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Evaluating performance of aerial survey data in elephant habitat modelling
Author(s) -
Ndaimani Henry,
Murwira Amon,
Masocha Mhosisi,
Gara Tawanda W.,
Zengeya Fadzai M.
Publication year - 2017
Publication title -
african journal of ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.499
H-Index - 54
eISSN - 1365-2028
pISSN - 0141-6707
DOI - 10.1111/aje.12348
Subject(s) - aerial survey , habitat , woodland , geography , wildlife , normalized difference vegetation index , ecology , forestry , cartography , physical geography , biology , leaf area index
Aerial survey data are widely used to model distribution of wildlife. However, their performance in habitat modelling remains largely untested. We used aerial survey and satellite‐linked Global Positioning System ( GPS ) collar data for elephants, to test (i) whether there is an optimal spatial resolution of predictor variables at which habitat models based on aerial survey data that are uncorrected for locational error can accurately predict elephant habitat and (ii) whether habitat models based on these data sets can accurately predict the presence of elephants in closed woodland habitats. We applied maximum entropy modelling (Maxent) to these data sets and used the Normalised Difference Vegetation Index ( NDVI ) as well as distance from water points as the habitat predictors to answer these questions. Our results demonstrate better ability of aerial survey data to predict elephant presence at the coarser spatial resolution of 1000 m of both predictor variables. Habitat models derived from aerial survey data underpredicted elephant presence in more closed woodland habitats than those derived from GPS collar data. This result implies that elephants located under dense tree canopies are likely missed during an aerial survey. Our study is one of the first to empirically test and report results on the poor performance of aerial survey data in habitat modelling especially in dense woodlands.