Statistical modeling of cumulative impacts of human activity on reindeer habitat. Identification of important habitat areas and scenario analysis for impact assessment and land planning.

Wild reindeer are threatened both nationally and internationally, and several populations have declined sharply or become extinct in recent decades. Several factors are responsible for these trends, but it is well documented that infrastructure development and disturbance by humans can cause habitat degradation and fragmentation and can have a major negative impact on reindeer populations. This led to a large amount of research aimed at understanding and quantifying anthropogenic disturbance on reindeer and supporting sustainable land planning. In the last decade, we have developed statistical methods and a software (ConScape) to quantify the functionality of reindeer habitats, to identify movement corridors, and to measure the degree to which these are affected by the piecemeal development and "cumulative impact" of different infrastructure and human activities. The models are based on more than 3 million GPS-positions from the largest wild reindeer management areas, and on ca. 350 environmental layers describing the landscape (topography, vegetation, roads, hydropower, trails, tourist volume, private cabins, tourist cabins, etc.), climate, and, in some areas, local knowledge. Based on these models, several maps have been produced to describe statistically how wild reindeer perceive resources and barriers on a local scale, and which areas and corridors are most functional in the entire landscape. The latter is particularly important, as reindeer perceive the landscape as a continuous network of functional areas that they can access through movement corridors. On the other side, reindeer also perceive the cumulative impact of different infrastructures and human activities and respond by avoiding or decreasing the use of some areas due to disturbance and/or barriers to movements. All maps, a description of methods, and the reference list to scientific and popular publications are available in the Web App: https://www.nina.no/Naturmangfold/Hjortedyr/reindeermapsnorway. In addition, we developed a simulation tool to guide sustainable land planning and impact assessment through scenario analyses. The tool has already been used to predict the expected effect of 80 mitigation measures, suggested by boards of local experts to minimize cumulative impacts on reindeer habitat functionality and movement corridors in several areas in Norway (see Appendix 1 and Web-App). The scenarios that can be tested to include a combination of the removal/closure/relocation of existing infrastructures, changes in their intensity of use, the construction of new infrastructure (e.g. cottage, road, hiking and skiing trial, bridge over water magazines), and climate change. The statistical approach, software, maps, web-app and scenario analyses were developed within the Norwegian Research Council projects led by NINA “RenewableReindeer” (https://www.nina.no/english/Fields-of-research/Projects/RenewableReindeer_new), «ProdChange» and “OneImpact”, and in the related project "Scenario analyse Øyulvsbu of formidling". Comparison between statistical and expert-based maps was funded by the project from the Norwegian Environment Agency «OneImpact og kvalitetsnorm for villrein». These projects were or are supported by several partners and funding sources including the Norwegian Environment Agency, the Directorate of Water and Energy, the Hydropower company Sira Kvina, the wild reindeer project in Setesdal, the Wild reindeer centre / wild reindeer council, Siri Bøthun nature management Norwegian University of Life Sciences NMBU, and several international collaboration partners (Universite Catholique Louvain, Julia Computing Inc, Sveriges landbruksuniversitet SLU, University of Guelp, Canada, University of Alberta, Canada, The Nature Conservancy, Universidad Politecnica de Madrid, University of Glasgow). Parallel to this analytical work, management measures have been undertaken in Norway to counter the degradation of wild reindeer areas. In 2020 the government adopted the “Quality Standards for wild reindeer in Norway” (Lovdata 2020), to meet both international obligations and national objectives for the conservation of viable populations within ecologically functioning habitats. Every fourth year, each of the 23 Norwegian sub-populations is classified into good (green), medium (yellow) or poor (red) quality, based on 3 sub-standards: 1) population conditions; 2) lichens; 3) human impact on habitats. Sub-standard 3 is therefore an important tool to ensure sustainable management of wild reindeer habitats. Sub-standard 3 aims to identify critical declines in habitat quality and connectivity in each wild reindeer area, so that the cause of the decline can be addressed, and the status of the area restored to acceptable levels (yellow) as soon as possible. In the longer term, the aim is that all national wild reindeer areas should be of good quality (green). The procedure thus needs to robustly identify areas where habitat loss and fragmentation increased above a critical threshold, and to provide information on the relative contribution of the responsible infrastructure and human activities. In the current Quality Standards, sub-standard 3 is implemented based on expert-based assessments of changes in available wild reindeer observations, that are assumed to reflect changes in human impact. The process involves the delineation of polygons representing reindeer seasonal ranges, corridors, and a set of focal areas where socio-ecological challenges related to human activities have been identified. The reduction in use of focal areas is assessed by the experts in the last decade compared to the previous four decades. The classification is then conducted by assessing the proportion of habitat lost within all focal areas, as compared to the habitat available within the seasonal range. In this report, we provide an overview of the statistical approach, and we compare the performance of what we for simplicity call the “statistical maps” to the “expert-based polygons” developed in sub-standard 3, using both visual and quantitative approaches. We discuss the lessons learned by comparing the two approaches, and how these can help achieving the sustainability goals for the management of wild reindeer areas. This was the main focus of the project "OneImpact and quality standard for wild reindeer" funded by the Norwegian Environment Agency. As a proof of concepts, we also perform a preliminary statistical classification of the state of the wild reindeer areas following Delnorm 3 (“Sub-standard 3”). Last, we show how statistical approaches and simulations can help identifying the most effective among 76 measures suggested to mitigate cumulative impacts from anthropogenic activities in Setesdal, Nordfjella and Snøhetta (Appendix 1).

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