Domestic attempts to advance the Sustainable Development Goals (SDGs) in a country can have synergistic and/or trade-off effects on the advancement of SDGs in other countries. Transboundary SDG interactions can be delivered through various transmission channels (e.g., trade, river flow, ocean currents, and air flow). This study quantified the transboundary interactions through these channels between 768 pairs of SDG indicators. The results showed that although high income countries only comprised 14.18% of the global population, they contributed considerably to total SDG interactions worldwide (60.60%). Transboundary synergistic effects via international trade were 14.94% more pronounced with trade partners outside their immediate geographic vicinity than with neighbouring ones. Conversely, nature-caused flows (including river flow, ocean currents, and air flow) resulted in 39.29% stronger transboundary synergistic effects among neighboring countries compared to non-neighboring ones. To facilitate the achievement of SDGs worldwide, it is essential to enhance collaboration among countries and leverage transboundary synergies.
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Abstract Free, publicly-accessible full text available December 1, 2025 -
A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of complex adaptive systems—CAS science—has a significant potential to handle such challenges. We address the advantages of CAS science for sustainability by identifying the key elements and challenges in sustainability science, the generic features of CAS, and the key advances and challenges in modeling CAS. Artificial intelligence and data science combined with agent-based modeling promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.more » « lessFree, publicly-accessible full text available November 1, 2025
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Abstract Understanding species distributions is a global priority for mitigating environmental pressures from human activities. Ample studies have identified key environmental (climate and habitat) predictors and the spatial scales at which they influence species distributions. However, regarding human influence, such understandings are largely lacking. Here, to advance knowledge concerning human influence on species distributions, we systematically reviewed species distribution modelling (SDM) articles and assessed current modelling efforts. We searched 12,854 articles and found only 1,429 articles using human predictors within SDMs. Collectively, these studies of >58,000 species used 2,307 unique human predictors, suggesting that in contrast to environmental predictors, there is no ‘rule of thumb’ for human predictor selection in SDMs. The number of human predictors used across studies also varied (usually one to four per study). Moreover, nearly half the articles projecting to future climates held human predictors constant over time, risking false optimism about the effects of human activities compared with climate change. Advances in using human predictors in SDMs are paramount for accurately informing and advancing policy, conservation, management and ecology. We show considerable gaps in including human predictors to understand current and future species distributions in the Anthropocene, opening opportunities for new inquiries. We pose 15 questions to advance ecological theory, methods and real-world applications.
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Abstract Protected areas are a key component of global conservation, and the world is aiming to increase protected areas to cover 30% of land and water through the 30 × 30 Initiative under the Post-2020 Global Biodiversity Framework. However, factors affecting their success or failure in regard to promoting mammal population recovery are not well studied, particularly using quantitative approaches comparing across diverse taxa, biomes, and countries. To better understand how protected areas contribute to mammalian recovery, we conducted an analysis of 2706 mammal populations both inside and outside of protected areas worldwide. We calculated the annual percent change of mammal populations within and outside of terrestrial protected areas and examined the relationship between the percent change and a suite of human and natural characteristics including biome, region, International Union for Conservation of Nature (IUCN) protected area category, IUCN Red List classification, and taxonomic order. Our results show that overall mammal populations inside and outside of protected areas are relatively stable. It appears that Threatened mammals are doing better inside of protected areas than outside, whereas the opposite is true for species of least concern and Near Threatened species. We also found significant population increases in protected areas classified as category III and significant population decreases in protected and unprotected areas throughout Oceania. Our results demonstrate that terrestrial protected areas can be an important approach for mammalian recovery and conservation.
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Free, publicly-accessible full text available April 1, 2025
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Concurrently implemented green initiatives to combat global environmental crises may be curtailed or even sacrificed given the ongoing global economic contraction. We collected empirical data and information about green initiatives from 15 sites or countries worldwide. We systematically explored how specific policy, intended behaviors, and gains of given green initiative may interact with those of other green initiatives concurrently implemented in the same geographic area or involving the same recipients. Surprisingly, we found that spillover effects were very divergent: one initiative could reduce the gain of another by 22 % ~ 100 %, representing alarming losses, while in other instances, substantial co-benefits could arise as one initiative can increase the gain of another by 9 % ~ 310 %. Leveraging these effects will help countries keep green initiatives with significant co-benefits but stop initiatives with substantial spillover losses in the face of widespread budget cuts, better meeting the United Nations’ sustainable development goals.more » « lessFree, publicly-accessible full text available March 1, 2025
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A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of Agent-based Complex Systems—ACS science—has a significant potential to handle such challenges. The advantages of ACS science for sustainability are addressed by way of identifying the key elements and challenges in sustainability science, the generic features of ACS, and the key advances and challenges in modeling ACS. Artificial intelligence and data science promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.
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Abstract Private lands are important for conservation worldwide, but knowledge about their effectiveness is still insufficient. To help fill this important knowledge gap, we analyzed the impacts of a national policy for conservation on private lands in Brazil, a global biodiversity hotspot with high potential for nature-based climate solutions. Through the evaluation of over 4 million private rural properties from the Rural Environmental Cadastre, we found that the last policy review in 2012 mainly affected the Amazon Forest. The amnesty granted to 80% of landowners of small properties prevented the restoration of 14.6 million hectares of agricultural land with a carbon sequestration potential of 2.4 gigatonnes. We found that private lands exist within the limits of public conservation areas and that between 2003 and 2020 deforestation rates in these private lands were higher than those across all conservation areas. The Rural Environmental Cadastre can be an effective tool for managing forests within private lands, with potential to integrate governance approaches to control deforestation and mitigate climate change.more » « less