نتایج جستجو برای: species distribution model sdms
تعداد نتایج: 3026550 فیلتر نتایج به سال:
Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology. The spatial distribution of fish populations observed in the wild results from the complex interactions of multiple controls both external or internal to the fish populations. Whilst species distribution models (SDMs) have been mostly concerned with static description of specie...
Exogenous selection via interactions between organisms and environments may influence the dynamics of hybrid zones between species in multiple ways. Two major models of a hybrid zone allowed us to hypothesize that environmental conditions influence hybrid zone dynamics in two ways. In the first model, an environmental gradient determines the mosaic distribution at the boundary between ecologica...
Species distribution models (SDMs) are a general suite of models that relate the frequency of species occurrences (presence only or presence/absence) to sets of environmental variables. These relationships can then be used to generate predictions of the geographic areas where the species are expected to occur, making SDMs powerful and widely used tools in conservation biology, biogeography and ...
Questions: To what extent do plant species traits, including life history, life form, and disturbance response characteristics, affect the degree to which species distributions are determined by physical environmental factors? Is the strength of the relationship between species distribution and environment stronger in some disturbance-response types than in others? Location: California southwes...
Good forecasts of climate change impacts on extinction risks are critical for effective conservation management responses. Species distribution models (SDMs) are central to extinction risk analyses. The reliability of predictions of SDMs has been questioned because models often lack a mechanistic underpinning and rely on assumptions that are untenable under climate change. We show how integrati...
Based on an integrative taxonomic approach, we examine the differentiation of Southeast Asian snail-eating turtles using information from 1863 bp of mitochondrial DNA, 12 microsatellite loci, morphology and a correlative species distribution model. Our analyses reveal three genetically distinct groups with limited mitochondrial introgression in one group. All three groups exhibit distinct nucle...
When species distribution models (SDMs) are used to predict how a species will respond to environmental change, an important assumption is that the environmental niche of the species is conserved over evolutionary time-scales. Empirical studies conducted at ecological time-scales, however, demonstrate that the niche of some species can vary in response to environmental change. We use habitat an...
Climate change may pose challenges to the conservation of plant species such as the Fritillaria imperialis that have narrow geographical distribution. In this study, the modeling suitable habitats of F.imperialis in Iran was done in the current condition and under climate change (2050). For this purpose, 78 species presence data along with 12 environmental variables including bioclimatic, physi...
Functional connectivity is essential for the long-term persistence of populations. However, many studies assess connectivity with a focus on structural connectivity only. Cityscapes, namely urban landscapes, are particularly dynamic and include numerous potential anthropogenic barriers to animal movements, such as roads, traffic or buildings. To assess and compare structural connectivity of hab...
Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models...
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