Time for Decarbonization of Conservation and Development Projects? The Political Ecology of Carbon Projects

The globe's first carbon projects were designed and implemented approximately 20 years ago following scientific insights that emissions of greenhouse gases needed to be mitigated. Visible in some of these early projects were the important aspects of social governance and local benefit sharing. The projects promised to be a panacea to environmental, social and economic problems in remote rural areas of developing countries. However, it took another decade before a wave of hundreds of carbon projects were launched. Many of the projects were offered under the mechanism of REDD+ (Reducing Emissions from Deforestation and forest Degradation, plus the role of conservation, sustainable forest management and carbon enhancement), as well as under a variety of voluntary schemes and national programs, public-private partnerships, and forestry-based investment initiatives. As decision-makers prepare the Conference of the Parties of the United Nations Framework Convention on Climatic Change in Paris (COP21), Earthscan has released a book entitled `Carbon conflicts and forest landscapes in Africa', edited by Melissa Leach and Ian Scoones. According to the editors, the focus of the book is on what happens on the ground when carbon forestry projects arrive, what types of projects work, and, equally important, what doesn’t work

Time for Decarbonization of Conservation and Development Projects? The Political Ecology of Carbon Projects

The globe's first carbon projects were designed and implemented approximately 20 years ago following scientific insights that emissions of greenhouse gases needed to be mitigated. Visible in some of these early projects were the important aspects of social governance and local benefit sharing. The projects promised to be a panacea to environmental, social and economic problems in remote rural areas of developing countries. However, it took another decade before a wave of hundreds of carbon projects were launched. Many of the projects were offered under the mechanism of REDD+ (Reducing Emissions from Deforestation and forest Degradation, plus the role of conservation, sustainable forest management and carbon enhancement), as well as under a variety of voluntary schemes and national programs, public-private partnerships, and forestry-based investment initiatives. As decision-makers prepare the Conference of the Parties of the United Nations Framework Convention on Climatic Change in Paris (COP21), Earthscan has released a book entitled `Carbon conflicts and forest landscapes in Africa', edited by Melissa Leach and Ian Scoones. According to the editors, the focus of the book is on what happens on the ground when carbon forestry projects arrive, what types of projects work, and, equally important, what doesn’t work

Current models broadly neglect specific needs of biodiversity conservation in protected areas under climate change

<p>Abstract</p> <p>Background</p> <p>Protected areas are the most common and important instrument for the conservation of biological diversity and are called for under the United Nations' <it>Convention on Biological Diversity</it>. Growing human population densities, intensified land-use, invasive species and increasing habitat fragmentation threaten ecosystems worldwide and protected areas are often the only refuge for endangered species. Climate change is posing an additional threat that may also impact ecosystems currently under protection. Therefore, it is of crucial importance to include the potential impact of climate change when designing future nature conservation strategies and implementing protected area management. This approach would go beyond reactive crisis management and, by necessity, would include anticipatory risk assessments. One avenue for doing so is being provided by simulation models that take advantage of the increase in computing capacity and performance that has occurred over the last two decades.</p> <p>Here we review the literature to determine the state-of-the-art in modeling terrestrial protected areas under climate change, with the aim of evaluating and detecting trends and gaps in the current approaches being employed, as well as to provide a useful overview and guidelines for future research.</p> <p>Results</p> <p>Most studies apply statistical, bioclimatic envelope models and focus primarily on plant species as compared to other taxa. Very few studies utilize a mechanistic, process-based approach and none examine biotic interactions like predation and competition. Important factors like land-use, habitat fragmentation, invasion and dispersal are rarely incorporated, restricting the informative value of the resulting predictions considerably.</p> <p>Conclusion</p> <p>The general impression that emerges is that biodiversity conservation in protected areas could benefit from the application of modern modeling approaches to a greater extent than is currently reflected in the scientific literature. It is particularly true that existing models have been underutilized in testing different management options under climate change. Based on these findings we suggest a strategic framework for more effectively incorporating the impact of climate change in models exploring the effectiveness of protected areas.</p

Does fragmentation contribute to the forest crisis in Germany?

Intact forests contribute to the ecosystem functionality of landscapes by storing and sequestering carbon, buffering and cooling the microclimate, and providing a range of related ecosystem functions. Forest fragmentation not only poses a threat to many organisms but also reduces the resistance and resilience of the ecosystem, which is especially relevant to the ongoing climate crisis. The effects of recent extreme heat years on forests in Germany have not been studied in detail for the influence of fragmentation. We investigate the relation of forest fragmentation with temperature and vitality in Germany per ecoregion at the canopy level using satellite imagery at 1-km and 30-m resolution. We compiled and correlated forest maps for connectivity based on Thiessen polygons, canopy temperatures on the hottest days based on land surface temperature, and forest vitality based on the maximum normalized difference vegetation index per growing season. We differentiated between ecoregions and main forest types. In 2022, larger intact tree-covered areas that are less fragmented have relatively low temperatures on hot days and higher overall vitality. Nearly 98% of the almost 1.95 million forest fragments at 30-m resolution in Germany are smaller than 1 km2, which cover nearly 30% of the total forest area. To counteract the forest crisis, forest and landscape management should aim to reduce fragmentation and maintain tree biomass and forest cover in the landscape. Increasing the size of continuous forest fragments contributes to ecosystem-based adaptation to climate change

Ecosystemic resilience of a temperate post-fire forest under extreme weather conditions

IntroductionThe effects of climate change are exacerbating the fire risk in forests worldwide. Conifer plantations in particular are especially vulnerable to fire outbreaks. At the end of the extraordinarily hot and dry summer of 2018, a forest pine plantation burned in Brandenburg, NE Germany. Different forestry interventions were carried out after the fire, while one area of the damaged plantation remained untouched.MethodsWe investigated the resilience of the forest ecosystem and the effectiveness of different active and passive forest restoration measures during the subsequent relatively warm and dry years 2019–2021.ResultsOne year after the fire, Populus tremula showed strong spontaneous colonization at all sites. In contrast, the majority of planted Pinus sylvestris plantlets died on the plots that had been salvage-logged after the fire. Three years after the fire, Populus tremula successfully established itself as the dominant tree species on all plots, with the highest abundance on the plot where the overstorey of the dead pines was left. Betula pendula, Salix caprea, and Pinus sylvestris showed lower abundance, with their proportion increasing with decreasing cover by dead trees. The distribution of regrowing trees is very heterogeneous across the different treatments and plots. In the clear-cut plots, the extreme microclimatic conditions expose the young trees to additional heat and drought, while the retention of deadwood measurably buffers the temperature and water stress.DiscussionThe resilience and adaptability of naturally regenerating forests that develop into ecosystems that are more diverse seem more promising than restoration through intervention. Apart from hampering restoration under extreme weather conditions, post-fire salvage logging contributes to soil degradation and loss of organic carbon

Infrastructure expansion challenges sustainable development in Papua New Guinea

The island of New Guinea hosts the third largest expanse of tropical rainforest on the planet. Papua New Guinea—comprising the eastern half of the island—plans to nearly double its national road network (from 8,700 to 15,000 km) over the next three years, to spur economic growth. We assessed these plans using fine-scale biophysical and environmental data. We identified numerous environmental and socioeconomic risks associated with these projects, including the dissection of 54 critical biodiversity habitats and diminished forest connectivity across large expanses of the island. Key habitats of globally endangered species including Goodfellow's tree-kangaroo (Dendrolagus goodfellowi), Matchie's tree kangaroo (D. matschiei), and several birds of paradise would also be bisected by roads and opened up to logging, hunting, and habitat conversion. Many planned roads would traverse rainforests and carbon-rich peatlands, contradicting Papua New Guinea's international commitments to promote low-carbon development and forest conservation for climate-change mitigation. Planned roads would also create new deforestation hotspots via rapid expansion of logging, mining, and oil-palm plantations. Our study suggests that several planned road segments in steep and high-rainfall terrain would be extremely expensive in terms of construction and maintenance costs. This would create unanticipated economic challenges and public debt. The net environmental, social, and economic risks of several planned projects—such as the Epo-Kikori link, Madang-Baiyer link, Wau-Malalaua link, and some other planned projects in the Western and East Sepik Provinces—could easily outstrip their overall benefits. Such projects should be reconsidered under broader environmental, economic, and social grounds, rather than short-term economic considerations

Tradition as asset or burden for transitions from forests as cropping systems to multifunctional forest landscapes: Sweden as a case study

Expectations of what forests and woodlands should provide vary among locations, stakeholder groups, and over time. Developing multifunctional forests requires understanding of the dynamic roles of traditions and cultural legacies in social-ecological systems at multiple levels and scales. Implementing policies about multifunctional forests requires a landscape and social-ecological perspective, and recognition of both spatial and temporal features at multiple scales. This study explores the dissemination of even-aged silviculture in central, eastern and northern Europe, and the consequences of choosing different vantage points in social-ecological systems for mapping of barriers, and to identify levers, towards multifunctional forest landscapes. Using a narrative approach, we first summarise the development of even-aged silviculture in four European regions. Next, we focus on Sweden as a keen adopter of even-aged silviculture, and identify levers at three groups of vantage points. They were (1) biosphere with biodiversity as short-hand for composition, structure and function of ecosystems, which support human well-being at multiple scales; (2) society in terms of different levels of stakeholder interactions from local to global, and (3) economy represented by value chain hierarchies and currencies. The emergence of even-aged silviculture >200 years ago formed an expanding frontier from central to northern Europe. Sustained yield wood production and biodiversity conservation encompass different portfolios of ecosystem aspects and spatio-temporal scales. Ignorance and lack of knowledge about these differences enforce their mutual rivalry. An exploratory review of six groups of stakeholders at multiple levels in the traditional industrial forest value chain highlights inequalities in terms of distribution of income and power across different levels of governance. This effectively marginalises other than powerful industrial actors. The distribution of financial results along the value chain is dynamic in space and time, and not all benefits of forest ecosystems can be measured using monetary valuation. There are also other currencies and incentives. A discussion of cultural trajectories in central and eastern European, Russian and Swedish forest management illustrates that forest history patterns repeat themselves. Longitudinal case studies of countries and regions can help foster holistic multi-dimensional and multilevel systems thinking. Application of deep levers of change is likely to require external drivers. A key challenge is to handle the manufacturing of doubt and decay of truth, i.e., the appearance of alternative facts, and the diminishing role of evidence and systems analyses in political and civic discourses. This transition is fuelled by new and rapidly evolving digital arenas

Roadless and Low-Traffic Areas as Conservation Targets in Europe

With increasing road encroachment, habitat fragmentation by transport infrastructures has been a serious threat for European biodiversity. Areas with no roads or little traffic (“roadless and low-traffic areas”) represent relatively undisturbed natural habitats and functioning ecosystems. They provide many benefits for biodiversity and human societies (e.g., landscape connectivity, barrier against pests and invasions, ecosystem services). Roadless and low-traffic areas, with a lower level of anthropogenic disturbances, are of special relevance in Europe because of their rarity and, in the context of climate change, because of their contribution to higher resilience and buffering capacity within landscape ecosystems. An analysis of European legal instruments illustrates that, although most laws aimed at protecting targets which are inherent to fragmentation, like connectivity, ecosystem processes or integrity, roadless areas are widely neglected as a legal target. A case study in Germany underlines this finding. Although the Natura 2000 network covers a significant proportion of the country (16%), Natura 2000 sites are highly fragmented and most low-traffic areas (75%) lie unprotected outside this network. This proportion is even higher for the old Federal States (western Germany), where only 20% of the low-traffic areas are protected. We propose that the few remaining roadless and low-traffic areas in Europe should be an important focus of conservation efforts; they should be urgently inventoried, included more explicitly in the law and accounted for in transport and urban planning. Considering them as complementary conservation targets would represent a concrete step towards the strengthening and adaptation of the Natura 2000 network to climate change

Co-limitation towards lower latitudes shapes global forest diversity gradients

Funding Information: The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159 ; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/ ; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108-00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/ S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)—‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change ’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007–2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109–00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10-2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2. Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Nature Limited.Peer reviewedPostprin

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers