Vulnerability of <scp>A</scp>ustralian tropical savanna birds to climate change

Reside, April E.; VanDerWal, Jeremy; Garnett, Stephen T.; Kutt, Alex S.

doi:10.1111/aec.12304

Cited by 16 publications

(11 citation statements)

References 70 publications

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“…Given spatiotemporal variation in the abundance of rare species and their vulnerability to environmental change (Reside et al. ), it is important that we understand how functionally unique species (and traits) respond to fire regimes. Such an understanding is critical to provide insights into mechanisms that support ecosystem function and to support the development of management strategies in the face of changing climate and fire regimes (Pausas and Parr ).…”

Section: Discussionmentioning

confidence: 99%

Burning savanna for avian species richness and functional diversity

Docherty

Hethcoat

MacTavish³

et al. 2020

Ecological Applications

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Prescribed fire is used throughout fire-prone landscapes to conserve biodiversity. Current best practice in managing savanna systems advocates methods based on the assumption that increased fire-mediated landscape heterogeneity (pyrodiversity) will promote biodiversity. However, considerable knowledge gaps remain in our understanding of how savanna wildlife responds to the composition and configuration of pyrodiverse landscapes. The effects of pyrodiversity on functional diversity have rarely been quantified and assessing this relationship at a landscape scale that is commensurate with fire management is important for understanding mechanisms underlying ecosystem resilience. Here, we assess the impact of spatiotemporal variation in a long-term fire regime on avian diversity in North West Province, South Africa. We examined the relationship between (1) species richness, (2) three indices of functional diversity (i.e., functional richness, functional evenness, and functional dispersion) and four measures of pyrodiversity, the spatial extents of fire age classes, and habitat type at the landscape scale. We then used null models to assess differences between observed and expected functional diversity. We found that the proportion of newly burned (<1-yr post-fire), old, unburned (≥10 yr post-fire), and woodland habitat on the landscape predicted species and functional richness. Species richness also increased with the degree of edge contrast between patches of varying fire age, while functional dispersion increased with the degree of patch shape complexity. Lower than expected levels of functional richness suggest that habitat filtering is occurring, resulting in functional redundancy across our study sites. We demonstrate that evaluating functional diversity and redundancy is an important component of conservation planning as they may contribute to previously reported fire resilience. Our findings suggest that it is the type and configuration, rather than the diversity, of fire patches on the landscape that promote avian diversity and conserve ecological functions. A management approach is needed that includes significant coverage of adjacent newly burned and older, unburned savanna habitat; the latter, in particular, is inadequately represented under current burning practices.

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Section: Discussionmentioning

confidence: 99%

Burning savanna for avian species richness and functional diversity

Docherty

Hethcoat

MacTavish³

et al. 2020

Ecological Applications

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“…, Reside et al. ). Evidence suggests that the correlative modeling approach can provide useful insights into the ways that species might be impacted by, or respond to, changing climate (Tingley et al.…”

Section: Introductionmentioning

confidence: 99%

“…Detailed behavioral, physiological, and ecological data sufficient for detailed mechanistic models are available for some species (Kearney and Porter 2009). For the vast majority of species, however, predicting the impact of climate change has involved correlative modeling and traitbased vulnerability assessments (Bellard et al 2012, Foden et al 2013, Reside et al 2016. Evidence suggests that the correlative modeling approach can provide useful insights into the ways that species might be impacted by, or respond to, changing climate (Tingley et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Beyond the model: expert knowledge improves predictions of species’ fates under climate change

Reside

Critchell

Crayn

et al. 2018

Ecological Applications

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The need to proactively manage landscapes and species to aid their adaptation to climate change is widely acknowledged. Current approaches to prioritizing investment in species conservation generally rely on correlative models, which predict the likely fate of species under different climate change scenarios. Yet, while model statistics can be improved by refining modeling techniques, gaps remain in understanding the relationship between model performance and ecological reality. To investigate this, we compared standard correlative species distribution models to highly accurate, fine‐scale, distribution models. We critically assessed the ecological realism of each species’ model, using expert knowledge of the geography and habitat in the study area and the biology of the study species. Using interactive software and an iterative vetting with experts, we identified seven general principles that explain why the distribution modeling under‐ or overestimated habitat suitability, under both current and predicted future climates. Importantly, we found that, while temperature estimates can be dramatically improved through better climate downscaling, many models still inaccurately reflected moisture availability. Furthermore, the correlative models did not account for biotic factors, such as disease or competitor species, and were unable to account for the likely presence of micro refugia. Under‐performing current models resulted in widely divergent future projections of species’ distributions. Expert vetting identified regions that were likely to contain micro refugia, even where the fine‐scale future projections of species distributions predicted population losses. Based on the results, we identify four priority conservation actions required for more effective climate change adaptation responses. This approach to improving the ecological realism of correlative models to understand climate change impacts on species can be applied broadly to improve the evidence base underpinning management responses.

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“…Species distribution models (SDMs) can provide information in this area, so it has been widely applied to the study of conservation area planning, and the impact of climate change on species distribution. At present, the study of SDMs has carried out climate change on animals [15][16][17][18], plants [19,20], landscape ecology [21], swamp vegetation [22], Chinese medicinal materials [23], and so on. Many algorithms have been applied to the construction of SDMs.…”

Section: Introductionmentioning

confidence: 99%

Assessing Habitat Suitability of Parasitic Plant Cistanche deserticola in Northwest China under Future Climate Scenarios

Liu

Yang

Wei

et al. 2019

Forests

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: Cistanche deserticola Ma, a perennial parasitic herb of family Orobanchaceae, is mainly parasitic on the roots of the Haloxylon ammodendron Bunge. In view of this special parasitic relationship, we applied random forest (RF) model to forecast potential geographic distribution, and developed a comprehensive habitat suitability model by integrating bioclimatic and soil factors to assess the suitable distribution of C. deserticola and H. ammodendron across China in 2050s and 2070s under RCP2.6, RCP4.5, and RCP8.5, respectively. We modeled the core potential geographic distribution of C. deserticola by overlaying the distribution of these two species, and analyzed the spatial distribution pattern and migration trend of C. deserticola by using the standard deviational ellipse. In addition, we evaluated the accuracy of RF model through three evaluation indexes, and analyzed the dominant climate factors. The results showed that the core potential distribution areas of C. deserticola are distributed in the Xinjiang Uygur Autonomous Region, the junction of Shaanxi–Gansu–Ningxia provinces, and the Inner Mongolia Autonomous Region. The spatial dispersion would intensify with the increasing of emission scenarios, and the geographical habitat is moving towards higher latitude. Among the three evaluation indexes, the area under the ROC curve (AUC) and True Skill Statistic (TSS) have better assessment results. The main bioclimatic factors affecting the distribution are min temperature of coldest month (Bio6), annual precipitation (Bio12), precipitation of wettest month (Bio13), precipitation of wettest quarter (Bio16), and precipitation of warmest quarter (Bio18), among which the importance of precipitation factors is greater than temperature factors. More importantly, the results of this study could provide some guidance for the improvement of desert forest system, the protection of endangered species and the further improvement of the ecological environment.

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Vulnerability of Australian tropical savanna birds to climate change

Cited by 16 publications

References 70 publications

Burning savanna for avian species richness and functional diversity

Burning savanna for avian species richness and functional diversity

Beyond the model: expert knowledge improves predictions of species’ fates under climate change

Assessing Habitat Suitability of Parasitic Plant Cistanche deserticola in Northwest China under Future Climate Scenarios

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