Explore the vast range of titles available.

International agreements aim to conserve 17% of Earth's land area by 2020 but include no area‐based conservation targets within the working landscapes that support human needs through farming, ranching, and forestry. Through a review of country‐level legislation, we found that just 38% of countries have minimum area requirements for conserving native habitats within working landscapes. We argue for increasing native habitats to at least 20% of working landscape area where it is below this minimum. Such target has benefits for food security, nature's contributions to people, and the connectivity and effectiveness of protected area networks in biomes in which protected areas are underrepresented. We also argue for maintaining native habitat at higher levels where it currently exceeds the 20% minimum, and performed a literature review that shows that even more than 50% native habitat restoration is needed in particular landscapes. The post‐2020 Global Biodiversity Framework is an opportune moment to include a minimum habitat restoration target for working landscapes that contributes to, but does not compete with, initiatives for expanding protected areas, the UN Decade on Ecosystem Restoration (2021–2030) and the UN Sustainable Development Goals.

Despite the growing recognition of sustainability in forest management, comprehensive multi-criteria evaluations of silvicultural practices remain scarce, particularly in Patagonia. In this study, we applied a multi-criteria decision analysis to evaluate the sustainability of different strip-cutting intensities in secondary Nothofagus antarctica forests in Northern Patagonia, Argentina. The performance of four management alternatives was assessed: no cutting, low cutting intensity, medium cutting intensity, and high cutting intensity. These alternatives were evaluated across 11 indicators of nature’s contributions to people. Indicator values were estimated from previous research across three contrasting sites, complemented by expert surveys to estimate weights and target values for each indicator. The results indicate that the key indicators included those associated with firewood harvesting, fire and invasions prevention, and timber species plantation performance. Medium cutting intensity consistently emerged as the most sustainable option across all sites, models, and scenarios. In contrast, no cutting performed poorly across most sites, models, and scenarios. These findings underscore the importance of integrating diverse ecological and socioeconomic indicators into forest management planning. The promotion of medium cutting intensity has the potential to enhance sustainability in N. antarctica forests, thereby contributing to the development of resilient and multifunctional landscapes in Northern Patagonia.

Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones En Recursos Naturales, Agroecología y Desarrollo Rural. - Universidad Nacional de Rio Negro. Instituto de Investigaciones En Recursos Naturales, Agroecología y Desarrollo Rural; Argentina

Fil: Huaylla, Claudia Alejandra. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina

Networks are a convenient way to represent many interactions among different entities as they provide an efficient and clear methodology to evaluate and organize relevant data. While there are many features for characterizing networks there is a quantity that seems rather elusive: Complexity. The quantification of the complexity of networks is nowadays a fundamental problem. Here, we present a novel tool for identifying the complexity of ecological networks. We compare the behavior of two relevant indices of complexity: K-complexity and Single value decomposition (SVD) entropy. For that, we use real data and null models. Both null models consist of randomized networks built by swapping a controlled number of links of the original ones. We analyze 23 plant-pollinator and 19 host-parasite networks as case studies. Our results show interesting features in the behavior for the K-complexity and SVD entropy with clear differences between pollinator-plant and host-parasite networks, especially when the degree distribution is not preserved. Although SVD entropy has been widely used to characterize network complexity, our analyses show that K-complexity is a more reliable tool. Additionally, we show that degree distribution and density are important drivers of network complexity and should be accounted for in future studies.