Kia ora all,

we are pleased to share our latest publication on the spatial transferability 
of species distribution models for Hector's dolphin. Article is available here: 
https://onlinelibrary.wiley.com/doi/10.1002/ece3.70074.

Abstract: Species distribution models (SDMs) can be used to predict 
distributions in novel times or space (termed transferability) and fill 
knowledge gaps for areas that are data poor. In conservation, this can be used 
to determine the extent of spatial protection required. To understand how well 
a model transfers spatially, it needs to be independently tested, using data 
from novel habitats. Here, we test the transferability of SDMs for Hector's 
dolphin (Cephalorhynchus hectori), a culturally important (taonga) and 
endangered, coastal delphinid, endemic to Aotearoa New Zealand. We collected 
summer distribution data from three populations from 2021 to 2023. Using 
Generalised Additive Models, we built presence/absence SDMs for each population 
and validated the predictive ability of the top models (with TSS and AUC). 
Then, we tested the transferability of each top model by predicting the 
distribution of the remaining two populations. SDMs for two populations showed 
useful performance within their respective areas (Banks Peninsula and Otago), 
but when used to predict the two areas outside the models' source data, 
performance declined markedly. SDMs from the third area (Timaru) performed 
poorly, both for prediction within the source area and when transferred 
spatially. When data for model building were combined from two areas, results 
were mixed. Model interpolation was better when presence/absence data from 
Otago, an area of low density, were combined with data from areas of higher 
density, but was otherwise poor. The overall poor transferability of SDMs 
suggests that habitat preferences of Hector's dolphins vary between areas. For 
these dolphins, population-specific distribution data should be used for 
conservation planning. More generally, we demonstrate that a one model fits all 
approach is not always suitable. When SDMs are used to predict distribution in 
data-poor areas an assessment of performance in the new habitat is required, 
and results should be interpreted with caution.

--------------------------------------
Steph Bennington (she/her)
PhD candidate
Marine Megafauna Research Group
Department of Marine Science,
University of Otago, Dunedin, NZ
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