Biodiversity is essential to human well-being, but people have been reducing biodiversity throughout human history. Loss of species and degradation of ecosystems are likely to further accelerate in the coming years. Our understanding of this crisis is now clear, and world leaders have pledged to avert it. Nonetheless, global goals to reduce the rate of biodiversity loss have mostly not been achieved. However, many examples of conservation success show that losses can be halted and even reversed. Building on these lessons to turn the tide of biodiversity loss will require bold and innovative action to transform historical relationships between human populations and nature.

Using the past to inform the future: The late Quaternary paleorecord, within the past ∼130,000 years, can help to inform present-day management of the Earth's ecosystems and biota under climate change. Fordham et al. review when and where rapid climate transitions can be found in the paleoclimate record. They show how such events in Earth's history can shape our understanding of the consequences of future global warming, including rates of biodiversity loss, changes in ecosystem structure and function, and degradation in the goods and services that these ecosystems provide to humanity. They also highlight how recent developments at the intersection of paleoecology, paleoclimatology, and macroecology can provide opportunities to anticipate and manage the responses of species and ecosystems to changing climates in the Anthropocene. Science , this issue p. eabc5654

Camera traps are widely used in wildlife research and monitoring, so it is imperative to understand their strengths, limitations, and potential for increasing impact. We investigated a decade of use of wildlife cameras (2012–2022) with a case study on Australian terrestrial vertebrates using a multifaceted approach. We (i) synthesised information from a literature review; (ii) conducted an online questionnaire of 132 professionals; (iii) hosted an in‐person workshop of 28 leading experts representing academia, non‐governmental organisations (NGOs), and government; and (iv) mapped camera trap usage based on all sources. We predicted that the last decade would have shown: (i) exponentially increasing sampling effort, a continuation of camera usage trends up to 2012; (ii) analytics to have shifted from naive presence/absence and capture rates towards hierarchical modelling that accounts for imperfect detection, thereby improving the quality of outputs and inferences on occupancy, abundance, and density; and (iii) broader research scales in terms of multi‐species, multi‐site and multi‐year studies. However, the results showed that the sampling effort has reached a plateau, with publication rates increasing only modestly. Users reported reaching a saturation point in terms of images that could be processed by humans and time for complex analyses and academic writing. There were strong taxonomic and geographic biases towards medium–large mammals (>500 g) in forests along Australia's southeastern coastlines, reflecting proximity to major cities. Regarding analytical choices, bias‐prone indices still accounted for ~50% of outputs and this was consistent across user groups. Multi‐species, multi‐site and multiple‐year studies were rare, largely driven by hesitancy around collaboration and data sharing. There is no widely used repository for wildlife camera images and the Atlas of Living Australia (ALA) is the dominant repository for sharing tabular occurrence records. However, the ALA is presence‐only and thus is unsuitable for creating detection histories with absences, inhibiting hierarchical modelling. Workshop discussions identified a pressing need for collaboration to enhance the efficiency, quality and scale of research and management outcomes, leading to the proposal of a Wildlife Observatory of Australia (WildObs). To encourage data standards and sharing, WildObs should (i) promote a metadata collection app; (ii) create a tagged image repository to facilitate artificial intelligence/machine learning (AI/ML) computer vision research in this space; (iii) address the image identification bottleneck via the use of AI/ML‐powered image‐processing platforms; (iv) create data commons for detection histories that are suitable for hierarchical modelling; and (v) provide capacity building and tools for hierarchical modelling. Our review highlights that while Australia's investments in monitoring biodiversity with cameras position it to be a global leader in this context, realising that potential requires a paradigm shift towards best practices for collecting, curating, sharing and analysing ‘Big Data’. Our findings and framework have broad applicability outside Australia to enhance camera usage to meet conservation and management objectives ranging from local to global scales. This review articulates a country/continental observatory approach that is also suitable for international collaborative wildlife research networks.

Spatially explicit population models (SEPMs) can simulate spatiotemporal changes in species' range dynamics in response to variation in climatic and environmental conditions, and anthropogenic activities. When combined with pattern‐oriented modelling methods, ecological processes and drivers of range shifts and extinctions can be identified, and plausible chains of causality revealed. The open‐source multi‐platform R package poems provides functionality for simulating and validating projections of species' range dynamics using stochastic, lattice‐based population models. Built‐in modules allow parameter uncertainty to propagate through to model simulations, with their effects on species' range dynamics evaluated using Approximate Bayesian Computation. These validation procedures identify models with the structural complexity and parameterisation needed to simulate the effects of past changes in climate, environment and human activities on species' range shifts and extinction risk. We illustrate the features and versatility of poems by simulating the historical decline and extinction of the Thylacine Thylacinus cynocephalus, an icon of recent extinctions in Australia. We show that poems can reveal likely ecological pathways to extinction using pattern‐oriented methods, providing validated projections of the range collapse and population decline of threatened species. By providing flexible and extendable modules for building and validating SEPMs of species' range dynamics, poems allows the effects of past and future threats on species' populations to be quantified using well‐parameterised, structurally realistic models, with important generative mechanisms. Since poems can directly unravel ecological processes of species responses to global change, and strengthen predictions of range shifts and extinction risk—within a flexible, R‐based environment—we anticipate that poems will be of significant value to ecologists, conservation managers and biogeographers.