Abstract
Habitat fragmentation generally reduces biodiversity at the patch scale (α diversity)1. However, there is ongoing debate about whether such negative effects can be alleviated at the landscape scale (γ diversity) if among-patch diversity (β diversity) increases as a result of fragmentation2,3,4,5,6. This controversial view has not been rigorously tested. Here we use a dataset of 4,006 taxa across 37 studies from 6 continents to test the effects of fragmentation on biodiversity across scales by explicitly comparing continuous and fragmented landscapes. We find that fragmented landscapes consistently have both lower α diversity and lower γ diversity. Although fragmented landscapes did tend to have higher β diversity, this did not translate into higher γ diversity. Our findings refute claims that habitat fragmentation can increase biodiversity at landscape scales, and emphasize the need to restore habitat and increase connectivity to minimize biodiversity loss at ever-increasing scales.
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Data availability
The datasets used in this paper are available at GitHub (https://github.com/thiago-goncalves-souza/ms-biodiversity-loss-fragmented-landscapes) and Zenodo (https://zenodo.org/records/14885581)61.
Code availability
The code used in this paper is available at GitHub (https://github.com/thiago-goncalves-souza/ms-biodiversity-loss-fragmented-landscapes) and Zenodo (https://zenodo.org/records/14885581)61.
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Acknowledgements
L.F.S.M was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) by grant 307984/2022-2. M.H.V. was supported by grant 2022/01899-6 (São Paulo Research Foundation; FAPESP). J.M.C. was supported by the German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (DFG FZT 118-202548816) and an ERC Advanced Grant (MetaChange) funded by the European Union. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. We thank N. Gotelli and G. Graves for feedback on the project.
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T.G.-S., J.M.C., N.M.H. and N.J.S. conceived and designed the study. T.G.-S. performed the analyses with support from J.M.C., N.M.H., N.J.S., M.H.V. and F.L.P.M. T.G.-S., J.M.C., N.M.H. and N.J.S. wrote the first version of the paper. F.L.P.M., M.A.A., E.B., A.G.C., R.K.D., D.F., H.G., M.G.d.L., L.F.S.M., E.M.-N., A.A.N., A.N., M.P., B.X.P., L.R.-S., R.C.R., N.V.H.S., B.A.S., A.S.-W., M.T., M.U.-P., H.L.V. and S.V. collected data. J.M.C., T.G.-S. and M.H.V. curated and maintained the data. All authors contributed to the revisions of the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Study locations.
A global map displaying the locations of the 37 studies, as well as the taxonomic groups sampled in each. Made with Natural Earth. Free vector and raster map data from naturalearthdata.com.
Extended Data Fig. 2 Fragment size classes.
Number (and percentage) of fragments or continuous forests in each fragment size class, which included fragments smaller than 100, 500 and 1,000 ha, as well as forest larger than 1,000 ha. The values were calculated using all 121 studies from the LandFrag dataset51.
Extended Data Fig. 3 Habitat amounts in continuous and fragmented landscapes across all buffer sizes.
The buffer size ranged from a radius of 200 m to 2,000 m, in 200 m increments. Large circles represent the mean habitat amount in continuous (blue circles) and fragmented (red circles) landscapes across studies (n = 37). In all panels, each study is represented by a small grey circle, with lines connecting the landscape types, and error bars represent standard deviations.
Extended Data Fig. 4 Number of patches in continuous and fragmented landscapes across all buffer sizes.
The buffer size ranged from a radius of 200 m to 2,000 m, in 200 m increments. Large circles represent the mean habitat amount in continuous (blue circles) and fragmented (red circles) landscapes across studies (n = 37). In all panels, each study is represented by a small grey circle, with lines connecting the landscape types, and error bars represent standard deviations.
Extended Data Fig. 5 Variation in landscape variables related to fragmentation between continuous and fragmented landscapes across all studies.
Dots represent the average value (error bars ± 1 s.e.) of the landscape variable (buffer radius = 2,000 m) in a given habitat amount class (n = 37 studies).
Extended Data Fig. 6 Differences in α, β and γ diversity between fragmented and continuous landscapes using a meta-analytical approach.
This orchard plot shows the effect size (log-response ratio, LRR) of the overall difference between continuous and fragmented landscapes across studies (n = 37). The values of α, β and γ diversity were computed using (a) all possible plot pairs or (b) only the nearest plot pairs (controlling for distance decay effects) in both continuous and fragmented landscapes. We also calculated α, β and γ diversity using the observed species richness without controlling for commonness or sampling effort, and with individual-based rarefaction giving greater relative weight to rare species (rarefied species richness; q = 0) and individual-based rarefaction giving greater relative weight to abundant species (effective number of species given Simpson diversity; q = 2). Solid points represent the LRR comparing α, β and γ diversity between continuous and fragmented landscapes, and the error bars represent 95% confidence intervals. Positive effect sizes indicate that continuous landscapes have higher diversity than fragmented landscapes, while negative effect sizes would indicate that fragmented landscapes have higher diversity. Transparent points indicate effect sizes from individual sites, and their sizes are proportional to the precision (inverse of the square root of the variance) of the individual effect size estimates.
Extended Data Fig. 7 Individual contribution of landscape type and habitat amount to α, β and γ diversity.
As described in the main text, this analysis represents the scaled importance of predictor variables in GLMMs. The most important variable (that is, the one with the highest unbiased AICc weight value) in a given model receives a value of 1, and the relative contribution of the other variables is calculated based on this benchmark. We performed these analyses using all species, as well as using rarefaction analyses to give weight to rare (order q = 0) and abundant (order q = 2) species.
Extended Data Fig. 8 Illustration of the analytical pipeline used to standardize species diversity comparisons between continuous and fragmented landscapes.
a, The grey squares represent one large forest in a continuous landscape and four small fragments in a fragmented landscape. The small black squares represent a sample and illustrate how differences in size generally affect the number of samples when comparing landscape types. Furthermore, when comparing these landscape types, there are at least four analytical challenges (1–4) that affect our ability to estimate and compare α, β, and γ diversity. b, Analytical approach used to estimate diversity by (1) standardizing α diversity while accounting for differences in study design and sampling effort, (2) standardizing β and γ diversity by calculating pairwise sample diversity, (3) controlling for distance decay effects to accurately estimate α, β, and γ diversity, and (4) standardizing α, β, and γ diversity through consistent sampling effort adjustments across landscapes. Silhouettes from PhyloPic (http://phylopic.org/), as a courtesy of Andy Wilson, Birgit Lang, Lauren Sumner-Rooney, Mattia Menchetti, Dorota Paczesniak, Birgit Lang, Wouter Koch, Guillaume Dera, Graham Montgomery and Gareth Monger.
Extended Data Fig. 9 Method to calculate pairwise diversity for α, β and γ using a patch-landscape study design.
a, The average α diversity for each pair is calculated as the mean number of species in pair i and pair ii, while γ diversity is the pooled ‘total’ number of distinct species in a given pair (accounting for the overlap of shared species occurring in both pairs). This pair is selected using two approaches. b, All possible pairs in fragmented or continuous landscapes in each study. c, Only the nearest pairs to control for the effect of distance decay on β and γ diversity. The black squares represent a plot, numbered between 1 and 10. Therefore, a pair can consist of either two plots within the same forest or fragment, or two plots in different fragments.
Extended Data Fig. 10 Estimated mixed-effects meta-analysis coefficients using the ‘leave-one-out’ analysis to compare the effects of removing one study from South America versus other continents.
Error bars represent 95% confidence intervals, shaded areas represent standard deviations, and points indicate the average coefficient by continent groups (South America in purple vs. other continents in green). The vertical dashed lines represent the observed coefficient value for the main model (n = 37 studies). We estimated α, β and γ diversity using all species, as well as giving greater relative weight for rare (q = 0) or abundant (q = 2) species in two scenarios: all plot pairs and the nearest plot pairs.
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Gonçalves-Souza, T., Chase, J.M., Haddad, N.M. et al. Species turnover does not rescue biodiversity in fragmented landscapes. Nature 640, 702–706 (2025). https://doi.org/10.1038/s41586-025-08688-7
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DOI: https://doi.org/10.1038/s41586-025-08688-7
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