Niches for Species, a multi-species model to guide woodland management: An example based on Scotland’s native woodlands

Abstract

Designating and managing areas with the aim of protecting biodiversity requires information on species distributions and habitat associations, but a lack of reliable occurrence records for rare and threatened species precludes robust empirical modelling. Managers of Scotland's native woodlands are obliged to consider 208 protected species, which each have their own, narrow niche requirements. To support decision-making, we developed Niches for Species (N4S), a model that uses expert knowledge to predict the potential occurrence of 179 woodland protected species representing a range of taxa: mammals, birds, invertebrates, fungi, bryophytes, lichens and vascular plants. Few existing knowledge-based models have attempted to include so many species. We collated knowledge to define each species' suitable habitat according to a hierarchical habitat classification: woodland type, stand structure and microhabitat. Various spatial environmental datasets were used singly or in combination to classify and map Scotland's native woodlands accordingly, thus Niches for Species 3 allowing predictive mapping of each species' potential niche. We illustrate how the outputs can inform individual species management, or can be summarised across species and regions to provide an indicator of woodland biodiversity potential for landscape scale decisions. We tested the model for ten species using available occurrence records. Although concordance between predicted and observed distributions was indicated for nine of these species, this relationship was statistically significant in only five cases. We discuss the difficulties in reliably testing predictions when the records available for rare species are typically low in number, patchy and biased, and suggest future model improvements. Finally, we demonstrate how using N4S to synthesise complex, multi-species information into an easily digestible format can help policy makers and practitioners consider large numbers of species and their conservation needs.

Potential Impact of Climate Change on the Forest Coverage and the Spatial Distribution of 19 Key Forest Tree Species in Italy under RCP4.5 IPCC Trajectory for 2050s

“…Climate change represents an important challenge for ecologists, biologists, and modelers whose research interest is the study of the potential effect of climate change on ecosystem services provided by forests [1][2][3][4]. The use of predictive models and statistical tools in scientific literature has increased since the 1980s [5][6][7], aimed at stimulating the most likely effect of climate change. A predicted spatial movement of ranges and suitable envelopes has been often the main result in many research papers.…”

Application of the Continuum Suitability Index (CSI) model to display the permeability of the Alpine-Dinaric landscape and to define intervention priorities for ecological linkages

“…Although the expert opinions introduced some bias, they were successfully used in biodiversity conservation studies where su cient data was not available (Di Febbraro et al, 2018;Broome et al, 2019). With 21.2% of the surface assigned to SACA1 category, the DINALPCONNECT study area shows a higher degree of naturalness compared to the EUSALP macro-region (8%, as in Plassmann et al, 2019).…”

Potential impact of climate change on the spatial distribution of key forest tree species in Italy under RCP4.5 for 2050s

“…Climate change represents an important challenge for ecologists, biologists and modellers whose research interest is the study of the potential effect of climate change on ecosystem services provided by forests (Deal et al 2017;Benito Garzón et al 2019;Fréjaville et al 2019;Ray et al 2019). The use of predictive models and statistical tools has registered an increased interest in scienti c literature since the 1980s (Falk and Mellert 2011;Di Biase et al 2018;Broome et al 2019) aimed at stimulating the most likely effect of climate change. A predicted spatial movement of ranges and suitable envelopes has been often the main result, both across a geographic and/or an altitudinal gradient (Lenoir et al 2008) representing one of the possible response of forest tree species to climate change impact (O'Neill et al 2008; Williams and Dumroese 2013).…”