Climate Stress Metric, Version 3.0, Northeast U.S.

The Climate Stress Metric is one of a suite of products from the Nature’s Network project (naturesnetwork.org). Nature’s Network is a collaborative effort to identify shared priorities for conservation in the Northeast, considering the value of fish and wildlife species and the natural areas they inhabit. This dataset represents a measure of the estimated magnitude of climate stress that may be exerted on habitats (ecosystem types) in 2080, on a scale of 30 m2 cells. Cells where 2080 climate conditions depart substantially from conditions where the underlying ecosystem type currently occurs (the ecosystem’s “climate niche”) are considered to be stressed. Cells where the projected 2080 climate conditions are not substantially different from the current climate niche in the Northeast region are considered to be under low climate stress. Areas with low or zero climate stress may be candidates to function as climate refugia; these are places where ecosystems and associated species can persist relatively longer, compared to typical locations where the ecosystems currently occur. A number of additional datasets that augment or complement the climate stress metric are available in the Nature’s Network gallery: https://nalcc.databasin.org/galleries/8f4dfe780c444634a45ee4acc930a055.

Intended Uses

A primary use of this product is to identify potential climate refugia: areas where particular ecosystem types, and the species that inhabit them, may be able to persist longer in the face of climate change than other examples of the same ecosystem type. Areas identified as having zero or low climate stress are candidates for functioning as climate refugia. The product may be particularly important for identifying conservation opportunities for rare ecosystem types. Conversely, areas predicted to be under extreme climate stress in the future may be considered less favorable sites for intensive investments to conserve sensitive species or ecosystems currently present. Management to facilitate adaptation and transition to new ecosystem types more suitable to the changing climate may be appropriate for such areas.

• You might explore the Climate Stress Metric in combination with the following products also available as part of Nature’s Network:

• The Terrestrial Core-Connector Network to identify which places within designated core areas may serve as climate refugia (low climate stress) and which areas might be better managed for transition to new ecosystem types (high climate stress).

• The Terrestrial and Aquatic Habitat Map (DSLland) to reveal how climate stress relates to the underlying ecological system. Additionally, it can be used as an ecological system mask to focus on how climate will affect specific rarer ecological systems, which may be difficult to visualize amongst more common ecological system types.

• The Sea Level Rise Metric to identify places within coastal systems that are predicted to become doubly stressed by both climate change (via air temperature and precipitation) and sea level rise.

• The Nature Conservancy’s Terrestrial Resilience to identify where, as a result of connectivity with diverse landforms, elevations and wetlands, the flora and fauna of an ecological system facing high climate stress may be able to persist.

• Climate products for representative species of wildlife (Climate Zones and Climate Response) and Brook Trout (Brook Trout Probability of Occurrence, considering future stream temperature changes) for a fuller understanding of potential implications of a changing climate to fish and wildlife species.

Description and Derivation

1) Climate models were developed and downscaled to 30m cells

• Climate models were built from averaged results of the 14 Global-coupled Atmospheric-Ocean General Circulation Models (AOGCM) that best fit historical data for the Northeast. AOGCM are complex models used to produce long-term climate projections by integrating both oceanic and atmospheric processes and the interactions between them. They have been standardized using historic data and standard Representative Concentration Pathways (RCPs).

• The average of output of the models for RCPs 4.5 and 8.5 were taken as the predicted future climate.

• In order to incorporate the local variation (e.g., climate differences due to local topographic effects), data were downscaled using the Bias Corrected Spatial Disaggregation (BCSD) approach and actual data from PRISM Climate Group, Oregon State University and the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model dataset.

• A detailed description of the process of modelling climate change on a fine spatial resolution for the Northeast is available here: http://jamba.provost.ads.umass.edu/web/lcc/dsl_documentation_climate.pdf

2) Climate Niche Models were created for each ecological system

• Climate niche breadth was modelled for each ecological system based on 30-year normals from a large number of randomly selected points in each class of ecological system. This provided the probability for each 30m cell that the climate is suitable for an ecological system, given a set of climate variables.

• The classification of ecological systems for the Climate Stress Metric followed the Terrestrial and Aquatic Habitat Map (DSLland https://nalcc.databasin.org/datasets/87ba0c8d6f5642b8a3f66c5d73d257e0), a substantial revision of the map of the Northeast Terrestrial Wildlife Habitat Classification System (developed by The Nature Conservancy and the northeastern states).

3) Future climate stress was calculated and rescaled by ecological system

• The probability that future climate will be suitable for each 30m cell was determined using the climate niche models and downscaled climate data. Lower probabilities of suitability resulted in higher stress.

• All the cells within an ecological system were ranked against each other in order to determine the cells with the greatest relative magnitude of climatic stress for each ecological system. A ranking of 1, therefore, indicates that a cell is predicted to experience the highest level of climate stress of all cells occurring in the same ecological system class. A ranking of 0.1 indicates that 90% of cells falling in the same ecological system class are predicted to experience a greater departure in climate.

Known Issues and Uncertainties

• It is best to consider climate stress separately for each ecological system. Abrupt changes in the absolute value of the climate stress metric between adjacent cells is likely to be due to changes in the underlying mapped ecological system; it does not reflect an abrupt change in the absolute climate stress. Consequently, it is best to use an ecological system mask when viewing the results.

• This layer reveals the magnitude of climate change stress; it does not reveal places where climate suitability is improving for a particular system. We excluded the climate stressor metric for ecological systems that range beyond the southern edge of the region (i.e., those for which suitability might be expected to improve)

• The mapping of ecosystem locations and development is known to be imperfect, which consequently affects the mapped values for ecosystem integrity and species habitat. While the ecosystem mapping is anticipated to correctly reflect broad patterns of ecosystem occurrence, errors in classification and placement do occur, as with any regional GIS data.

• Individual fish and wildlife species can be expected to respond uniquely to changing climate conditions and may have different vulnerabilities than suggested by the climate stress metric results for ecosystems they inhabit.

• A number of uncertainties are associated with future climate projections. Additional assumptions and limitations associated with future climate projections are summarized in the climate technical documentation (http://jamba.provost.ads.umass.edu/web/lcc/dsl_documentation_climate.pdf).