nicholson-influenceofdata-2019.pdf (902.45 kB)
The influence of data source and species distribution modelling method on spatial conservation priorities
journal contribution
posted on 2019-07-01, 00:00 authored by W La Marca, J Elith, R S C Firth, B P Murphy, T J Regan, J C Z Woinarski, Emily NicholsonEmily NicholsonAim: Species distribution models are an important conservation tool; however, performance can vary with factors including data inputs and modelling method. Model outputs are often under‐evaluated for explanatory and predictive capacity. Our aim was to evaluate the capacity of existing data for seven small mammal species to provide useful inferences for management planning. Location: Bathurst and Melville (collectively the Tiwi) Islands, Northern Territory, Australia. Methods: We developed species distribution models (SDMs) with generalized linear models (GLMs) and boosted regression trees (BRTs) using survey data (351 sites) of small mammals, with two sets of environmental predictors: (a) field‐study measurements and (b) available remotely sensed rasters. Predictive capacity of models was evaluated using percentage of deviance explained (�) and area under the receiver operating characteristic curve (AUC). We used Marxan to evaluate the influence of different model and data types as input for identifying spatial priorities. Results: Field‐informed SDMs performed well across both modelling methods, with relatively high test AUC values (mean = 0.82, range = 0.64–0.97) and test � (mean = 22.5%, range = 3.5%–65.8%). Remotely sensed models performed relatively poorly, with lower test AUC values (mean = 0.7, range = 0.56–0.86) and lower test � (mean = 8.9%, range = 0.03%–24.9%). A notable exception was remotely sensed models for Melomys burtoni (AUC = 0.85 & 0.86, � = 23.3% & 24.9%, Bathurst and Melville respectively). Marxan site irreplaceability rankings demonstrated low to marginal agreement using field‐informed and remotely sensed inputs (Pearson correlation coefficient = 0.3), and similarly, using GLM and BRT model inputs (0.29). Main conclusions: The occurrence of small mammals on the Tiwi Islands can be reasonably explained with field‐informed variables, but not with remotely sensed alternatives. Different models lead to different conservation priorities. Our work emphasizes the importance of thoroughly testing SDMs prior to decision‐making.
History
Journal
Diversity and distributionsVolume
25Issue
7Pagination
1060 - 1073Publisher
John Wiley & SonsLocation
Chichester, Eng.Publisher DOI
Link to full text
ISSN
1366-9516eISSN
1472-4642Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2019, The AuthorsUsage metrics
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No categories selectedKeywords
ConservationManagement planningSmall mammalsSpecies distribution modellingTiwi IslandsScience & TechnologyLife Sciences & BiomedicineBiodiversity ConservationEcologyBiodiversity & ConservationEnvironmental Sciences & EcologyAUSTRALIAN ISLANDSBIODIVERSITYREGRESSIONUNCERTAINTIESACCURACYRODENTIAMURIDAEFOREST
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