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Ecological forecasts to inform near‐term management of threats to biodiversity

AbstractEcosystems are being altered by rapid and interacting changes in natural processes and anthropogenic threats to biodiversity. Uncertainty in historical, current and future effectiveness of actions hampers decisions about how to mitigate changes to prevent biodiversity loss and species extinctions. Research in resource management, agriculture and health indicates that forecasts predicting the effects of near‐term or seasonal environmental conditions on management greatly improve outcomes. Such forecasts help resolve uncertainties about when and how to operationalize management. We reviewed the scientific literature on environmental management to investigate whether near‐term forecasts are developed to inform biodiversity decisions in Australia, a nation with one of the highest recent extinction rates across the globe. We found that forecasts focused on economic objectives (e.g. fisheries management) predict on significantly shorter timelines and answer a broader range of management questions than forecasts focused on biodiversity conservation. We then evaluated scientific literature on the effectiveness of 484 actions to manage seven major terrestrial threats in Australia, to identify opportunities for near‐term forecasts to inform operational conservation decisions. Depending on the action, between 30% and 80% threat management operations experienced near‐term weather impacts on outcomes before, during or after management. Disease control, species translocation/reintroduction and habitat restoration actions were most frequently impacted, and negative impacts such as increased species mortality and reduced recruitment were more likely than positive impacts. Drought or dry conditions, and rainfall, were the most frequently reported weather impacts, indicating that near‐term forecasts predicting the effects of low or excessive rainfall on management outcomes are likely to have the greatest benefits. Across the world, many regions are, like Australia, becoming warmer and drier, or experiencing more extreme rainfall events. Informing conservation decisions with near‐term and seasonal ecological forecasting will be critical to harness uncertainties and lower the risk of threat management failure under global change.
- University of Queensland Australia
- University of Sydney Australia
- University of Queensland Australia
- University of Queensland Australia
- Queensland University of Technology Australia
2300 Environmental Science, Conservation of Natural Resources, 330, conservation decision-making, ecological prediction models, Climate Change, 2306 Global and Planetary Change, 577, Extinction, Biological, 333, invasive species, fire management, Environmental Chemistry, species translocation, near-term ecological forecasting, Ecosystem, General Environmental Science, Global and Planetary Change, Ecology, species reintroduction, Australia, threatening processes, Biodiversity, Primary Research Articles, climate change, 2304 Environmental Chemistry, 2303 Ecology, habitat restoration
2300 Environmental Science, Conservation of Natural Resources, 330, conservation decision-making, ecological prediction models, Climate Change, 2306 Global and Planetary Change, 577, Extinction, Biological, 333, invasive species, fire management, Environmental Chemistry, species translocation, near-term ecological forecasting, Ecosystem, General Environmental Science, Global and Planetary Change, Ecology, species reintroduction, Australia, threatening processes, Biodiversity, Primary Research Articles, climate change, 2304 Environmental Chemistry, 2303 Ecology, habitat restoration
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
