Abstract Urban biodiversity remains one of the most persistent blind spots in global monitoring frameworks. Despite over four decades of efforts to advance biodiversity indicators, existing frameworks still struggle to define meaningful metrics for cities, especially those that enable comparison, policy alignment, and mutual learning across diverse urban contexts. This gap is especially evident in efforts to implement the Kunming‐Montreal Global Biodiversity Framework (KM‐GBF), where municipalities, researchers, and practitioners continue to face difficulties in identifying appropriate indicators for its urban‐focused Target 12. Addressing this gap requires a deeper understanding of how urban practitioners navigate the science‐policy interface when translating global ambitions into actionable, context‐sensitive measures. This study investigates how urban biodiversity practitioners approach the selection and implementation of indicators under science‐policy constraints. We draw on experiences from Kigali, Rwanda, and Melbourne, Australia—two cities that reflect contrasting urban realities in the Global South and North. From these complementary perspectives, we identify five practitioner‐informed criteria to support the development of fit‐for‐purpose urban biodiversity indicators. Rather than presenting these criteria as a universal framework, we position them as a screening approach. They are intended to help identify indicators that are more likely to be locally meaningful, operationally workable, and relevant across policy scales in cities with urban biodiversity monitoring contexts similar to those examined in Kigali and Melbourne.
Abstract Landscape connectivity is critical for maintaining populations of wildlife species and ecological integrity. However, connectivity can refer to a wide array of ecological processes across many spatio‐temporal scales, making it a nebulous concept for managers needing to develop concrete objectives. Furthermore, systematic and consistent connectivity information at multiple scales and for multiple species and ecosystems is lacking, leaving managers without baseline information from which to begin assessing connectivity needs. To fill this information gap, we conducted connectivity analyses across multiple spatial scales that represent connectivity for species guilds with different habitat associations and movement abilities. We used two different connectivity approaches, resistant kernels and Omniscape, and capitalized on the strengths of each method to classify the outputs into a typology that we call “kernel‐scape” for spatial management decision‐making. We describe the utility of these products for managers of the US National Forest System, who are required to consider connectivity in land management planning. We provide a set of seamless connectivity products that are applicable to multiple species and ecological processes across tiered planning extents, from the contiguous US, to geographic regions, to individual management units. These products provide baseline information for considering connectivity for a variety of natural resource needs.
Abstract Conservation practitioners can often struggle to achieve multiple goals—such as monitoring community diversity, tracking species of concern, and evaluating community and species' responses to on‐the‐ground activities—within limited time and budgets. This study aimed to identify the most efficient field and analytical methods for achieving monitoring goals simultaneously in pollinator surveys. We evaluated whether integrating targeted visual surveys with standard community netting surveys could improve detection efficiency for Bombus occidentalis (western bumble bee), a declining species of concern, while still capturing broader community data. In 2023, we conducted netting surveys for bumble bees ( Bombus spp.) at 22 sites in Glacier National Park and added visual surveys specifically for western bumble bees if not detected during netting. We estimated western bumble bee occupancy and detection using two site‐occupancy models: (1) traditional detection/non‐detection (DND) models and (2) time‐to‐detection (TTD) models. We also assessed model performance with reduced (subsampled) survey effort. Models that integrated net and visual surveys produced similar occupancy estimates but higher cumulative detection probability than net‐only surveys, with visual surveys requiring less effort than additional net surveys. Notably, 17% of visits (11 of 66) yielded western bumble bee detections during visual surveys only. Although full datasets yielded comparable results between TTD and DND models, subsampling introduced large bias and decreased precision, particularly for net‐only and single‐survey TTD models. For conservation practitioners with limited time and budgets for monitoring, incorporating targeted visual surveys into community‐level surveys can increase detection of species of concern without increasing the number of visits.
Reducing threats to sea turtle eggs and hatchlings is critical for increasing hatching survival and recruitment, which supports the recovery of sea turtle populations. However, changes in temperature and rainfall from climate change have been identified as emergent risks to the nesting success of sea turtles globally. To reduce both of these threats and increase the nesting success of the beach, eggs are relocated to a protected area and covered in mesh (e.g., hatchery). However, the success rates of these nests in light of the changing climate are not fully understood, and must be continually assessed as climate change progresses. This study aims to elucidate and update the impacts of nest temperatures and rainfall on the San Miguel olive ridley hatchery success from 2019 to 2022 sea turtle seasons. Nest excavations were conducted inside the hatchery to determine emergence, hatching, and hatchery success (the proportion of viable relocated eggs that produce live emerging hatchlings under protected incubation conditions). We found mean nest sand temperature to be 29.63 degrees C ranging from 28 to 31 degrees C. Nest sand temperatures significantly affect nest failures (Estimate = 0.123 +/- 0.059 SE, z = 2.088, p = .037) while nesting seasons also significantly affect nest failures with lower failure rates observed in 2021 (Estimate = -0.485 +/- 0.171 SE, z = -2.827, p = .0047) and 2022 (Estimate = -0.398 +/- 0.190 SE, z = -2.094, p = .036), but rainfall did not. Overall, hatchery success was 85% across the seasons, except in 2020 when success declined to 70%. These findings demonstrate that hatchery management at Playa San Miguel has been effective in maintaining high incubation success and suggest that adaptive management practices may help buffer nests from the effects of rising sand temperatures.
The blue‐crowned laughingthrush (BCLT; Pterorhinus courtoisi ) is a Critically Endangered bird restricted to southeast China. Breeding sites are situated within agricultural‐forest mosaic habitats; it is unclear why the species is not more widely distributed across similar landscapes. Identifying factors that restrict the species' breeding range is essential for conservation planning. We quantified BCLT habitat preferences by combining fine‐scale vegetation measures from 39 villages in Jiangxi and Anhui Provinces with topographic and satellite data across the species' breeding range, applying resource selection functions at both the breeding‐site and the nest‐site scale. We found that BCLT may be considered a broadly generalist species with little evidence of habitat differences between breeding sites and those with no known history of breeding BCLT at this spatial scale. However, nest‐sites are more likely to contain larger broadleaf trees, bamboo stands, conifer or mixed forest, and to be on lower slope inclines. Our findings indicate that nest‐site selection is important for BCLT and highlight the need to protect remaining large broadleaf trees across the landscape. These results also demonstrate the importance of integrating conservation‐relevant data across multiple scales to provide new insights for threatened species management planning and landscape policy.
