Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate-induced species' movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species' movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving-window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species' dispersal capabilities. We compared connectivity maps generated with our climate-change-informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present-day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate.
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http://dx.doi.org/10.1111/cobi.12938 | DOI Listing |
J Environ Manage
January 2025
Tetra Tech, Inc., P.O. Box 14409, Research Triangle Park, NC, 27709, United States. Electronic address:
Due to the recent improved availability of global and regional climate change (CC) models and associated data, the projected impact of CC on urban stormwater management is well documented. However, most studies are based on simplified design storm analysis and unit-area runoff models; evaluations of the long-term, continuous hydrologic response of extensive stormwater control measures (SCM) implementation under future CC scenarios are limited. Moreover, channel stability in response to CC is seldom evaluated due to the input data required to develop a long-term, continuous sediment transport model.
View Article and Find Full Text PDFPLoS One
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Woodwell Climate Research Center, Falmouth, MA, United States of America.
Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs.
View Article and Find Full Text PDFAmbio
January 2025
Department of Biological Sciences, Virginia Tech, 926 West Campus Drive, Blacksburg, VA, 24061, USA.
Microb Biotechnol
January 2025
Institute of Biochemical Engineering/Institut für Bioverfahrenstechnik, University of Stuttgart, Stuttgart, Germany.
While rising greenhouse gases cause climate change, global economies ask for resilient solutions for the business of the future. Biomanufacturing may well serve as a pillar of a circular economy with minimised environmental impact. Therefore, innovations of the lab need to successfully bridge the imminent 'death-valley of innovation' for making commercial production happen.
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January 2025
Department of Agricultural, Food and Environmental Sciences Università Politecnica delle Marche Ancona Italy.
This study investigates climate change impacts on spontaneous vegetation, focusing on the Mediterranean basin, a hotspot for climatic changes. Two case study areas, Monti Sibillini (central Italy, temperate) and Sidi Makhlouf (Southern Tunisia, arid), were selected for their contrasting climates and vegetation. Using WorldClim's CMCC-ESM2 climate model, future vegetation distribution was predicted for 2050 and 2080 under SSP 245 (optimistic) and 585 (pessimistic) scenarios.
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