Potential distribution of emerald ash borer: What can we learn from ecological niche models using Maxent and GARP?

Sobek-Swant, Stephanie; Kluza, Daniel A.; Cuddington, Kim; Lyons, D. Barry

doi:10.1016/j.foreco.2012.06.017

Cited by 102 publications

(56 citation statements)

References 56 publications

(53 reference statements)

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“…We assumed that this area reflects the geographic region that has been accessible to the species over relevant time periods (M in the BAM framework; Peterson et al., ). We randomly chose 20% of the 453 unique occurrences of collared peccary and left them aside for model evaluations. Thus, we used the remaining 363 occurrences and the environmental values (see the section environmental variables) correspondent to the extent of the study area for model development. We modelled the ecological niche of the collared peccary using GARP (Genetic Algorithm for Rule‐set Production; e.g., Kumara & Suganthasakthivel, ; Sobek‐Swant, Kluza, Cuddington, & Lyons, ; Peterson, Radocy, Hall, Peterhans, & Celesia, ; Gentry, Sturm, & Peterson, ), a machine learning algorithm that works in an artificial intelligence framework. GARP detects non‐random relationships between species’ occurrences and pseudo‐absences in relation to environmental variables.…”

Section: Methodsmentioning

confidence: 99%

Niche centrality and human influence predict rangewide variation in population abundance of a widespread mammal: The collared peccary (Pecari tajacu)

Martínez-Gutiérrez

Martínez‐Meyer

Palomares

et al. 2017

Diversity and Distributions

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Aim: (1) To evaluate whether geographic variation in population abundance of a widespread mammal (Pecari tajacu) is related to its location with respect to the centroid of its ecological niche or to the centroid of its geographic range. (2) To assess whether the abundance-niche centrality relationship defines the maximum expected abundance at any location, rather than the realized abundance. (3) To test whether including human impacts improves the abundance-niche centrality relationship, and therefore the prediction of geographic variation in population abundance.Location: The Americas. Methods:We modelled the ecological niche of the species using occurrence and environmental data and created spatial models of distance to the niche centroid (DNC) and to the geographic centroid (DGC). We tested the relationships between population abundance and DNC and between abundance and DGC. We evaluated whether the rate of change in the abundance-DNC relationship was steeper near the upper boundary of quantile regressions. We tested whether the human influence index (HII) contributed to improve niche-based predictions of population abundance. Finally, we generated broad-scale predictions of collared peccary population abundances. Results:We found a negative relationship between abundance and DNC and a nonsignificant relationship between abundance and DGC. The abundance-DNC relationship was wedge-shaped, steeper in the upper quantile boundary than in the median.HII also had a negative effect on abundance. The model including DNC and HII was best supported for predicting the median abundance, while DNC alone was the best to predict the upper boundary of population abundances. Main conclusions:Population abundances are associated with the structure of the ecological niche, especially the maximum abundance expected in an area. Thus, the DNC approach can be useful in obtaining a spatial approximation of potential abundance patterns at biogeographic extents. To achieve a better prediction of realized abundances, it is critical to consider the human influence. K E Y W O R D Sabundance prediction, distribution range, ecological niche modelling, human influence index, range centroid, spatial abundance patterns

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Section: Methodsmentioning

confidence: 99%

Niche centrality and human influence predict rangewide variation in population abundance of a widespread mammal: The collared peccary (Pecari tajacu)

Martínez-Gutiérrez

Martínez‐Meyer

Palomares

et al. 2017

Diversity and Distributions

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“…; Sobek‐Swant et al. ), and estimating response to global climate change (Guisan and Thuiller ). An implicit assumption of SDMs is that in sites predicted to be highly suitable, species would have higher fitness compared to sites predicted to be poorly suitable (Guisan and Thuiller ); however, this relationship is rarely tested.…”

Section: Introductionmentioning

confidence: 99%

Confronting species distribution model predictions with species functional traits

Wittmann

Barnes

Jerde

et al. 2016

Ecology and Evolution

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Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day−1. Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = −0.26, 95% CI (−0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

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“…However, Qin et al () concluded the opposite; for large sample sizes ( n > 150) like ours, which used 634 GARP training points, Terribile and Diniz‐Filho () reported that Maxent and GARP were similar in their predicted areas. One of the commonly stated weaknesses of GARP is its potential to overestimate the geographic range and generate false positives (Elith and Graham , Sobek‐Swant et al ). If these over predictions did occur, then our extent:summer range ratio is a more conservative estimate of the area affected, which we would argue is preferred for species protection initiatives.…”

Section: Discussionmentioning

confidence: 99%

Red bat fatality: Geographic extents through deuterium and niche models

et al. 2019

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Bat fatality at wind energy facilities is a conservation issue, but its effect on bat populations is difficult to estimate. We have little understanding of wind turbine effects on bat population persistence, in part because we have poor knowledge of bat migration pathways and hence the source populations for individual fatalities. We used deuterium ratio analysis combined with genetic algorithm for rule‐set prediction and the web‐based isoscapes modeling, analysis, and prediction in a geographic information system environment as a novel approach. Our objectives were to explore the utility of these methods together and map the geographic extents of eastern red bat (Lasiurus borealis) specimens salvaged in 2008–2010 from a single, 92‐km2 wind energy facility in Illinois, USA. Results indicate that combining these methods can be successful and support their use with species where ranges may be less well defined. Because of the migratory nature of this species and the range of deuterium values of pixels in our isotope model, we predicted that 18% and 82% of the specimens would have isotope results inside and outside of the wind facility's isocline respectively. We concluded that 71.4% of the specimens had isotope signatures placing them outside the wind facility's isocline. It could be argued that the wide distribution of bat fatalities dilutes the overall effect of those fatalities on the bat species; however, if other facilities show a similar pattern, each facility could have cumulative and far reaching population‐level effects. © 2019 The Wildlife Society.

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Potential distribution of emerald ash borer: What can we learn from ecological niche models using Maxent and GARP?

Cited by 102 publications

References 56 publications

Niche centrality and human influence predict rangewide variation in population abundance of a widespread mammal: The collared peccary (Pecari tajacu)

Niche centrality and human influence predict rangewide variation in population abundance of a widespread mammal: The collared peccary (Pecari tajacu)

Confronting species distribution model predictions with species functional traits

Red bat fatality: Geographic extents through deuterium and niche models

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