Post provided by Jana McPherson
Correlative distribution models have become essential tools in conservation, macroecology and ecology more generally. They help turn limited occurrence records into predictive maps that help us get a better sense of where species might be found, which areas might be critical for their protection, how large their range currently is, and how it might change with climate change, urban encroachment or other forms of habitat conversion.
It can be frustrating, however, when species distribution models (and the predictive maps they produce) don’t adequately capture what we already know about the habitat needs of a species. A major challenge to date has been to represent the environmental needs of species that require distinct habitats during different life stages or behavioural states. Rainbow parrotfish (Scarus guacamaia), for example, spend their youth sheltered from predators in mangrove areas before moving onto coral reefs, and European nightjars (Caprimulgus europaeus) breed in heathland but require access to grazed grassland for foraging. Correlative distribution models confronted with occurrence records from both life stages or behavioural modes tend to produce poor predictive maps because they confound these distinct requirements.
Veronica Frans and her colleagues propose a simple, three-in-one solution to this problem in their recent article ‘Quantifying apart what belongs together: A multi-state species distribution modelling framework for species using distinct habitats’. Separate distribution models are calibrated for each ‘state’ (life stage or behavioural mode) and combined into a single, easy to interpret map in one of three ways. The first maps which (and how many) of the distinct habitats requirements are met within each site or predictive cell. The other two approaches recognise that, depending on the spatial resolution of the model, distinct habitat needs may not all have to be met in one cell, but may have to be met within a certain distance or be associated with minimum area requirements.
Their elegant solution to the problem is illustrated by way of mapping the sandy beaches, grassy areas and forests required by female New Zealand sea lions and their pups during three distinct phases of the breeding period. The multi-state model identified up to 77 potentially suitable breeding sites in the study area.
To find out more, read the Methods in Ecology and Evolution article ‘Quantifying apart what belongs together: A multi-state species distribution modelling framework for species using distinct habitats’ by Frans et al.
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