Studies predicting how the distribution of aquatic organisms will shift with climate change often use projected increases in air temperature or water temperature. However, the assumed correlations between water temperature change and air temperature change can be problematic, especially for mountainous, high elevation streams. Using stream fish assemblage data from 1,442 surveys across a mountain-plains gradient (Wyoming, USA; 1990-2018), we compared the responsiveness of thermal guilds, native status groups, and assemblage structure to projected climate warming from generalized air temperature models and stream-specific water temperature models. Air temperature models consistently predicted greater range shift differences between warm-water and cold-water species, with air temperatures predicting greater increases in occurrence and greater range expansions for warm-water species. The "over-prediction" of warm-water species expansions resulted in air temperature models predicting higher rates of novel species combinations, greater increases in local species richness, and higher magnitudes of biotic homogenization compared with water temperature models. Despite differences in model predictions for warm-water species, both air and water temperature models predicted that three cold-water species would exhibit similar decreases in occurrence (decline of 1.0% and 1.8% of sites per 1°C warming, respectively) and similar range contractions (16.6 and 21.5 m elevation loss per 1°C warming, respectively). The "over-prediction" for warm-water species is partially attributable to water temperatures warming at slower rates than air temperatures because local, stream-scale factors (e.g., riparian cover, groundwater inputs) buffer high elevation streams from rising air temperatures. Our study provides the first comparison of how inferences about climate-induced biotic change at the species- and assemblage-levels differ when modeling with generalized air temperatures versus stream-specific water temperatures. We recommend that future studies use stream-specific water temperature models, especially for mountainous, high elevation streams, to avoid the "over-prediction" of biotic changes observed from air temperature variables.
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http://dx.doi.org/10.1002/eap.2465 | DOI Listing |
The purpose of this study was to investigate the application of an innovative extrusion-based 3D food printing (3DFOODP) technique in developing rice protein-starch (RP-S) gel-based products. The effects of 3DFOODP conditions were examined, which included variations in the concentrations of rice protein (RP) and corn starch (S) (15, 17.5, and 20 wt.
View Article and Find Full Text PDFRaisins are so popular in the human diet as a nutritional and sweet snack. The quality of this foodstuff depends on drying conditions. To minimize ochratoxin A (OTA) content and yeast and mold content (YMC) in raisins with favorable physicochemical and sensory properties, the response surface methodology (RSM) and the face-centered central composite design (FCCD) were utilized.
View Article and Find Full Text PDFEcol Evol
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.
View Article and Find Full Text PDFAnthropogenic planetary heating is disrupting global alpine systems, but our ability to empirically measure and predict responses in alpine species distributions is impaired by a lack of comprehensive data and technical limitations. We conducted a comprehensive, semi-quantitative review of empirical studies on contemporary range shifts in alpine insects driven by climate heating, drawing attention to methodological issues and potential biotic and abiotic factors influencing variation in responses. We highlight case studies showing how range dynamics may affect standing genetic variation and adaptive potential, and discuss how data integration frameworks can improve forecasts.
View Article and Find Full Text PDFProcess-based models for range dynamics are urgently needed due to increasing intensity of human-induced biodiversity change. Despite a few existing models that focus on demographic processes, their use remains limited compared to the widespread application of correlative approaches. This slow adoption is largely due to the challenges in calibrating biological parameters and the high computational demands for large-scale applications.
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