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Aim: Invertebrates make up the vast majority of fauna species but are often overlooked in impact assessment and conservation response. The extent to which the 2019–2020 Australian megafires overlapped with the range of vertebrate species has been well documented; consequently, substantial resourcing has been directed towards their recovery. Here, we attempt to document the extent of overlap of these megafires with invertebrate species. In doing so, we seek to demonstrate that it is possible and worthwhile to assess the effect of a catastrophic event on a large number of poorly known species. Location: Temperate and subtropical Australia. Time period: 2019–2020. Major taxa: Australian invertebrates. Methods: We adapted a published analytical pathway for the assessment of distributional fire overlap on vertebrate species. Overlaps with fire for 32,163 invertebrate taxa were determined using point records and polygons. Results: We found that 13,581 invertebrate taxa had part of their range burnt in the 2019–2020 Australian megafires. Of these, 382 taxa had the whole of their known range burnt, and a further 405 taxa had 50–99.9% of their range burnt. Five examples are described. Main conclusions Poorly known groups of biodiversity can be impacted significantly by major disturbance events, but such impact is often overlooked. This oversight has the consequences of under‐estimating the magnitude of impacts and the potential failure to direct conservation responses to those species most in need of them. Our analysis demonstrates that the 2019–2020 megafires burnt ≥50% of the known range of nearly 800 Australian invertebrate taxa, a tally far higher than for vertebrates (19 taxa). Assessment of the real impact (i.e., beyond simply overlap with fire) requires more consideration of susceptibility and/or post‐fire survey and monitoring. The magnitude of overlap of the 2019–2020 megafires on invertebrate species justifies a conservation response that is less biased towards iconic vertebrate species. [ABSTRACT FROM AUTHOR]

Equilibrium models (EMs) are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Despite their central role coupling economic and environmental systems, environmental scientists are largely unfamiliar with the structure and methodology underpinning EMs, which serves as a barrier to interdisciplinary collaboration and model improvement. In this study we systematically extract data from 10 years of published EMs with a focus on how these models have been extended beyond their economic origins to encompass environmentally relevant sectors of interest. The results indicate that there is far greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. For example, we were unable to identify a single temporally dynamic study that distinguished between products arising from managed versus natural forest, or pastures relative to natural grasslands. Due to the necessary breadth and associated knowledge gaps within a model of the entire global economy, we see considerable potential for cross‐disciplinary innovation as natural scientists gain familiarity into the role these models play in bridging the nexus between socioeconomic systems and environmental change. Plain Language Summary: This analysis of studies using equilibrium models provides an introduction to how they have been employed across a wide range of disciplines with an emphasis on their application within environmental analyses. We find that many model components are represented in a highly aggregated form, hampering their usefulness in policy‐making. This problem is particularly acute in low income geographic areas as well as within key production inputs. Key Points: Heterogeneity in ecologically consequential production inputs are rarely represented in temporally dynamic studiesSpatial aggregation disproportionately affects low income countries, notably Central America, Africa, the Middle East, and Central AsiaKey socioeconomic drivers within global socioeconomic scenarios have largely not been implemented within equilibrium studies [ABSTRACT FROM AUTHOR]

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Effective biodiversity conservation requires responding to threats in a timely fashion. This requires understanding the impacts of threats on biodiversity and when management needs to be implemented. However, most ecological systems face multiple threats, so monitoring to assess their impacts on biodiversity is a complex task. Indicators help simplify the challenge of monitoring but choosing the best indicator(s) to inform management is not straightforward.We provide a decision framework that can help identify optimal indicators to trigger management in a system faced with multiple threats. The approach evaluates indicators based on criteria spanning monitoring efficiency, management outcomes and the economic constraints for decision‐making. Critical decision factors (or parameters) are identified and detailed in a six‐step process to estimate the cost‐effectiveness of alternate indicators, including threat impacts, sensitivity of indicators to detect change, and the benefits, costs and feasibility of alternative indicators and management actions.Using the Kimberley as a case study, we evaluate 18 indicators for informing management of three key threats in the region: fire and grazing, feral cat predation, and weeds. We show that indicator selection based on our approach can help improve the expected outcome of management decisions under limited resources. By accounting for multiple factors in estimating benefit and costs of monitoring, our approach improves on common approaches that select indicators based only on whether they are sensitive to change and/or cheap to monitor. We also identify how uncertainty in decision factors influences indicator selection.Although cost‐effectiveness analyses are gaining popularity, ours is the first study to integrate multiple selection criteria using a return on investment framework to compare indicators for monitoring multiple threats and triggering management. [ABSTRACT FROM AUTHOR]

Abstract: Making effective management decisions is challenging in multi‐species, multi‐threat systems because of uncertainty about the effects of different threats on different species. To inform management decisions, we often monitor species to detect spatial or temporal trends that can help us learn about threatening processes. However, which species to monitor and how to monitor to inform the management of threats can be difficult to determine. Value of information (VOI) analysis is an approach for quantifying the value of monitoring to inform management decisions. We developed a novel method that applies VOI analysis to quantify the benefits of different species monitoring strategies in multi‐threat, multi‐species systems. We applied the approach to compare the effectiveness of surveillance monitoring (monitoring species without experimentation) to targeted monitoring (monitoring species with experimentation to learn about a specific threat), and how prior information drives the benefits of these two different strategies and the species to monitor. We also illustrate the approach by applying it to two contrasting case studies for monitoring and managing declining mammals in Western Australia. Our approach shows that surveillance monitoring generally provides far lower benefits than targeted monitoring for managing threats in multi‐species, multi‐threat systems under economic constraints. Our approach also informs the choice of species to monitor and which threats to manage experimentally to most improve threat management outcomes. We show that the key parameters driving these choices include: the budget available for management, prior understanding of which threats cause declines in which species, the relative cost of managing these threats, and the background probability of decline. Our new VOI approach allows the evaluation of monitoring decisions in multi‐species, multi‐threat systems in the face of uncertainty, while explicitly accounting for the improvement in management outcomes. We recommend that managers need to explicitly consider a range of decision parameters when selecting which species to monitor to inform management. Our framework provides an objective way to do this. [ABSTRACT FROM AUTHOR]

Donors, NGOs, and governments increasingly invest in campaigns to reduce consumer demand for wildlife products in an attempt to prevent the decline of overexploited and poached species. We provide a novel framework to aid these investment decisions based on a demand reduction campaign's return on investment compared to antipoaching law enforcement. A resulting decision rule shows that the relative effectiveness of demand reduction compared to increased enforcement depends entirely on social and economic uncertainties rather than ecological ones. Illustrative case studies on bushmeat and ivory reveal that campaigning to reduce demand may be more cost‐effective than antipoaching enforcement if demand reduction campaigns drive modest price reductions. The outputs from this framework can link targeted monitoring of wildlife product prices to management decisions that protect species threatened by harvest and trade. [ABSTRACT FROM AUTHOR]