Abstract
Forest biodiversity and ecosystem services are hitherto predominantly quantified in forest interiors, well away from edges. However, these edges also represent a substantial proportion of the global forest cover. Here we quantified plant biodiversity and ecosystem service indicators in 225 plots along forest edge-to-interior transects across Europe. We found strong trade-offs: phylogenetic diversity (evolutionary measure of biodiversity), proportion of forest specialists, decomposition and heatwave buffering increased towards the interior, whereas species richness, nectar production potential, stemwood biomass and tree regeneration decreased. These trade-offs were mainly driven by edge-to-interior structural differences. As fragmentation continues, recognizing the role of forest edges is crucial for integrating biodiversity and ecosystem service considerations into sustainable forest management and policy.
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Data availability
All data needed to reproduce the analyses and figures presented in this study are available on Figshare (https://doi.org/10.6084/m9.figshare.24559891.v3) and GitHub (https://github.com/to-vanneste/tradeoffs.git).
Code availability
All R code needed to reproduce the analyses and figures presented in this study is available on Figshare (https://doi.org/10.6084/m9.figshare.24559891.v3) and GitHub (https://github.com/to-vanneste/tradeoffs.git).
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Acknowledgements
Special thanks go to L. Willems and G. De Bruyn for performing the chemical analysis and to A. Ghrairi for the texture analysis. We also thank E. Ampoorter, H. Blondeel, F. Ceunen, K. Ceunen, R. De Beelde, E. De Lombaerde, K. Hansson, L. Hertzog, D. Landuyt, P. Lhoir, S. M. Krishna Moorthy, A. Peiffer, M. Perring, M. Tolosano, S. Van Den Berge, L. Van Nevel and M. Vedel-Sørensen for their assistance during the fieldwork. T.V., L.D., E.D.L., C.M., P.S., P.V. and P.D.F. received funding through the ERC Starting grant FORMICA (no. 757833, http://www.formica.ugent.be). S.G., K.D.P. and L.D. were supported by the Research Foundation Flanders (FWO) (nos. G0H1517N, ASP035-19 and 1221523N, respectively). The plot network and data collection were realized through the FWO Scientific research network FLEUR (http://www.fleur.ugent.be).
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T.V., L.D., P.D.F., P.V. and K.V. conceived and designed the study. E.D.L., C.M., S.G., K.D.P., P.S., K.B., J.B., K.C., S.A.O.C., M.D., C.G., B.J.G., P.-O.H., G.I., J.L., S.L., A.O., Q.P., J.P., F. Selvi, F. Spicher, H.V., F.Z. and P.V. collected the data. C.M., S.G., K.D.P. and P.S. processed the data, while T.V. and L.D. performed the data analyses under supervision of P.D.F. and K.V. T.V. and L.D. drafted the manuscript, and all authors contributed to later versions.
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Extended data
Extended Data Fig. 1 Study design and set-up.
Study design with broadleaved forests in nine regions spanning a ± 2300-km wide latitudinal gradient across the European sub-Mediterranean, temperate and boreonemoral forest biome. three forest stands were selected per region with contrasting management intensity: (1) ‘dense forests’ that where not thinned over the past 10–30 years, (2) ‘intermediate forests’ with frequent thinning and most recent thinning about 5–10 years ago, and (3) ‘open forests’ with regular thinning and most recent thinning less than 4 years before sampling. In each forest stand, a 100-m transect was established perpendicular to the south-facing forest edge. Five plots of 3 m × 3 m were installed along each transect, with their plot centres at an exponentially increasing distance from the focal forest edge (1.5, 4.5, 12.5, 35.5 and 99.5 m). All plots were at least 100 m away from any forest edge other than the focal forest edge. Figure adapted from Meeussen et al. (2021) with background map on the left from https://databasin.org/ and picture of the transect on the right from Google Earth (Map data ©Google 2020 Geobasis-DE/BKG ©2009, Google Imagery ©2020 TerraMetrics). Hemispherical pictures of the three different forest management types in the middle were taken during the fieldwork.
Extended Data Fig. 2 Schematic overview of the collected data and data analyses.
Selection of biodiversity and ecosystem service indices for which edge-to-interior patterns were investigated in deciduous forest stands across temperate Europe. Subsequently, the underlying effect of several environmental drivers acting across three biogeographical scales on these indicators was assessed to explain the observed edge-to-interior variation. Icons were extracted from The Noun Project (https://thenounproject.com).
Extended Data Fig. 3 Effect of design variables and environmental variables on an ecosystem multifunctionality index.
Effect of design variables, that is distance to the edge, latitude, forest density and elevation (A), and environmental drivers (B) on ecosystem multifunctionality quantified for each 3 m × 3 m plot in the forest-edge-to-interior transects (n = 225 biologically independent plots). To quantify ecosystem multifunctionality, we followed the desirability function approach, outlined in Slade et al.63. For each measured ecosystem function, we established a desirability function that describes how desirability changes in function of the measured value of the ecosystem function. For each ecological function yi, a desirability function assigns numbers between 0 and 1, with di = 0 representing a completely undesirable value of yi and di = 1 representing a completely desirable or ideal function value [3,63]. For each ecosystem function, we assumed a linear relationship with desirability, positive for all functions except summer offset, because a lower offset indicates more temperature buffering and is therefore more desirable during heatwave conditions. Each function was scaled relative to the minimum and maximum values in the dataset, that is for a positive relation, the lowest and highest observed value of the ecological function were given a desirability of 0 and 1, respectively. Next, we determined importance weights for each ecosystem function, and calculated an overall multifunctionality index as the weighted average of the desirability scores of all ecosystem functions. All functions were given an importance weight of 1, except for the five ecosystem function measures related to biodiversity (total richness, specialist richness, generalist richness, phylogenetic diversity, and functional diversity), whose weights were reduced to 0.2 to avoid overweighting of the biodiversity aspect in the final multifunctionality index. Circles represent mean standardized effect sizes with 80% (thick line) and 95% credible intervals (thin line) and distributions obtained from a Bayesian model.
Extended Data Fig. 4 Effect of edaphic properties and landscape-scale variables on biodiversity and ecosystem service indices.
Forest plots displaying the effect of soil texture (% sand), soil acidity (pH), litter quality (mass of the organic soil layer), habitat availability (forest cover in 500-m radius), drought (SPEI) and atmospheric pollution (N deposition) on the biodiversity and ecosystem service indices quantified for each 3 m × 3 m plot in the forest-edge-to-interior transects (n = 225 biologically independent plots). Circles represent mean standardized effect sizes with 80% (thick line) and 95 % credible intervals (thin line) and distributions obtained from a multivariate Bayesian model. Colours denote biodiversity indices (green), regulating (blue) and provisioning ecosystem services (orange).
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Supplementary Figs. 1–6, Tables 1–9 and Methods 1.
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Vanneste, T., Depauw, L., De Lombaerde, E. et al. Trade-offs in biodiversity and ecosystem services between edges and interiors in European forests. Nat Ecol Evol (2024). https://doi.org/10.1038/s41559-024-02335-6
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DOI: https://doi.org/10.1038/s41559-024-02335-6
