PMID- 28708854
OWN - NLM
STAT- MEDLINE
DCOM- 20170927
LR  - 20240326
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 12
IP  - 7
DP  - 2017
TI  - Missing in action: Species competition is a neglected predictor variable in 
      species distribution modelling.
PG  - e0181088
LID - 10.1371/journal.pone.0181088 [doi]
LID - e0181088
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.
FAU - Mpakairi, Kudzai Shaun
AU  - Mpakairi KS
AD  - Department of Geography and Environmental Science, University of Zimbabwe, 
      Harare, Zimbabwe.
FAU - Ndaimani, Henry
AU  - Ndaimani H
AD  - Department of Geography and Environmental Science, University of Zimbabwe, 
      Harare, Zimbabwe.
FAU - Tagwireyi, Paradzayi
AU  - Tagwireyi P
AUID- ORCID: 0000-0001-6065-918X
AD  - Department of Geography and Environmental Science, University of Zimbabwe, 
      Harare, Zimbabwe.
FAU - Gara, Tawanda Winmore
AU  - Gara TW
AD  - Department of Geography and Environmental Science, University of Zimbabwe, 
      Harare, Zimbabwe.
AD  - Faculty of Geo-Information Science and Earth Observation (ITC), University of 
      Twente, Enschede, The Netherlands.
FAU - Zvidzai, Mark
AU  - Zvidzai M
AD  - Department of Geography and Environmental Science, University of Zimbabwe, 
      Harare, Zimbabwe.
FAU - Madhlamoto, Daphine
AU  - Madhlamoto D
AD  - Zimbabwe Parks and Wildlife Management Authority, Gonarezhou National Park, 
      Chiredzi, Zimbabwe.
LA  - eng
PT  - Journal Article
DEP - 20170714
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Algorithms
MH  - Animals
MH  - Artiodactyla/*physiology
MH  - Ecosystem
MH  - Equidae/*physiology
MH  - *Models, Biological
MH  - Population Dynamics
MH  - Zimbabwe
PMC - PMC5510852
COIS- Competing Interests: The authors have declared that no competing interests exist.
EDAT- 2017/07/15 06:00
MHDA- 2017/09/28 06:00
PMCR- 2017/07/14
CRDT- 2017/07/15 06:00
PHST- 2016/12/28 00:00 [received]
PHST- 2017/06/25 00:00 [accepted]
PHST- 2017/07/15 06:00 [entrez]
PHST- 2017/07/15 06:00 [pubmed]
PHST- 2017/09/28 06:00 [medline]
PHST- 2017/07/14 00:00 [pmc-release]
AID - PONE-D-16-51265 [pii]
AID - 10.1371/journal.pone.0181088 [doi]
PST - epublish
SO  - PLoS One. 2017 Jul 14;12(7):e0181088. doi: 10.1371/journal.pone.0181088. 
      eCollection 2017.