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<p>Priority areas are typically identified based on mean conditions, while ignoring variance around the mean (i.e., “stochasticity’). This is problematic as high environmental stochasticity can increase extinction risk and reduce the effectiveness of protected areas. Here we use daily Normalized Difference Vegetation Index data from 1981 to 2025 to generate spatially-explicit estimates of both the mean and variance in environmental productivity across Canada. From these models, we found that environmental stochasticity shows strong spatial structure and has been steadily increasing over the past four decades. Additionally, stochasticity had a negative effect on species richness. We found no clear relationship between stochasticity and protection status, suggesting that Canada’s network of protected areas are not well-buffered against a climate-change induced increase in stochasticity. Promisingly, we identified 2,709,580 km<sup>2</sup> of currently unprotected land that may minimise the impact(s) of growing stochasticity. This work provides a framework for incorporating environmental stochasticity into conservation planning.</p>

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Environmental variability shapes biodiversity and protected area priorities in Canada

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月9日

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  • Rekha Marcus,
  • Stefano Mezzini,
  • Dwija Desai,
  • Michael J. Noonan

摘要

Priority areas are typically identified based on mean conditions, while ignoring variance around the mean (i.e., “stochasticity’). This is problematic as high environmental stochasticity can increase extinction risk and reduce the effectiveness of protected areas. Here we use daily Normalized Difference Vegetation Index data from 1981 to 2025 to generate spatially-explicit estimates of both the mean and variance in environmental productivity across Canada. From these models, we found that environmental stochasticity shows strong spatial structure and has been steadily increasing over the past four decades. Additionally, stochasticity had a negative effect on species richness. We found no clear relationship between stochasticity and protection status, suggesting that Canada’s network of protected areas are not well-buffered against a climate-change induced increase in stochasticity. Promisingly, we identified 2,709,580 km2 of currently unprotected land that may minimise the impact(s) of growing stochasticity. This work provides a framework for incorporating environmental stochasticity into conservation planning.