Using probability of persistence to identify important areas for biodiversity conservation

Area of Science:

• Conservation Biology
• Biodiversity Management
• Ecological Planning

Background:

• Current biodiversity conservation planning often relies on representing species' current distributions.
• This approach treats all occurrence records equally, potentially overlooking long-term survival probabilities.
• Integrating diverse factors affecting conservation success into planning remains a challenge.

Purpose of the Study:

• To develop a novel approach for conservation planning based on the probability of species persistence.
• To create a method for identifying networks of conservation areas that maximize species persistence probabilities.
• To evaluate the effectiveness of this new method compared to traditional approaches.

Main Methods:

• Developed a method to identify conservation area networks that maximize species persistence probabilities.
• Applied the method using data for European trees to assess its efficiency.
• Compared the number of areas required and the resulting persistence probabilities against an earlier distribution-based method.

Main Results:

• The new method required less than half the number of areas to achieve a 0.95 persistence probability for all species compared to a previous method.
• For a fixed number of areas (1-50), the method increased mean species persistence probability by over 10%.
• Improvements were most significant for least-widespread species, leading to increased connectivity.

Conclusions:

• Prioritizing species persistence probability offers a more direct and effective strategy for conservation planning.
• The proposed method is more efficient in area selection and enhances overall conservation outcomes.
• This approach is adaptable to various biodiversity surrogates and can incorporate local constraints.