Wang, W., X. Wang, T. Swystun, et al. 2026. “Fighting Fire With Fires: The Fire-Fuel Feedback Effect in Canadian Forests.” Global Ecology and Biogeography 35, no. 1: e70182. https://doi.org/10.1111/geb.70182.
In the originally published article, author Wanli Wu's affiliation was given incorrectly. The correct affiliation is below. The online version of this article has been updated.
We apologise for this error.
Incorrect:
6Conservation Programs Branch, Vancouver, British Columbia, Canada
Correct:
6Conservation Programs Branch, Parks Canada, Vancouver, British Columbia, Canada
Fire disturbances are integral to fire-prone landscapes of southern Europe. While evidence of changing fire frequency has been documented, the dynamics of forest reburns—defined as previously burned areas that ignite again within intervals shorter than the historical range with which forests ecologically evolved—remain largely unexplored. Here, we aim to provide the first large-scale characterisation of reburns in southern Europe.
Europe.
1985–2023.
Using a novel remote sensing dataset on fire disturbances, we identified areas burning multiple times by aggregating the annual information on fire disturbances. We calculated the proportion of forest area affected by fire (burn fraction) and the proportion that reburned (reburn fraction) across space and time to characterise the spatiotemporal patterns of reburn occurrence.
We quantified the spatial extent and frequency of reburns, revealing that 30.1% of burned area in southern Europe experienced multiple fire events within the 1985–2023 period (4.24 Mha), with 84.5% of these reburns occurring within a 20-year interval, and thus approaching the lower limit of reproductive maturity for many tree species. Reburn hotspots emerged across the Mediterranean, where 19%–21.1% year−1 of all fires were reburns within 20 years, and in the temperate forests of western Europe, where reburns accounted for 40.8% year−1. We further show that, although the overall burned area decreased, reburns continued to account for a substantial share of annual burn activity since 2005, with even slight increases in eastern regions.
Our results highlight that reburns are integral to southern Europe's disturbance regimes, and we emphasise the critical role of long time series for understanding forest dynamics. Based on our results, we suggest that reburns may increasingly shape fire regimes in southern Europe under intensifying forest fire activity, which may undermine post-fire recovery and require special consideration from management.
Sayol, F., M. C. H. Neate-Clegg, C. Sheard, A. L. Pigot, and J. A. Tobias. 2026. “AVONICHE: A Global Dataset of Dietary and Foraging Niches for Birds.” Global Ecology and Biogeography 35, no. 1: e70197. https://doi.org/10.1111/geb.70197.
In the originally published article, the author Montague C. H. Neate-Clegg's name and affiliations were given incorrectly. The correct information is given below. The online version of the article has been corrected.
We apologise for this error.
Incorrect:
Ferran Sayol1,2, Monte Neate-Clegg3,4, Catherine Sheard3,5, Alex L. Pigot6, Joseph A. Tobias3,7
1BETA Technological Centre, University of Vic-Central University of Catalonia, Vic, Spain
2BiBio Research Group, Natural Sciences Museum of Granollers, Granollers, Spain
3Department of Zoology, University of Oxford, Oxford, UK
4Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA
5School of Biological Sciences, University of Aberdeen, Aberdeen, UK
6Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, UK
7Department of Life Sciences, Imperial College London, Ascot, UK
Correct:
Ferran Sayol1,2, Montague C. H. Neate-Clegg3,4,5, Catherine Sheard3,6, Alex L. Pigot7, Joseph A. Tobias3,8
1BETA Technological Centre, University of Vic-Central University of Catalonia, Vic, Spain
2BiBio Research Group, Natural Sciences Museum of Granollers, Granollers, Spain
3Department of Zoology, University of Oxford, Oxford, UK
4Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA
5Environmental Studies, University of California, Santa Cruz, California, USA
6School of Biological Sciences, University of Aberdeen, Aberdeen, UK
7Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, UK
8Department of Life Sciences, Imperial College London, Ascot, UK
Wetland restoration is expected to play an important role in helping Europe achieve its climate and biodiversity targets as stated in the European Green Deal. Restored wetlands sequester atmospheric carbon and provide habitat for a wide range of plant and animal species. To design effective, evidence-based restoration targets and guide future projects, it is critical to understand the impacts of wetland restoration on a diverse range of ecosystem functions. Existing knowledge, however, is scattered across empirical studies assessing restoration outcomes on a limited set of indicators, in specific settings and single locations. This fragmentation limits our ability to assess the effectiveness of wetland restoration across different indicators and contexts. To address this gap, we present a comprehensive dataset on the effects of wetland restoration across Europe. The dataset compiles 2534 entries representing changes in carbon stocks, greenhouse gases (GHG) fluxes, and biodiversity indicators across different wetland types, pre-restoration land use and restoration strategies. The database allows comparisons between restored and both degraded and pristine sites.
The database contains data on carbon stock, GHG fluxes and biodiversity indicators in restored and control wetlands, with standard error, sampling methodology, wetland type, location, climate, restored site area, water table depth, soil characteristics, pre-restoration land use, time since restoration started, and restoration strategy.
Europe.
Original data were published between 2000 and 2024. Restoration age ranges from a few months to 139 years.
Carbon stocks, GHG fluxes and biodiversity indicators in restored wetlands and two controls: degraded and pristine sites.
The dataset is available at https://doi.org/10.17026/LS/H5MFEH as a .xlsx file and as a .shp file, with a metadata file.
Species distribution models (SDMs) address the whereabouts of species and are central to ecology. Deep learning (DL) is poised to further elevate the already significant role of SDMs in ecology and conservation, but the potential and limitations of this transformation are still largely unassessed.
North America.
2009–2021.
Mammals, amphibians, reptiles, ants, and butterflies.
We evaluate DL SDMs for 2299 terrestrial vertebrate and invertebrate species at continental scale and 0.00833° resolution in a like-for-like comparison with latest implementation of conventional SDMs. We compare two DL methods (a multi-layer perceptron (MLP) on point covariates and a convolutional neural network (CNN) on geospatial patches) against non-DL SDMs (Maxent and Random Forest), emphasising fair comparison and induced pitfalls from information leakage, species imbalances, and location biases.
On average, DL models match, but do not surpass, the performance of non-DL methods. DL performance is moderately to substantially weaker for species with narrow geographic ranges, fewer data points, and those assessed as threatened and hence often of greatest conservation concern. Furthermore, information leakage across dataset splits substantially inflates performance metrics, especially of CNNs.
Our results indicate that biases known from conventional SDM settings are strongly amplified for DL models. Although recent advancements in DL draw promising new avenues for ecological process modelling, their benefits beyond improved numerical performance can only be met when pitfalls are accounted for. Realising the potential of DL in its entirety will thus require a closer collaboration between ecology and machine learning disciplines.
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