Looking to the past to conserve present-day biodiversity: using distributional information and ecological modelling

Species conservation has long focused on preventing human-driven extinctions. Conservation success has therefore been measured using changes in species' extinction risk over the past 50 years, with the primary example being the IUCN Red List of Species. However, recently calls have been made for a parallel focus on species' recovery, and on developing metrics with which to assess its achievement. This shift in perspective within the conservation community can be partially attributed to the recognition that baselines of species' abundance and distribution have shifted dramatically across human generations, with globally detectable human impacts on ecosystems beginning at least several thousand years ago. Assessment of extinction risk generally only considers species' change over the past few decades, whereas assessment of recovery means considering change over centuries to millennia. This requires identifying the baseline status at the time when humans first became a major factor influencing the abundance and distribution of a species.

In order to facilitate research on baselines, the primary aim of the Conservation Paleobiology Network (CPN) working group is the development and implementation of the new IUCN Green Status of Species framework. This framework considers the conservation status of species relative to a pre-impact baseline. Globally-derived palaeo-ecological and historical ecological datasets will be leveraged to facilitate estimation of these distributional baselines. A crucial aspect of this work will be to provide an easily accessible way for practitioners to determine baselines for their species of interest. The goal of the CPN project is to apply methods for predicting species distributions to reconstruct the past range of a given species. The general approach is:
1. Identification of datasets that can be used to inform past species' distributions. The major categories of variables will be:
> Land cover (e.g. LUH2)
> Climate (e.g. BioClim variables, CHELSA)
> Human footprint (e.g. ANTHROMES)
> Species occurrences (e.g. GBIF)
> Historical or Archaeological species' presence points.
2. Model the ecological niche of the species' using current data (such as climate and land cover) and current species occurrences.
3. Use the model with historical data on the predictor variables to extrapolate the species' distribution back in time.
4. Use historical data on species occurrences (such as museum records, fossil data, historical accounts) to validate the model prediction. Priority will be on reconstructing species' distributions in the temporal range 1500 to 1750 CE.

The ultimate goal is to demonstrate and validate a workflow, and to make this workflow widely accessible to conservation assessors. An appropriate starting point is to apply the above approach to one or few species as a demonstration of feasibility and as a way to figure out difficulties. Initial target species should cover a range of habitat niches (terrestrial, freshwater, and marine examples) and spatial scales (localised population to global distribution). Another important element will be to develop and validate alternate workflows when certain elements are missing (e.g. current occurrences exist, but not past occurrences; occurrences exist for related/associated taxa but not focal species).