An empirical, cross-taxon evaluation of landscape-scale connectivity

Abstract

Connectivity is vital for the maintenance of spatially structured ecosystems, but is threatened by anthropogenic processes that degrade habitat networks. Thus, connectivity enhancement has become a conservation priority, with resources dedicated to enhancing habitat networks. However, much effort may be wasted on ineffective management, as conservation theory and practice can be poorly linked. Here we evaluate the success of landscape management designed to restore connectivity in the Humberhead wetlands (UK). Hybrid pattern-process models were created for six species, representing key taxa in the wetland ecosystem. Habitat suitability models were used to provide the spatial context for individual-based models that predicted metapopulation dynamics, including functional connectivity. To create models representing post-management conditions, landscape structure was modified to represent local improvements in habitat quality achieved through management. Models indicate that management had limited success in enhancing connectivity. Interventions have buffered existing connectivity in several species' habitat networks, with inter-patch movement increasing for modelled species by up to 22% (for water vole, Arvicola amphibius), but have not reconnected isolated habitat fragments. Field surveys provided provisional support for the accuracy of baseline models, but could not identify predicted benefits from management interventions, likely due to time-lags following these interventions. Despite lacking clear empirical support as yet, models suggest the management of the Humberhead wetlands has successfully enhanced the landscape-scale ecological network, achieving management targets. However we identify key limitations to this success and provide specific recommendations for improvement of future landscapescale management. Our developments in model application and integration can be developed further and be usefully applied to studies of species and/or community dynamics in a range of contexts.

Climate and habitat configuration limit range expansion and patterns of dispersal in a non‐native lizard

“…These models were constructed using the platform RangeShifter v1.1 (Bocedi, Palmer, et al., 2014) where behaviors of individuals within a population are simulated in relation to life‐history parameters and conditions determined by a set of spatial inputs. The local habitat suitability maps generated by MaxEnt were the basis of the spatial inputs used for individual‐based models and included: habitat quality landscape layers that were created by rescaling the MaxEnt logistic values (estimates between 0 and 1 of relative suitability) to a scale of 1–100 to represent the percentage of maximum carrying capacity that a cell can support; and cost surface layers (where cell values represent the resistance for dispersing individuals to move through cells), created based on a reciprocal transformation of habitat suitability resulting in a scale of matrix hostility of 1–10 (Hunter‐Ayad & Hassall, 2020) (Figure Appendix ). All inputs were resampled using bilinear interpolation to 15 × 15 m cell size to reduce demands on computational memory while retaining relevance to wall lizard movement capabilities.…”

“…Consideration of dispersal processes across heterogeneous landscapes is therefore central to predicting potential for range expansion during the invasion process Grayson & Johnson, 2018;Travis et al 2011). The development of platforms for spatially explicit individual-based modeling (Bocedi, Zurell, et al, 2014;Samson et al, 2017) has enabled the nested interactions between dispersal, landscape properties, and population dynamics to be considered in predicting species distributions, increasing the ecological realism of range expansion models (Andrew & Ustin, 2010;Ferrari et al 2014;Hunter-Ayad & Hassall, 2020;Mang et al 2018).…”

“…The development of platforms for spatially explicit individual‐based modeling (Bocedi, Zurell, et al., 2014; Samson et al., 2017) has enabled the nested interactions between dispersal, landscape properties, and population dynamics to be considered in predicting species distributions, increasing the ecological realism of range expansion models (Andrew & Ustin, 2010; Ferrari et al. 2014; Hunter‐Ayad & Hassall, 2020; Mang et al. 2018).…”

Novel Conditions in Conservation Translocations: A Conservative-Extrapolative Strategic Framework

“…This could include indigenous distributions prior to range contractions (Lentini et al, 2017) or biophysical and behavioural information from captive animals (Mitchell et al, 2012). Alternatively, evidence could be sought from other species, e.g., from sister-species (Hunter-Ayad and Hassall, 2020), or trophically analogous species (Andelman and Fagan, 2000). However, while additional data sources can inform extrapolative translocations, they are not always available, or might not be considered reliable due to temporal, spatial, environmental, ecological, and/or taxonomic distance from the relevant management conditions (Osborne and Seddon, 2012;Svenning et al, 2016).…”

Climate and habitat configuration limit range expansion and patterns of dispersal in a non-native lizard

“…Consideration of dispersal processes across heterogeneous landscapes is therefore central to predicting potential for range expansion during the invasion process (Travis, Harris, Park, & Bullock, 2011;Bocedi, Zurell, Reineking, & Travis, 2014;Grayson & Johnson, 2018). The development of platforms for spatially explicit individual-based modelling (Bocedi, Zurell, et al, 2014;Samson et al, 2017) have enabled the nested interactions between dispersal, landscape properties, and population dynamics to be considered in predicting species distributions, increasing the ecological realism of range expansion models (Andrew & Ustin, 2010;Ferrari, Preisser, & Fitzpatrick, 2014;Mang, Essl, Moser, Kleinbauer, & Dullinger, 2018;Hunter-Ayad & Hassall, 2020).…”