Integrating plant- and animal-based perspectives for more effective restoration of biodiversity

Ecological restoration of modified and degraded landscapes is an important challenge for the 21st century, with potential for major gains in the recovery of biodiversity. However, there is a general lack of agreement between plant- and animal-based approaches to restoration, both in theory and practice. Here, we review these approaches, identify limitations from failing to effectively integrate their different perspectives, and suggest ways to improve outcomes for biodiversity recovery in agricultural landscapes. We highlight the need to strengthen collaboration between plant and animal ecologists, to overcome disciplinary and cultural differences, and to achieve a more unified approach to restoration ecology. Explicit consideration of key ecosystem functions, the need to plan at multiple spatial and temporal scales, and the importance of plant–animal interactions can provide a bridge between plant- and animal-based methods. A systematic approach to restoration planning is critical to achieving effective biodiversity outcomes while meeting long-term social and economic needs

The conservation impacts of ecological disturbance : time-bound estimates of population loss and recovery for fauna affected by the 2019–2020 Australian megafires

Aim: After environmental disasters, species with large population losses may need urgent protection to prevent extinction and support recovery. Following the 2019–2020 Australian megafires, we estimated population losses and recovery in fire-affected fauna, to inform conservation status assessments and management. Location: Temperate and subtropical Australia. Time period: 2019–2030 and beyond. Major taxa: Australian terrestrial and freshwater vertebrates; one invertebrate group. Methods: From > 1,050 fire-affected taxa, we selected 173 whose distributions substantially overlapped the fire extent. We estimated the proportion of each taxon’s distribution affected by fires, using fire severity and aquatic impact mapping, and new distribution mapping. Using expert elicitation informed by evidence of responses to previous wildfires, we estimated local population responses to fires of varying severity. We combined the spatial and elicitation data to estimate overall population loss and recovery trajectories, and thus indicate potential eligibility for listing as threatened, or uplisting, under Australian legislation. Results: We estimate that the 2019–2020 Australian megafires caused, or contributed to, population declines that make 70–82 taxa eligible for listing as threatened; and another 21–27 taxa eligible for uplisting. If so-listed, this represents a 22–26% increase in Australian statutory lists of threatened terrestrial and freshwater vertebrates and spiny crayfish, and uplisting for 8–10% of threatened taxa. Such changes would cause an abrupt worsening of underlying trajectories in vertebrates, as measured by Red List Indices. We predict that 54–88% of 173 assessed taxa will not recover to pre-fire population size within 10 years/three generations. Main conclusions: We suggest the 2019–2020 Australian megafires have worsened the conservation prospects for many species. Of the 91 taxa recommended for listing/uplisting consideration, 84 are now under formal review through national processes. Improving predictions about taxon vulnerability with empirical data on population responses, reducing the likelihood of future catastrophic events and mitigating their impacts on biodiversity, are critical. © 2022 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Diana Kuchinke” is provided in this record*

Fire and biodiversity in the Anthropocene

The workshop leading to this paper was funded by the Centre Tecnològic Forestal de Catalunya and the ARC Centre of Excellence for Environmental Decisions. L.T.K. was supported by a Victorian Postdoctoral Research Fellowship (Victorian Government), a Centenary Fellowship (University of Melbourne), and an Australian Research Council Linkage Project Grant (LP150100765). A.R. was supported by the Xunta de Galicia (Postdoctoral Fellowship ED481B2016/084-0) and the Foundation for Science and Technology under the FirESmart project (PCIF/MOG/0083/2017). A.L.S. was supported by a Marie Skłodowska-Curie Individual Fellowship (746191) under the European Union Horizon 2020 Programme for Research and Innovation. L.R. was supported by the Australian Government’s National Environmental Science Program through the Threatened Species Recovery Hub. L.B. was partially supported by the Spanish Government through the INMODES (CGL2014-59742-C2-2-R) and the ERANET-SUMFORESTS project FutureBioEcon (PCIN-2017-052). This research was supported in part by the U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station.BACKGROUND Fire has shaped the diversity of life on Earth for millions of years. Variation in fire regimes continues to be a source of biodiversity across the globe, and many plants, animals, and ecosystems depend on particular temporal and spatial patterns of fire. Although people have been using fire to modify environments for millennia, the combined effects of human activities are now changing patterns of fire at a global scale—to the detriment of human society, biodiversity, and ecosystems. These changes pose a global challenge for understanding how to sustain biodiversity in a new era of fire. We synthesize how changes in fire activity are threatening species with extinction across the globe, highlight forward-looking methods for predicting the combined effects of human drivers and fire on biodiversity, and foreshadow emerging actions and strategies that could revolutionize how society manages fire for biodiversity in the Anthropocene. ADVANCES Our synthesis shows that interactions with anthropogenic drivers such as global climate change, land use, and biotic invasions are transforming fire activity and its impacts on biodiversity. More than 4400 terrestrial and freshwater species from a wide range of taxa and habitats face threats associated with modified fire regimes. Many species are threatened by an increase in fire frequency or intensity, but exclusion of fire in ecosystems that need it can also be harmful. The prominent role of human activity in shaping global ecosystems is the hallmark of the Anthropocene and sets the context in which models and actions must be developed. Advances in predictive modeling deliver new opportunities to couple fire and biodiversity data and to link them with forecasts of multiple drivers including drought, invasive plants, and urban growth. Making these connections also provides an opportunity for new actions that could revolutionize how society manages fire. Emerging actions include reintroduction of mammals that reduce fuels, green fire breaks comprising low-flammability plants, strategically letting wildfires burn under the right conditions, managed evolution of populations aided by new genomics tools, and deployment of rapid response teams to protect biodiversity assets. Indigenous fire stewardship and reinstatement of cultural burning in a modern context will enhance biodiversity and human well-being in many regions of the world. At the same time, international efforts to reduce greenhouse gas emissions are crucial to reduce the risk of extreme fire events that contribute to declines in biodiversity. OUTLOOK Conservation of Earth’s biological diversity will be achieved only by recognition of and response to the critical role of fire in shaping ecosystems. Global changes in fire regimes will continue to amplify interactions between anthropogenic drivers and create difficult trade-offs between environmental and social objectives. Scientific input will be crucial for navigating major decisions about novel and changing ecosystems. Strategic collection of data on fire, biodiversity, and socioeconomic variables will be essential for developing models to capture the feedbacks, tipping points, and regime shifts characteristic of the Anthropocene. New partnerships are also needed to meet the challenges ahead. At the local and regional scale, getting more of the “right” type of fire in landscapes that need it requires new alliances and networks to build and apply knowledge. At the national and global scale, biodiversity conservation will benefit from greater integration of fire into national biodiversity strategies and action plans and in the implementation of international agreements and initiatives such as the UN Convention on Biological Diversity. Placing the increasingly important role of people at the forefront of efforts to understand and adapt to changes in fire regimes is central to these endeavors.PostprintPeer reviewe

Predicting reliability through structured expert elicitation with the repliCATS (Collaborative Assessments for Trustworthy Science) process

As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predictions about the replicability of research. This process is a structured expert elicitation approach based on a modified Delphi technique applied to the evaluation of research claims in social and behavioural sciences. The utility of processes to predict replicability is their capacity to test scientific claims without the costs of full replication. Experimental data supports the validity of this process, with a validation study producing a classification accuracy of 84% and an Area Under the Curve of 0.94, meeting or exceeding the accuracy of other techniques used to predict replicability. The repliCATS process provides other benefits. It is highly scalable, able to be deployed for both rapid assessment of small numbers of claims, and assessment of high volumes of claims over an extended period through an online elicitation platform, having been used to assess 3000 research claims over an 18 month period. It is available to be implemented in a range of ways and we describe one such implementation. An important advantage of the repliCATS process is that it collects qualitative data that has the potential to provide insight in understanding the limits of generalizability of scientific claims. The primary limitation of the repliCATS process is its reliance on human-derived predictions with consequent costs in terms of participant fatigue although careful design can minimise these costs. The repliCATS process has potential applications in alternative peer review and in the allocation of effort for replication studies

Expert Status and Performance

Expert judgements are essential when time and resources are stretched or we face novel dilemmas requiring fast solutions. Good advice can save lives and large sums of money. Typically, experts are defined by their qualifications, track record and experience [1], [2]. The social expectation hypothesis argues that more highly regarded and more experienced experts will give better advice. We asked experts to predict how they will perform, and how their peers will perform, on sets of questions. The results indicate that the way experts regard each other is consistent, but unfortunately, ranks are a poor guide to actual performance. Expert advice will be more accurate if technical decisions routinely use broadly-defined expert groups, structured question protocols and feedback

Using Remote Sensing to Estimate Understorey Biomass in Semi-Arid Woodlands of South-Eastern Australia

Monitoring ground layer biomass, and therefore forage availability, is important for managing large, vertebrate herbivore populations for conservation. Remote sensing allows for frequent observations over broad spatial scales, capturing changes in biomass over the landscape and through time. In this study, we explored different satellite-derived vegetation indices (VIs) for their utility in estimating understorey biomass in semi-arid woodlands of south-eastern Australia. Relationships between VIs and understorey biomass data have not been established in these particular semi-arid communities. Managers want to use forage availability to inform cull targets for western grey kangaroos (Macropus fuliginosus), to minimise the risk that browsing poses to regeneration in threatened woodland communities when grass biomass is low. We attempted to develop relationships between VIs and understorey biomass data collected over seven seasons across open and wooded vegetation types. Generalised Linear Mixed Models (GLMMs) were used to describe relationships between understorey biomass and VIs. Total understorey biomass (live and dead, all growth forms) was best described using the Tasselled Cap (TC) greenness index. The combined TC brightness and Modified Soil Adjusted Vegetation Index (MSAVI) ranked best for live understorey biomass (all growth forms), and grass (live and dead) biomass was best described by a combination of TC brightness and greenness indices. Models performed best for grass biomass, explaining 70% of variation in external validation when predicting to the same sites in a new season. However, we found empirical relationships were not transferrable to data collected from new sites. Including other variables (soil moisture, tree cover, and dominant understorey growth form) improved model performance when predicting to new sites. Anticipating a drop in forage availability is critical for the management of grazing pressure for woodland regeneration, however, predicting understorey biomass through space and time is a challenge. Whilst remotely sensed VIs are promising as an easily-available source of vegetation information, additional landscape-scale data are required before they can be considered a cost-efficient method of understorey biomass estimation in this semi-arid landscape

Modelling the benefits of habitat restoration in socio-ecological systems

Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decision