants being more exposed in open grassland than a closed forest. Wet deposition of sulfate, nitrate, and mercury is more likely to have a negative impact in open areas where transport rate to groundwater and creeks will be greater than areas such as forest where more rainfall is intercepted by plant canopies and where there is greater plant biomass to reabsorb nutrients from soils.
2.5. Definition of Thresholds and Calculation of Condition Assessment
To assess the natural resource condition of Rock Creek Park, thresholds were established for the 19 separate metrics using scientific literature, management goals, regulations, and professional judgment where necessary (Table 2).
In nearly all cases these thresholds were justified ecologically by the scientific literature, even though many of them were set as either management or regulatory thresholds (Table 2). For the seven metrics identified to assess each habitat, data were compared to these threshold values. The percentage of sites and times attaining the threshold value for each metric was calculated, where a value of 100 indicated that all sampling sites and times met the threshold to maintain natural resources (desired condition), and a value of zero indicated that no sites at any sampling time met the threshold value (degraded). The attainment of threshold condition for each of the three habitat types present within Rock Creek Park was calculated as an unweighted mean of the attainment scores for the seven metrics used to assess the condition of that particular habitat. Calculation of the park condition status was calculated as an area-weighted mean, based upon the relative area of each habitat type within Rock Creek Park. For determination of status of metrics, habitats, and the whole park assessment, percentage attainment scores were categorized on a uniform scale from very good (81–100% attainment) to very degraded (0–20% attainment).
Three habitats were defined within Rock Creek Park; Forest habitat making up 81% of the total area (575 ha), Wetland habitat 2% (14 ha), and Artificial-terrestrial habitat comprising the remaining 17% of Park area (121 ha) (Figure 4). Within the habitat assessment framework, the threshold attainment scores for individual metrics ranged from 0% attainment (very degraded) to 100% attainment (very good) (Table 3). The overall, area-weighted, habitat-based condition of Rock Creek Park, based on attainment of ecological threshold for 19 metrics, was assessed as fair to good (60% attainment; Table 3, Figure 5).
3.1. Forest Habitats
Forest habitats within Rock Creek Park were assessed to be in good condition (67% attainment of threshold condition; Table 3, Figure 5). These habitats had high deer populations of deer km−1 (mean ± standard error; 0% attainment) and low native seedling regeneration of seedlings ha−1 (0% attainment). However, the Park had generally low but highly variable exotic tree and shrub density (% of total basal area; 70% attainment), low impervious surface (5% of land surface impervious), and high forest patch connectivity, with the Park achieving critical connectivity (Dcrit), by assuming that patches within 340 m of one another are connected (100% attainment within the park). The Park also had low forest pest species (none observed) and diverse forest interior dwelling bird species (100% attainment).
3.2. Wetland Habitats
These habitats had a high total phosphorus concentration of μgL−1 (mean ± standard error; 0% attainment), a low benthic index of biotic integrity of (0% attainment), and high salinity (; 30% attainment) and nitrate concentration mgL−1 (46% attainment). The habitats had high dissolved oxygen of mgL−1 (87% attainment), physical habitat index (; 100% attainment), and proportion of area occupied (PAO) by adult amphibians (; 78% attainment).
3.3. Artificial-terrestrial Habitats
Artificial-terrestrial habitats within Rock Creek Park were assessed to be in degraded condition (26% attainment of threshold condition; Table 3, Figure 5). While these habitats had just 5% impervious surface within the park (100% attainment), they had degraded condition for NO3 deposition of kg ha−1 yr−1 (mean ± standard error; 40% attainment) and mg m−3 (PM2.5; 27% attainment), respectively, and highly degraded conditions for deer population with deer km−1 (12.5% attainment), ozone concentration ( ppm), wet SO4 deposition ( kg ha−1 yr−1), and mercury deposition ( ng L−1; all 0% attainment).
Effective ecosystem management relies on clear, synthetic communication of natural resource condition to managers, decision makers, and the interested public. The habitat framework developed for the assessment of natural resource condition in Rock Creek Park provides a framework for the synthesis of diverse metrics to allow integrated assessments at multiple spatial and temporal scales, presenting results in a readily understandable and communicable format.
4.1. Implications of Rock Creek Park Assessment
An overall fair/good assessment of natural resource condition for the entire Park (60% attainment of ecological threshold condition) reflected the large area of Forest habitat in good condition the relatively small area of Artificial-terrestrial habitat (mostly mowed grasslands) in degraded condition, and the very small area of wetland in fair condition (Table 3, Figure 5).
The assessment of Forest habitat within the Park was good; however, this habitat is clearly challenged by very high deer populations and low native seedling regeneration (Table 3, Figure 5), suggesting that the Forest is susceptible to further degradation. Species richness and abundance of herbs and shrubs have shown measurable reductions at densities as low as 3.7 deer km−2 and are consistently reduced as densities approach 8.0 deer km−2 . Densities of 10–17 deer km−2 inhibited the regeneration of understorey species in a large manipulation study, whereas a diverse understorey was supported at 3–6 deer km−2 . It is therefore likely that high deer populations recorded for Rock Creek Park (approximately 26 deer km−2) are related to the low native seedling regeneration (Table 3). Measurement of exotic tree and shrub density was highly variable (Table 3) with a mean value three times the threshold of 5% of total basal area, suggesting patchy but intense infestations. This metric was assessed from only three forest sampling plots (Table 2) and so increased spatial assessment would be valuable to more fully assess the potential impact of exotic plants on forest condition. Forest connectivity was close to the threshold (340 m measured, 360 m threshold; Table 3), suggesting that the Forest is susceptible to further fragmentation within the Park (by roads and trails, etc.), potentially reducing the habitat value for both flora and fauna.
High nutrient concentrations, depauperate benthic stream communities, and high salinity resulted in an assessment rating of fair for Wetland habitats within Rock Creek Park (Table 3). Nitrate concentration has been found to be negatively correlated to the integrity of benthic communities , and the statewide mean nitrate concentration of 2.45 mg L−1 is lower than the mean of mg L−1 measured within Rock Creek Park. Rock Creek watershed is also highly urbanized and the integrity of benthic communities has previously been correlated negatively to urbanization within the surrounding watershed . Salinity in Rock Creek and tributaries was greater than 0.25 g L−1 in 70% of samples, with salinities reported as high as 1.7 g L−1 during winter, when road salting occurs . Although short-term exposure (96 hrs) to salinities as high as 10 g L−1 has been found to have little effect on individuals of multiple macro-invertebrate species , many studies have reported biotic degradation or species loss and promotion of exotic species at salinities greater than 1.0–1.4 g L−1 [85, 86]. There has been a regional (Maryland, USA) increase in salinity over the past 30 years , so salinity has high potential to pose an increasing threat to the water quality in Rock Creek, with its highly urbanized watershed.
The degraded assessment for Artificial-terrestrial habitats within the Park resulted from the desired condition being largely based on air quality (Figure 3), with all five metrics of air quality having very low threshold attainment (Table 3). This raises the issue of how to define desired condition, especially for altered habitats that still have ecosystem values. In this case, for example, the Artificial-terrestrial habitats are mostly mowed grasslands—but with best management they could contain meadow areas habitat for insects and buffer areas along streamlines to limit nutrient inputs. This indicates a data gap, as no metrics are currently monitored to address changes in native meadow to mowed grass or extent of these data, which would allow an improved assessment of the natural resource condition of Artificial-terrestrial habitats, atmospheric metrics, which indicate more regional challenges.
4.2. A Habitat Framework Can Assist in the Assessment Process
Scientific understanding of ecosystem processes is often limited to the temporal and spatial scales of the research, requiring clear frameworks to facilitate translation of understanding across scales and application by decision-makers and managers . Assessments of ecosystem status are increasingly being recognized for their value to direct and assess management actions [3, 4]. However, as the spatial scale of impacts becomes larger (e.g., air quality and climate change), the challenge is to develop frameworks that will allow comparison between different locations, or management units, as well as across spatial and temporal scales.
The condition and trend of natural resources can be evaluated over multiple temporal and spatial scales (Figure 1). Global  and national  level assessments have long been a focus of attention and regional level assessments have become increasingly prominent [23, 91]. At the local level, however, most environmental assessments still tend to focus on a few, specific resources rather than providing an integrated overview of site conditions. The most common framework for conducting ecosystem assessments is a geographic basis, for example, estuaries along a coastline  or regions within a larger system . This is ideal when the different regions can be measured with the same metrics and are essentially similar (e.g., all temperate forest, all estuarine habitats, etc.). However, when disparate comparisons are requested (e.g., tropical and temperate estuaries, coastal and mountain landscapes), different ecological drivers may be present and the various communities may interact differently. One approach to dealing with this variability is to assess on a species by species basis; careful choice of indicator species can provide valid assessments of some aspects of an ecosystem . However, an indicator species approach is limited to the range of the particular organism or organisms . To understand, assess, and manage natural resources undergoing change requires a synthetic approach that looks across spatiotemporal scales and associated organizational levels [95, 96]. Hierarchical classification systems for forests  and streams  have been specifically designed to allow integration of data for broader level assessments. However, forests are not always accurately described by an accounting of individual trees and large basins are not simply a sum of smaller catchments , and the presented habitat framework has the potential to effectively bridge these hierarchies of scale.
Pat Campbell, John-Paul Schmit, Marion Norris, Geoff Sanders, and Jeff Runde (CUE/NPS) as well as Sara Stevens (NCBN/NPS), Elizabeth Johnson (NER/NPS), and NCRN park managers provided helpful comments and discussion in the development of these ideas. Staff at Rock Creek Park provided insightful comments and input. Jeff Runde assisted with GIS data synthesis. Funding was facilitated through the Chesapeake Watershed CESU. UMCES contribution number is 4611.
- J. R. Karr and E. W. Chu, “Biological monitoring and assessment: using multimetric indexes effectively,” EPA 235-R97-001, University of Washington, Seattle, Wash, USA, 1997.
- M. A. Harwell, V. Myers, T. Young et al., “A framework for an ecosystem integrity report card: examples from south Florida show how an ecosystem report card links societal values and scientific information,” BioScience, vol. 49, no. 7, pp. 543–556, 1999.
- S. G. Fancy, J. E. Gross, and S. L. Carter, “Monitoring the condition of natural resources in US national parks,” Environmental Monitoring and Assessment, vol. 151, no. 1–4, pp. 161–174, 2008.
- W. C. Dennison, T. R. Lookingbill, T. J. B. Carruthers, J. M. Hawkey, and S. L. Carter, “An eye-opening approach to developing and communicating integrated environmental assessments,” Frontiers in Ecology and the Environment, vol. 5, no. 6, pp. 307–314, 2007.
- J. R. Karr, “Assessment of biotic integrity using fish communities,” Fisheries, vol. 6, no. 6, pp. 21–27, 1981.
- N. Roth, M. Southerland, J. Chaillou et al., “Maryland biological stream survey: development of a fish index of biotic integrity,” Environmental Monitoring and Assessment, vol. 51, no. 1-2, pp. 89–106, 1998.
- N. E. Roth, M. T. Southerland, J. C. Chaillou, P. F. Kazyak, and S. A. Stanko, “Refinement and validation of a fish index of biotic integrity for Maryland streams,” Chesapeake Bay and Watershed Programs: Monitoring and Non-Tidal Assessment CBWP-MANTA-EA-00, 2000.
- T. D. Harrison and A. K. Whitfield, “A multi-metric fish index to assess the environmental condition of estuaries,” Journal of Fish Biology, vol. 65, no. 3, pp. 683–710, 2004.
- S. L. Carter, G. Mora-Bourgeois, T. R. Lookingbill, T. J. B. Carruthers, and W. C. Dennison, “The challenge of communicating monitoring results to effect change,” The George Wright Forum, vol. 24, no. 2, pp. 48–58, 2007.
- U. S. EPA, “Mid-atlantic highland streams assessment,” Tech. Rep. EPA903/R-00/015, U.S. Environmental Protection Agency Region 3, Philadelphia, Pa, USA, 2000.
- U. S. EPA, “A framework for assessing and reporting on ecological condition: an SAB Report,” Tech. Rep. EPA-SAB-EPEC-02-009, Environmental Protection Agency, Science Advisory Board, Washington, DC, USA, 2002.
- J. G. Ferreira, “Development of an estuarine quality index based on key physical and biogeochemical features,” Ocean and Coastal Management, vol. 43, no. 1, pp. 99–122, 2000.
- J. A. Kiddon, J. F. Paul, H. W. Buffum et al., “Ecological condition of US Mid-Atlantic estuaries, 1997-1998,” Marine Pollution Bulletin, vol. 46, no. 10, pp. 1224–1244, 2003.
- L. Turner, D. Tracey, J. Tilden, and W. C. Dennison, Where River Meets Sea: Exploring Australia's Estuaries, Cooperative Research Centre for Coastal Zone, Estuary and Waterways Management, Brisbane, Australia, 2004.
- S. B. Bricker, B. Longstaff, W. Dennison et al., “Effects of nutrient enrichment in the nation's estuaries: a decade of change,” Harmful Algae, vol. 8, no. 1, pp. 21–32, 2008.
- H. R. Delcourt and P. A. Delcourt, “Quaternary landscape ecology: relevant scales in space and time,” Landscape Ecology, vol. 2, no. 1, pp. 23–44, 1988.
- D. C. Schneider, “The rise of the concept of scale in ecology,” BioScience, vol. 51, no. 7, pp. 545–553, 2001.
- D. F. Boesch, “Global Warming and the Free State: Comprehensive Assessment of Climate Change Impacts in Maryland,” Report of the Scientific and Technical Working Group of the Maryland Commission on Climate Change, University of Maryland Center for Environmental Science, Cambridge, Mass, USA, 2008.
- N. Knowlton and J. B. C. Jackson, “Shifting baselines, local impacts, and global change on coral reefs,” PLoS Biology, vol. 6, no. 2, article e54, 2008.
- H. Stommel, “Varieties of oceanographic experience,” Science, vol. 139, no. 3555, pp. 572–576, 1963.
- J. H. Steele, “The ocean ‘landscape’,” Landscape Ecology, vol. 3, no. 3-4, pp. 185–192, 1989.
- C. E. Wazniak, M. R. Hall, T. J. B. Carruthers, B. Sturgis, W. C. Dennison, and R. J. Orth, “Linking water quality to living resources in a mid-atlantic lagoon system, USA,” Ecological Applications, vol. 17, no. 5, pp. S64–S78, 2007.
- M. Williams, B. Longstaff, R. Llanso, C. Buchanan, and W. C. Dennison, “Development and evaluation of a spatially-explicit index of Chesapeake Bay health,” Marine Pollution Bulletin, vol. 59, no. 1–3, pp. 14–25, 2009.
- N. E. Roth, M.T. Southerland, G. Mercurio, et al., “State of the streams: 1995–1997 maryland biological stream survey results,” Tech. Rep. CBWP-MANTA-EA-99-6, Chesapeake Bay and Watershed Programs, Monitoring and Non-Tidal Assessment, 1999.
- C. L. Arnold Jr. and C. J. Gibbons, “Impervious surface coverage: the emergence of a key environmental indicator,” Journal of the American Planning Association, vol. 62, no. 2, pp. 243–269, 1996.
- U. S. EPA, The Clean Air Act. Washington United States Environmental Protection Agency, Washington DC, USA, 2004, http://epw.senate.gov/envlaws/cleanair.pdf.
- P. A. Townsend, T. R. Lookingbill, C. C. Kingdon, and R. H. Gardner, “Spatial pattern analysis for monitoring protected areas,” Remote Sensing of Environment, vol. 113, no. 7, pp. 1410–1420, 2009.
- S. A. Levin, “The problem of pattern and scale in ecology,” Ecology, vol. 73, no. 6, pp. 1943–1967, 1992.
- T. J. B. Carruthers, L. Carter, L. Florkowski, J. Runde, and W. Dennison, “Rock creek natural resource condition assessment,” Natural Resource Report NPS/NCRN/NRR – 2009/109, National Park Service, Fort Collins, Colo, USA, 2009.
- B. Mackintosh, Rock Creek Park: An Administrative History, United States Department of the Interior, National Park Service, Washington, DC, USA, 1985.
- “An act authorizing the establishing of a public park in the District of Columbia,” in Proceedings of the 51st United States Congress, September 1890, Ch. 1001, 26 Stat 492.
- R. P. Brooks, T. J. O'Connell, D. H. Wardrop, and L. E. Jackson, “Towards a regional index of biological integrity: the example of forested riparian ecosystems,” Environmental Monitoring and Assessment, vol. 51, no. 1-2, pp. 131–143, 1998.
- Y. Ding, W. Wang, X. Cheng, and S. Zhao, “Ecosystem health assessment in inner Mongolia region based on remote sensing and GIS,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37, no. B1, pp. 1029–1034, 2008.
- M. Anderson, P. Bourgeron, M.T. Bryer, et al., International Classification of Ecological Communities: Terrestrial Vegetation of the United States. Volume II. The National Vegetation Classification System: List of Types, The Nature Conservancy, Arlington, Va, USA, 1998.
- D. H. Grossman, D. Faber-Langendoen, A. S. Weakley, et al., International Classification of Ecological Communities: Terrestrial Vegetation of the United States. Volume I. The National Vegetation Classification System: Development, Status, and Applications, The Nature Conservancy, Arlington, Va , USA, 1998.
- J. R. Anderson, E. E. Hardy, J. T. Roach, and R. E. Witmer, “A Land use and land cover classification system for use with remote sensor data,” U.S. Geological Survey Professional Paper 964, U.S. Geological Survey, Reston, Va, USA, 1976.
- IUCN, “Habitats classification scheme (version 3.0),” International Union for the Conservation of Nature, 2007, http://www.iucnredlist.org/technical-documents/classification-schemes/habitats-classification-scheme-ver3.
- J. P. Schmit and J. P. Campbell, “National Capital Region Network 2006 forest vegetation monitoring report,” Tech. Rep. NPS/NCRN/NRTR-2007/046, National Park Service, Fort Collins, Colo, USA, 2007.
- J. P. Schmit and J. P. Campbell, “National Capital Region Network 2007 forest vegetation monitoring report,” Tech. Rep. NPS/NCRN/NRTR-2008/125, National Park Service, Fort Collins, Colo, USA, 2008.
- J. Hadidian, J. Saver, C. Swarth, et al., “A citywide breeding bird survey for Washington, D.C.,” Urban Ecosystems, vol. 1, pp. 87–102, 1997.
- D. K. Dawson and M. G. Efford, “National Capital Region Network–Protocol for monitoring forest-nesting birds,” Tech. Rep., National Park Service parks, Fort Collins, Colo, USA, 2006.
- S. Bates, “National Capital Region Network 2006 deer monitoring report,” Tech. Rep. NPS/NCRN/NRTR-2007/033, National Park Service, Fort Collins, Colo, USA, 2007.
- M. Norris, J. P. Schmit, and J. Pieper, “National Capital Region Network 2005-2006 water resources monitoring report,” Tech. Rep. NPS/NCRN/NRTR-2007/066, Natural Resource Program Center, Fort Collins, Colo, USA, 2007.
- R. H. Hilderbrand, R. L. Raesly, and D. M. Boward, National Capital Region Network-Biological Stream Survey Protocol, 2007.
- S. D. Mattfield, E. H. Grant, and L. L. Bailey, “Amphibian monitoring in the National Capital Region: a focus on lentic and lotic habitats,” Tech. Rep. NPS/NCRN/NRTR-2008/088, National Park Service, National Cancer Research Network, 2008.
- M. E. Montgomery, “Predicting defoliation by the gypsy moth using egg mass counts and a helper variable,” General Technical Report NE-146, USDA Forest Service, Proceedings US Department of Agriculture Interagency Gypsy Moth Research Review, 1990.
- A. Liebhold, K. Thorpe, J. Ghent, and D. B. Lyons, “Gypsy moth egg mass sampling for decision-making: a user's guide,” USDA-Forest Service, NA-TP-04-94, 1994, http://www.sandyliebhold.com/pubs/Liebhold_etal_1994_guide_color.pdf.
- D. G. McCullough and N. W. Siegert, “Estimating potential emerald ash borer (Coleoptera: Buprestidae) populations using ash inventory data,” Journal of Economic Entomology, vol. 100, no. 5, pp. 1577–1586, 2007.
- C. Jones, J. McCann, and S. McConville, “A guide to the conservation of forest interior dwelling birds in the Chesapeake Bay Critical Area. Report to the Critical Area Commission for the Chesapeake and Atlantic Coastal Bays,” 2000, http://www.dnr.state.md.us/criticalarea/pdfs/tweetyjune_2000.pdf.
- P. Koskimies, “Birds as a tool in environmental monitoring,” Annales Zoologici Fennici, vol. 26, no. 3, pp. 153–166, 1989.
- S. B. Horsley, S. L. Stout, and D. S. deCalesta, “White-tailed deer impact on the vegetation dynamics of a northern hardwood forest,” Ecological Applications, vol. 13, no. 1, pp. 98–118, 2003.
- D. S. Decalesta, “The science of overabundance: deer ecology and population management,” in Deer Ecosystem Management, W. J. McShea, H. B. Underwood, and J. H. Rappole, Eds., pp. 267–279, Springer, Amsterdam, The Netherlands, 1997.
- C. M. Stewart, W. J. Mcshea, and B. P. Piccolo, “The impact of white-tailed deer on agricultural landscapes in 3 national historical parks in Maryland,” Journal of Wildlife Management, vol. 71, no. 5, pp. 1525–1530, 2007.
- W. H. McWilliams, T. W. Bowersox, D. A. Gansner, L. H. McCormick, and S. L. Stout, “Landscape-level regeneration adequacy for native hardwood forests of Pennsylvania,” Tech. Rep. NE-197, U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station, Radnor, Pa, USA, 1995.
- W. K. Carter and T. S. Fredericksen, “Tree seedling and sapling density and deer browsing incidence on recently logged and mature non-industrial private forestlands in Virginia, USA,” Forest Ecology and Management, vol. 242, no. 2-3, pp. 671–677, 2007.
- D. A. Marquis, R. L. Ernst, and S. L. Stout, “Prescribing silvicultural treatments in hardwood stands of the Alleghenies (Revised),” General Technical Report NE-96, United States Department of Agriculture, Forest Service, 1992.
- J. Bowman, A. Jaeger, and L. Fahrig, “Dispersal distance of mammals is proportional to home range size,” Ecology, vol. 83, no. 7, pp. 2049–2055, 2002.
- H. S. He and D. J. Mladenoff, “The effects of seed dispersal on the simulation of long-term forest landscape change,” Ecosystems, vol. 2, no. 4, pp. 308–319, 1999.
- S. M. Lussier, S. N. da Silva, M. Charpentier et al., “The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams,” Environmental Monitoring and Assessment, vol. 139, no. 1–3, pp. 119–136, 2008.
- T. M. Conway, “Impervious surface as an indicator of pH and specific conductance in the urbanizing coastal zone of New Jersey, USA,” Journal of Environmental Management, vol. 85, no. 2, pp. 308–316, 2007.
- U. S. EPA, “Ambient water quality criteria recommendations—Rivers and streams in nutrient ecoregion,” IX. EPA 822-B-00-019. 3., 2000, http://www.epa.gov/waterscience/criteria/nutrient/ecoregions/rivers/rivers_9.pdf.
- U. S. EPA, “National Secondary Drinking Water Regulations,” 2009, http://ecfr.gpoaccess.gov/cgi/t/text/text-idx?c=ecfr&rgn=div5&view=text&node=40:18.104.22.168.5&idno=40.
- DCMR, “District of Columbia Municipal Regulations. Amendment to chapter 11 of Title 21, sections 1100 to 1106,” 2005, http://www.epa.gov/waterscience/standards/wqslibrary/dc/dc_3_register.pdf.
- U. S. EPA, “Freshwater recreation standards,” 2005, http://ddoe.dc.gov/ddoe/frames.asp?doc=/ddoe/lib/ddoe/wqd/WaterFinalRules06.pdf.
- J. B. Stribling, B. K. Jessup, J. S. White, D. Boward, and M. Hurd, “Development of a benthic index of biotic integrity for Maryland streams. Chesapeake Bay and watershed programs monitoring and non-tidal assessment,” Tech. Rep. CBWP-EA-98-3, 1998.
- D. I. MacKenzie, J. D. Nichols, J. E. Hines, M. G. Knutson, and A. B. Franklin, “Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly,” Ecology, vol. 84, no. 8, pp. 2200–2207, 2003.
- D. I. MacKenzie, J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines, Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Academic Press, New York, NY, USA, 2005.
- L. L. Bailey, E. H. Campbell-Grant, and P. Mattfeldt, National Capital Region Network Amphibian Monitoring Protocol, 2007, http://science.nature.nps.gov/im/monitor/VitalSigns/BrowseProtocol.aspx/.
- NAAQS, “National Ambient Air Quality Standards,” 2008, http://www.epa.gov/air/criteria.html#6/.
- U. S. EPA, “Air Quality Criteria for Particulate Matter Vol I of II. EPA/600/P-99/002aF,” 2004, http://cfpub2.epa.gov/ncea/cfm/recordisplay.cfm?deid=87903.
- U. S. EPA, “Provisional Assessment of Recent Studies on Health Effects of Particulate Matter Exposure,” EPA/600/R-06/063, 2006, http://www.epa.gov/air/particlepollution/pdfs/ord_report_20060720.pdf.
- NPS, “2006 annual performance & progress report: air quality in National Parks,” Tech. Rep., National Parks Service, Fort Collins, CO, USA, 2007.
- L. J. Kline, D. D. Davis, J. M. Skelly, J. E. Savage, and J. Ferdinand, “Ozone sensitivity of 28 plant selections exposed to ozone under controlled conditions,” Northeastern Naturalist, vol. 15, no. 1, pp. 57–66, 2008.
- D. W. Schindler, “Effects of acid rain on freshwater ecosystems,” Science, vol. 239, no. 4836, pp. 149–157, 1988.
- J. Dupont, T. A. Clair, C. Gagnon et al., “Estimation of critical loads of acidity for lakes in Northeastern United States and Eastern Canada,” Environmental Monitoring and Assessment, vol. 109, no. 1–3, pp. 275–291, 2005.
- J. Hendricks and J. Little, Thresholds for regional vulnerability analysis. National exposure research laboratory. U.S. EPA (E243-05), 2003, http://www.epa.gov/reva/docs/final_stressor_threshold_table.pdf.
- P. Greenfelt and E. Thornelof, “Critical loads of nitrogen—a workshop report,” Tech. Rep. 41, Nordic Council of Ministers, Copenhagen. Regional Vulnerability Assessment Program National Exposure Research Laboratory U.S. EPA (E243-05), 1992, (E243-05).
- M. Meili, K. Bishop, L. Bringmark et al., “Critical levels of atmospheric pollution: criteria and concepts for operational modelling of mercury in forest and lake ecosystems,” The Science of the Total Environment, vol. 304, no. 1–3, pp. 83–106, 2003.
- C. R. Hammerschmidt and W. F. Fitzgerald, “Methylmercury in freshwater fish linked to atmospheric mercury deposition,” Environmental Science and Technology, vol. 40, no. 24, pp. 7764–7770, 2006.
- U. S. EPA, “Water quality criterion for the protection of human health: methylmercury,” Tech. Rep. EPA-823-R-01-001, United States Environmental Protection Agency, Washington, DC, USA, 2001.
- D. S. DeCalesta and S. L. Stout, “Relative deer density and sustainability: a conceptual framework for integrating deer management with ecosystem management,” Wildlife Society Bulletin, vol. 25, no. 2, pp. 252–258, 1997.
- W. M. Healy, “Influence of deer on the structure and composition of oak forests in central Massachesetts,” in The Science of Overabundance: Deer Ecology and Population Management, W. J. McShea, H. B. Underwood, and J. H. Rappole, Eds., pp. 249–266, Springer, Amsterdam, The Netherlands, 1997.
- J. H. Volstad, N. E. Roth, G. Mercurio, M. T. Southerland, and D. E. Strebel, “Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators,” Environmental Monitoring and Assessment, vol. 84, no. 3, pp. 219–242, 2003.
- B. J. Blasius and R. W. Merritt, “Field and laboratory investigations on the effects of road salt (NaCl) on stream macroinvertebrate communities,” Environmental Pollution, vol. 120, no. 2, pp. 219–231, 2002.
- B. T. Hart, P. Bailey, R. Edwards et al., “A review of the salt sensitivity of the Australian freshwater biota,” Hydrobiologia, vol. 210, no. 1-2, pp. 105–144, 1991.
- C. Piscart, J. C. Moreteau, and J. N. Beisel, “Biodiversity and structure of macroinvertebrate communities along a small permanent salinity gradient (Meurthe River, France),” Hydrobiologia, vol. 551, no. 1, pp. 227–236, 2005.
- S. Kaushal, P. Groffman, G. Likens et al., “Increased salinization of fresh water in the Northeastern United States,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 38, pp. 13517–13520, 2005.
- J. E. Petersen, V. S. Kennedy, W. C. Dennison, and W. M. Kemp, Eds., Enclosed Experimental Ecosystems and Scale: Tools for Understanding and Managing Coastal Ecosystems, Springer, New York, NY, USA, 2009.
- M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson, Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 2007.
- H. Center, The State of the Nation's Ecosystems: Measuring Land, Waters, and Living Resources of The United States, Island Press, 2008.
- B. S. Brown, W. R. Munns Jr., and J. F. Paul, “An approach to integrated ecological assessment of resource condition: the Mid-Atlantic estuaries as a case study,” Journal of Environmental Management, vol. 66, no. 4, pp. 411–427, 2002.
- F. J. Pantus and W. C. Dennison, “Quantifying and evaluating ecosystem health: a case study from Moreton Bay, Australia,” Environmental Management, vol. 36, no. 5, pp. 757–771, 2005.
- R. S. Morin, A. M. Leibold, E. R. Luzader, A. J. Lister, K. W. Gottschalk, and D. B. Twardus, “Mapping host species abundance of three major exotic forest pests,” Research Paper NE-726, Northeastern Research Station, USDA forest service, 2004.
- S. J. Andelman and W. F. Fagan, “Umbrellas and flagships: efficient conservation surrogates or expensive mistakes?” Proceedings of the National Academy of Sciences of the United States of America, vol. 97, no. 11, pp. 5954–5959, 2000.
- R. V. O'Neill and R. H. Gardner, “Sources of uncertainty in ecological models,” in Methodology in Systems Modelling and Simlulation, B. P. Zeigler, M. S. Elzas, G. J. Kliv, and T. I. Oren, Eds., pp. 447–463, North-Holland Publishing, Amsterdam, The Netherlands, 1979.
- T. F. H. Allen and T. B. Starr, Hierarchy: Perspectives for Ecological Complexity, The University of Chicago Press, Chicago, Ill, USA, 1982.
- P. Comer, D. Faber-Langendoen, R. Evans, et al., Ecological Systems of the United States: A Working Classification of U.S. Terrestrial Systems, NatureServe, Arlington, Tex, USA, 2003.
- A. N. Strahler, “Quantitative analysis of watershed geomorphology,” American Geophysical Union Transactions, vol. 38, pp. 913–920, 1957.
- J. Shaman, M. Stieglitz, and D. Burns, “Are big basins just the sum of small catchments?” Hydrological Processes, vol. 18, no. 16, pp. 3195–3206, 2004.