Enhancing Biodiversity Conservation: A New Framework for Multi-Species Landscape Connectivity

Landscape connectivity is a cornerstone of ecological health. It allows animals to move across habitats, find food, mate, and adapt to changing environments. However, evaluating connectivity across diverse species has long been a challenging task. Traditional methods often rely on simplified models that overlook the complex behaviours of wildlife, leading to gaps in our understanding. But a new approach promises to change that. 

  

The Connectivity Challenge 

Ecological connectivity assessments typically involve mapping how landscapes either help or hinder wildlife movement. Historically, researchers have simplified this process by focusing on “generic” or “surrogate” species, assumed to represent broader biodiversity. While this approach saves time, it can miss the unique movement patterns of specific species, leading to less reliable results. 

Another challenge is the tools used to measure connectivity. The most common methods—network theory and circuit theory—each have strengths and weaknesses. Network theory models landscapes as a series of nodes (like protected areas) connected by pathways, offering precise connectivity metrics. However, it assumes animals always take the most efficient route, which isn’t realistic in unfamiliar territories. Circuit theory, by contrast, treats the landscape like an electrical grid, mapping multiple potential pathways animals might use. While more flexible, it struggles to deliver the detailed metrics often required for planning and research. 

Finally, many studies overlook uncertainty—the natural variation in movement patterns or assumptions made during modelling. Without addressing this variability, connectivity estimates may not fully reflect reality. 

  

A New Framework: Blending Insights and Overcoming Gaps 

To address these limitations, a novel framework was developed which brings greater accuracy and flexibility to connectivity assessments. Here’s how it works: 

  

  • Grouping Species by Traits 

Instead of using generic species, this method clusters animals into groups based on shared environmental needs and traits like body size, habitat preferences, and sensitivity to habitat fragmentation. For example, birds that thrive in open landscapes are analysed separately from forest-dwelling species. This improves the realism of connectivity models without increasing complexity. 

  

  • Combining Circuit and Network Theories 

The framework leverages the strengths of both methods. Circuit theory maps continuous connectivity across landscapes, identifying “ecological continuities”—key areas that facilitate movement. These are then fed into network theory to calculate detailed metrics for specific conservation zones, like protected areas. This dual approach ensures both breadth and precision. 

  

  • Integrating Uncertainty 

To improve reliability, the framework accounts for variability in modelling choices, such as differences in habitat resistance or dispersal capacities. This allows planners to make more robust, evidence-based decisions. 

Summary of the framework workflow

Summary of the framework workflow.

A Case Study: Connecting France’s Protected Areas 

The framework was tested on 193 species of mammals and birds across metropolitan France, analysing the connectivity of 1,619 protected areas. The results revealed: 

  

  • Low Connectivity Across the Board: Many protected areas are not well-connected for wildlife, limiting their effectiveness. 
  • Group Variations: Some species groups, like small mammals and certain birds, were more affected than others. 
  • Unequal Contributions: Different types of protected areas (e.g., national parks vs. local reserves) played varying roles in maintaining connectivity. 

These insights underline the need for targeted interventions, such as expanding protected areas or restoring natural corridors. 

  

A Vision for Conservation 

This new framework offers a comprehensive way to assess connectivity for multiple species while addressing gaps in traditional methods. It’s adaptable to different landscapes and scenarios, including future environmental changes. More importantly, it provides actionable insights for policymakers and conservationists. 

  

To support biodiversity, the researchers urge a twofold strategy: 

  • Expanding Protected Areas: Increase the size and number of protected zones to cover critical habitats. 
  • Restoring Ecological Corridors: Reconnect fragmented habitats to facilitate wildlife movement. 

By adopting such strategies, we can ensure that landscapes remain navigable for wildlife, safeguarding biodiversity for generations to come. This innovative framework represents a significant step forward in our ability to evaluate and enhance landscape connectivity, offering a more nuanced and adaptable approach to biodiversity conservation. By bridging theoretical insights and practical applications, it provides valuable tools to guide spatial planning and conservation efforts in diverse environmental contexts. 

  

For an in-depth exploration of this research, read the full article by Marie-Caroline Prima, Julien Renaud, Isabelle Witté, Léa Suarez, Paul Rouveyrol, Martina Fernando, Andrea Sacchi, Francesca Cosentino, Luca Santini, Luigi Maiorano, Francisco Moreira, Jeremy Dertien, Néstor Fernández, and Wilfried Thuiller at the following link.