Researchers have developed a groundbreaking approach to uncover the hidden impacts of human activities on the geographic ranges of species. By applying explainable artificial intelligence (XAI) techniques to species distribution models, they can now delineate a species’ “shadow distribution” – the areas where natural factors support a species’ presence, but human threats reduce its ability to thrive. This novel framework provides critical insights for conservation efforts, helping identify where and how to target interventions to protect threatened species.
Unveiling the Hidden Costs of Human Impacts
In the face of alarming biodiversity loss, scientists are racing to understand the complex web of factors shaping species’ geographic distributions. While previous research has often focused on identifying the overall ranking of global threats, the new study by a team of researchers takes a more nuanced approach. By applying cutting-edge XAI tools, they can now quantify the local contribution of each environmental factor – both natural and human-driven – to a species’ suitability in a given location.
The key innovation is the concept of a species’ “shadow distribution” – the areas where natural factors like temperature, flow, and connectivity would support a species’ presence, but human activities like habitat degradation and pollution undermine its ability to thrive. This insight is a game-changer for conservation, as it reveals where species are being held back by threats, even in areas that appear suitable based on abiotic conditions alone.
Deconstructing the Drivers of Species Distributions
The researchers applied their framework to model the geographic distributions of nine fish species in the rivers and streams of Switzerland. By using random forest models and SHAP (SHapley Additive exPlanations) values, they were able to quantify the independent contributions of 11 environmental variables, including natural factors like river discharge and temperature, as well as anthropogenic threats like habitat modification and urbanization.
The results were eye-opening. For the spirlin fish (Alburnoides bipunctatus), the team found that while natural factors like discharge and temperature were highly important in determining its distribution, a significant portion of its expected range was negatively impacted by threats such as poor connectivity and habitat degradation. In fact, they estimated that threats reduced the environmental suitability for spirlin by 25% compared to its expected distribution based on natural factors alone.
Informing Targeted Conservation Strategies
This powerful approach goes beyond simply mapping species distributions or threats. By deconstructing the relative contributions of different environmental factors, the researchers can provide conservation practitioners with crucial information to guide their interventions. For example, they found that while connectivity was the overall most important threat, much of its negative impact was outside the natural abiotic niche of the species. In contrast, habitat quality indicators had lower overall importance but negatively impacted a larger portion of the expected distribution.
“This knowledge is a game-changer for conservation,” explained lead author Conor Waldock. “By understanding where threats are actually constraining species, we can target our efforts to the most limiting factors in each location, rather than relying on general threat rankings. This helps ensure our limited resources are used as effectively as possible to protect threatened species.”
A Roadmap for Biodiversity Recovery
The researchers’ framework not only reveals the hidden impacts of human activities on species distributions, but also provides a roadmap for biodiversity recovery. By defining a species’ “expected distribution” – the areas where natural factors would support its presence – the team can help identify priority locations for restoration and conservation. Furthermore, by quantifying the relative contributions of different threats, the approach can guide the implementation of tailored, multi-faceted management strategies to address the most limiting factors in each location.
“Our work shows how priority actions for nature’s recovery can be identified and contextualized within the multiple natural constraints on biodiversity,” said co-author Ole Seehausen. “This is crucial for meeting national and international biodiversity targets, like the Kunming-Montreal Global Biodiversity Framework, which calls for restoring 30% of degraded areas by 2030.”
As the world grapples with the biodiversity crisis, tools like this that unlock the spatial nuances of human impacts on species are invaluable. By revealing the hidden shadows cast over species’ natural distributions, researchers can help guide conservation efforts to where they are most needed and most likely to succeed.
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