Co-production of a software tool for field-scale species distribution modelling (fs-SDM) and mapping using local biodiversity records

共同开发用于野外规模物种分布建模 (fs-SDM) 和使用当地生物多样性记录进行绘图的软件工具

• 批准号: NE/V007726/1
• 负责人: David Baker
• 金额: $ 25.61万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV007726%2F1
• 关键词: Co; production; software; tool; field

Summary: Research Translation Fellowship.Biodiversity underpins many of the key ecosystem services provided by multifunctional landscapes, including food and water security and human health and wellbeing. The integration of species protection within the landscape decisions process is a legal requirement under the Wildlife & Countryside Act 1981 and a key goal of Defra's 25-year Environment Plan. Legislation mandates mitigation of impacts to biodiversity in the planning process and will soon require a policy of net gain for biodiversity in all development projects. It is only possible to provide mitigation to reduce or remove impacts if ecologists have identified the species that will be negatively affected by a proposed development. However, the precise location of species occurrence at finer scales is not known for the majority of species across the majority of locations.Planning decisions are typically made at field-scales and risks to priority species are often identified at these scales through the screening of local species occurrence records against planning proposals. The absence of records at a site is typically assumed to indicate the absence of the species, but this is a critical error, mistaking the absence-of-evidence for the evidence-of-absence. Preliminary analyses showing that a large proportion of apparent absences at a 1-hectare resolution are false absences. The consequence of these false absences is the weakening of protections for biodiversity in the landscape decisions process and an increase in project costs when the need for mitigation is discovered relatively late in the planning process. For landscape decisions to protect biodiversity effectively, field-scale information on the distribution of species must be available, particularly for priority species requiring special legal protection. Biodiversity data is now streaming into online archives as technological advances have removed many of the barriers to reporting field observations. For example, the Environmental Records Centre for Cornwall and the Isles of Scilly (ERCCIS) holds more than 6.5 million species records. The vast majority of biological records are collected opportunistically, without a statistically rigorous sampling strategy. Trading-off quality for quantity, both in terms of geographic and taxonomic coverage, these records provide a potential information base to develop high-resolution maps of species distributions. Species distribution models (SDMs) can be used to infer the distribution of a species across a landscape from relatively sparse survey data. These models must however be developed with considerable care in order to produce unbiased estimates of species distributions from opportunistic records.Through this Research Translation Fellowship, I will lead the co-production of a user-friendly software tool to implement field-scale species distribution modelling (fs-SDM) and mapping based on local biodiversity records. I will work alongside staff at the ERCCIS, the region's premier accredited organisation for collating, managing, and disseminating biological information. This project will unleash the potential of this vast resource and provide the toolset for ERCCIS staff, and staff at other UK biological record centres, to add-value to these records prior to dissemination. The fs-SDM package will capture the practitioner's species-specific expert knowledge to build models, but automate the modelling process itself, including the acquisition and processing of spatial data, and the optimisation and evaluation of the models. Finally, the production of easily interpretable outputs is critical and this will be developed in close collaboration with relevant end-users to ensure there is clarity and confidence in the outputs. The software will be made freely available for download via online archives to increase the availability of field-scale modelling and mapping capacity to support landscape decisions.

生物多样性是多功能景观提供的许多关键生态系统服务的基础，包括食物和水安全以及人类健康和福祉。将物种保护纳入景观决策过程是1981年《野生动物和乡村法》的法律要求，也是Defra 25年环境计划的关键目标。立法规定在规划过程中减轻对生物多样性的影响，并将很快要求在所有发展项目中制定生物多样性净收益政策。只有当生态学家确定了将受到拟议开发项目负面影响的物种时，才有可能提供缓解措施以减少或消除影响。然而，对于大多数地区的大多数物种来说，在较细的尺度上物种出现的准确位置是未知的。规划决策通常是在实地尺度上做出的，并且经常通过对照规划建议筛选本地物种发生记录来确定优先物种所面临的风险。在一个地点没有记录通常被认为表明该物种的存在，但这是一个严重的错误，将缺乏证据误认为缺乏证据。初步分析表明，在1公顷的分辨率下，有很大比例的明显缺席是虚假缺席。这些虚假缺席的后果是在景观决策过程中削弱了对生物多样性的保护，并在规划过程中较晚发现需要缓解时，增加了项目成本。为了有效保护生物多样性的景观决策，必须提供关于物种分布的实地范围的信息，特别是需要特别法律保护的优先物种。随着技术进步消除了报告实地观测的许多障碍，生物多样性数据现在正源源不断地进入在线档案。例如，康沃尔和西利岛环境记录中心(ERCCIS)保存了超过650万种物种的记录。绝大多数生物记录都是机会主义地收集的，没有严格的统计抽样策略。质量与数量的权衡--在地理和分类学覆盖范围方面，这些记录为开发高分辨率的物种分布图提供了潜在的信息基础。物种分布模型(SDMS)可用于从相对稀疏的调查数据中推断物种在整个景观中的分布。然而，这些模型的开发必须相当谨慎，以便根据机会主义的记录产生对物种分布的公正估计。通过这次研究翻译奖学金，我将领导一个用户友好的软件工具的共同制作，以实施基于当地生物多样性记录的野外范围的物种分布建模(FS-SDM)和绘图。我将与ERCCIS的工作人员一起工作，ERCCIS是该地区整理、管理和传播生物信息的首要认可组织。该项目将释放这一巨大资源的潜力，并为ERCCIS工作人员和英国其他生物记录中心的工作人员提供工具包，以便在传播之前为这些记录增加价值。FS-SDM包将获取从业者特定物种的专家知识来建立模型，但会使建模过程本身自动化，包括空间数据的获取和处理，以及模型的优化和评估。最后，制作易于解释的产出至关重要，这将与相关最终用户密切合作制定，以确保产出的清晰度和信心。该软件将通过在线档案免费下载，以增加实地范围的建模和绘图能力，以支持景观决策。

项目成果

Correlations between spatial sampling biases and environmental niches affect species distribution models

• DOI: 10.1111/geb.13491
• 发表时间: 2022-03-23
• 期刊: GLOBAL ECOLOGY AND BIOGEOGRAPHY
• 影响因子: 6.4
• 作者: Baker, David J.;Maclean, Ilya M. D.;Gaston, Kevin J.
• 通讯作者: Gaston, Kevin J.

The effectiveness of UK protected areas in preventing local extinctions

• DOI: 10.1111/conl.12980
• 发表时间: 2023-10-03
• 期刊: CONSERVATION LETTERS
• 影响因子: 8.5
• 作者: Gardner, Alexandra S.;Baker, David J.;Maclean, Ilya M. D.
• 通讯作者: Maclean, Ilya M. D.

Global variation in unique and redundant mammal functional diversity across the daily cycle

• DOI: 10.1111/jbi.14564
• 发表时间: 2023-01
• 期刊: Journal of Biogeography
• 影响因子: 3.9
• 作者: D. Cox;David J. Baker;Alexandra S. Gardner;K. Gaston

Microclimates can be accurately predicted across ecologically important remote ecosystems

可以准确预测具有重要生态意义的偏远生态系统的微气候

• DOI: 10.1101/2021.01.14.426699
• 发表时间: 2021
• 作者: Baker D

Species distribution modelling is needed to support ecological impact assessments

• DOI: 10.1111/1365-2664.13782
• 发表时间: 2020-11-05
• 期刊: JOURNAL OF APPLIED ECOLOGY
• 影响因子: 5.7
• 作者: Baker, David J.;Maclean, Ilya M. D.;Gaston, Kevin J.
• 通讯作者: Gaston, Kevin J.