One important goal of the Kunming-Montreal Global Biodiversity Framework (KMGBF) aims to halt extinction of species and reduce extinction risk 10-fold by 2050. To help ensure that the actions taken under the targets of the KMGBF contribute to reducing species' extinction risk, the Species Threat Abatement and Restoration (STAR) metric was designed to enable science-based target setting for species. STAR quantifies the potential contribution of threat abatement actions or habitat restoration to reducing species' extinction risk in an area. To support the effective implementation of STAR, we developed a framework to move from determining the threat abatement component of STAR (START) using global data to calibrating START using local data to setting targets and calculating realized START scores to measure progress. The framework outlines the specific approaches that can be implemented to calculate these different START metrics. First, estimated START scores use global data to provide an initial indication of the species and threats expected to be present within an area. Then, calibrated START scores involve confirming the local presence of species and threats, and the locally verified data allow for setting robust threat abatement targets, which can be articulated as target START scores. Calibrated START can also inform both reactive and proactive threat management. Finally, changes in threat intensity are then monitored and used to calculate realized START. Achieving realized START requires actors to not only reduce existing threats but also prevent additional threats emerging within the area. This framework provides a means for all potential actors, working across varying spatial scales, to quantify, plan, monitor, and deliver interventions to address species threats and then report the impact of the interventions using a consistent method and metric that are comparable and aggregable across actors and locations.
Abstract The application of hot product frameworks, such as value, inertia, visibility, and accessibility (VIVA) and concealable, removable, available, (abundance and accessibility), valuable, enjoyable, and disposable (CRAVED/CRAAVED), to illegal markets to understand the selection of wildlife products in them has gained momentum. Originally developed to study property crimes, these frameworks have been adapted for predictive analysis of wildlife product selection. However, their utility in explaining target selection and their empirical testability remain ambiguous. This study critically examined the use of the VIVA and CRA(A)VED frameworks in analyzing wildlife product selection for illegal markets. By reviewing peer‐reviewed studies and conducting a case study on Southeast Asian monitor lizards ( Varanus spp.), we identified the challenges of applying these frameworks to real‐world contexts. These challenges are not merely methodological shortcomings of individual studies but reflect systematic difficulties inherent to applying these frameworks to wildlife contexts. The application of these frameworks to Southeast Asian monitor lizards confirmed that these issues transcend species groups. We also examined issues related to intraspecific variation in measures and variation between harvesters. Our analysis revealed complex interactions between attributes that influence wildlife product selection and identified key challenges to applying these frameworks, including incomplete data, inconsistent attribute measurements, and the dynamic nature of decision‐making during wildlife harvesting. A significant concern is the reliance on trade data, which are typically collected much later in the wildlife trade chain, to infer harvesting decisions. Moreover, we argued that target selection is not solely determined by product attributes. A more problem‐oriented and individualized approach that accounts for opportunity structures relevant to individual harvesters is needed to prevent aggregation fallacies. Thus, applying hot product frameworks to study the selection of target wildlife products cannot be quantitatively tested using an additive equation, and these frameworks should not be applied alone but situated within other theories of crime.
Abstract To achieve Kunming–Montreal Global Biodiversity Framework (GBF) Target 3, the selection of protected areas must consider the condition of ecosystems at sites in addition to the GBF 30% area target. Implementing this consideration for coral reef ecosystems is challenging because data describing condition are patchy and limited. Thus, there is uncertainty in how effective coral reef condition data are for informing conservation priorities. To address this uncertainty, we evaluated whether including ecosystem condition data changed conservation priorities when the objective was to protect reefs and implement Target 3. We tested multiple static and modeled temporal coral reef condition datasets for the Great Barrier Reef and found that including reef condition significantly altered spatial planning priorities ( p < 0.001), with effects varying according to the condition indicator used. Almost half of the reefs prioritized for protection when condition metrics were included became low priority when they were excluded. Ignoring information about condition missed conservation targets for ∼22% of reef habitats once condition measures were included, highlighting how presence‐only approaches can overestimate conservation benefits by treating lower‐condition reefs as equal contributors to biodiversity protection. These differences in priority areas highlight the need to develop and use effective condition metrics for designing marine protected area systems for coral reefs globally. Making such data available and usable for managers and practitioners is a priority for coral reef conservation.
Abstract Climate change is driving increasingly frequent and severe weather events that can undermine the effectiveness of conservation interventions for threatened species, yet the extent and mechanisms of such impacts remain poorly understood. We assessed both peer‐reviewed and gray literature to determine how climate adaptation interventions have been affected by weather events across different land types, Australian bioregions, taxonomic groups, and intervention categories. Specifically, we evaluated 593 climate adaptation interventions for 145 threatened species in Australia. We found 36% of the interventions experienced impacts from weather events, with only 9% of these reporting positive outcomes, which were significantly associated with above‐average rainfall. Critically, our dataset was dominated by plant‐focused translocations, with drought and wildfire representing the primary stressors. Most taxonomic groups, despite being targeted by conservation interventions, experienced population declines and habitat loss following weather events. Inadequate mitigation of cumulative threats, such as grazing pressure and weed invasion, frequently exacerbated negative impacts and reduced the resilience of ecosystems to withstand and recover from weather impacts. Our findings suggested that although extreme weather risks have been recognized, they are not yet being systematically incorporated into the design and implementation of climate adaptation interventions in Australia. We recommend adopting adaptive and integrated management approaches to enhance climate adaptation success for threatened species, particularly by enabling the systematic management of multiple threats and facilitating flexible, evidence‐informed interventions in response to changing environmental conditions. Future research should prioritize adopting more rigorous, proactive experimental designs that bridge the gap between recognizing extreme weather risks and implementing robust mitigation strategies. Expanding the empirical basis for climate adaptation is also needed for less‐represented taxa such as reptiles, invertebrates, and freshwater fish, as well as in regions with limited data such as central and northern Australia where increased cyclone and flooding intensities are already occurring.
Amid a global biodiversity crisis hastened by climate change, it is urgent that species' declines are halted. To design the most effective conservation strategies to address these declines, the nature and timing of the most probable genetic or nongenetic factors behind population collapses need to be identified. We used high-density RADseq genetic markers to determine the demographic history and track population-level exposure of the Knysna seahorse (Hippocampus capensis), the first syngnathid listed as endangered by the International Union for Conservation of Nature (IUCN), to historical and current threats. Our results revealed an initial link between sea-level fluctuations and settlement for this estuarine endemic species that occurred on a coastline without obvious alternative habitats that were followed by divergence and progressive isolation of the extant populations. Two of the three extant Knysna seahorse populations, those inhabiting estuaries most affected by floods and natural or human-mediated breaching of the estuary mouths, showed severe and continued contractions in effective population size. We illustrated the potential of genomics for the conservation of the most vulnerable species and their fragile ecosystems and highlighted the urgency and type of measures required to maintain species' persistence and resilience. Our results provide practical insights to help protect this endangered seahorse, namely, the need for proactive management, which is essential for preventing the expected losses of genetic diversity that follow shrinking effective population sizes. Additionally, we showed that hydrological stability and increased substratum availability can foster recoveries without the need for potentially riskier alternatives such as the recently proposed seahorse translocations. Recuento de la informaci & oacute;n gen & oacute;mica del caballito de mar, un pasado de asilamiento aplicado y una gu & iacute;a para futuros esfuerzos de conservaci & oacute;n
