Biology subjects

Panzacchi, M.

Publications and source records attributed to Panzacchi, M..

3 recordsLinked to original sources

bioRxiv2026

Where conservation and restoration matter most: sensitivity-based prioritization of connected forest

Achieving global conservation and restoration targets requires knowing not only how much land to conserve and restore, but also where such actions will have the greatest ecological effect. Conservation and, in particular, restoration priorities are often inferred from habitat condition, opportunity, or broad ecological value, yet these criteria do not necessarily identify where local changes generate the largest landscape-scale consequences. Building on sensitivity-based conservation prioritization, we extend the approach to derive ecological loss and gain potential by differentiating a persistence-relevant connectivity metric with respect to local habitat condition. Sensitivity identifies areas where local degradation or improvement would most strongly affect connected habitat at the landscape scale. Combining sensitivity with current condition distinguishes high loss potential, where degradation would have large ecological consequences, from high gain potential, where ecological improvement could generate large benefits. Applying the framework to national forest-naturalness data in Norway, we show that loss and gain potential are spatially related but far from redundant, and that gain potential is not simply concentrated in the most degraded forests. Both high-loss and high-gain areas were poorly represented within current protected areas, although loss potential was consistently better represented than gain potential. Extending sensitivity-based prioritization in this way provides a general and scalable means of linking local habitat-condition change to persistence-relevant landscape outcomes, while distinguishing the ecological potentials that can inform conservation and restoration decisions.

ecology↗

bioRxiv2026

A unified framework for prioritizing habitat and connectivity conservation through analytical sensitivity

ContextConnected habitats underpin key ecological processes such as movement, gene flow, and recolonization. As land-use change accelerates habitat loss and fragmentation, there is an urgent need to identify priority areas for conserving habitat and maintaining connectivity. ObjectivesWe develop a unified spatial prioritization framework for functional connectivity that is grounded in metapopulation theory, accommodates species-specific movement behavior, and captures the dual role of landscape units as both habitat providers and connectivity facilitators. MethodsWe formalize the landscape as a network in which nodes represent spatial units characterized by habitat quality and edges encode permeability for movement. Pairwise ecological proximities are defined from species-specific movement capacity and an ecological distance that integrates costs across paths, expressed as least-cost distance, effective resistance, expected cost, or survival probability depending on the movement ecology of the focal species. From these proximities and node qualities, we construct the landscape matrix. Based on the sensitivity of the landscape matrix to local perturbations in habitat quality or permeability, we develop a prioritization approach that identifies where local changes most strongly influence landscape-scale habitat connectivity. ResultsOur framework unifies widely used landscape connectivity metrics across the full spectrum of movement models, including least-cost paths, circuit theory, spatial absorbing Markov chains, and randomized shortest paths. We show that summation-based metrics serve as computationally efficient approximations of metapopulation capacity, enabling evaluation of functional connectivity in large, high-resolution landscapes. We derive sensitivities for these metrics with respect to habitat quality and permeability and show that they correspond to two families of centrality measures: a closeness-like centrality reflecting the influence of habitat quality, and a betweenness-like centrality reflecting the influence of habitat permeability. Applying our prioritization approach based on these sensitivities to a case study involving wild reindeer in Norway, we identify high-value habitat and key movement corridors that closely align with a reference node-removal approach while reducing computation time by several orders of magnitude. ConclusionsBy linking metapopulation theory with sensitivity analysis, our work provides a unified and scalable framework for spatial prioritization of functional connectivity. It supports evidence-based management of fragmented landscapes and advances both theoretical understanding and practical application in landscape ecology.

ecology↗

bioRxiv2022

Estimating the cumulative impact and zone of influence of anthropogenic infrastructure on biodiversity

O_LIThe concept of cumulative impacts is widespread in policy documents, regulations, and ecological studies, but quantification methods are still evolving. Infrastructure development usually takes place in landscapes with preexisting anthropogenic features. Typically, their impact is determined by computing the distance to the nearest feature only, thus ignoring the potential cumulative impacts of multiple features. We propose the cumulative ZOI approach to assess whether and to what extent anthropogenic features lead to cumulative impacts. C_LIO_LIThe approach estimates both effect size and zone of influence (ZOI) of anthropogenic features and allows for estimation of cumulative effects of multiple features distributed in the landscape. First, we use simulations and an empirical study to understand under which circumstances cumulative impacts arise. Second, we demonstrate the approach by estimating the cumulative impacts of tourist infrastructure in Norway on the habitat of wild reindeer (Rangifer t. tarandus), a nearly-threatened species highly sensitive to anthropogenic disturbance. C_LIO_LISimulations show that analyses based on the nearest feature and our cumulative approach are indistinguishable in two extreme cases: when features are few and scattered and their ZOI is small, and when features are clustered and their ZOI is large. Empirical analyses revealed cumulative impacts of private cabins and tourist resorts on reindeer, extending up to 10 and 20 km, with different decaying functions. Although the impact of an isolated private cabin was negligible, the cumulative impact of cabin villages could be much larger than that of a single large tourist resort. Focusing on the nearest feature only underestimates the impact of cabin villages on reindeer. C_LIO_LIThe suggested approach allows us to quantify the magnitude and spatial extent of cumulative impacts of point, linear, and polygon features in a computationally efficient and flexible way and is implemented in the oneimpact R package. The formal framework offers the possibility to avoid widespread underestimations of anthropogenic impacts in ecological and impact assessment studies and can be applied to a wide range of spatial response variables, including habitat selection, population abundance, species richness and diversity, community dynamics, and other ecological processes. C_LI

ecology↗