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

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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.