Browsing by Subject "SPATIAL SCALES"

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  • Mammola, Stefano; Aharon, Shlomi; Seifan, Merav; Lubin, Yael; Gavish-Regev, Efrat (2019)
    Caves are excellent model systems to study the effects of abiotic factors on species distributions due to their selective conditions. Different ecological factors have been shown to affect species distribution depending on the scale of analysis, whether regional or local. The interplay between local and regional factors in explaining the spatial distribution of cave-dwelling organisms is poorly understood. Using the troglophilic subterranean spider Artema nephilit (Araneae: Pholcidae) as a model organism, we investigated whether similar environmental predictors drive the species distribution at these two spatial scales. At the local scale, we monitored the abundance of the spiders and measured relevant environmental features in 33 caves along the Jordan Rift Valley. We then extended the analysis to a regional scale, investigating the drivers of the distribution using species distribution models. We found that similar ecological factors determined the distribution at both local and regional scales for A. nephilit. At a local scale, the species was found to preferentially occupy the outermost, illuminated, and warmer sectors of caves. Similarly, mean annual temperature, annual temperature range, and solar radiation were the most important drivers of its regional distribution. By investigating these two spatial scales simultaneously, we showed that it was possible to achieve an in-depth understanding of the environmental conditions that governs subterranean species distribution.
  • Nikula, Ari; Nivala, Vesa; Matala, Juho; Heliövaara, Kari Tapani (2019)
    We modelled the effect of habitat composition and roads on the number and occurrence of moose (Alces alces L.) damage in Ostrobothnia and Lapland using a zero-inflated count model. Models were developed for 1 km(2), 25 km(2) and 100 km(2) landscapes consisting of equilateral rectangular grid cells. Count models predict the number of damage, i.e. the number of plantations and zero models the probability of a landscape being without damage for a given habitat composition. The number of moose damage in neighboring grid cells was a significant predictor in all models. The proportion of mature forest was the most frequent significant variable, and an increasing admixture of mature forests among plantations increased the number and occurrence of damage. The amount of all types of plantations was the second most common significant variable predicting increasing damage along with increasing amount of plantations. An increase in thinning forests as an admixture also increased damage in 1 km(2) landscapes in both areas, whereas an increase in pine-dominated thinning forests in Lapland reduced the number of damage in 25 km(2) landscapes. An increasing amount of inhabited areas in Ostrobothnia and the length of connecting roads in Lapland reduced the number of damage in 1 and 25 km(2) landscapes. Differences in model variables between areas suggest that models of moose damage risk should be adjusted according to characteristics that are specific to the study area.
  • Mod, Heidi K.; Chevalier, Mathieu; Luoto, Miska; Guisan, Antoine (2020)
    A comprehensive understanding of the scale dependency of environmental filtering and biotic interactions influencing the local assembly of species is paramount to derive realistic forecasts of the future of biodiversity and efficiently manage ecological communities. A classical assumption is that environmental filters are more prevalent at coarser scales with diminishing effects towards the finest scales where biotic interactions become more decisive. Recently, a refinement was proposed stipulating that the scale dependency of biotic interactions should relate to the type of interaction. Specifically, the effect of negative interactions (e.g. competition) should diminish with coarsening scale, whereas positive interactions (i.e. facilitation) should be detected irrespective of the scale. We use multiple vascular plant species datasets sampled at nested spatial scales (plot size varying from 0.04 to 64 m(2)) and recently developed joint species distribution models to test the hypotheses. Our analyses indicate slightly stronger environmental filtering with increasing plot size. While the overall strength of biotic interactions did not vary consistently across scales, we found a tendency for negative interactions to fade away with increasing plot size slightly more than positive interactions. Synthesis. We provide partial, but not unambiguous, evidence of the scale dependency of ecological assembly rules. However, our correlative methodology only allows us to interpret the findings as indication of environmental filtering and biotic interactions.