نتایج جستجو برای: species distribution modelling sdm
تعداد نتایج: 1259497 فیلتر نتایج به سال:
MIMO systems using a space division multiplexing (SDM) technique in which each transmit antenna sends an independent signal substream have been studied as one of the successful applications to increase data rates in wireless communications. The throughput of a MIMO channel can be maximized by using an eigenbeam-SDM (E-SDM) technique, and this paper investigates the practical performance of 2×2 ...
Spatial records of species are commonly misidentified, which can change the predicted distribution of a species obtained from a species distribution model (SDM). Experiments were undertaken to predict the distribution of real and simulated species using MaxEnt and presence-only data “contaminated” with varying rates of misidentification error. Additionally, the difference between the niche of t...
Spatial records of species are commonly misidentified, which can change the predicted distribution of a species obtained from a species distribution model (SDM). Experiments were undertaken to predict the distribution of real and simulated species using MaxEnt and presence-only data contaminated with varying rates of misidentification error. Additionally, the difference between the niche of t...
Evolution may improve the invasiveness of populations, but it often remains unclear whether key adaptation events occur after introduction into the recipient habitat (i.e. post-introduction adaptation scenario), or before introduction within the native range (i.e. prior-adaptation scenario) or at a primary site of invasion (i.e. bridgehead scenario). We used a multidisciplinary approach to dete...
Predictions of future species' ranges under climate change are needed for conservation planning, for which species distribution models (SDMs) are widely used. However, global climate model-based (GCM) output grids can bias the area identified as suitable when these are used as SDM predictor variables, because GCM outputs, typically at least 50x50 km, are biologically coarse. We tested the assum...
Lorestan newt (Neurergus kaiseri) is an endemic species which has restricted dispersal in southern Zagros Mountains in Iran, and it is listed as critically endangered in IUCN red list. Today the populations of this species are decreasing and facing serious threats. In this study, habitat suitability of Neurergus kaiseri was evaluated using a MaxEnt modelling approach according to environmental ...
This paper is a case study applying our story driven modelling approach to the Paderborn Shuttle system application. Story Driven Modeling (SDM) aims to provide a very systematic process for the development of object oriented software , cf. [KNNZ00, Zuen01]. A crucial step of SDM is the derivation of general behavior specifications from a number of analysis scenarios. Based on a large number of...
Beach litter accumulation patterns are influenced by biotic and abiotic factors, as well the distribution of anthropogenic sources. Although importance comprehensive approaches to deal with pollution is acknowledged, integrated studies including geomorphologic, biotic, anthropic factors in relation beach debris still needed. In this perspective, Species Distribution Models (SDMs) might represen...
Species distribution models (SDMs) are empirical models relating species occurrence to environmental variables based on statistical or other response surfaces. Species distribution modeling can be used as a tool to solve many theoretical and applied ecological and environmental problems, which include testing biogeographical, ecological and evolutionary hypotheses, assessing species invasion an...
The largest plateau Tibetan Plateau supplied an excellent opportunity to investigate the influence of the Pleistocene events on the high-elevation species. To test for the alternative hypotheses of Pleistocene glacial refugia, we used partial sequences of two mitochondrial genes and one nuclear gene to examine the phylogeographic patterns of the endemic frog species Nanorana pleskei across its ...
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