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Modified items

All recently modified items, latest first.
Digital Elevation Model, Northern Appalachian
This dataset represents elevation for the Northern U.S. and Canada. This Digital Elevation Model (DEM) was created by mosaicing two data sets: 1. U.S. Geological Survey's (USGS) 30 meter National Elevation Dataset (NED) 2. The Canadian Digital Elevation Data, Level 1 (CDED1)
Bird Conservation Regions, Northern Appalachians
Bird Conservation Regions (BCRs) are ecologically distinct regions in North America with similar bird communities, habitats, and resource management issues. These ecoregions encompass areas that are similar in their biotic (e.g., plant and wildlife) and abiotic (e.g., soils, drainage patterns, temperature, and annual precipitation) characteristics.
Bedrock Geology, Northern Appalachians
Developed by The Nature Conservancy Eastern Division. We grouped bedrock units on the bedrock geology maps of ME, NH, VT, MA, CT, RI, NY, PA, NJ, and MD into seven general classes. We based our scheme on broad classification schemes developed by other investigators which emphasize chemistry and texture, and on bedrock settings that are important to many ecological communities, particularly to herbaceous associations.
Aspect, Northeast
Aspect is the orientation of the earth's surface with respect to the sun. This dataset is a grid created from a 30 meter digital elevation model (DEM) that was split into warm and cool aspect slopes.
Northatlantic Terrestrial
Data sets oriented around terrestrial
Terrestrial design products
 
Probability of Development
This dataset represents the integrated probability of development between 2010-2080 based on a custom urban growth model that accounts for the type (low intensity, medium intensity and high intensity), amount and spatial pattern of development. This index represents the probability of development occurring sometime between 2010 and 2080 at the 30 m cell level. The projected amount of development in an area is downscaled from county level forecasts based on a U.S. Forest Service 2010 Resources Planning Act (RPA) assessment. The type and pattern of development is based on models of historical development and is influenced by factors such as geophysical conditions (e.g., slope, proximity to open water), existing secured lands, and proximity to roads and urban centers.
Climate Stress
This dataset represents the climate stress metric, which is a measure of the estimated climate stress that may be exerted on a focal cell in 2080. Specifically, the climate stress metric reflects the 2080 departure from the current climate conditions that a cell may be exposed to in relation to its current climate niche breadth. Essentially, this metric measures the magnitude of climate change stress at the focal cell based on the climate niche of the corresponding ecological system and the predicted change in climate (i.e., how much is the climate of the focal cell moving away from the climate niche of the corresponding ecological system) between 2010-2080 based on the average of two climate change scenarios: RCP 4.5 and 8.5. Cells where the predicted climate suitability in the future decreases (i.e., climate is becoming less suitable for that ecological system) are considered stressed, and the stress increases as the predicted climate becomes less suitable based on the ecological system's current climate niche model. Conversely, cells where the predicted climate suitability in the future increases (i.e., climate is improving for that ecological systems) are considered unstressed and assigned a value of zero.
Weighted Index of Ecological Integrity
This dataset represents the weighted index of ecological integrity (IEI), which is a measure of relative intactness (i.e., freedom from human modifications and disturbance) and resiliency to environmental change (e.g., as caused by disturbance and climate change). Raw IEI is a composite index derived from 19 different landscape metrics that measure different aspects of intactness and resiliency. For the derivation of this layer, raw IEI is (quantile) scaled by ecological system and HUC6 watershed so that the poorest cell of each ecological system gets a 0 and the best gets a 1 within each watershed. In the layer provided here, scaled IEI has been modified to reflect weights assigned to each ecological system by the planning team, such that the final index gives more emphasis to certain terrestrial and wetland ecological systems deemed more vulnerable or in greater need of conservation (e.g., wetlands, alpine, boreal upland forest). Note that weights were not applied to aquatic systems. Thus, Aquatic Index of Ecological Integrity, which is provided for convenience in displaying the results of the aquatic conservation design but is otherwise equivalent to IEI except that it only has values for aquatic cells (all non-aquatic cells are set to nodata), is technically unweighted IEI. Weighted IEI is a major component of the terrestrial and aquatic core area selection indices and thus the terrestrial and aquatic network of core areas.
Sea Level Rise
This dataset represents the sea level rise metric based on a model developed by Rob Theiler and associates at USGS Woods Hole, which is a measure of the probability of a focal cell being unable to adapt to predicted inundation by sea level rise. Specifically, whether a site gets inundated by salt water permanently due to sea level rise or intermittently via storm surges associated with sea level rise clearly determines whether an ecosystem can persist at a site and thus its ability to support a characteristic plant and animal community. USGS examined future sea-level rise impacts on the coastal landscape from Maine to Virginia by producing spatially-explicit, probabilistic predictions using sea-level projections (based on an average of two climate change scenarios: RCP 4.5 and 8.5), vertical land movement (due to glacial isostacy) rates, elevation, and land cover data. The data span the coastal zone from an elevation of 5 m inland to -10 m offshore, and are provided for the forecast year 2080.In the layer provided here, the raw coastal response metric produced by USGS is scaled and inverted so that a cell with high probability of exhibiting a dynamic (or adaptive) response to sea level rise gets a zero (low stress) and a cell with low probability of exhibiting a dynamic response gets a value approaching 1 (high stress). In addition, we set all cells classified as sub-tidal to nodata for consistency with other products.
Terrestrial Ecosystem-Based Core Area Selection Index
This dataset represents the selection index used to create terrestrial ecosystem-based cores. The selection index is a continuous surface in which every cell is assigned a value (0-1) based on its relative ecological integrity and/or biodiversity value within each HUC6 watershed. Specifically, for all terrestrial and wetland cells, the selection index is a composite index derived from a weighted combination of the 1) weighted index of ecological integrity, 2) TNC's terrestrial resiliency index, and a binary representation of 3) TNC's tier 1 floodplains and 4) S1-S3 rare natural communities as defined and mapped by the state Natural Heritage programs. For aquatic cells (which are also included in this layer), the index is equal to IEI, except in headwater creeks where IEIis averaged with USGS's stream temperature tolerance index
TNC Terrestrial Resiliency, CT River Watershed
This dataset represents a scaled version of the terrestrial resiliency index developed by Mark Anderson and associates at The Nature Conservancy (Anderson et al 2012), which is a measure of the relative long-term resiliency of a site based on connectivity to a diversity of landforms, elevations and wetlands. Thus, a value of 0.9 in a cell means that it has a resiliency score that is greater than 90% of all the cells of the same geophysical setting in that watershed, and all the cells with >0.9 values comprise the best 10% of all cells across all geophysical settings within the watershed. TNC's resiliency index, as scaled here, is a major component of the terrestrial core area selection index and thus the terrestrial core area network.
Terrestrial Cores and Connectors
Included in this download are a set of Tier 1 terrestrial core areas and their connectors, grassland bird core areas, and additional tier 2 cores and tier 3 supporting landscapes. In combination with the aquatic core areas, they spatially represent the ecological network derived from the Connecticut River Landscape Conservation Design (CTR LCD) project. Terrestrial Core and Connectors: The network is designed to provide strategic guidance for conserving natural areas, and the fish, wildlife, and other components of biodiversity that they support within the Connecticut River watershed. Connectors represent “corridors” that could facilitate the movement of plants and animals (i.e., ecological flow) between terrestrial tier 1 core areas. Grassland Bird Cores: Represents a set of terrestrial core areas for grassland birds based on the eastern meadowlark as a representative species for grassland birds. Terrestrial Core Tiers: This layer depicts the terrestrial tier 1 cores (encompassing 25% of the landscape), nested within tier 2 cores (encompassing 50% of the landscape), nested with tier 3 supporting landscapes (encompassing 77% of the landscape). The tiers reflect the arbitrariness in selecting thresholds for designating priority core areas.
Terrestrial design products
Photo credit: Michael Goulet
Species
 
Brook Trout Current Probability of Occurrence
This dataset represents the probability of occurrence of brook trout in headwater creeks based on current habitat and climate conditions. Brook trout are a representative species for cool/cold headwater creeks. This layer was derived from a model developed by Ben Letcher and associates at the USGS Conte Anadromous Fish Lab. Specifically, this index represents the species' current probability of occurrence, presented as an integerized range from 0 (low=0% probability of occurrence) to 100 (high=100 % probability of occurrence). The brook trout probability of occurrence model is applied only to headwater creeks. Note, the brook trout current probability of occurrence is analogous to the landscape capability index developed for representative terrestrial wildlife species; it represents the suitability of habitat and climate conditions today. This index is an input into the selection of core areas in headwater creeks along with the Index of Ecological Integrity.
Landscape Capability for Northern Waterthrush
This dataset depicts the potential capability of the landscape throughout the Connecticut River Watershed to provide habitat for Northern Waterthrush (Parkesia noveboracensis) based on environmental conditions existing in approximately 2010. Landscape capability integrates factors influencing climate suitability, habitat capability, and other biogeographic factors affecting the species’ prevalence in the area. All locations are scored on a scale from 0 to 1, with a value of 0 indicating no capacity to support the species and 1 indicating optimal conditions for the species.
Landscape Capability for Wood Duck
This dataset depicts the potential capability of the landscape throughout the Connecticut River Watershed to provide habitat for Wood Duck (Aix sponsa) based on environmental conditions existing in approximately 2010. Landscape capability integrates factors influencing climate suitability, habitat capability, and other biogeographic factors affecting the species’ prevalence in the area. All locations are scored on a scale from 0 to 1, with a value of 0 indicating no capacity to support the species and 1 indicating optimal conditions for the species.
Landscape Capability for Wood Thrush
This dataset depicts the potential capability of the landscape throughout the Connecticut River Watershed to provide habitat for Wood Thrush (Hylocichla mustelina) based on environmental conditions existing in approximately 2010. Landscape capability integrates factors influencing climate suitability, habitat capability, and other biogeographic factors affecting the species’ prevalence in the area. All locations are scored on a scale from 0 to 1, with a value of 0 indicating no capacity to support the species and 1 indicating optimal conditions for the species.
Landscape Capability for Ruffed Grouse
This dataset depicts the potential capability of the landscape throughout the Connecticut River Watershed to provide habitat for Ruffed Grouse (Bonasa umbellus) based on environmental conditions existing in approximately 2010. Landscape capability integrates factors influencing climate suitability, habitat capability, and other biogeographic factors affecting the species’ prevalence in the area. All locations are scored on a scale from 0 to 1, with a value of 0 indicating no capacity to support the species and 1 indicating optimal conditions for the species.