Global Forest Resources Assessment 2020 (FAO, 2020).
Taubert, F. et al. Global patterns of tropical forest fragmentation. Nature 554, 519–522 (2018).
Google Scholar
Vancutsem, C. et al. Long-term (1990–2019) monitoring of forest cover changes in the humid tropics. Sci. Adv. 7, eabe1603 (2021).
Google Scholar
Foley, J. A. et al. Amazonia revealed: Forest degradation and loss of ecosystem goods and services in the Amazon Basin. Front. Ecol. Environ. 5, 25–32 (2007).
Barlow, J. et al. The future of hyperdiverse tropical ecosystems. Nature 559, 517–526 (2018).
Google Scholar
Brandon, K. Ecosystem services from tropical forests: Review of current science. SSRN J. https://doi.org/10.2139/ssrn.2622749 (2014).
Google Scholar
Indarto, J. & Mutaqin, D. J. An overview of theoretical and empirical studies on deforestation. MPRA. Paper No. 70178 (2016).
Geist, H. J. & Lambin, E. F. Proximate causes and underlying driving forces of tropical deforestation: Tropical forests are disappearing as the result of many pressures, both local and regional, acting in various combinations in different geographical locations. Bioscience 52, 143–150 (2002).
Angelsen, A. & Kaimowitz, D. Rethinking the causes of deforestation: Lessons from economic models. World Bank Res. Obs. 14, 73–98 (1999).
Google Scholar
Contreras-Hermosilla, A. The Underlying Causes of Forest Decline (Center for International Forestry Research, 2000).
Turner, B. L. et al. Two types of global environmental change: Definitional and spatial-scale issues in their human dimensions. Glob. Environ. Change 1, 14–22 (1990).
Meyer, W. B. & Turner, B. L. Human population growth and global land-use/cover change. Ann. Rev. Ecol. Syst. 2, 39–61 (1992).
Miyamoto, M., Mohd Parid, M., Noor Aini, Z. & Michinaka, T. Proximate and underlying causes of forest cover change in Peninsular Malaysia. For. Policy Econ. 44, 18–25 (2014).
Lim, C. L., Prescott, G. W., De Alban, J. D. T., Ziegler, A. D. & Webb, E. L. Untangling the proximate causes and underlying drivers of deforestation and forest degradation in Myanmar. Conserv. Biol. 31, 1362–1372 (2017).
Carodenuto, S. et al. A methodological framework for assessing agents, proximate drivers and underlying causes of deforestation: Field test results from southern cameroon. Forests 6, 203–224 (2015).
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).
Google Scholar
Hosonuma, N. et al. An assessment of deforestation and forest degradation drivers in developing countries. Environ. Res. Lett. 7, 044009 (2012).
Google Scholar
Köthke, M., Leischner, B. & Elsasser, P. Uniform global deforestation patterns—An empirical analysis. For. Policy Econ. 28, 23–37 (2013).
Busch, J. & Ferretti-Gallon, K. What drives deforestation and what stops it? A meta-analysis. Rev. Environ. Econ. Policy 11, 3–23 (2017).
Ferrer Velasco, R. F., Köthke, M., Lippe, M. & Günter, S. Scale and context dependency of deforestation drivers: Insights from spatial econometrics in the tropics. PLoS One 15, e0226830 (2020).
Google Scholar
Lambin, E. F. et al. Effectiveness and synergies of policy instruments for land use governance in tropical regions. Glob. Environ. Change 28, 129–140 (2014).
Börner, J., Schulz, D., Wunder, S. & Pfaff, A. The effectiveness of forest conservation policies and programs. Ann. Rev. Resour. Econ. 12, 45–64 (2020).
Bemelmans-Videc, M.-L., Rist, R. C. & Vedung, E. Carrots, Sticks & Sermons: Policy Instruments and their Evaluation (Transaction Publishers, 1998).
Seymour, F. & Harris, N. L. Reducing tropical deforestation. Science 365, 756–757 (2019).
Google Scholar
Lambin, E. F. et al. The role of supply-chain initiatives in reducing deforestation. Nat. Clim. Change 8, 109–116 (2018).
Google Scholar
Wolff, S. & Schweinle, J. Effectiveness and economic viability of forest certification: A systematic review. Forests 13, 798 (2022).
Müller, R., Pistorius, T., Rohde, S., Gerold, G. & Pacheco, P. Policy options to reduce deforestation based on a systematic analysis of drivers and agents in lowland Bolivia. Land Use Policy 30, 895–907 (2013).
Tegegne, Y. T., Lindner, M., Fobissie, K. & Kanninen, M. Evolution of drivers of deforestation and forest degradation in the Congo Basin forests: Exploring possible policy options to address forest loss. Land Use Policy 51, 312–324 (2016).
Hoffmann, C., García Márquez, J. R. & Krueger, T. A local perspective on drivers and measures to slow deforestation in the Andean-Amazonian foothills of Colombia. Land Use Policy 77, 379–391 (2018).
Henders, S., Ostwald, M., Verendel, V. & Ibisch, P. Do national strategies under the UN biodiversity and climate conventions address agricultural commodity consumption as deforestation driver?. Land Use Policy 70, 580–590 (2018).
Salvini, G. et al. How countries link REDD+ interventions to drivers in their readiness plans: implications for monitoring systems. Environ. Res. Lett. 9, 074004 (2014).
Google Scholar
Bos, A. B. et al. Integrated assessment of deforestation drivers and their alignment with subnational climate change mitigation efforts. Environ. Sci. Policy 114, 352–365 (2020).
Google Scholar
Fritz, S. et al. A continental assessment of the drivers of tropical deforestation with a focus on protected areas. Front. Conserv. Sci. https://doi.org/10.3389/fcosc.2022.830248 (2022).
Google Scholar
Lawrence, D. & Vandecar, K. Effects of tropical deforestation on climate and agriculture. Nat. Clim. Change 5, 27–36 (2015).
Google Scholar
Fedele, G., Locatelli, B., Djoudi, H. & Colloff, M. J. Reducing risks by transforming landscapes: Cross-scale effects of land-use changes on ecosystem services. PLoS One 13, e0195895 (2018).
Yackulic, C. B. et al. Biophysical and socioeconomic factors associated with forest transitions at multiple spatial and temporal scales. Ecol. Soc. https://doi.org/10.5751/ES-04275-160315 (2011).
Google Scholar
Loran, C., Ginzler, C. & Bürgi, M. Evaluating forest transition based on a multi-scale approach: Forest area dynamics in Switzerland 1850–2000. Reg. Environ. Change 16, 1807–1818 (2016).
Moonen, P. C. et al. Actor-based identification of deforestation drivers paves the road to effective REDD+in DR Congo. Land Use Policy 58, 123–132 (2016).
Strassburg, B. The tragedy of the tropics: A dynamic, cross-scale analysis of deforestation incentives. Working Paper—Centre for Social and Economic Research on the Global Environment No. 07-02 (2007).
López-Carr, D. et al. Space versus place in complex human–natural systems: Spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala. Ecol. Model. 229, 64–75 (2012).
Hoang, N. T. & Kanemoto, K. Mapping the deforestation footprint of nations reveals growing threat to tropical forests. Nat. Ecol. Evol. 5, 845–853 (2021).
Pendrill, F. et al. Agricultural and forestry trade drives large share of tropical deforestation emissions. Glob. Environ. Change 56, 1–10 (2019).
Ferrer Velasco, R. et al. Towards accurate mapping of forest in tropical landscapes: A comparison of datasets on how forest transition matters. Remote Sens. Environ. 274, 112997 (2022).
Google Scholar
Jayathilake, H. M., Prescott, G. W., Carrasco, L. R., Rao, M. & Symes, W. S. Drivers of deforestation and degradation for 28 tropical conservation landscapes. Ambio 50, 215–228 (2021).
Minang, P. A. et al. REDD+Readiness progress across countries: Time for reconsideration. Clim. Policy 14, 685–708 (2014).
Current pledges | Bonn challenge. https://www.bonnchallenge.org/pledges. Accessed: 15th August 2022.
Nansikombi, H. et al. Can de facto governance influence deforestation drivers in the Zambian Miombo?. For. Policy Econ. 120, 102309 (2020).
Sullivan, A., York, A., White, D., Hall, S. & Yabiku, S. D. Jure versus de facto institutions: Trust, information, and collective efforts to manage the invasive mile-a-minute weed (Mikania micrantha). Int. J. Commons 11, 171–199 (2017).
Busch, J. & Amarjargal, O. Authority of second-tier governments to reduce deforestation in 30 tropical countries. Front. For. Glob. Change https://doi.org/10.3389/ffgc.2020.00001 (2020).
Google Scholar
Sandström, C., Eckerberg, K. & Raitio, K. Studying conflicts, proposing solutions—Towards multi-level approaches to the analyses of forest conflicts. For. Policy Econ. 33, 123–127 (2013).
Hoogstra-Klein, M. A., Permadi, D. B. & Yasmi, Y. The value of cultural theory for participatory processes in natural resource management. For. Policy Econ. 20, 99–106 (2012).
de Jong, W., Ruiz, S. & Becker, M. Conflicts and communal forest management in northern Bolivia. For. Policy Econ. 8, 447–457 (2006).
Eckerberg, K. & Sandström, C. Forest conflicts: A growing research field. For. Policy Econ. 33, 3–7 (2013).
Sierra, R., Calva, O. & Guevara, A. La Deforestación en el Ecuador, 1990–2018. Factores promotores y tendencias recientes, 216 (2021).
Wasserstrom, R. & Southgate, D. Deforestation, agrarian reform and oil development in Ecuador, 1964–1994. Nat. Resour. 04, 31 (2013).
Wiebe, P. C., Zhunusova, E., Lippe, M., Ferrer Velasco, R. & Günter, S. What is the contribution of forest-related income to rural livelihood strategies in the Philippines’ remaining forested landscapes?. For. Policy Econ. 135, 102658 (2022).
Le, H. D., Smith, C. & Herbohn, J. What drives the success of reforestation projects in tropical developing countries? The case of the Philippines. Glob. Environ. Change 24, 334–348 (2014).
Carandang, A. P. et al. Analysis of key drivers of deforestation and forest degradation in the Philippines. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) (2013).
Phiri, D., Morgenroth, J. & Xu, C. Four decades of land cover and forest connectivity study in Zambia—An object-based image analysis approach. Int. J. Appl. Earth Obs. Geoinf. 79, 97–109 (2019).
Google Scholar
Nansikombi, H., Fischer, R., Kabwe, G. & Günter, S. Exploring patterns of forest governance quality: Insights from forest frontier communities in Zambia’s Miombo ecoregion. Land Use Policy 99, 104866 (2020).
Zhang, H., Wang, P. & Wood, J. Does institutional quality matter for the nexus between environmental quality and economic growth?: A tropics perspective. In Business, Industry, and Trade in the Tropics (eds Wood, J. et al.) (Routledge, 2022).
Reed, J., Van Vianen, J., Deakin, E. L., Barlow, J. & Sunderland, T. Integrated landscape approaches to managing social and environmental issues in the tropics: Learning from the past to guide the future. Glob. Change Biol. 22, 2540–2554 (2016).
Google Scholar
Fischer, R. et al. Interplay of governance elements and their effects on deforestation in tropical landscapes: Quantitative insights from Ecuador. World Dev. 148, 105665 (2021).
Torres, B., Vasco, C., Günter, S. & Knoke, T. Determinants of agricultural diversification in a hotspot area: Evidence from colonist and indigenous communities in the Sumaco biosphere reserve Ecuadorian Amazon. Sustainability 10, 1432 (2018).
Ojeda Luna, T., Zhunusova, E., Günter, S. & Dieter, M. Measuring forest and agricultural income in the Ecuadorian lowland rainforest frontiers: Do deforestation and conservation strategies matter?. For. Policy Econ. 111, 102034 (2020).
Kazungu, M. et al. Effects of household-level attributes and agricultural land-use on deforestation patterns along a forest transition gradient in the Miombo landscapes Zambia. Ecol. Econ. 186, 107070 (2021).
Kleemann, J. et al. Deforestation in continental ecuador with a focus on protected areas. Land 11, 268 (2022).
Mulenga, M. M. & Roos, A. Assessing the awareness and adoptability of pellet cookstoves for low-income households in Lusaka, Zambia. J. Energy South. Afr. 32, 52–61 (2021).
Eguiguren, P., Ojeda Luna, T., Torres, B., Lippe, M. & Günter, S. Ecosystem service multifunctionality: Decline and recovery pathways in the amazon and chocó lowland rainforests. Sustainability 12, 7786 (2020).
Google Scholar
Vasco, C., Torres, B., Pacheco, P. & Griess, V. The socioeconomic determinants of legal and illegal smallholder logging: Evidence from the Ecuadorian Amazon. For. Policy Econ. 78, 133–140 (2017).
van der Ploeg, J., van Weerd, M., Masipiqueña, A. B. & Persoon, G. A. Illegal logging in the Northern Sierra Madre Natural Park, the Philippines. Conserv. Soc. 9, 202–215 (2011).
Liu, D. S., Iverson, L. R. & Brown, S. Rates and patterns of deforestation in the Philippines: Application of geographic information system analysis. For. Ecol. Manag. 57, 1–16 (1993).
Boquet, Y. Environmental challenges in the Philippines. In The Philippine Archipelago (ed. Boquet, Y.) 779–829 (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-51926-5_22.
Google Scholar
MAGAP. ATPA: Reconversión Agro productiva Sostenible en la Amazonía Ecuatoriana (2014).
Jones, K. W. et al. Forest conservation incentives and deforestation in the Ecuadorian Amazon. Environ. Conserv. 44, 56–65 (2017).
Lindsey, P. A. et al. Underperformance of African protected area networks and the case for new conservation models: Insights from Zambia. PLoS One 9, e94109 (2014).
Google Scholar
Fischer, R. et al. Effectiveness of policy instrument mixes for forest conservation in the tropics – a stakeholder perspective from Ecuador, the Philippines and Zambia. Land Use Policy https://doi.org/10.1016/j.landusepol.2023.106546 (2022).
Google Scholar
Gurney, G. G. et al. Biodiversity needs every tool in the box: Use OECMs. Nature 595, 646–649 (2021).
Google Scholar
Maxwell, S. L. et al. Area-based conservation in the twenty-first century. Nature 586, 217–227 (2020).
Google Scholar
Priebe, J. et al. Transformative change in context—Stakeholders’ understandings of leverage at the forest–climate nexus. Sustain. Sci. 17, 1921–1938 (2022).
Höhl, M. et al. Forest landscape restoration—What generates failure and success?. Forests 11, 938 (2020).
Köthke, M., Ahimbisibwe, V. & Lippe, M. The evidence base on the environmental, economic and social outcomes of agroforestry is patchy—An evidence review map. Front. Environ. Sci. https://doi.org/10.3389/fenvs.2022.925477 (2022).
Google Scholar
Fischer, R., Giessen, L. & Günter, S. Governance effects on deforestation in the tropics: A review of the evidence. Environ. Sci. Policy 105, 84–101 (2020).
Bare, M., Kauffman, C. & Miller, D. C. Assessing the impact of international conservation aid on deforestation in sub-Saharan Africa. Environ. Res. Lett. 10, 125010 (2015).
Google Scholar
Vuohelainen, A. J., Coad, L., Marthews, T. R., Malhi, Y. & Killeen, T. J. The effectiveness of contrasting protected areas in preventing deforestation in Madre de Dios. Peru. Environ. Manag. 50, 645–663 (2012).
Google Scholar
Hull, V. & Liu, J. Telecoupling: A new frontier for global sustainability. Ecol. Soc. 23, 41 (2018).
Aitchison, J. The statistical analysis of compositional data. J. Roy. Stat. Soc. 44, 139–160 (1982).
Google Scholar
Norman, G. Likert scales, levels of measurement and the “laws” of statistics. Adv. Health Sci. Educ. 15, 625–632 (2010).
Day, M., Gumbo, D., Moombe, K. B., Wijaya, A. & Sunderland, T. Zambia Country Profile: Monitoring, Reporting and Verification for REDD+ Vol. 113 (CIFOR, 2014).
Piotrowski, M. Nearing the tipping point. Drivers of Deforestation in the Amazon Region (2019).
Sarker, P. K., Fischer, R., Tamayo, F., Navarrete, B. T. & Günter, S. Analyzing forest policy mixes based on the coherence of policies and the consistency of legislative policy instruments: A case study from Ecuador. For. Policy Econ. 144, 102838 (2022).
Likert, R. A technique for the measurement of attitudes. Arch. Psychol. 22(140), 55–55 (1932).
Altinsoy, M. et al. Ambulatory ECG monitoring for syncope and collapse in United States, Europe, and Japan: The patients’ viewpoint. J. Arrhythm. 37, 1023–1030 (2021).
R Core Team. R: A language and environment for statistical computing. https://www.R-project.org/. (R Foundation for Statistical Computing, Vienna, Austria, 2022).
Kassambara, A. rstatix: Pipe-friendly framework for basic statistical tests. R package version 0.7.0 (2021).
Kassambara, A. & Mundt, F. factoextra: Extract and visualize the results of multivariate data analyses. R package version 1.0.7 (2020).
Komsta, L. & Novometsky, F. moments: Moments, cumulants, skewness, kurtosis and related tests. R package version 0.14.1 (2022).
Zhang, Y., Zhou, M. & Shao, Y. mvnormalTest: Powerful tests for multivariate normality. R package version 1.0.0 (2020).
Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plots. R package version 0.4.0 (2020).
Wickham, H. et al. Welcome to the Tidyverse. JOSS 4, 1686 (2019).
Google Scholar
Bache, S. M. & Wickham, H. magrittr: A Forward-Pipe Operator for R. R package version 2.0.3 (2022).
Ushey, K., Allaire, J., Wickham, H. & Ritchie, G. rstudioapi: Safely Access the RStudio API. R package version 0.13 (2020).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer International Publishing, 2016). https://doi.org/10.1007/978-3-319-24277-4.
Google Scholar
Wilkins, D. treemapify: Draw Treemaps in ‘ggplot2’. R package version 2.5.5 (2021).
Shapiro, S. S. & Wilk, M. B. An analysis of variance test for normality (complete samples). Biometrika 52, 591–611 (1965).
Google Scholar
Mardia, K. V. Measures of multivariate skewness and kurtosis with applications. Biometrika 57, 519–530 (1970).
Google Scholar
Kruskal, W. H. & Wallis, W. A. Use of ranks in one-criterion variance analysis. J. Am. Stat. Assoc. 47, 583–621 (1952).
Google Scholar
Dunn, O. J. Multiple comparisons using rank sums. Technometrics 6, 241–252 (1964).
Conover, W. J. & Iman, R. L. Rank transformations as a bridge between parametric and nonparametric statistics. Am. Stat. 35, 124–129 (1981).
Google Scholar
Student,. The probable error of a mean. Biometrika 6, 1–25 (1908).
Google Scholar
Tukey, J. W. Comparing individual means in the analysis of variance. Biometrics 5, 99–114 (1949).
Google Scholar
Jolliffe, I. T. Principal Component Analysis (Springer, 2002).
Google Scholar
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