Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.

中文翻译：

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动物保护和恢复决策的空间显式模型

模型是理解和预测生态模式和过程的有用工具。在持续的气候和生物多样性变化下，它们可以极大地促进保护和恢复的决策，并有助于为不确定的未来设计适当的管理策略。在这里，我们回顾了空间显式模型在决策支持中的使用，并确定了当前模型在保护和恢复方面的关键差距。在 650 篇审查过的出版物中，有 217 篇有明确的管理应用，并被纳入我们的定量分析。总体而言，建模研究偏向于静态模型（79%）、物种和种群水平（80%）以及保护（而不是恢复）应用（71%）。相关利基模型是使用最广泛的模型类型。动态模型以及基因到个体水平和社区到生态系统水平的代表性不足，并且仅在 10% 的研究中使用了明确的成本优化方法。我们提出了一种新的模型类型，用于选择动物保护和恢复模型，根据组织级别、感兴趣的生物过程和所需的管理应用来表征模型类型。这种类型学将有助于更紧密地将模型与管理目标联系起来。此外，未来的努力需要克服与数据集成、模型集成和决策相关的重要挑战。我们总结了五个关键建议，表明更广泛地使用空间显式模型进行决策支持可以通过以下方式实现：1）开发一个具有多种更易于使用的方法的工具箱，2) 改进动态建模方法的校准和验证，以及 3) 制定应用这些模型的最佳实践指南。此外，通过 4) 结合多种建模方法来评估不确定性，以及 5) 将模型置于自适应管理的核心，可以实现更稳健的决策。这些努力必须伴随着建模和监测的长期资金，并改善研究与实践之间的沟通，以确保最佳的保护和恢复结果。