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RESEARCH PRODUCT

Datapackage for national high-resolution conservation prioritisation of boreal forests

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This data package concerns the following work: Ninni Mikkonen, Niko Leikola, Joona Lehtomäki, Panu Halme, Atte Moilanen, National high-resolution conservation prioritisation of boreal forests, Forest Ecology and Management, Volume 541, 2023, 121079 ISSN 0378-1127 https://doi.org/10.1016/j.foreco.2023.121079 The overall objective of the work was to develop spatial prioritizations that can assist the forest conservation programme METSO (The Finnish Government 2008; 2014) to make well-informed decisions about acquisition of forests for protection. The results are also aimed to be useful for other actors interested in forest conservation or biodiversity friendly forest management. We focused the prioritization on the most threatened forest types and areas that display some or many elements of natural forests: more than one and preferably more than two tree species, forest structure that present else than even age structure or a history of clear-cut harvesting, and the amount of dead wood that exceed the volume of dead tree material in managed forests. From the perspective of connectivity, these areas should be situated close (varying from metres to a few kilometres) to other valuable forest areas. These kinds of forest areas represent the most threatened forest types and forest species in Finland (Hyvärinen et al. 2019; Kontula and Raunio 2019). This data package includes 3 folders (see details of the data in the article): 1) Data folder a) DWP features: the 20 input data layers of the modelled biodiversity surrogate: dead wood potential. These are combinations of 4 tree species and 5 forest site type classes. Not that these are not normalized. (1) bir = birch, obl = other broad leaved tree, st = forest site type b) Other data layers: i) condition_layer.img where the magnitude of the penalty is defined ii) ProtectedOrNot.img layer is used in hierarchical analysis to define whether the area is permanently protected or not iii) WRSCR04_PA.img layer consists of permanently protected areas cut form weighted range size corrected richness output layer from analysis version 4 to execute the positive interaction between the forests and permanently protected areas. iv) similarity matrix 2) Input folder a) example setup files for analysis version 7 (hierarchical analysis where permanently protected areas are forced to highest priorities, including information on dead wood potential of the forest stands, penalties followed by the forest management, connectivity within the forests, observations of red-listed forest species, and connectivity to forest key habitats and permanently protected areas) i) .spp file for list of input features for the analysis ii) .dat file for the analysis settings iii) .bat file to run the analysis in command line iv) conditionlayer.txt to define the used condition file in the analysis v) groups file to define the use of the condition layer vi) interact file to define the interactions between feature layers in connectivity calculations 3) Output folder a) includes folder for each analysis version. Each folder includes i) rank file in .img format which is the actual spatial priority ranking result ii) wrscr file which describes the weighted range size corrected richness of all input features iii) curves file: the performance of each input feature within the cell removal iv) jpg picture of the result The package DOES NOT include sensitive data. For species observations, ask for Finnish Biodiversity Info Facility https://laji.fi/en. For forest key habitats (small forest patches protected by the Forest Act, that are classified as “habitats of special importance to safeguard the biodiversity of forests”) on state owned land and land owned by companies, ask the data providers and owners. See Moilanen et al. (2014) for more technical information on the input and output files. Overview of the data The resolution of the spatial data is 96 m x 96 m. The study area covered the forested land area in Finland, excluding the autonomous Åland Islands. The data on forest stands are from year 2015, the forest management year 2017, and protected area network early winter 2018. See details of the data extraction in the article, Appendix A. The main source of biodiversity information were the modelled dead wood potential (DWP) indices. The DWP is an estimation of the potential of a stand for hosting dead wood dependent species. The potential is increased when the stand can be expected to produce more dead wood and more varied dead wood in terms of size and tree species composition. The modelling is based on forest growth and increase of dead wood calculated with Motti forest simulator 3.3 (Salminen et al., 2005; Hynynen et al., 2014; Hynynen et al., 2015) for 168 combinations of seven tree species, six forest site types, and four vegetation zones. See detailed information on the dead wood potential modelling in doi:10.3390/f11090913 (Mikkonen et al. 2020, Modeling of Dead Wood Potential Based on Tree Stand Data) The DWP was calculated for each stand or pixel based on the forest data (Finnish Forest Centre 2015; Metsähallitus 2015; Metsähallitus Parks & Wildlife Finland and Centres for Economic Development Transport and the Environment 2015; Natural Resources Institute Finland 2015b; 2015a): tree species and tree stock quantities (mean diameter at breast height and volume), soil fertility (Cajander, 1926), and location. In the DWP modelling the size information was combined with stand volume and forest site type. Eventually, the data were compiled to 20 input layers. See detailed information on the pre-processing of the input-data in the Appendix B. Spatial conservation prioritizations were made with the Zonation software 4.0 (Moilanen et al. 2005; Moilanen et al. 2009; Moilanen et al. 2011). With multiple analysis versions, the greatest interest is on those areas that repeatedly receive high ranks – these areas are important from all perspectives included in analysis. The ecological model of conservation value included seven analysis versions that start from a local perspective and then evolve towards regional and national levels (following Lehtomäki et al. 2009). Each new analysis version included everything that had been included in the previous simpler versions. The versions are 1) local estimation of the conservation potential of the forests based on tree stock alone, 2) local estimation with additional information about forest management and drainage, 3) landscape level (not local but not regional either) estimation with internal forest connectivity, 4) landscape level estimation with additional information about observations of red-listed forest species, 5) landscape-level estimation with added short distance connectivity to key forest habitats, 6) regional estimation with added long distance connectivity to permanently protected areas, and 7) regional estimation of the most appropriate addition to the present conservation network. These results do not replace in-depth ecological inventory assessment. They can be used as one source of information in land use planning. Literature Finnish Forest Centre. 2015. [dataset] Field and forest stand database AARNI. Hyvärinen, E., Juslén, A., Kemppainen, E., Uddström, A. & Liukko, U.-M. (Eds.). 2019. The 2019 Red List of Finnish Species. Helsinki, Ministry of the Environment & Finnish Environment Institute. 704 p. Kontula, T. & Raunio, A. (Eds.). 2019. Threatened Habitat Types in Finland 2018. Red List of Habitats – Results and Basis for Assessment. Helsinki, Finnish Environment Institute and Ministry of the Environment. The Finnish Environment 2/2019. 254 p. http://urn.fi/URN:ISBN:978-952-11-5110-1 http://hdl.handle.net/10138/308426. Lehtomäki, J., Tomppo, E., Kuokkanen, P., Hanski, I. & Moilanen, A. 2009. Applying spatial conservation prioritization software and high-resolution GIS data to a national-scale study in forest conservation. Forest Ecology and Management 258(11): 2439-2449. Metsähallitus. 2015. [dataset] SutiGIS 2015. Forestry resource and planning system for Metsähallitus Forestry Ltd and Protected Area Biotope Information System; biotope, and tree stock data on state-owned conservation areas, for Metsähallitus Parks & Wildlife Finland. Metsähallitus Parks & Wildlife Finland & Centres for Economic Development Transport and the Environment. 2015. [dataset] SutiGIS 2015: Protected area biotope information system, biotope and tree stock data on private conservation areas. Mikkonen, N., Leikola, N., Lehtomäki, J., Halme, P. & Moilanen, A. 2023. National high-resolution conservation prioritisation of boreal forests. Forest Ecology and Management, Volume 541. https://doi.org/10.1016/j.foreco.2023.121079 Mikkonen, N., Leikola, N., Halme, P., Heinaro, E., Lahtinen, A. & Tanhuanpää, T. 2020. Modeling of Dead Wood Potential Based on Tree Stand Data. Forests 11(913): 21. Moilanen, A., Franco, A. M. A., Early, R. I., Fox, R., Wintle, B. & Thomas, C. D. 2005. Prioritizing multiple-use landscapes for conservation: methods for large multi-species planning problems. Proceedings of the Royal Society B-Biological Sciences 272(1575): 1885-1891. Moilanen, A., Kujala, H. & Leathwick, J. 2009. The Zonation framework and software for conservation prioritization. In: Moilanen, A., Wilson, K. A. & Possingham, H. P. (Eds.). Spatial conservation prioritization - Quantitative Methods & Computational tools. New York, Oxford University Press Inc. p. 196-210. Moilanen, A., Leathwick, J. R. & Quinn, J. M. 2011. Spatial prioritization of conservation management. Conservation Letters 4(5): 383-393. Moilanen, A., Pouzols, F. M., Meller, L., Veach, V., Arponen, A., Leppänen, J. & Kujala, H. 2014. Zonation - Spatial conservation planning methods and software. Version 4. User Manual. 4. Helsinki, C-BIG Conservation Biology, Informatics Group, Department of Biosciences, University of Helsinki, Finland. 290 p. Natural Resources Institute Finland. 2015a. [dataset] Segmented multi-source national forest inventory data of Finland: estimates of mean diameter at breast height for tree species based on National Forest Inventory 2013. Unpublished. Date of datacut 19.8.2015. Natural Resources Institute Finland. 2015b. [dataset] The Multi-Source National Forest Inventory of Finland (MS-NFI) 2013, CC BY 4.0. The Finnish Government. 2008. Decision-in-Principle of The Finnish Government on the Forest Biodiversity Programme for Southern Finland for years 2008-2016 (in Finnish). 13. The Finnish Government. 2014. Decision-in-Principle of the Finnish Government on extension of the Forest Biodiversity Programme for Southern Finland (METSO) for years 2014-2025. 18.