In the face of the growing challenges brought about by human activities, effective planning and decision-making in biodiversity and ecosystem conservation, restoration, and sustainable development are urgently needed. Ecological models can play a key role in supporting this need and helping to safeguard the natural assets that underpin human wellbeing and support life on land and below water (United Nations Sustainable Development Goals; SDG 15 & 14). The urgency and complexity of safeguarding forest (SDG 15.2) and mountain ecosystems (SDG 15.4), for example, and halting decline in biodiversity (SDG 15.5) in the Anthropocene requires a re-envisioning of how ecological models can best support the comprehensive assessments of biodiversity and its change that are required for successful action. A key opportunity to advance ecological modeling for both predictive and explanatory purposes arises through a collaboration between ecologists and the Earth observation community, and a close integration of remote sensing and species distribution models. Remote sensing products have the capacity to provide continuous spatiotemporal information about key factors driving the distribution of organisms, therefore improving both the use and accuracy of these models for management and planning. Here we first survey the literature on remote sensing data products available to ecological modelers interested in improving predictions of species range dynamics under global change. We specifically explore the key biophysical processes underlying the distribution of species in the Anthropocene including climate variability, changes in land cover, and disturbances. We then discuss potential synergies between the ecological modeling and remote sensing communities, and highlight opportunities to close the data and conceptual gaps that currently impede a more effective application of remote sensing for the monitoring and modeling of ecological systems. Specific attention is given to how potential collaborations between the two communities could lead to new opportunities to report on progress towards global agendas - such as the Agenda 2030 for sustainable development of the United Nations or the Post-2020 Global Biodiversity Framework of the Convention for Biological Diversity, and help guide conservation and management strategies towards sustainability.

中文翻译：

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在物种分布模型中使用遥感监测人类世的生物多样性

面对人类活动带来的日益严峻的挑战，迫切需要在生物多样性和生态系统保护、恢复和可持续发展方面进行有效的规划和决策。生态模型可以在支持这一需求和帮助保护支撑人类福祉和支持陆地和水下生命的自然资产方面发挥关键作用（联合国可持续发展目标；可持续发展目标 15 和 14）。例如，保护森林（SDG 15.2）和山区生态系统（SDG 15.4）以及阻止人类世生物多样性下降（SDG 15.5）的紧迫性和复杂性需要重新设想生态模型如何最好地支持对成功行动所需的生物多样性及其变化。通过生态学家和地球观测界之间的合作，以及遥感和物种分布模型的紧密结合，为预测和解释目的推进生态建模的关键机会出现了。遥感产品能够提供有关推动生物体分布的关键因素的连续时空信息，从而提高这些管理和规划模型的使用和准确性。在这里，我们首先调查了生态建模者可用的遥感数据产品的文献，这些文献对改善全球变化下物种范围动态的预测感兴趣。我们专门探索了人类世物种分布背后的关键生物物理过程，包括气候变异、土地覆盖变化、和干扰。然后，我们讨论了生态建模和遥感社区之间的潜在协同作用，并强调了缩小目前阻碍遥感在生态系统监测和建模中更有效应用的数据和概念差距的机会。特别关注两个社区之间的潜在合作如何能够带来新的机会来报告全球议程的进展——例如联合国可持续发展的 2030 年议程或生物多样性公约的 2020 年后全球生物多样性框架多样性，并帮助指导可持续发展的保护和管理战略。并强调有机会弥补目前阻碍更有效地应用遥感监测和建模生态系统的数据和概念差距。特别关注两个社区之间的潜在合作如何能够带来新的机会来报告全球议程的进展——例如联合国可持续发展的 2030 年议程或生物多样性公约的 2020 年后全球生物多样性框架多样性，并帮助指导可持续发展的保护和管理战略。并强调有机会弥补目前阻碍更有效地应用遥感监测和建模生态系统的数据和概念差距。特别关注两个社区之间的潜在合作如何能够带来新的机会来报告全球议程的进展——例如联合国可持续发展的 2030 年议程或生物多样性公约的 2020 年后全球生物多样性框架多样性，并帮助指导可持续发展的保护和管理战略。