scholarly journals Muddy Boots Beget Wisdom: Implications for Rare or Endangered Plant Species Distribution Models

Diversity ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 10 ◽  
Author(s):  
Nora Oleas ◽  
Kenneth Feeley ◽  
Javier Fajardo ◽  
Alan Meerow ◽  
Jennifer Gebelein ◽  
...  
Keyword(s):  
Species Distribution ◽  
Species Distribution Models ◽  
Conservation Strategies ◽  
Distribution Models ◽  
Online Data ◽  
Species Ranges ◽  
Geographic Ranges ◽  
Standard Data ◽  
Herbarium Collections ◽  
Species Specific

Species distribution models (SDMs) are popular tools for predicting the geographic ranges of species. It is common practice to use georeferenced records obtained from online databases to generate these models. Using three species of Phaedranassa (Amaryllidaceae) from the Northern Andes, we compare the geographic ranges as predicted by SDMs based on online records (after standard data cleaning) with SDMs of these records confirmed through extensive field searches. We also review the identification of herbarium collections. The species’ ranges generated with corroborated field records did not agree with the species’ ranges based on the online data. Specifically, geographic ranges based on online data were significantly inflated and had significantly different and wider elevational extents compared to the ranges based on verified field records. Our results suggest that to generate accurate predictions of species’ ranges, occurrence records need to be carefully evaluated with (1) appropriate filters (e.g., altitude range, ecosystem); (2) taxonomic monographs and/or specialist corroboration; and (3) validation through field searches. This study points out the implications of generating SDMs produced with unverified online records to guide species-specific conservation strategies since inaccurate range predictions can have important consequences when estimating species’ extinction risks.

Do species distribution models explain spatial structure within tree species ranges?

2009 ◽  
Vol 18 (6) ◽  
pp. 662-673 ◽  
Author(s):  
Daniel Montoya ◽  
Drew W. Purves ◽  
Itziar R. Urbieta ◽  
Miguel A. Zavala
Keyword(s):  
Spatial Structure ◽  
Species Distribution ◽  
Tree Species ◽  
Species Distribution Models ◽  
Distribution Models ◽  
Species Ranges

scholarly journals Testing the Influence of Seascape Connectivity on Marine-Based Species Distribution Models

2021 ◽  
Vol 8 ◽  
Author(s):  
Giorgia Cecino ◽  
Roozbeh Valavi ◽  
Eric A. Treml
Keyword(s):  
Species Distribution ◽  
Larval Dispersal ◽  
Species Distribution Models ◽  
Temporal Dynamics ◽  
Explanatory Power ◽  
Model Performance ◽  
Boosted Regression Trees ◽  
Distribution Models ◽  
Flexible Tool ◽  
Species Specific

Species distribution models (SDMs) are commonly used in ecology to predict species occurrence probability and how species are geographically distributed. Here, we propose innovative predictive factors to efficiently integrate information on connectivity into SDMs, a key element of population dynamics strongly influencing how species are distributed across seascapes. We also quantify the influence of species-specific connectivity estimates (i.e., larval dispersal vs. adult movement) on the marine-based SDMs outcomes. For illustration, seascape connectivity was modeled for two common, yet contrasting, marine species occurring in southeast Australian waters, the purple sea urchin, Heliocidaris erythrogramma, and the Australasian snapper, Chrysophrys auratus. Our models illustrate how different species-specific larval dispersal and adult movement can be efficiently accommodated. We used network-based centrality metrics to compute patch-level importance values and include these metrics in the group of predictors of correlative SDMs. We employed boosted regression trees (BRT) to fit our models, calculating the predictive performance, comparing spatial predictions and evaluating the relative influence of connectivity-based metrics among other predictors. Network-based metrics provide a flexible tool to quantify seascape connectivity that can be efficiently incorporated into SDMs. Connectivity across larval and adult stages was found to contribute to SDMs predictions and model performance was not negatively influenced from including these connectivity measures. Degree centrality, quantifying incoming and outgoing connections with habitat patches, was the most influential centrality metric. Pairwise interactions between predictors revealed that the species were predominantly found around hubs of connectivity and in warm, high-oxygenated, shallow waters. Additional research is needed to quantify the complex role that habitat network structure and temporal dynamics may have on SDM spatial predictions and explanatory power.

Testing climate-based species distribution models with recent field surveys of pond-breeding amphibians in eastern Missouri

2011 ◽  
Vol 89 (11) ◽  
pp. 1074-1083 ◽  
Author(s):  
D.R. Trumbo ◽  
A.A. Burgett ◽  
J.H. Knouft
Keyword(s):  
Species Distribution ◽  
Species Distribution Models ◽  
Species Range ◽  
Environmental Data ◽  
Limited Attention ◽  
Distribution Models ◽  
Field Surveys ◽  
Geographic Ranges ◽  
Using Data ◽  
Study Species

Species distribution models (SDMs) have become an important tool for ecologists by providing the ability to predict the distributions of organisms based on species niche parameters and available habitat across broad geographic areas. However, investigation of the appropriate extent of environmental data needed to make accurate predictions has received limited attention. We investigate whether SDMs developed with regional climate and species locality data (i.e., within Missouri, USA) produce more accurate predictions of species occurrences than models developed with data from across an entire species range. To test the accuracy of the model predictions, field surveys were performed in 2007 and 2008 at 103 study ponds for eight amphibian study species. Models developed using data from across the entire species range did not accurately predict the occurrences of any study species. However, models developed using data only from Missouri produced accurate predictions for four study species, all of which are near the edge of their geographic ranges within the study area. These results suggest that species distribution modeling with regionally focused data may be preferable for local ecological and conservation purposes, and that climate factors may be more important for determining species distributions at the edge of their geographic ranges.

scholarly journals Species-specific adaptations determine how aridity and biotic interactions drive the assembly of dryland plant communities

2017 ◽  
Author(s):  
Miguel Berdugo ◽  
Fernando T. Maestre ◽  
Sonia Kéfi ◽  
Nicolas Gross ◽  
Yoann Le Bagousse-Pinguet ◽  
...  
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Species Distribution ◽  
Community Assembly ◽  
Species Distribution Models ◽  
List Type ◽  
Relative Importance ◽  
Distribution Models ◽  
Species Specific ◽  
Plant Community Assembly

AbstractDespite being a core ecological question, disentangling individual and interacting effects of plant-plant interactions, abiotic factors and species-specific adaptations as drivers of community assembly is challenging. Studies addressing this issue are growing rapidly, but they generally lack empirical data regarding species interactions and local abundances, or cover a narrow range of environmental conditions.We analysed species distribution models and local spatial patterns to isolate the relative importance of key abiotic (aridity) and biotic (facilitation and competition) drivers of plant community assembly in drylands worldwide. We examined the relative importance of these drivers along aridity gradients and used information derived from the niches of species to understand the role that species-specific adaptations to aridity play in modulating the importance of community assembly drivers.Facilitation, together with aridity, was the major driver of plant community assembly in global drylands. Due to community specialization, the importance of facilitation as an assembly driver decreased with aridity, and became non significant at the border between arid and semiarid climates. Under the most arid conditions, competition affected species abundances in communities dominated by specialist species. Due to community specialization, the importance of aridity in shaping dryland plant communities peaked at moderate aridity levels.Synthesis: We showed that competition is an important driver of community assembly even under harsh environments, and that the effect of facilitation collapses as driver of species relative abundances under high aridity because of the specialization of the species pool to extremely dry conditions. Our findings pave the way to develop more robust species distribution models aiming to predict the consequences of ongoing climate change on community assembly in drylands, the largest biome on Earth.

scholarly journals Scale effects in species distribution models: implications for conservation planning under climate change

2008 ◽  
Vol 5 (1) ◽  
pp. 39-43 ◽  
Author(s):  
Changwan Seo ◽  
James H Thorne ◽  
Lee Hannah ◽  
Wilfried Thuiller
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Climate Model ◽  
Scale Effects ◽  
Global Climate ◽  
Global Climate Model ◽  
Distribution Models ◽  
Species Ranges

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 50×50 km, are biologically coarse. We tested the assumption that species ranges can be equally well portrayed in SDMs operating on base data of different grid sizes by comparing SDM performance statistics and area selected by four SDMs run at seven grid sizes, for nine species of contrasting range size. Area selected was disproportionately larger for SDMs run on larger grid sizes, indicating a cut-off point above which model results were less reliable. Up to 2.89 times more species range area was selected by SDMs operating on grids above 50×50 km, compared to SDMs operating at 1 km 2 . Spatial congruence between areas selected as range also diverged as grid size increased, particularly for species with ranges between 20 000 and 90 000 km 2 . These results indicate the need for caution when using such data to plan future protected areas, because an overly large predicted range could lead to inappropriate reserve location selection.

scholarly journals Species Distribution Models and Ecological Suitability Analysis for Potential Tick Vectors of Lyme Disease in Mexico

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Patricia Illoldi-Rangel ◽  
Chissa-Louise Rivaldi ◽  
Blake Sissel ◽  
Rebecca Trout Fryxell ◽  
Guadalupe Gordillo-Pérez ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Eastern Coast ◽  
Suitability Analysis ◽  
Amblyomma Cajennense ◽  
Distribution Models ◽  
Geographic Ranges ◽  
Lower Temperature ◽  
Tick Vectors

Species distribution models were constructed for tenIxodesspecies andAmblyomma cajennensefor a region including Mexico and Texas. The model was based on a maximum entropy algorithm that used environmental layers to predict the relative probability of presence for each taxon. For Mexico, species geographic ranges were predicted by restricting the models to cells which have a higher probability than the lowest probability of the cells in which a presence record was located. There was spatial nonconcordance between the distributions ofAmblyomma cajennenseand theIxodesgroup with the former restricted to lowlands and mainly the eastern coast of Mexico and the latter to montane regions with lower temperature. The risk of Lyme disease is, therefore, mainly present in the highlands where someIxodesspecies are known vectors; ifAmblyomma cajennenseturns out to be a competent vector, the area of risk also extends to the lowlands and the east coast.

Which species distribution models are more (or less) likely to project broad-scale, climate-induced shifts in species ranges?

2016 ◽  
Vol 342 ◽  
pp. 135-146 ◽  
Author(s):  
Linda J. Beaumont ◽  
Erin Graham ◽  
Daisy Englert Duursma ◽  
Peter D. Wilson ◽  
Abigail Cabrelli ◽  
...  
Keyword(s):  
Species Distribution ◽  
Species Distribution Models ◽  
Distribution Models ◽  
Species Ranges ◽  
Broad Scale
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