Uses and Requirements of Ecological Niche Models and Related Distributional Models

Peterson, A. Townsend

doi:10.17161/bi.v3i0.29

Cited by 381 publications

(312 citation statements)

References 124 publications

(141 reference statements)

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“…To focus the analysis where deer are more likely to be found, we developed a species distribution model of white-tailed deer. For this, we used the TRS locations of all tested deer (N = 28,954) and a set of environmental variables (described below) in an ecological niche model (Peterson, 2006). This model was developed using the MaxEnt software, which employs a machine-learning approach to predict the geographical distribution of a species based on presence-only data (Elith et al, 2011).…”

Section: Study Areamentioning

confidence: 99%

Influence of landscape factors and management decisions on spatial and temporal patterns of the transmission of chronic wasting disease in white-tailed deer

et al. 2013

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Abstract. Chronic wasting disease (CWD) has been reported in white-tailed deer at the border of the US states of Illinois and Wisconsin since 2002. Transmission of infectious prions between animals and from the environment has resulted in spatial and temporal structure observable in the spatio-temporal patterns of reported cases. Case locations of 382 positive cases from 28,954 deer tested between 2002 and 2009 provided insight into the potential risk factors and landscape features associated with transmission using a combination of clustering, generalised linear modelling and descriptive evaluations of a risk map of predicted cases of CWD. A species distribution map of white-tailed deer developed using MaxEnt provided an estimate of deer locations. We found that deer probability increased in areas with larger forests and less urban and agricultural lands. Spatial clustering analysis revealed a core area of persistent CWD transmission in the northern part of the region. The regression model indicated that larger and more compact forests were associated with higher risk for CWD. High risk areas also had soils with less clay and more sand than other parts of the region. The transmission potential was higher where landscape features indicated the potential for higher deer concentrations. The inclusion of spatial lag variables improved the model. Of the 102 cases reported in the study area in the two years following the study period, 89 (87%) of those were in the 32% of the study area with the highest 50% of predicted risk of cases.

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Section: Study Areamentioning

confidence: 99%

Influence of landscape factors and management decisions on spatial and temporal patterns of the transmission of chronic wasting disease in white-tailed deer

et al. 2013

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“…Habitat suitability modelling allows the relative importance of environmental factors to be assessed and supports distribution and relative density mapping of such species (Peterson 2006;Hirzel and Lay 2008), and this can be used to prioritise areas for management and protection (Renwick et al 2012;Johnston et al 2015). However, estimating their actual population size is much more problematic, although this is a necessary requirement for evidence-based management of exploited populations (Waber et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Effects of habitat and land use on breeding season density of male Asian Houbara Chlamydotis macqueenii

et al. 2016

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Landscape-scale habitat and land use influences on Asian Houbara Chlamydotis macqueenii (IUCN Vulnerable) remain unstudied, while estimating numbers of this cryptic, low-density, over-hunted species is challenging. In spring 2013, male houbara were recorded at 231 point counts, conducted twice, across a gradient of sheep density and shrub assemblages within 14,300 km 2 of the Kyzylkum Desert, Uzbekistan. Four sets of models related male abundance to: (1) vegetation structure (shrub height and substrate); (2) shrub assemblage; (3) shrub species composition (multidimensional scaling); (4) remote-sensed derived land cover (GLOBCOVER, 4 variables). Each set also incorporated measures of landscape rugosity and sheep density. For each set, multi-model inference was applied to generalised linear mixed models of visit-specific counts that included important detectability covariates and point ID as random effects. Vegetation structure received strongest support, followed by shrub species composition and shrub assemblage, with weakest support for the GLOBCOVER model set. Male houbara numbers were greater with lower mean shrub height, more gravel and flatter surfaces, but were unaffected by sheep density. Male density (mean 0.14 km -2 ) estimated by distance analysis differed substantially among shrub assemblages, being highest in vegetation dominated by Salsola rigida, high in areas of S. arbuscula and Astragalus, respectively, lower in Artemisia and lowest in Calligonum. The study area was estimated to hold 1824 males (CI 1645(CI -2030. The spatial distribution of relative male houbara abundance, predicted from vegetation structure models, had the strongest correspondence with observed numbers in both model calibration and the subsequent year's data. We found no effect of pastoralism on male distribution, but potential effects on nesting females are unknown. Density differences among shrub communities suggest extrapolation to estimate country-or range-wide population size must take into account vegetation composition.

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“…Such models typically use a variety of correlative methods to provide detailed predictions of distributions by relating presence or abundance of species to gradients of observed environmental predictors. As such, nichebased models are used extensively and have provided researchers with an innovative tool to explore diverse questions in ecology and conservation (see Peterson, 2007). In particular, it has become common to use such models to assess potential distribution responses to future climate scenarios (e.g., Bakkenes et al, 2002;Araú jo et al, 2004;Thomas et al, 2004;Thuiller et al, 2005;Gomez-Mendoza & Arriaga, 2007;Thuiller, 2010), using sophisticated interpolation of climate data (e.g., Hijmans et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Predicting the future of forests in the Mediterranean under climate change, with niche- and process-based models: CO2 matters!

Keenan

Serra

Lloret

et al. 2010

Global Change Biology

205

170

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Assessing the potential future of current forest stands is a key to design conservation strategies and understanding potential future impacts to ecosystem service supplies. This is particularly true in the Mediterranean basin, where important future climatic changes are expected. Here, we assess and compare two commonly used modeling approaches (niche-and process-based models) to project the future of current stands of three forest species with contrasting distributions, using regionalized climate for continental Spain. Results highlight variability in model ability to estimate current distributions, and the inherent large uncertainty involved in making projections into the future. CO 2 fertilization through projected increased atmospheric CO 2 concentrations is shown to increase forest productivity in the mechanistic process-based model (despite increased drought stress) by up to three times that of the non-CO 2 fertilization scenario by the period 2050-2080, which is in stark contrast to projections of reduced habitat suitability from the niche-based models by the same period. This highlights the importance of introducing aspects of plant biogeochemistry into current niche-based models for a realistic projection of future species distributions. We conclude that the future of current Mediterranean forest stands is highly uncertain and suggest that a new synergy between niche-and process-based models is urgently needed in order to improve our predictive ability.

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Uses and Requirements of Ecological Niche Models and Related Distributional Models

Cited by 381 publications

References 124 publications

Influence of landscape factors and management decisions on spatial and temporal patterns of the transmission of chronic wasting disease in white-tailed deer

Influence of landscape factors and management decisions on spatial and temporal patterns of the transmission of chronic wasting disease in white-tailed deer

Effects of habitat and land use on breeding season density of male Asian Houbara Chlamydotis macqueenii

Predicting the future of forests in the Mediterranean under climate change, with niche- and process-based models: CO2 matters!

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