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opencc-by-4.0Apr 2020View details →

Spatially corrected dataset for natural variation across Arabidopsis diversity panel in early responses to salt stress

The spatially corrected data of Arabidopsis thaliana accessions, which were grown according to the established protocol for studying salt stress in soil experiment (described in detail here dx.doi.org/10.17504/protocols.io.4xzgxp6), in the PSI facility, Czech Republic. The spatial correction was done using the asreml package. The data was subsequently used for the Genome-Wide Association Study.

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Data from: Spatial and seasonal variation in thermal sensitivity within North American bird species

Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity given adaptation to local environments and plasticity required to adjust to seasonal environments. Spatial and temporal variation in thermal responses may carry important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 20 bird species. Across their ranges, most birds demonstrated regional and seasonal variation in both thermal peak and range, or the temperature and range of temperatures of greatest occurrence. Some birds demonstrated constant thermal peaks or ranges across their geographic distributions and while others varied according to local and current environmental conditions. Across species, birds typically invested in either geographic or seasonal adaptation to climate. Local adaptation and phenotypic plasticity are likely important but neglected aspects of organismal responses to climate change.

opencc-zeroOct 2023View details →

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Data from: A species' response to spatial climatic variation does not predict its response to climate change

The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.

opencc-zeroJan 2024View details →

Fig. 3 in Spatial Variation Of The Land Snail Brephulopsis Cylindrica (Gastropoda, Pulmonata, Enidae): A Fractal Approach

Fig. 3. The dependence between intrapopulation variation (Mst) and the sample sites number in B. cylindrica: A — shell height (HS); B — shell width (WS); C — shell form index (FS) (95 % confidence interval is indicated by dotted lines).

Fig. 4 in Spatial Variation Of The Land Snail Brephulopsis Cylindrica (Gastropoda, Pulmonata, Enidae): A Fractal Approach

Fig. 4. Plots of the logarithms of semivariance versus logarithms of spatial scale (in meter) for morphometric shells traits of B. cylindrica of the studying population. D — fractal dimension value; R2 — determination coefF ficient): A — shell height (HS); B — shell width (WS); C — shell form index (FS).

Fig. 2 in Spatial Variation Of The Land Snail Brephulopsis Cylindrica (Gastropoda, Pulmonata, Enidae): A Fractal Approach

Fig. 2. Moran's index for morphometric shells traits of B. cylindrica of the studying population: A — shell height (HS); B — shell width (WS); C — shell form index (FS). Significant values of Moran's index indicated as solid circles.

Fig. 1 in Spatial Variation Of The Land Snail Brephulopsis Cylindrica (Gastropoda, Pulmonata, Enidae): A Fractal Approach

Fig. 1. The variation of morphometric shell traits in B. cylindrica from different sample sites: A — shell height (HS); B — shell width (WS); C — shell form index (FS).

Fig. 6 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract

Fig. 6: Spatial variation of copepod demographic class density: copepod nauplii, copepodit and adult males and females along the west and east coasts of Djerba Island.

Fig 8 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract

Fig 8: Correlation matrix (Pearson test) for biological variables in relation to abiotic variables determined along the west and east coasts of Djerba Island.

Fig. 4 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract

Fig. 4: Spatial variations of microphytoplankton abundance, microphytoplankton groups, dominant species, species richness and species diversity index along the west and east coasts of Djerba Island.

Fig. 7 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract

Fig. 7: Principal component analysis (PCA) (axis I and II) of microphytoplankton and zooplankton communities' abundance and selected environmental variables along the west and east coasts of Djerba Island.

Fig. 3 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract

Fig. 3: Spatial variations of nutrient concentrations: nitrite (NO -), nitrate (NO -), ammonium (NH +), total nitrogen (T- 2 3 4 N), orthophosphate (PO 3-), total phosphate (T-P), N/P ratio, 4 and silicate along the west and east coasts of Djerba Island.

Fig. 1 in Spatial variation of summer microphytoplankton and zooplankton communities related to environmental parameters in the coastal area of Djerba Island (Tunisia, Eastern Mediterranean) Abstract

Fig. 1: Location of sampling stations along the western and eastern coasts of Djerba Island. The grey contour lines in the maps show the position of the isobaths and the numbers in parenthesis indicate the depths of these isobaths. Table 1. Sampling date, depth, latitude and longitude of sampled stations.

opencc-by-4.0May 2010View details →

Fig. 2 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population

Fig. 2. Cluster analyses of imperial eagle breeding areas based on prey composition data. Region codes are presented in Fig. 1. Codes with bold characters represent mountainous habitats. The single breeding pair of the Cserehát Mountains was excluded from the analysis, because of low sample size