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Allison Fowler

Publications and source records attributed to Allison Fowler.

2 recordsLinked to original sources

Scenario planning and multispecies occupancy models reveal positive avian responses to restoration of afforested woodlands

Scenario planning is a powerful approach for assessing restoration outcomes under alternative futures. However, developing plausible scenarios remains daunting in complex systems like ecological communities. Here, we used Bayesian multispecies occupancy modeling to develop scenarios to assess woodland restoration outcomes in afforested communities in seven wildlife management areas in Arkansas, U.S.A. Our objectives were (1) to define plausible woodland restoration and afforestation scenarios by quantifying historic ranges of variation in mean tree cover and tree cover heterogeneity from 1986 to 2021 and (2) to predict changes in bird species richness and occupancy patterns for six species of greatest conservation need under two future scenarios: complete afforestation (100% tree cover) and woodland restoration (based on remotely sensed historic tree cover). Using 35 years of remotely sensed tree cover data and 6 years of bird monitoring data, we developed multispecies occupancy models to predict future bird species richness and occupancy under the complete afforestation and woodland restoration scenarios. Between 1986 and 2021, tree cover increased in all study areas—with one increasing 70%. Under the woodland restoration scenario, avian species richness increased up to 20%, and four of six species of greatest conservation need exhibited gains in occupancy probability. The complete afforestation scenario had negligible effects on richness and occupancy. Overall, we found decreasing tree cover to historic levels prior to widespread afforestation would provide community-level benefits and would do little harm even to forest-dependent species of conservation concern. Applying multispecies occupancy modeling within a scenario planning framework allows for comparing multiscale trade-offs between plausible futures.

Restoration Ecology

Developing a decision-support process for landscape conservation design

Planning for sustainable landscapes is hampered by uncertainty in how species will respond to conservation actions amidst impacts from landscape and climate change. Planning decisions, including tradeoffs among competing species objectives, are complex. We developed a decision-support framework that integrates dynamic-landscape metapopulation models (DLMPs) and structured decision making (SDM) to help guide landscape conservation design. With this framework, we demonstrated that planning for viable populations across broad scales can be achieved under global change. Furthermore, the integration of DLMPs with SDM enabled decisions to be more objective and transparent, and thus, more defensible.

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