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The sustainable use of farmland depends on the precise identification of promising reserved cultivated land resources, particularly in regions with fragmented spatial patterns and complex environmental conditions. Traditional evaluation methods often rely on limited indicators and neglect patch morphology, leading to restricted accuracy and applicability. To address this issue, an innovative intelligent-selection framework is proposed that integrates multi-source data evaluation with patch-morphology verification and employs convolutional neural networks (CNNs), applied in Qinghai Province, China. The framework combines one-dimensional and two-dimensional CNN models, incorporating 11 key indicators—including slope, irrigation conditions, and contiguity—together with patch morphology to predict development priority. Results show that the two models achieve predictive accuracies of 98.48% and 91.95%, respectively, outperforming the traditional Analytic Hierarchy Process (AHP) and effectively filtering out irregular patches unsuitable for cultivation. Further SHAP analysis and ablation experiments reveal the contributions of individual indicators, with slope identified as the dominant factor in prioritization. Overall, the study demonstrates that integrating multi-source data evaluation with patch-morphology verification within a machine-learning framework significantly enhances prioritization accuracy. The proposed framework provides a transferable, evidence-based pathway for the graded utilization of reserved cultivated land resources and the reinforcement of farmland security strategies.

The decline and extinction of native plant species is a global conservation crisis, and there is a need for rapid prioritization of our conservation efforts. In the USA, the two main systems used to identify at-risk species, Threatened and Endangered (T&E) status and conservation status ranks by NatureServe (G- and S-ranks), are categorical and typically assessed with large-scale criteria, thus are not ideal to aid practitioners in developing priorities at smaller scales. Our goal was to develop a continuous risk assignment for plant species using monitoring data collected at a smaller scale so that limited conservation resources can be better prioritized among at-risk species. To do this, we modified a count-based population viability analysis to produce two regional, species-level viability metrics: a regional growth rate and a regional 50-y probability of extinction. Our validation exercises confirmed these metrics could reliability place 24 rare forb species along a continuous scale of viability. We identified nine species (37.5% of those analyzed) in need of conservation effort in northern Illinois. The challenges we faced developing these metrics and our solutions are discussed more generally to improve rare plant species monitoring practices. Overall, this method is an innovative expansion of the use of population size monitoring data to inform conservation beyond the population.

Occasionally, doctors and health providers have to choose whom they save from death and this is an extremely hard decision to take. Here, I work on what I deem to be a crucial caveat: scarcity of resources should never be used as an alibi for bad, and sometimes wicked, public policies. In other words, if scarcity is somewhat produced or at least induced, it should never serve as a pretext to put the blame or the responsibility on medical doctors, nurses and other people who are at the front of the war against COVID-19. During the COVID-19 pandemic, an ethical question was often raised: if resources are scarce (and they often have been), whom should you prioritize? Should we protect first of all those who are young and can then have a long life before them? Or should we rather prioritize those who have rendered important services to health, or broadly to mankind, and could, therefore, bring other good results to society? This discussion is of course important, but it leaves aside something more fundamental: the fact that resources are not simply scarce, they have been made scarce in the last years by a series of public policies nourished by an economic view that sacrificed social welfare on behalf of neoliberal beliefs.

The application of a geographic information system (GIS) in public health is relatively common in Bangladesh. However, the use of GIS for planning, monitoring and decision-making by local-level managers has not been well documented. This assessment explored how effectively local government health managers used maps with spatial data for planning, resource allocation and programme monitoring. The United States Agency for International Development-funded MaMoni Health Systems Strengthening project supported the introduction of the maps into district planning processes in 2015 and 2016. GIS maps were used to support the prioritisation of underserved unions (the lowest administrative units) and clusters of disadvantaged communities for the allocation of funds. Additional resources from local government budgets were allocated to the lowest performing unions for improving health facility service readiness and supervision. Using a mixed-methods approach, the project evaluated the outputs of this planning process. District planning reports, population-based surveys, local government annual expenditure reports and service availability and utilisation data were reviewed. The goal was to determine the degree to which district planning teams were able to use the maps for their intended purpose. Key informant interviews were conducted with upazila (subdistrict) managers, elected government representatives and service providers to understand how the maps were used, as well as to identify potential institutionalisation scopes. The project observed improvements in health service availability and utilisation in the highest priority unions in 2016. Quick processing of maps during planning sessions was challenging. Nevertheless, managers and participants expressed their satisfaction with the use of spatial analysis, and there was an expressed need for more web-based GIS both for improving community-level service delivery and for reviewing performance in monthly meetings. Despite some limitations, the use of GIS maps helped local health managers identify health service gaps, prioritise underserved unions and monitor results.

This chapter examines whether an individual’s being worse off than others should be a relevant consideration in the allocation of limited medical resources. It reviews arguments pressed by proponents of different theories of justice about whether being worse off than others makes special demands on health care resource prioritization. Even if there is good reason to restrict the concern for the worse off to those with worse health in the prioritization and allocation of health care resources, additional issues remain. One is how to determine who has worse health, and whether the worse off are those with the worse overall health or those with the most serious medical condition now in need of treatment. Another issue is whether only individuals’ present health, or instead their lifetime health, including past and expected future health, is relevant.

This research paper presents a detailed investigation into the morphometric characteristics of sub-basins within the Naama region of Algeria, aiming to prioritize areas vulnerable to soil erosion and runoff risks. Focusing on five key sub-basins that collectively represent 75% of the Wilaya of Naama, the study employs a comprehensive methodological framework, integrating morphometric analysis (MA), weighted sum analysis (WSA), principal component analysis (PCA), and the novel approach of compositional data analysis (CoDA). Through the rigorous evaluation of sixteen distinct morphometric parameters selected based on their relevance to hydrological and geomorphological processes that influence erosion and runoff, this research provides a nuanced understanding of the factors influencing erosion susceptibility within each sub-basin. The analysis reveals a clear hierarchy of sub-basins based on their calculated compound parameters, effectively classifying them into high, moderate, and low priority categories for targeted intervention and resource allocation. The results highlight the Ain Sefra and Wadi Er Rosafa sub-basins as the highest priority areas, collectively encompassing 31.51% of the wilaya and posing the most significant threats of runoff and soil erosion. This identification allows for the prioritization of conservation efforts and the implementation of tailored management strategies in these critical areas. Furthermore, the integration of multiple prioritization approaches, including the innovative application of CoDA, ensures a robust and comprehensive assessment of the sub-basin landscapes. This multi-faceted approach provides a more nuanced understanding of the complex interplay between various morphometric parameters and their influence on erosion and runoff potential. The findings of this research have significant implications for sustainable land and water resource management within the Naama region. By identifying and prioritizing vulnerable sub-basins, the study provides a crucial foundation for informed decision-making, enabling stakeholders to implement targeted interventions and mitigate the detrimental impacts of soil erosion and excessive runoff. Moreover, the methodological framework presented in this research paper offers a valuable blueprint for similar studies in other regions facing comparable challenges. The cost-effective and time-efficient nature of the approach makes it a practical tool for prioritizing erosion and runoff risks in arid and semi-arid environments worldwide, contributing to the broader goals of environmental sustainability and land degradation neutrality.

Conservation prioritization requires knowledge about organism distribution and density. This information is often inferred from models that estimate the probability of species occurrence rather than from models that estimate species abundance, because abundance data are harder to obtain and model. However, occurrence and abundance may not display similar patterns and therefore development of robust, scalable, abundance models is critical to ensuring that scarce conservation resources are applied where they can have the greatest benefits. Motivated by a dynamic land conservation program, we develop and assess a general method for modeling relative abundance using citizen science monitoring data. Weekly estimates of relative abundance and occurrence were compared for prioritizing times and locations of conservation actions for migratory waterbird species in California, USA. We found that abundance estimates consistently provided better rankings of observed counts than occurrence estimates. Additionally, the relationship between abundance and occurrence was nonlinear and varied by species and season. Across species, locations prioritized by occurrence models had only 10–58% overlap with locations prioritized by abundance models, highlighting that occurrence models will not typically identify the locations of highest abundance that are vital for conservation of populations.

Watershed prioritization is essential in sub-watershed (SW) natural resource management. The Swat River watershed in the Hindukush mountains of Pakistan's Khyber Pakhtunkhwa province covers an area of 5337 km2. Using an Advanced Spaceborne Thermal Emission and Reflection Radiometer digital elevation model with a resolution of 30 m obtained from the United States Geological Survey (USGS), the present study identified 17 SWs (SW1–17) with drainage patterns ranging from dendritic to sub-dendritic. The SWs were assessed for their susceptibility to erosion via GIS-based assessment using a morphometry-based compound factor (CF) approach. A total of 15 linear, aerial, and relief morphometric characteristics were identified and analyzed. The SWs were ranked for each morphometric parameter based on their contribution to the erodibility of the SW. A ranking of 1 indicated that the SW had the greatest susceptibility to erosion for that parameter and a ranking of 17 indicates that it had the lowest. These rankings were summed to calculate the CF, which thus indicated the combined influence of these characteristics on the erosion susceptibility of the SW (a lower CF indicated a higher susceptibility to erosion). The SWs were consequently divided into four groups based on their susceptibility to erosion using the calculated CF: very high, high, moderate, and low susceptibility. SW8, SW12, and SW15 had the lowest CFs (8.0, 8.9, and 8.9, respectively) and were thus extremely vulnerable to erosion. In contrast, SW1, SW2, and SW4 had the highest CFs (13.4, 13.8, and 11.8, respectively) and were the least vulnerable to erosion. The very high-priority SWs were characterized by the presence of fifth-order streams, a length of the overland flow of 1.20–1.61, a very high basin relief of 1720–2937, the highest relief ratio of 102.10–205.24, a low shape factor of 1.51–2.67, and a farm factor of 0.37–0.66. The present study demonstrates that the key morphometric characteristics that impact soil erosion are basin form and relief parameters, such as the basin relief and relief ratio. This study illustrates that the CF approach to determining the susceptibility of SWs to soil erosion is extremely valuable for planners and decision-makers for soil conservation efforts at the SW level.

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat-specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species. Enlazar la diversidad con los procesos biológicos es esencial para el desarrollo de decisiones informadas y efectivas de conservación. Desafortunadamente, los patrones observables brindan sólo una proporción de la información necesaria para entender por completo los mecanismos y los procesos que actúan sobre una población o comunidad en particular. Le sugerimos a los administradores de la conservación que usen la información que es ignorada continuamente en relación a la ausencia de especies y que le presentar particular atención a la diversidad oscura (es decir, un conjunto de especies que está ausente de un sitio pero que podría dispersarse a y establecerse ahí, en otras palabras, la porción ausente de un acervo de especies específicas de habitat). Junto con las medidas y conceptos ecológicos y las herramientas de conservación, la diversidad oscura puede utilizarse para complementary desarrollar afondo lapriorización de la conservación y las decisiones administrativas por medio del entendimiento de la biodiversidad relativizada por su potencial (es decir, su acervo de especies). Más allá, a través del entendimiento detallado de la población, la comunidad y la diversidad oscura funcional, el potencial de restauración de los habitats degradados puede ser valorado a fondo de manera más rigurosa, así como la probabilidad de invasiones exitosas de especies. Sugerimos que la aplicación del concepto de diversidad oscura actualmente es una fuente de información poco valorada que es valiosa para las aplicaciones de la conservación, que van desde la priorización de la conservación a macroescala hasta la ecología de restauración con escalas más locales y el manejo de especies invasoras.