In a recent study*, focused on the identification of climate-resilent areas for ten vertebrate species in the verge of extinction to adapt to climate change in North Western France, we observed that the use of data at distinct temporal resolutions (ie. maps respecting time-frames distanced by different time-lengths - in the case, 30, 10 and 1 yrs) provided very dissimilar overviews about: a) the locations where to invest conservation efforts; b) the timings those locations are prediced to provide high adaptive value for each species, and; c) the measured success of current established conservation areas in the region in safeguarding those adaptive paths.
Because spatial resolute climate data are usually available at crude temporal resolutions (30 yrs time intervals) here we support that, instead on relying on linear assumptions about the trajectories of species within large intervals of time, planners may consider to statistically treat climate data into less discrete resolutions (eg. spurious linear interpolations) and
use those data to appraise with more detail the climate-adaptive regions potentially used by species when following their dynamic suitable climates.
With the lack of quality data, uncertainty needs to be integrated in long-term predictive plans and some degree of freedom needs to be assumed such to adapt the proposed optimized solutions to unmodelled factors and to the other socioeconomic dimensions, part of production landscapes, which dominate Central and Southern European lands - Bocage landscapes (the arena herein studied), Montado and Dehesa in Iberian Peninsula, among many others.
* Dupont-Doaré, C; Alagador, D. 2021. Overlooked effects of temporal resolution choice on climate-proof spatial conservation plans for biodiversity. Biological Conservation, 263: 109330
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