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Here, we use records between 1998 and 2024 to document the occurrence of a native population of the turtle Kinosternon leucostomum leucostomum (Duméril & Bribon in Duméril & Duméril, 1851) in the Central Depression of Chiapas, Mexico. Morphological measurements are provided to characterize variation among individuals. We report 22 individuals, which were captured from Laguna Bélgica, captured in October and November 1998, and six individuals photographed by rangers in 2024. This is the first record of the species in the region, which represent a higher altitude locality compared with previously documented for wild populations of this turtle in Mexico.

Biodiversity and ecosystem service models are frequently used to consider current conditions or recent changes in the availability of a service. The application of scenarios for biodiversity and ecosystem service assessment remains underdeveloped, particularly co-designed and fine-granular scenarios across different decision-making boundaries. Consequently, the data created by these modeling efforts may not be as valuable to conservation partners and policy makers. In this project, we used land use and land cover change scenarios co-developed with local and regional decision-makers in northwestern Virginia USA as key inputs for 18 different biodiversity and ecosystem service models. Specifically, we used the InVEST suite of models to predict the change in biodiversity and ecosystem indicators and evaluated differences in that change between scenarios and decision-making boundaries. We found that the scenarios produced distinct results for the majority of biodiversity and ecosystem services, especially as a function of population growth. However, we also found that some services varied more as a function of subregions reflecting the existing diversity of ecosystems and governance structures in the area. The co-designed scenarios and summary of the data across units resulted in the production of varied results that can be used to support land use planning by implementing partners.

Abstract Land use is one of the largest threats to biodiversity, ecosystem function, and ecosystem services. These losses can be mitigated through strategic land use planning efforts that balance the social, economic, and environmental needs of society and the ecosystems that support it. A crucial component in the development of strategic plans is a concrete understanding of land use change and the impacts and influence of it on the landscape. Land change models are one method for quantifying the effect of these relationships and projecting the resulting changes on landscapes of the future. However, in order for the resulting model products to be useful to planners, policy makers, and conservationists, they must be focused on addressing questions of relevance to the community they intend to serve. Scenario planning offers a framework for integrating community‐developed visions of the future with land change models in order to increase relevancy and uptake of products. We developed a land change model for five future scenarios of land use change in northwestern Virginia, integrating regional stakeholder knowledge throughout the process. Across scenarios, we found consistent increases in development across our study area, but the form and configuration of land use types varied sub‐regionally. This manuscript describes not only our results, but the process of integrating stakeholder input throughout. We describe our model outputs in the context of usefulness for planners, policy makers, and conservation decision makers, often through the lens of the importance of geographic scale. This work serves as an additional example of land use modeling across scenarios. We conclude with guidance for scientists interested in integrating similar approaches in their work.

Biodiversity is in precipitous decline globally across both terrestrial and marine environments. Therefore, conservation actions are needed everywhere on Earth, including in the biodiversity rich landscapes and seascapes where people live and work that cover much of the planet. Integrative landscape and seascape approaches to conservation fill this niche. Making evidence-informed conservation decisions within these populated and working landscapes and seascapes requires an in-depth and nuanced understanding of the human dimensions through application of the conservation social sciences. Yet, there has been no comprehensive exploration of potential conservation social science contributions to working landscape and seascape initiatives. We use the Smithsonian Working Land and Seascapes initiative – an established program with a network of 14 sites around the world – as a case study to examine what human dimensions topics are key to improving our understanding and how this knowledge can inform conservation in working landscapes and seascapes. This exploratory study identifies 38 topics and linked questions related to how insights from place-based and problem-focused social science might inform the planning, doing, and learning phases of conservation decision-making and adaptive management. Results also show how conservation social science might yield synthetic and theoretical insights that are more broadly applicable. We contend that incorporating insights regarding the human dimensions into integrated conservation initiatives across working landscapes and seascapes will produce more effective, equitable, appropriate and robust conservation actions. Thus, we encourage governments and organizations working on conservation initiatives in working landscapes and seascapes to increase engagement with and funding of conservation social science.

Abstract The United Nations Sustainable Development Goals (SDGs) provide a global blueprint to end extreme poverty, reduce inequality, and protect the planet. Progress toward these goals is falling short. Achieving the SDGs requires coordination among government, private industry, and nongovernmental organizations to align the actions of multiple sectors with SDG targets. Adapting an approach used by industry sectors, we mapped the Smithsonian Institution Working Land and Seascapes network to the SDGs. The network of programs aims to foster healthy and productive ecosystems through collaborations with diverse stakeholders. Across the network, we identified clear and measurable contributions to 16 of the 17 SDGs and specifically mapped past and current activities to 76 of the 169 targets, thereby demonstrating how conservation actions can contribute to achieving the SDGs, beyond SDGs 14 and 15. We also identified the need for clear results chain and greater capacity to achieve the SDGs and then provide examples of how different sectors can increase complementarity of their actions. By mapping activities to the SDGs, different sectors can increase alignment and strengthen collective contributions towards common global goals.

Future climate projections of warming, drying, and increased weather variability indicate that conventional agricultural and production practices within the Northern Great Plains (NGP) will become less sustainable, both ecologically and economically. As a result, the livelihoods of people that rely on these lands will be adversely impacted. This is especially true for Native American communities, who were relegated to reservations where the land is often vast but marginal and non-tribal operators have an outsized role in food production. In addition, NGP lands are expected to warm and dry disproportionately relative to the rest of the United States. It is therefore critical to identify models of sustainable land management that can improve ecological function and socio-economic outcomes for NGP communities, all while increasing resilience to a rapidly changing climate. Efforts led by Native American Nations to restore North American Plains bison (Bison bison bison) to tribal lands can bring desired socio-ecological benefits to underserved communities while improving their capacity to influence the health of their lands, their people, and their livelihoods. Ecological sustainability will depend on the restoration of bison herds and bison’s ability to serve as ecosystem engineers of North America’s Plains. The historically broad distribution of bison suggests they can adapt to a variety of conditions, making them resilient to a wide range of management systems and climates. Here we review bison’s ecological, cultural, and economic value using four case studies from tribal communities within the NGP. We discuss the potential contributions of bison to food sovereignty, sustainable economies, and conservation of a working landscape with limited protections and significant risk of conversion. The ecological role of bison within this setting has potential due to cultural acceptance and the vast availability of suitable lands; however, it is critical to address tribal needs for funding support, enhanced community capacity, and solving complex landownership for these goals to be achieved.

Abstract Background Speed and distance traveled provide quantifiable links between behavior and energetics, and are among the metrics most routinely estimated from animal tracking data. Researchers typically sum over the straight-line displacements (SLDs) between sampled locations to quantify distance traveled, while speed is estimated by dividing these displacements by time. Problematically, this approach is highly sensitive to the measurement scale, with biases subject to the sampling frequency, the tortuosity of the animal’s movement, and the amount of measurement error. Compounding the issue of scale-sensitivity, SLD estimates do not come equipped with confidence intervals to quantify their uncertainty. Methods To overcome the limitations of SLD estimation, we outline a continuous-time speed and distance (CTSD) estimation method. An inherent property of working in continuous-time is the ability to separate the underlying continuous-time movement process from the discrete-time sampling process, making these models less sensitive to the sampling schedule when estimating parameters. The first step of CTSD is to estimate the device’s error parameters to calibrate the measurement error. Once the errors have been calibrated, model selection techniques are employed to identify the best fit continuous-time movement model for the data. A simulation-based approach is then employed to sample from the distribution of trajectories conditional on the data, from which the mean speed estimate and its confidence intervals can be extracted. Results Using simulated data, we demonstrate how CTSD provides accurate, scale-insensitive estimates with reliable confidence intervals. When applied to empirical GPS data, we found that SLD estimates varied substantially with sampling frequency, whereas CTSD provided relatively consistent estimates, with often dramatic improvements over SLD. Conclusions The methods described in this study allow for the computationally efficient, scale-insensitive estimation of speed and distance traveled, without biases due to the sampling frequency, the tortuosity of the animal’s movement, or the amount of measurement error. In addition to being robust to the sampling schedule, the point estimates come equipped with confidence intervals, permitting formal statistical inference. All the methods developed in this study are now freely available in the ctmm R package or the ctmmweb point-and-click web based graphical user interface.