Missing in action: Species competition is a neglected predictor variable in species distribution modelling

Kudzai Shaun Mpakairi, Henry Ndaimani, Paradzayi Tagwireyi, Tawanda Winmore Gara, Mark Zvidzai, Daphine Madhlamoto

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)
39 Downloads (Pure)

Abstract

The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.

Original languageEnglish
Article numbere0181088
JournalPLoS ONE
Volume12
Issue number7
DOIs
Publication statusPublished - 1 Jul 2017

Fingerprint

Herbivory
Equidae
Buffaloes
Ecosystem
Swine
biogeography
Zimbabwe
Proxy
Phacochoerus aethiopicus
wildebeest
zebras
Soil
buffaloes
Water
herbivores
habitat preferences
ecologists
roads
national parks
community structure

Cite this

Mpakairi, K. S., Ndaimani, H., Tagwireyi, P., Gara, T. W., Zvidzai, M., & Madhlamoto, D. (2017). Missing in action: Species competition is a neglected predictor variable in species distribution modelling. PLoS ONE, 12(7), [e0181088]. https://doi.org/10.1371/journal.pone.0181088
Mpakairi, Kudzai Shaun ; Ndaimani, Henry ; Tagwireyi, Paradzayi ; Gara, Tawanda Winmore ; Zvidzai, Mark ; Madhlamoto, Daphine. / Missing in action : Species competition is a neglected predictor variable in species distribution modelling. In: PLoS ONE. 2017 ; Vol. 12, No. 7.
@article{178cdb30ef3a4109b64ae23a4f258774,
title = "Missing in action: Species competition is a neglected predictor variable in species distribution modelling",
abstract = "The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.",
author = "Mpakairi, {Kudzai Shaun} and Henry Ndaimani and Paradzayi Tagwireyi and Gara, {Tawanda Winmore} and Mark Zvidzai and Daphine Madhlamoto",
year = "2017",
month = "7",
day = "1",
doi = "10.1371/journal.pone.0181088",
language = "English",
volume = "12",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "7",

}

Mpakairi, KS, Ndaimani, H, Tagwireyi, P, Gara, TW, Zvidzai, M & Madhlamoto, D 2017, 'Missing in action: Species competition is a neglected predictor variable in species distribution modelling' PLoS ONE, vol. 12, no. 7, e0181088. https://doi.org/10.1371/journal.pone.0181088

Missing in action : Species competition is a neglected predictor variable in species distribution modelling. / Mpakairi, Kudzai Shaun; Ndaimani, Henry; Tagwireyi, Paradzayi; Gara, Tawanda Winmore; Zvidzai, Mark; Madhlamoto, Daphine.

In: PLoS ONE, Vol. 12, No. 7, e0181088, 01.07.2017.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Missing in action

T2 - Species competition is a neglected predictor variable in species distribution modelling

AU - Mpakairi, Kudzai Shaun

AU - Ndaimani, Henry

AU - Tagwireyi, Paradzayi

AU - Gara, Tawanda Winmore

AU - Zvidzai, Mark

AU - Madhlamoto, Daphine

PY - 2017/7/1

Y1 - 2017/7/1

N2 - The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.

AB - The central role of species competition in shaping community structure in ecosystems is well appreciated amongst ecologists. However species competition is a consistently missing variable in Species Distribution Modelling (SDM). This study presents results of our attempt to incorporate species competition in SDMs. We used a suit of predictor variables including Soil Adjusted Vegetation Index (SAVI), as well as distance from roads, settlements and water, fire frequency and distance from the nearest herbivore sighting (of selected herbivores) to model individual habitat preferences of five grazer species (buffalo, warthog, waterbuck, wildebeest and zebra) with the Ensemble SDM algorithm for Gonarezhou National Park, Zimbabwe. Our results showed that distance from the nearest animal sighting (a proxy for competition among grazers) was the best predictor of the potential distribution of buffalo, wildebeest and zebra but the second best predictor for warthog and waterbuck. Our findings provide evidence to that competition is an important predictor of grazer species’ potential distribution. These findings suggest that species distribution modelling that neglects species competition may be inadequate in explaining the potential distribution of species. Therefore our findings encourage the inclusion of competition in SDM as well as potentially igniting discussions that may lead to improving the predictive power of future SDM efforts.

UR - http://www.scopus.com/inward/record.url?scp=85023776391&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0181088

DO - 10.1371/journal.pone.0181088

M3 - Article

VL - 12

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 7

M1 - e0181088

ER -