Submissions by Organization:

Despite growing commitment for tropical forest conservation, the understanding of complex spatio-temporal deforestation patterns and their underlying drivers remains limited. This study uses archetype analysis to examine global spatio-temporal deforestation patterns in tropical moist forests (TMFs) over the last two decades. This work underpins our attempt to develop a systematized diagnostic of tropical forest policies, aimed at stemming deforestation and forest degradation. We identify seven archetypes of forest state and its change in tropical moist forests, assess conversion from forest to other land uses in deforestation areas, and evaluate deforestation risk in landscapes with high remaining forest cover and low historical deforestation. Our analysis covers approximately 2.8 billion hectares of land area in the tropics that contained tropical moist forest in 2000 – equivalent to about three quarters of the world’s TMF landscapes – and thus includes both forest and non-forest areas within those units. Only less than a third of TMFs were classified as intact forest areas (i.e., high forest cover, low deforestation), while approximately a quarter were classified as deforestation areas (i.e., high deforestation). TMFs in Southeast Asia are showing higher proportions of deforestation areas and degraded forests than other regions. Central and South America has the largest absolute area of deforestation areas. While deforestation rates in sub-Saharan Africa have historically been lower, the proportion of deforestation areas is similar to that in the other continents. We could not discern clear patterns linking deforestation areas to specific types of land-use conversion, which suggests that local context plays a more significant role in shaping deforestation patterns. Low accessibility provides passive protection to a substantial part (34%) of intact forest landscapes with good agricultural suitability, particularly in the Amazon, the Congo Basin and southern New Guinea. These results indicate that tropical moist forests remain under continued pressure, with deforestation persisting at high rates. Once elevated deforestation levels are reached, they become difficult to reduce. The archetypes approach is a pragmatic tool to classify tropical deforestation, identify important hotspots under threat, and support spatially targeted policy interventions. The present paper provides the analytical foundation for four country reports, each examining deforestation policies through the lens of deforestation archetypes in a specific national context: Brazil, the Democratic Republic of the Congo (DRC), Indonesia, and Peru. Together, these five papers introduce the deforestation diagnostic framework.

This report is part of a wider inquiry into the intertwined challenges of climate change, deforestation and policy design, where global environmental goals depend on highly local realities. Forest loss remains a major driver of emissions, but its causes and trajectories vary widely across regions, shaped by governance systems, economic pressures and social dynamics. Moving beyond generic prescriptions, this study adopts a context-sensitive perspective that asks not only what policies exist, but how and where they are likely to be effective. In the Democratic Republic of the Congo, vast tropical forests remain largely intact, yet face growing pressure from small-scale agriculture, fuelwood demand and infrastructure expansion. Unlike contexts dominated by industrial drivers, deforestation here is often diffuse, incremental and closely tied to livelihoods, making policy design particularly challenging. The report applies a diagnostic framework that links patterns (archetypes) of forest change with the behavioural mechanisms that policies aim to influence, including incentives, regulation, social dynamics and capacity constraints. This approach helps identify which interventions are most relevant in different settings, from remote forest areas to emerging frontiers. The DRC’s case highlights the importance of aligning forest conservation with development needs, strengthening governance while recognizing structural limitations. By grounding policy analysis in context, the report offers a way to navigate complexity and support more effective, equitable strategies to reduce deforestation.

This report is part of a wider inquiry into the intertwined challenges of climate change, deforestation and policy design, where global environmental goals depend on highly local realities. Forest loss remains a major driver of emissions, but its causes and trajectories vary widely across regions, shaped by governance systems, economic pressures and social dynamics. Moving beyond generic prescriptions, this study adopts a context-sensitive perspective that asks not only what policies exist, but how and where they are likely to be effective. In Brazil, home to the largest share of the Amazon rainforest, deforestation has followed a striking trajectory—marked by rapid expansion, periods of strong decline, and more recent fluctuations—reflecting shifts in political priorities, enforcement capacity and market conditions. This variability makes Brazil a critical case for understanding how policy mixes perform over time and across changing contexts. The report applies a diagnostic framework that connects spatial patterns (archetypes) of forest change with the behavioural mechanisms that policies seek to influence, from strict enforcement and monitoring to incentives and supply chain pressures. By examining how these instruments interact with different deforestation contexts, it highlights why similar approaches can succeed or fail depending on where they are applied. Brazil’s experience underscores both the power of coordinated policy action and the variation in outcomes over time, offering important lessons for designing more resilient and adaptive strategies to curb deforestation.

This report is part of a wider inquiry into the intertwined challenges of climate change, deforestation and policy design, where global environmental goals depend on highly local realities. Forest loss remains a major driver of emissions, but its causes and trajectories vary widely across regions, shaped by governance systems, economic pressures and social dynamics. Moving beyond generic prescriptions, this study adopts a context-sensitive perspective that asks not only what policies exist, but how and where they are likely to be effective. In Indonesia, a vast archipelagic country with highly heterogeneous forest landscapes, deforestation has been both extensive and uneven, concentrated in long-established agricultural frontiers while large tracts of relatively intact forest remain elsewhere. This diversity makes it a critical case for understanding how policies interact with different ecological and institutional contexts. The report applies a diagnostic framework that connects spatial patterns (archetypes) of forest change with the behavioural mechanisms that policies aim to influence, from enforcement and regulatory controls to incentives, social norms and capacity-building. By examining how these instruments align with specific deforestation contexts, it highlights why policy effectiveness depends not only on design but also on where and how interventions are deployed. Indonesia’s experience—particularly the marked decline in deforestation since the mid-2010s—offers valuable insights into the potential of coordinated policy mixes, while also revealing the ongoing challenges of governance, land-use pressures and sustaining long-term change.

Rujukan Tingkat Emisi Hutan pertama Indonesia (FREL 1) telah diserahkan kepada Konvensi Kerangka Kerja PBB tentang Perubahan Iklim (UNFCCC) pada 2015 dan direvisi pada 2016 (FREL-2016). FREL Pertama bertujuan untuk mengkaji kegiatan pengurangan emisi dari deforestasi, degradasi hutan, peningkatan cadangan karbon hutan, pengelolaan hutan berkelanjutan, dan konservasi karbon hutan (REDD+) pasca-2012. Green Climate Fund menyetujui proposal Indonesia yang mengakses pembayaran REDD+ sebesar US$103,8 juta untuk periode 2014-2016. Pemerintah Indonesia telah mengidentifikasi kesenjangan dan potensi penyempurnaannya yang kemudian didokumentasikan dalam FREL-2016 oleh tim penilai teknis UNFCCC untuk pengkajian FREL-2016. Studi ini mengidentifikasi belum disertakannya sejumlah aktivitas, kantong penyimpanan karbon, dan gas ke dalam FREL- 2016 agar sesuai dengan rencana penyempurnaan; serta rekomendasi dari penilaian teknisnya. Para pemangku kepentingan di Indonesia mengidentifikasi adanya kesenjangan pada saat lokakarya “Peningkatan Kapasitas Suplemen Lahan Basah IPCC 2013 dan Diagnostik FREL” April 2020. Sebagai tambahan, kami menggunakan Suplemen Lahan Basah IPCC 2013 untuk mengidentifikasi kesenjangan pendugaan dan penyerapan emisi dari perubahan tutupan hutan serta kebakaran mangrove dan lahan gambut.