Conservation planning: using only one habitat model (even if validated), as the foundation of a conservation plan is risky.

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

D. Todd Jones-Farrand, Todd M. Fearer, Wayne E. Thogmartin,Frank R. Thompson III,Mark D. Nelson, and John M. Tirpak

Ecological Applications  Volume 21, Issue 6 (September 2011)

In conservation planning process selection of a suitable modeling approach is a very important step.

Here the researchers look at two statistical and three theoretical habitat modeling approaches These represens those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA).

The researchers focused their comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. They used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence.

The researchers found that rank correlations were significantly positive among models for each species. This is an indication of general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P < 0.05). Redheaded Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region.

The researchers assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This in turn allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk.

The researchers sign off with the following words “Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.”