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Data layers of current and projected suitable habitat for five species: big-eared woodrat (Neotoma macrotis), California gnatcatcher, Ceanothus greggii, Ceanothus verrucosus, and Tecate cypress in the South Coast Ecoregion in California, USA. Data set includes scenarios with and without projected urban growth over a 50 year period, and with and without projected climate change over a 50 year period. The potential distribution of Ceanothus greggii was modeled using a MaxEnt species distribution model using recent and future climate data with presence records from the San Diego Natural History Museum. Species distributions were modeled only for the South Coast Ecoregion in California, USA as this is where management...
Data layers of current and projected suitable habitat for five species: big-eared woodrat (Neotoma macrotis), California gnatcatcher, Ceanothus greggii, Ceanothus verrucosus, and Tecate cypress in the South Coast Ecoregion in California, USA. Data set includes scenarios with and without projected urban growth over a 50 year period, and with and without projected climate change over a 50 year period. The potential distribution of the big-eared woodrat (Neotoma macrotis) was modeled using a MaxEnt species distribution model using recent and future climate data with presence records from the San Diego Natural History Museum. Species distributions were modeled only for the South Coast Ecoregion in California, USA as...
Data layers of current and projected suitable habitat for five species: big-eared woodrat (Neotoma macrotis), California gnatcatcher, Ceanothus greggii, Ceanothus verrucosus, and Tecate cypress in the South Coast Ecoregion in California, USA. Data set includes scenarios with and without projected urban growth over a 50 year period, and with and without projected climate change over a 50 year period.
Environmental Change Network: Current and Future Zonation PrioritizationZonation is a spatial conservation planning software tool that can take into account multiple species to create a hierarchical prioritization of the landscape. This is in contrast to other spatial conservation planning tools which may require predefined conservation targets or areas. Here, we used 199 California landbirds along with Zonation’s “core-area” algorithm to prioritize the California landscape. Species were weighted according to the California Bird Species of Special Concern criteria and probability of occurrence was discounted by distribution model and climate model uncertainty surfaces.The dataset provides priority areas for “current”...
This set of elevation models was developed to understand current (2010) conditions of San Francisco salt marshes and for input into sea-level rise prediction models. These elevation models were built by interpolating surveyed elevation points. The elevation surveys were conducted with a Leica RX1230 Real-Time Kinematic GPS which is capable of < 2 cm vertical accuracy.
Bird community turnover for current and future climate (GFDL) based on maxent models for 198 land bird species.
These maps display the magnitude of projected future climate change in relation to the interannual variability in late 20th century CA climate. The maps show the standardized Euclidean distance between the late 20th century climate at each pixel and the future climate at each pixel. The standardization puts all of the climate variables included on the same scale and down weights changes in future climate which have had large year to year variation historically. Warmer colors indicate greater climate change and cooler colors indicate less extreme climate change.
Data layers of current and projected suitable habitat for five species: big-eared woodrat (Neotoma macrotis), California gnatcatcher, Ceanothus greggii, Ceanothus verrucosus, and Tecate cypress in the South Coast Ecoregion in California, USA. Data set includes scenarios with and without projected urban growth over a 50 year period, and with and without projected climate change over a 50 year period. The potential distribution of Tecate cypress was modeled using a MaxEnt species distribution model using recent and future climate data with presence records from the San Diego Natural History Museum. Species distributions were modeled only for the South Coast Ecoregion in California, USA as this is where management...
Priority areas for conservation of tidal marsh birds given current and future environmental conditions. Maps were created using Zonation, a spatial conservation planning software tool that can take into account multiple species and scenarios to create a hierarchical prioritization of the landscape.The current (2010) and future (2030-2110) prioritization is based upon distribution and abundance models for five tidal marsh bird species which utilized avian observation data (2000 - 2009), a marsh accretion model, and physical variables (e.g. salinity, distance to nearest channel, slope, etc). Values represent the rank in which pixels were removed from the landscape using Zonation Conservation Planning software with...
In California, the near-shore area where the ocean meets the land is a highly productive yet sensitive region that supports a wealth of wildlife, including several native bird species. These saltmarshes, mudflats, and shallow bays are not only critical for wildlife, but they also provide economic and recreational benefits to local communities. Today, sea-level rise, more frequent and stronger storms, saltwater intrusion, and warming water temperatures are among the threats that are altering these important habitats.To support future planning and conservation of California’s near-shore habitats, researchers examined current weather patterns, elevations, tides, and sediments at these sites to see how they affect plants...
Full Title: Environmental Change Network: Current and Projected VegetationThe current vegetation layer is derived from the vegetation map developed as part of the California Gap Analysis project. The derivation takes the California Wildlife Habitat Relationships (CWHR) habitat classification provided in the California Gap Analysis layer, generalizes the classes to a set of broader habitat types, and rasterizes it at 800 meter resolution.The future vegetation layers for both the GFDL and CCSM GCM models are derived using a random forest model of the vegetation classification. The original CWHR classification has been generalized to 12 classes for ease in modeling. Inputs to the model include eight bioclimatic variables...
Marsh accretion was modeled by ESA PWA using the Marsh-98 model, described here. The model assumes that rates of marsh plain elevation change depend on the availability of suspended sediment and organic material, water depth, and duration of inundation periods. If enough suspended sediment is available, then tidal marsh elevations can keep pace with increased inundation. Model outputs were linearly interpolated in 10-cm increments for starting elevations ranging from -3.7 to 1.7 m (relative to mean higher high water, or MHHW), and applied to a composite 5-m elevation grid (see below) for SF Bay. Results for each possible combination of projected sea level rise, sediment and organic material availability, and target...
The development of sophisticated species distribution modeling techniques provides an opportunity to examine the potential effects of climate change on bird communities. Using these modeling approaches, we are relating bird data to environmental layers to generate robust predictions of current (1971–2000) and projected future species occurrence. Future bird distributions are based on regional climate model projections for the periods 2038–2070 (IPCC Scenario A2). Bird species distributions were created using the Maxent modeling technique: Maxent (Phillips et al. 2006), which is able to model non-linear responses to environmental variables. Map values represent the predicted habitat suitability; the higher the values,...
Densities for five key tidal marsh-dependent bird species were modeled using boosted regression trees (Elith et al. 2008). The models are able to fit non-linear functions between environmental variables and the presence/absence or density of a species. Map values represent the probability of occurrence of a species or the density (birds/ha). Higher values in a map indicate a higher likelihood that a species will be present at a site. Bird species modeled: Common yellowthroat, black rail, clapper rail, marsh wren, song sparrow. Model outputs: Probably of occurrence, density (birds per hectare)
Maps of the probability of occurrence of tidal marsh plant species were created using generalized additive models (Hastie and Tibshirani 1990). Species modeled: Saltgrass, alkali-heath, SF Bay gumplant, jaumea, wirerush, pepperweed, giant reed, pickleweed, hard-stem tule, three-square bullrush, smooth cordgrass, California cordgrass, cattail.
Data layers of current and projected suitable habitat for five species: big-eared woodrat (Neotoma macrotis), California gnatcatcher, Ceanothus greggii, Ceanothus verrucosus, and Tecate cypress in the South Coast Ecoregion in California, USA. Data set includes scenarios with and without projected urban growth over a 50 year period, and with and without projected climate change over a 50 year period. The potential distribution of California gnatcatcher was modeled using a MaxEnt species distribution model using recent and future climate data with presence records from the San Diego Natural History Museum. Species distributions were modeled only for the South Coast Ecoregion in California, USA as this is where management...
Current and projected bird distribution and abundance layers, updated with new model that has better inputs. Point Blue Conservation Science assessed the effects of sea-level rise (SLR) and salinity changes on San Francisco Bay tidal marsh ecosystems. Tidal marshes are naturally resilient to SLR, in that they can build up elevation through the capture of suspended sediment and deposition of organic material (vegetation). Thus, a “bathtub” model approach is not appropriate for assessing impacts to this dynamic habitat. Rather, dynamic accretion potential can be modeled annually based on tidal inundation, sediment availability, and the rate of organic accumulation (related to salinity).Working with researchers at...
Understanding San Francisco Bay’s vulnerabilities to sea level rise is important for both biodiversity conservation and for management of public infrastructure. Coastal marshes provide essential ecosystem services such as water filtration and flood abatement while also providing important habitat for species of conservation concern. Improving our understanding of how tidal marsh habitats will be affected by sea level rise is important so that we maximize ecosystem services that coastal marshes provide and ensure that endemic populations of plants and animals persist into the future. For this project, marsh accretion was modeled by ESA PWA (http://www.pwa-ltd.com/index.html) using the Marsh-98 model, described here:...
Species richness indicates the number of different species predicted to be able to occur at a location. Maps show the projected species richness under current climate and two models of future climate conditions. Species richness is calculated by converting the predictions from maxent models into binary maps of presence and absence and summing the maps across all species. Higher values in the maps indicate where more bird species are projected to be able to occur.