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7 results for “environmental mismatches”
Raw data from: "Thermal mismatches explain consumer-resource dynamics in response to environmental warming".
<p>Data from:</p> <p>Álvarez-Codesal, S, Faillace CA, Garreau, A, Bestion, E, Synodinos, AD, & Montoya, JM. 2023. Thermal mismatches explain consumer-resource dynamics in response to environmental warming. Ecology and Evolution.<br> </p> <p>Composed of seven associated datasets:</p> <p>- Algae_Net_Photosynthesis.csv</p> <p>- Daphnia_Ingestion.csv</p> <p>- Algae_Respiration.csv</p> <p>- Daphnia_Ingestion.csv</p> <p>- Daphnia_respiration.csv</p> <p>- Interaction_Strength.csv</p> <p>- Energy_Balance_Ratios_dataset.csv</p> <p> </p> <p>A detailed explanation of the methods is provided in the related Alvarez-Codesal et al. 2023 article, please refer to it for a full understanding of the methods and results.</p> <p>Briefly: our aim was to quantify the impact of warming on consumer-resource interactions, using as consumer <em>Daphnia pulex</em>, and as resources two algae species, <em>Chlamydomonas reinhardtii</em> and <em>Desmodesmus</em> sp.</p> <p>First, we measured thermal dependencies of physiological rates related to energy gain (i.e., ingestion, net photosynthesis) and loss (i.e., respiration) for <em>Daphnia</em> and the algae in basal conditions at eight temperatures. From these, we calculated species energetic balances as net photosynthesis-to-respiration ratio (P/R<sub>r</sub>) for resources, or as ingestion-to-respiration ratio (I/R<sub>c</sub>) for consumers, using predicted values of each (per capita) rate from the models. We used energetic balances as an indicator of how species respond to increasing temperatures, defining intraspecific energetic mismatches when the energetic balance decreases.</p> <p>Second, we inferred interspecific thermal mismatches (inter-TM) by comparing individual energetic balances for both consumer-resource pairs, and identified the thermal mismatch regions, where: 1) trends of energetic balances contrast between the interacting species; and 2) both species reduce their energetic balance with increasing temperature. The inter-TMs were used to increase our qualitative understanding on the outcomes of thermal dependencies of interaction strength.</p> <p>Third, we calculated the natural logarithm of the consumer-resource energetic balance for each interacting pair as the ratio between consumer energetic balance and the resource energetic balance to get qualitative predictions on the trends of interaction strength with temperature.</p> <p>Finally, we measured experimentally thermal dependencies of interaction strength for each consumer-resource pair and verified if our predictions using the thermal mismatches fitted the trends of interaction strengths across temperatures.</p>
Supported data for manuscript: 'Future hydrogen economies imply environmental trade-offs and a supply-demand mismatch' (DOI: 10.1038/s41467-024-51251-7)
<p>After unpacking the ZIP file, this repository contains the following files:</p> <p><strong>results_lcoh_ecoinvent_391_reference.tif:</strong> grid-specific hydrogen production cost (euro/kg H2) for the reference scenario.</p> <p><strong>results_lcoh_SSP2-Base_2050_base.tif:</strong> grid-specific hydrogen production cost (euro/kg H2) for the baseline scenario in 2050.</p> <p><strong>results_lcoh_SSP2-PkBudg1150_2050_base.tif:</strong> grid-specific hydrogen production cost (euro/kg H2) for the 2°C scenario in 2050.</p> <p><strong>results_lcoh_SSP2-PkBudg500_2050_base.tif:</strong> grid-specific hydrogen production cost (euro/kg H2) for the 1.5°C scenario in 2050.</p> <p><strong>results_ghg_kg_h2_ecoinvent_391_reference.tif:</strong> grid-specific GHG emissions (kg CO2-eq./kg H2) from hydrogen production for the reference scenario.</p> <p><strong>results_ghg_kg_h2_SSP2-Base_2050_base.tif:</strong> grid-specific GHG emissions (kg CO2-eq./kg H2) from hydrogen production for the baseline scenario in 2050.</p> <p><strong>results_ghg_kg_h2_SSP2-PkBudg1150_2050_base.tif:</strong> grid-specific GHG emissions (kg CO2-eq./kg H2) from hydrogen production for the 2°C scenario in 2050.</p> <p><strong>results_ghg_kg_h2_SSP2-PkBudg500_2050_base.tif:</strong> grid-specific GHG emissions (kg CO2-eq./kg H2) from hydrogen production for the 1.5°C scenario in 2050.</p> <p><strong>main_gen_figures.ipynb: </strong>Jupyter Notebook script used to generate the main figures of the manuscript.</p>
Data and code for "Competition contributes to quantitative mismatches between plant fitness and occurrence along environmental gradients"
<p>This repository contains data and code for the following manuscript: Hayashi, K. T., & Kraft, N. J. B. (2025). Competition contributes to quantitative mismatches between plant fitness and occurrence along environmental gradients. Journal of Ecology, 113, 2590–2602. <a href="https://doi.org/10.1111/1365-2745.70115">https://doi.org/10.1111/1365-2745.70115</a></p>
Data from: Environmental factors explain the spatial mismatches between species richness and phylogenetic diversity of terrestrial mammals
Aim: Explore the spatial variation of the relationships between species richness (SR), phylogenetic diversity (PD) and environmental factors to infer the possible mechanisms underlying patterns of diversity in different regions of the globe. Location: Global. Time period: Present day. Major taxa studied: Terrestrial mammals. Methods: We used a hexagonal grid to map SR and PD of mammals and four environmental factors (temperature, productivity, elevation and climate-change velocity since the Last Glacial Maximum). We related those variables through direct and indirect pathways using a novel combination of Path Analysis and Geographically Weighted Regression to account for spatial non-stationarity of path coefficients. Results: SR, PD and environmental factors relate differently across the geographic space, with most relationships varying in both, magnitude and direction. Species richness is associated with lower phylogenetic diversity in much of the tropics and in the Americas, which reflects the tropical origin and the recent diversification of some mammalian clades in these regions. Environmental effects on PD are predominantly mediated by their effects on SR. But once richness is controlled for, the relationships between environmental factors and PD (i.e. PDSR) highlight environmentally driven changes in species composition. Environmental-PDSR relationships suggest that the relative importance of different mechanisms driving biodiversity shifts spatially. Across most of the globe, temperature and productivity are the strongest predictors of richness, while PDSR is best predicted by temperature. Main conclusions: Richness explains most spatial variation in PD, but both dimensions of biodiversity respond differently to environmental conditions across the globe, as indicated by the spatial mismatches in the relationships between environmental factors and these two types of diversity. We show that accounting for spatial non-stationarity and environmental effects on PD while controlling for richness uncovers a more complex scenario of drivers of biodiversity than previously observed.
Pollination-related plant traits under environmental changes: seasonal and daily mismatches produce temporal constraints
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Data from: Environmental factors explain the spatial mismatches between species richness and phylogenetic diversity of terrestrial mammals
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Differences in oxidative stress across seasons and ability to cope with environmental mismatch in muscle and brain of black-capped chickadees (Poecile atricapillus) and rock pigeons (Columba livia)
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