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Amazonian forests function as biomass and biodiversity reservoirs, contributing to climate change mitigation. While they continuously experience disturbance, the effect that disturbances have on biomass and biodiversity over time has not yet been assessed at a large scale. Here, we evaluate the degree of recent forest disturbance in Peruvian Amazonia and the effects that disturbance, environmental conditions and human use have on biomass and biodiversity in disturbed forests. We integrate tree-level data on above ground biomass (AGB) and species richness from 1840 forest plots from Peru's National Forest Inventory with remotely sensed monitoring of forest change dynamics, based on disturbances detected from Landsat-derived Normalized Difference Moisture Index time series. Our results show a clear negative effect of disturbance intensity tree species richness. This effect was also observed on AGB and species richness recovery values towards undisturbed levels, as well as on the recovery of species composition towards undisturbed levels. Time since disturbance had a larger effect on AGB than on species richness. While time since disturbance has a positive effect on AGB, unexpectedly we found a small negative effect of time since disturbance on species richness. We estimate that roughly 15% of Peruvian Amazonian forests have experienced disturbance at least once since 1984, and that, following disturbance, have been increasing in AGB at a rate of 4.7 Mg ha−1 year−1 during the first 20 years. Furthermore, the positive effect of surrounding forest cover was evident for both AGB and its recovery towards undisturbed levels, as well as for species richness. There was a negative effect of forest accessibility on the recovery of species composition towards undisturbed levels. Moving forward, we recommend that forest-based climate change mitigation endeavours consider forest disturbance through the integration of forest inventory data with remote sensing methods.

Background Amazon palm swamp peatlands are major carbon (C) sinks and reservoirs. In Peru, this ecosystem is widely threatened owing to the recurrent practice of cutting Mauritia flexuosa palms for fruit harvesting. Such degradation could significantly damage peat deposits by altering C fluxes through fine root productivity, mortality, and decomposition rates which contribute to and regulate peat accumulation. Along a same peat formation, we studied an undegraded site (Intact), a moderately degraded site (mDeg) and a heavily degraded site (hDeg) over 11 months. Fine root C stocks and fluxes were monthly sampled by sequential coring. Concomitantly, fine root decomposition was investigated using litter bags. In the experimental design, fine root stocks and dynamics were assessed separately according to vegetation type (M. flexuosa palm and other tree species) and M. flexuosa age class. Furthermore, results obtained from individual palms and trees were site-scaled by using forest composition and structure. Results At the scale of individuals, fine root C biomass in M. flexuosa adults was higher at the mDeg site than at the Intact and hDeg sites, while in trees it was lowest at the hDeg site. Site-scale fine root biomass (Mg C ha−1) was higher at the mDeg site (0.58 ± 0.05) than at the Intact (0.48 ± 0.05) and hDeg sites (0.32 ± 0.03). Site-scale annual fine root mortality rate was not significantly different between sites (3.4 ± 1.3, 2.0 ± 0.8, 1.5 ± 0.7 Mg C ha−1 yr−1 at the Intact, mDeg, and hDeg sites) while productivity (same unit) was lower at the hDeg site (1.5 ± 0.8) than at the Intact site (3.7 ± 1.2), the mDeg site being intermediate (2.3 ± 0.9). Decomposition was slow with 63.5−74.4% of mass remaining after 300 days and it was similar among sites and vegetation types. Conclusions The significant lower fine root C stock and annual productivity rate at the hDeg site than at the Intact site suggests a potential for strong degradation to disrupt peat accretion. These results stress the need for a sustainable management of these forests to maintain their C sink function.

Flooded savannas are extensive in South America and this study was conducted to assess two digital soil mapping (DSM) approaches to predict the spatial distribution of soil organic carbon (SOC) content and stocks in the Orinoco flooded savannas of Casanare department, located in the eastern plains of Colombia. SOC was estimated using a total of 80 sites sampled at two soil depth intervals (0-10 cm and 10-30 cm). SOC ranged from 0.41% at 0-10 cm and 0.23% at 10-30 cm in drier soils found in continental dunes with sandy textures and low vegetation cover (steppe) to over 14.50% and 7.51% in soils that experienced seasonal flooding located in depressions with loamy textures and flooded savanna vegetation. Predictions of the spatial distribution of SOC were done through Expert Knowledge (EK) and Random Forest (RF) approaches across the study area at 0-10 cm and 10-30 cm soil depth. Both DSM approaches were assessed through root mean square errors, mean absolute errors, and coefficients of determination. Although both DSM approaches performed very well, EK was considered slightly superior to predict SOC in the Casanare flooded savannas. Covariates derived from vegetation coverage, topography, and soil texture properties were identified as key drivers in controlling its distribution at the study area. We found total SOC stocks of 55.07 Mt with a mean density of 83.13 ± 24.32 t ha-1 stored in the first 30 cm soil depth, with 12.3% of this being located in the flooded parts of the savanna landscape, which represented only 7.9% of the study area (664,752 ha). This study provides the first effort to systematically quantify SOC stocks in the Casanare flooded savannas and shows the importance of conserving this ecosystem with the aim of avoiding SOC losses and consequent increased CO2 emissions to the atmosphere. We estimate that the department of Casanare would release an average of 2,42 Mton of CO2 emissions per year over 30 years if there were large scale conversion of the flooded savannas to intensive agriculture, which corresponds to 62% of the current emissions of the department. At regional level, the impact of a large-scale land use conversion of the flooded Llanos del Orinoco ecosystem area (15 Mha) would represent 1/3 of the current net Colombian CO2 emission (AFOLU), which makes this region a potentially important source of emissions if correct decisions are not taken regarding the land management.

Mauritia flexuosa palm swamp, the prevailing Peruvian Amazon peatland ecosystem, isextensively threatened by degradation. The unsustainable practice of cutting wholepalms for fruit extraction modifies forest's structure and composition and eventuallyalters peat-derived greenhouse gas (GHG) emissions. We evaluated the spatio-temporalvariability of soil N2O and CH4 fluxes and environmental controls along a palm swampdegradation gradient formed by one undegraded site (Intact), one moderately degradedsite (mDeg) and one heavily degraded site (hDeg). Microscale variability differentiatedhummocks supporting live or cut palms from surrounding hollows. Macroscale analysisconsidered structural changes in vegetation and soil microtopography as impactedby degradation. Variables were monitored monthly over 3 years to evaluate intra- andinter-annual variability. Degradation induced microscale changes in N2O and CH4 emissiontrends and controls. Site-scale average annual CH4 emissions were similar along thedegradation gradient (225.6 ± 50.7, 160.5 ± 65.9 and 169.4 ± 20.7 kg C ha−1 year−1 atthe Intact, mDeg and hDeg sites, respectively). Site-scale average annual N2O emissions(kg N ha−1 year−1) were lower at the mDeg site (0.5 ± 0.1) than at the Intact (1.3 ± 0.6) andhDeg sites (1.1 ± 0.4), but the difference seemed linked to heterogeneous fluctuationsin soil water-filled pore space (WFPS) along the forest complex rather than to degradation.Monthly and annual emissions were mainly controlled by variations in WFPS, watertable level (WT) and net nitrification for N2O; WT, air temperature and net nitrificationfor CH4. Site-scale N2O emissions remained steady over years, whereas CH4 emissionsrose exponentially with increased precipitation. While the minor impact of degradationon palm swamp peatland N2O and CH4 fluxes should be tested elsewhere, the evidencedlarge and variable CH4 emissions and significant N2O emissions call for improved modelingof GHG dynamics in tropical peatlands to test their response to climate changes.

Peruvian national and regional plans promoting oil palm have prompted a rapid expansion of the crop in the Amazonian region. This expansion has taken place primarily at the expense of forest, both undisturbed and disturbed. Assessments of carbon emissions from forest-to-oil palm conversion have essentially been confined to Southeast Asia, and research on Peruvian Amazonian forests has mainly targeted undisturbed sites. This study characterizes the vegetation structure and composition of disturbed forests and smallholder oil palm plantations and evaluates the change in ecosystem (that is, phytomass and soil) carbon stocks associated with forest-to-oil palm conversion. Inventories were conducted in four degraded forest sites neighboring six oil palm plantation sites in Ucayali. Time-averaged carbon stocks over the 30-year oil palm rotation were computed from models developed upon the sampled chronosequence (1 to 28 years old). Disturbed forests harbored species typical of primary forests, pioneer species and gaps opportunistic species. Their tree basal area (18.7 ± 1.4 m2 ha−1) and above-ground C stock (71.3 ± 4.2 Mg C ha−1) were, respectively, 50 and 60% of the values of undisturbed forests from the literature. The growth curve for oil palm above-ground biomass was consistently below models developed for plantations in Indonesia. Thirty-year time-averaged ecosystem C stock (Mg C ha−1) in oil palm plantations (78.2 ± 2.0) represented 55% of the stock in disturbed forest (140.9 ± 5.8), resulting in a 62.7 ± 6.1 loss from such conversion. These results reinforce recommendations to redirect oil palm expansion toward low-carbon degraded lands, sparing disturbed and undisturbed forests.

As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of aboveground net biomass change (∆AGB) are needed. Countries with limited forest monitoring capabilities in the tropics and subtropics rely on IPCC 2006 default ∆AGB rates, which are values per ecological zone, per continent. Similarly, research into forest biomass change at a large scale also makes use of these rates. IPCC 2006 default rates come from a handful of studies, provide no uncertainty indications and do not distinguish between older secondary forests and old‐growth forests. As part of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, we incorporate ∆AGB data available from 2006 onwards, comprising 176 chronosequences in secondary forests and 536 permanent plots in old‐growth and managed/logged forests located in 42 countries in Africa, North and South America and Asia. We generated ∆AGB rate estimates for younger secondary forests (≤20 years), older secondary forests (>20 years and up to 100 years) and old‐growth forests, and accounted for uncertainties in our estimates. In tropical rainforests, for which data availability was the highest, our ∆AGB rate estimates ranged from 3.4 (Asia) to 7.6 (Africa) Mg ha−1 year−1 in younger secondary forests, from 2.3 (North and South America) to 3.5 (Africa) Mg ha−1 year−1 in older secondary forests, and 0.7 (Asia) to 1.3 (Africa) Mg ha−1 year−1 in old‐growth forests. We provide a rigorous and traceable refinement of the IPCC 2006 default rates in tropical and subtropical ecological zones, and identify which areas require more research on ∆AGB. In this respect, this study should be considered as an important step towards quantifying the role of tropical and subtropical forests as carbon sinks with higher accuracy; our new rates can be used for large‐scale GHG accounting by governmental bodies, nongovernmental organizations and in scientific research., As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of aboveground biomass change (∆AGB) in natural forests are needed. Countries with limited forest monitoring capabilities in the (sub)tropics rely on the 2006 IPCC guidelines for default ∆AGB rates. This study provides refined default ∆AGB rate estimates based on forest plot data in younger secondary forests, older secondary forests and old‐growth forests, located in 42 countries across (sub)tropical ecozones. These new estimates contribute towards the 2019 IPCC Refinement and can be used for large‐scale GHG accounting by governmental bodies, nongovernmental organizations and in scientific research.

Forests, trees and agroforestry are part of major land-use transitions worldwide, with an impact on the balance between the global issues of planetary boundaries and local concerns about livelihoods and peoples’ rights. The 17 Sustainable Development Goals (SDGs) include complex trade-offs between various local and global interests in forests or derived land uses that require effective science-policy boundary work. Use-oriented research carried out by FTA connects three knowledge systems: the various scientific disciplines, local ways of knowing, and the way public discourses and policy reforms (re)frame issues, articulate common goals and seek effective means of implementation. Place-based, context-responsive sustainable development solutions need to build on identities and core values. These interact with socially contextualized rights, knowledge, markets, local ecosystem services and global teleconnections. This is an introduction to the FTA Highlights of a Decade series, which showcases the main findings, results and achievements of the CGIAR Research Program on Forests, Trees and Agroforestry (FTA) from 2011 to 2021. FTA, the world’s largest research-for-development partnership on forests, trees and agroforestry, started in 2011. This series features the work undertaken under the FTA program by its strategic partners: Center for International Forestry Research-World Agroforestry (CIFOR-ICRAF), The Alliance of Bioversity and CIAT, Centro Agronomico Tropical de Investigacion y Ensenanza (CATIE), French Agricultural Research Centre for International Development (CIRAD), Tropenbos International and International Bamboo and Rattan Organisation (INBAR); and other national and international partners. A decade of research and action by the FTA program has deepened the understanding of the roles of trees in farms and forests on the planet and of land-use and tree-use options in context. It has supported new market connections (traditional and new tree-based food, energy, biomaterials, environmental services), contributed to the emergence of more inclusive business models for tree-based value chains, informed the agendas of national and global forest, climate and food policy and facilitated new forms of governance for the “global commons.” All the work presented in this introduction and in the FTA highlights series was undertaken as part of the FTA program. The series aims to show the extent of actual contributions of FTA to research and development challenges and solutions over a decade, and indirectly, in doing so, to also provide a perspective on the genesis, history and evolving narratives on the related development issues.

The CGIAR Research Program on Forests, Trees and Agroforestry (FTA) organized over 10 days from 14 to 25 September 2020 its decadal conference. The fully digital event titled Forest, trees and agroforestry science for transformational change gathered more than 500 scientists from the programme and its working partners, from 69 countries across the globe, with more than 100 presentations and 40 posters. The conference also featured a set of science – policy – implementation panel discussions, including around controversial issues, with high profile scientists and key stakeholders, as well as a series of keynote speeches. The present publication gathers the 179 abstracts accepted for the conference. It constitutes a vivid illustration of the research developed by the program and its collaborative partners worldwide. All the material and presentations over the course of the 10-day conference is freely accessible on the FTA website: https://www.foreststreesagroforestry.org/fta-2020-science-conference-forests-trees-and-agroforestry-science-for-transformational-change/

Forest and landscape restoration (FLR) provides a framework for implementing restorative interventions that collectively address major environmental challenges such as soil and land degradation, biodiversity loss, water scarcity, lack of sustainable rural livelihoods, and climate change mitigation and adaptation. Restorative interventions can take many forms, which vary in cost, trajectory and specific economic and social outcomes; likewise, their benefits accrue to various actors and stakeholders. Over the last decade, the CGIAR Program on Forests, Trees and Agroforestry (FTA) has undertaken innovative basic and applied research across different scientific disciplines on the multiple dimensions of FLR for improving policy and practice and facilitating the uptake of new knowledge, tools and approaches — both from the top down and the bottom up. This publication presents key FTA outputs on forest and landscape restoration from 2011 to 2021. Many of them have contributed to informing the implementation of FLR interventions at multiple scales of work. These outputs are presented according to five broad areas of influence: (i) contributions to restoration science; (ii) contributions to global narratives and discourses; (iii) contributions to policy and governance; (iv) focusing on actors on the ground; and (v) contributions to national and international dialogues. The last section discusses ways to move forward.

Populations in sub-Saharan Africa (SSA) living on the fringes of forests indubitably rely on them for income and subsistence. But unsustainable practices can lead to resource degradation and depletion, threatening the very basis of their livelihoods. A forest-based ‘circular’ bioeconomy approach could stabilize sustainable natural resource use, yet bioeconomy strategies so far have focused mostly on technology and economics, rather than on matters of social sustainability. This study reviews literature published between 2000 and 2020, with the aim of identifying whether socio-economic impacts were taken into account in the forest sectors and bioeconomy elements covered in this SSA-focused literature. Many studies investigate forest-related value chain development across a forest sector that remains mostly traditional and largely informal. Non-timber forest products (NTFPs) play a significant role and could represent an entry point for bioeconomy development. Energy security could also benefit from taking a bioeconomy perspective. Forest activities resulted in positive social outcomes in just a third of the studied cases. Challenges to bioeconomy development include uncoordinated and often bureaucratic forest policies and regulations, as well as overlaps and clashes between formal and informal economic activities and land tenure regimes. Lack of knowledge and skills – around entrepreneurship, investment and finance – further hampers development. In conclusion, while forest-based bioeconomy could enrich the forest sector and contribute to poverty reduction and natural resource conservation, strategies must adopt a strong social sustainability approach, or this transition risks reproducing patterns of land grabbing, elite capture, spatial injustice and the displacement and disempowerment of rural populations.

Major land use changes such as deforestation and restoration influence water resources in agriculture–forest landscapes. Changes are observed in water flows, groundwater infiltration, water quality and rainfall. Interdisciplinary water–forest research has unravelled biophysical parts of the interplay that influences forest and water resources. In this Perspective paper, we propose an expanded interdisciplinary research approach to study water and policies in agriculture–forest frontiers. The approach differs in four important aspects from previous ones: (i) a conceptual ‘frontier’ understanding; an analytical focus on (ii) agriculture and (iii) policy–water linkages; (iv) empirical attention to northern and southern countries. The approach is put into practice with the “Pendulum” framework, with interventions and the agriculture–forest frontier oscillating over time between exploitation and restoration. Through the approach, a better understanding will be provided on the dynamic interplay of water and policies in oscillating agriculture–forest frontiers, with changing outcomes for people and environment.

Assessing land-use following deforestation is vital for reducing emissions from deforestation and forest degradation. In this paper, for the first time, we assess the potential of spatial, temporal and spatio-temporal deep learning methods for large-scale classification of land-use following tropical deforestation using dense satellite time series over six years on the pan-tropical scale (incl. Latin America, Africa, and Asia). Based on an extensive reference database of six forest to land-use conversion types, we find that the spatio-temporal models achieved a substantially higher F1-score accuracies than models that account only for spatial or temporal patterns. Although all models performed better when the scope of the problem was limited to a single continent, the spatial models were more competitive than the temporal ones in this setting. These results suggest that the spatial patterns of land-use within a continent share more commonalities than the temporal patterns and the spatial patterns across continents. This work explores the feasibility of extending and complementing previous efforts for characterizing follow-up land-use after deforestation at a small-scale via human visual interpretation of high resolution RGB imagery. It supports the usage of fast and automated large-scale land-use classification and showcases the value of deep learning methods combined with spatio-temporal satellite data to effectively address the complex tasks of identifying land-use following deforestation in a scalable and cost effective manner.

Replacement of forest by agricultural systems is a major factor accelerating the emissions of greenhouse gases; however, related field studies in the tropics are very scarce. To evaluate the impact of forest transition to plantations on soil methane (CH4) and respiration (CO2) fluxes, we conducted measurements in an undisturbed forest, a disturbed forest, young and old rubber plantations, and an oil palm plantation on mineral soil in Jambi, Sumatra, Indonesia. Methane fluxes and their controlling variables were monitored monthly over fourteen months; soil respiration was measured less frequently. All of the plantations were managed by smallholders and had never been fertilized. To assess the effect of common management practices in oil palm plantations, we added urea at a rate of 33.3 kg N/ha and thereafter monitored intensively soil CH4 fluxes. The soil acted as a sink for CH4 (kg CH4‐C·ha−1·yr−1) in the undisturbed forest (−1.4 ± 1.0) and young rubber plantation (−1.7 ± 0.7). This was not the case in the other land‐use systems which had fluxes similar to fluxes in the undisturbed forest, with 0.4 ± 0.9, −0.2 ± 0.3, and 0.2 ± 0.7 kg·ha−1·yr−1 in the disturbed forest, old rubber plantation, and oil palm plantation, respectively. In the oil palm plantation, there was no inhibitory effect of nitrogenous fertilizer on methanotrophy. Annual soil respiration (Mg CO2‐C·ha−1·yr−1) was higher in the oil palm plantation (17.1 ± 1.9) than in the undisturbed forest (13.9 ± 1.2) while other land‐use systems respired at a similar level to the undisturbed forest (13.1 ± 1.4, 15.9 ± 1.7, and 14.1 ± 1.0 in the disturbed forest, young, and old rubber plantations, respectively). Substrate (litterfall and soil) availability and quality exerted a strong control over annual fluxes of both gases along the land‐use gradient. Temporal variation in CH4 was extremely high and in respiration fluxes was moderate, but was not specifically linked to seasonal variation. Further comprehensive and long‐term research is critically needed to determine more thoroughly the direction and magnitude of changes in soil trace gas emissions as affected by forest‐to‐plantation conversion in the tropics.

Mauritia flexuosa palm swamp, the prevailing Peruvian Amazon peatland ecosystem, is extensively threatened by degradation. The unsustainable practice of cutting whole palms for fruit extraction modifies forest's structure and composition and eventually alters peat‐derived greenhouse gas (GHG) emissions. We evaluated the spatiotemporal variability of soil N2O and CH4 fluxes and environmental controls along a palm swamp degradation gradient formed by one undegraded site (Intact), one moderately degraded site (mDeg) and one heavily degraded site (hDeg). Microscale variability differentiated hummocks supporting live or cut palms from surrounding hollows. Macroscale analysis considered structural changes in vegetation and soil microtopography as impacted by degradation. Variables were monitored monthly over 3 years to evaluate intra‐ and inter‐annual variability. Degradation induced microscale changes in N2O and CH4 emission trends and controls. Site‐scale average annual CH4 emissions were similar along the degradation gradient (225.6 ± 50.7, 160.5 ± 65.9 and 169.4 ± 20.7 kg C ha−1 year−1 at the Intact, mDeg and hDeg sites, respectively). Site‐scale average annual N2O emissions (kg N ha−1 year−1) were lower at the mDeg site (0.5 ± 0.1) than at the Intact (1.3 ± 0.6) and hDeg sites (1.1 ± 0.4), but the difference seemed linked to heterogeneous fluctuations in soil water‐filled pore space (WFPS) along the forest complex rather than to degradation. Monthly and annual emissions were mainly controlled by variations in WFPS, water table level (WT) and net nitrification for N2O; WT, air temperature and net nitrification for CH4. Site‐scale N2O emissions remained steady over years, whereas CH4 emissions rose exponentially with increased precipitation. While the minor impact of degradation on palm swamp peatland N2O and CH4 fluxes should be tested elsewhere, the evidenced large and variable CH4 emissions and significant N2O emissions call for improved modeling of GHG dynamics in tropical peatlands to test their response to climate changes., Over 3 years of monitoring, Peruvian Amazon Mauritia flexuosa palm swamp peatlands showed significant N2O emissions and large CH4 emissions, the later exhibiting an exponential rise with increased precipitation. Their degradation, which results from cutting whole palms for fruit extraction, induced microscale (hummock and hollow of live and cut palms) changes in N2O and CH4 emission trends and controls but no obvious changes at the macroscale. Monthly and annual emissions were mainly controlled by variations in: WFPS, water table level (WT), and net nitrification for N2O; WT, air temperature and net nitrification for CH4.

Nitrogen (N) deposition to soils is globally rising, but its effect on soil organic carbon (SOC) turnover is still uncertain. Moreover, common theories of stoichiometric decomposition and microbial N mining predict opposing effects of N supply on SOC turnover. We hypothesized that the effect of N deposition on SOC turnover depends on initial soil nutrient conditions. Thus, we sampled tropical forests and rubber gardens with pronounced gradients of nutrient availability from the topsoil to the deep subsoil (up to 400 cm) and measured substrate-induced respiration (SIR) for 30 days in four treatments (C, CN, CP, CNP additions). A natural 13C abundance approach was conducted to quantify priming effects (PE) of the added C on SOC mineralization. For this purpose we assessed the 13CO2 isotope composition after adding a C4 sugar to the C3 soil; to correct for isotopic fractionation a treatment with C3 sugar additions served as control. We found that nutrient additions to topsoil did neither alter cumulative CO2 release within 30 days (SIRacc) nor PE (PE = 1.6, i.e., sugar additions raised the release of SOC-derived CO2 by a factor of 1.6). In the upper subsoil (30-100 cm), however, both CN and CP additions increased SIRacc (by 239% and 92%, respectively) and the PE (PE = 5.2 and 3.3, respectively) relative to the treatments that received C only (PE = 1.7), while CNP additions revealed the largest increase of SIRacc (267%) and PE (PE = 6.0). In the deep subsoil (>130 cm depth), only the CNP addition consistently increased SIRacc (by 871%) and PE (PE = 5.2) relative to only C additions (PE = 2.0). We conclude that microbial activity was not limited by nutrients in the topsoil but was co-limited by both N and P in the subsoil. The results imply that microbes mine nutrients from previously unavailable pools under the conditions that 1) deficiency actually exists, 2) co-limitation is alleviated, and 3) nutrient reserves are present. Yet, as opposed to microbial nutrient mining theories, we showed that the subsoil PE is highest when nutrient supply matches microbial demand. As a result also N deposition might exert variable effects on SOC turnover in tropical soils: it might have no effect in nutrient-rich topsoils and in co-limited subsoils without P reserves but might increase SOC turnover in co-limited subsoils with potentially acquirable P reserves.

The goal to improve food security in sub-Saharan Africa (SSA) through domestic, resource efficient and low carbon agriculture is importance. Interventions to produce more food could impact the resource-base and lead to increase in greenhouse gas (GHG) emissions from agroecosystems. Unfortunately, existing methods are limited in analyzing small-scale agricultural systems, and this situation is an obstacle to decision making which aims at sustainable agriculture. In this paper, we showcase the recently developed Emergy-Data Envelopment Analysis (EM-DEA) approach to assess the resource use efficiency (RUE) and sustainability in maize production systems in Ghana, SSA. Using the Agricultural Production Systems sIMulator (APSIM), five land use and resource management scenarios were modeled to represent practices as decision making units (DMUs) in small-scale maize systems. The carbon footprint of the systems was assessed using an approach, which we adapted from the FAO Ex-Ante Carbon balance Tool (EX-ACT). The overall trend of the results showed that the yield, total emergy, GHG emissions and carbon footprint all increased with increase in urea application intensity. However, the relationship between the yield and urea intensity was not always linear. A system that used more renewable or fewer resources to produce a yield equal to that of its peer was considered more efficient and sustainable in relative terms. In particular, the business-as-usual scenario (12 kg/ha/yr NPK input to rainfed maize system, i.e. Extensive12) was inefficient when compared to the four contrasting scenarios. The ecological intensive scenario (20 kg/ha/yr urea input to rainfed maize-legume intercropping system, i.e. Intercrop20) achieved the greatest marginal yield, better RUE and sustainability. The high input scenario (100 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e. Intensive100) produced the greatest yield, but the demand for purchased inputs as well as GHG emissions and carbon footprint were greatest. The no external input scenario (0 kg/ha/yr urea input to rainfed maize system, i.e. Extensive0), and the moderate input scenario (50 kg/ha/yr urea input plus supplemental irrigation to maize monoculture, i.e. Intensive50) showed the greatest and least yield gaps relative to Intensive100, respectively. Based on these results and trade-off analysis, it was evident that Intercrop20 and Intensive50 were the two best case scenarios. As such, land use policy that aims at sustainable agriculture could recommend Intercrop20 and Intensive50 for implementation in low and high input maize production systems, respectively. Comparison between our results and other existing empirical studies revealed similarities that confirm our results. We conclude that the information derived using the EM-DEA and EX-ACT approaches could be useful when making informed decisions that aim at sustainable agriculture. Despite the limitation caused by scarcity of data, the use of the EM-DEA approach led to inclusive information on RUE and sustainability of the DMUs. Hence, the EM-DEA approach represents a way forward to better assess energy footprint in agricultural land use as a whole.

1. Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above-ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three-dimensional (3D) tree modelling of TLS point clouds. 2. Twenty-nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species-specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. 3. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV-RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV-RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. 4. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non-destructive method can be further used for testing and calibrating new allometric models, reducing the current under-representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests. publishedVersion

Programs to provide alternative energy sources such as biogas improve indoor air quality and potentially reduce pressure on forests from fuelwood collection. This study tests whether biogas intervention is associated with higher forest biomass and forest regeneration in degraded forests in Chikkaballapur district in Southern India. Using propensity score matching, we find that forest plots in proximity to villages with biogas interventions (treatment) had greater forest biomass than comparable plots around villages without biogas (control). We also found significantly higher sapling abundance and diversity in treatment than control plots despite no significant difference in seedling abundances and diversity in treatment forests, suggesting that plants have a higher probability of reaching sapling stage. These results indicate the potential for alternative energy sources that reduce dependence on fuelwood to promote regeneration of degraded forests. However, forest regrowth is not uniform across treatments and is limited by soil nutrients and biased towards species that are light demanding, fire-resistant and can thrive in poor soil conditions.

In the last 40 years, large areas of the Mau forest, the largest contiguous tropical montane forest in East Africa, have been cleared for agriculture. To date, there are no empirical data on how this land use change affects carbon dioxide (CO2) fluxes from soil respiration and soil methane (CH4) fluxes. This study reports measured annual soil CO2 and CH4 fluxes from the native Mau forest and previously forested lands converted to smallholder grazing land, smallholder and commercial tea plantations and eucalyptus plantations. Fluxes were measured weekly from August 2015 to August 2016 using the static chamber method. Grazing lands had the highest (p = 0.028) cumulative respiratory CO2 fluxes (25.6 ± 2.9 Mg CO2–C ha¯¹ year¯¹), whereas lowest fluxes were observed in commercial tea plantations (5.6 ± 0.5 Mg CO2–C ha¯¹ year¯¹). Soil respiratory CO2 fluxes were positively correlated with soil pH, but negatively correlated with soil C:N ratio. Annual soil fluxes were explained by soil pH, bulk density and the interaction between soil pH and C:N ratio. Most soils were sinks for atmospheric CH4 across all land use types. Methane uptake was highest for native forest sites (- 3.08 ± 0.35 to - 5.84 ± 0.61 kg CH4–C ha¯¹ year¯¹) and for eucalyptus plantations (- 3.43 ± 0.19 kg CH4–C ha¯¹ year¯¹). Uptake decreased significantly with increasing land use intensity (smallholder tea plantations: - 1.42 ± 0.09 kg CH4–C ha¯¹ year¯¹, commercial tea plantations: - 1.44 ± 0.29 kg CH4–C ha¯¹ year¯¹). Soils of smallholder grazing lands had the lowest CH4 uptake rates (- 0.36 ± 0.25 kg CH4–C ha¯¹ year¯¹). Annual CH4 uptake was negatively correlated with mean annual soil water-filled pore space (p

Key messagesLand restoration will happen under climate change and different knowledge systems are needed to navigate uncertainties and plan adaptation.The emergence of novel ecosystems presents a challenge for land restoration; they harbor unknown unknowns.This brief presents key research linking land restoration and societal adaptation and an example of a practical framework for transformative adaptation.It also proposes questions that can guide stakeholders in exploring different change narratives for adaptation and restoration planning.

Assessing the performance of efforts to reduce emissions from deforestation and forest degradation (REDD+) requires data on forest cover change. Innovations in remote sensing and forest monitoring provide ever-increasing levels of coverage, spatial and temporal detail, and accuracy. More global products and advanced open-source algorithms are becoming available. Still, these datasets and tools are not always consistent or complementary, and their suitability for local REDD+ performance assessments remains unclear. These assessments should, ideally, be free of any confounding factors, but performance estimates are affected by data uncertainties in unknown ways. Here, we analyse (1) differences in accuracy between datasets of forest cover change; (2) if and how combinations of datasets can increase accuracy; and we demonstrate (3) the effect of (not) doing accuracy assessments for REDD+ performance measurements. Our study covers five local REDD+ initiatives in four countries across the tropics. We compared accuracies of a readily available global forest cover change dataset and a locally modifiable open-source break detection algorithm. We applied human interpretation validation tools using Landsat Time Series data and high-resolution optical imagery. Next, we assessed whether and how combining different datasets can increase accuracies using several combination strategies. Finally, we demonstrated the consequences of using the input datasets for REDD+ performance assessments with and without considering their accuracies and uncertainties. Estimating the amount of deforestation using validation samples could substantially reduce uncertainty in REDD+ performance assessments. We found that the accuracies of the various data sources differ at site level, although on average neither one of the input products consistently excelled in accuracy. Using a combination of both products as stratification for area estimation and validated with a sample of high-resolution data seems promising. In these combined products, the expected trade-offs in accuracies across change classes (before, after, no change) and across accuracy types (user’s and producer’s accuracy) were negligible, so their use is advantageous over single-source datasets. More locally calibrated wall-to-wall products should be developed to make them more useful and applicable for REDD+ purposes. The direction and degree of REDD+ performance remained statistically uncertain, as CIs were overlapping in most cases for the deforestation estimates before and after the start of the REDD+ interventions. Given these uncertainties and inaccuracies and to increase the credibility of REDD+ it is advised to (1) be conservative in REDD+ accounting, and (2) not to rely on results from single currently available global data sources or tools without sample-based validation if results-based payments are intended to be made on this basis.

The geometric structure of tree branches has been hypothesized to relate to the mechanical safety and efficiency of resource transport within a tree. As such, the topology of tree architecture links physical properties within a tree and influences the interaction of the tree with its environment. Prior work suggests the existence of general principles which govern tree architectural patterns across of species and bio-geographical regions. In particular, West, Brown and Enquist (WBE, 1997) and Savage et al. (2010) derive scaling exponents (branch radius scaling ratio α and branch length scaling ratio β ) from symmetrical branch parameters and from these, an architecture-based metabolic scaling rate ( θ ) for the whole tree. With this key scaling exponent, the metabolism (e.g., number of leaves, respiration, etc.) of a whole tree, or potentially a group of trees, can be estimated allometrically. Until now, branch parameter values have been measured manually; either from standing live trees or from harvested trees. Such measurements are time consuming, labour intensive and susceptible to subjective errors. Remote sensing, and specifically terrestrial LiDAR (TLS), is a promising alternative, being objective, scalable, and able to collect large quantities of data without destructive sampling. In this paper, we calculated branch length, branch radius, and architecture-based metabolic rate scaling exponents by first using TLS to scan standing trees and then fitting quantitative structure models (TreeQSM) models to 3D point clouds from nine trees in a tropical forest in Guyana. To validate these TLS-derived scaling exponents, we compared them with exponents calculated from direct field measurements of all branches >10 cm at four scales: branch-level, cumulative branch order, tree-level and plot-level. We found a bias on the estimations of α and β exponents due to a bias on the reconstruction of the branching architecture. Although TreeQSM scaling exponents predicted similar θ as the manually measured exponents, this was due to the combination of α and β scaling exponents which were both biased. Also, the manually measured α and β scaling exponents diverged from the WBE’s theoretical exponents suggesting that trees in tropical environments might not follow the predictions for the symmetrical branching geometry proposed by WBE. Our study provides an alternative method to estimate scaling exponents at both the branch- and tree-level in tropical forest trees without the need for destructive sampling. Although this approach is based on a limited sample of nine trees in Guyana, it can be implemented for large-scale plant scaling assessments. These new data might improve our current understanding of metabolic scaling without harvesting trees.

Globally, countries report forest information to the Food and Agriculture Organization (FAO) of the United Nations Global Forest Resources Assessments (FRA) at regular intervals. While the status and trends of national forest monitoring capacities have been previously assessed for the tropics, this has not been systematically done worldwide. In this paper, we assess the use and quality of forest monitoring data sources for national reporting to the FRA in 236 countries and territories. More specifically, we (a) analyze the use of remote sensing (RS) for forest area monitoring and the use of national forest inventory (NFI) for monitoring forest area, growing stock, biomass, carbon stock, and other attributes in FRA 2005–2020, (b) assess data quality in FRA 2020 using FAO tier-based indicators, and (c) zoom in to investigate changes in tropical forest monitoring capacities in FRA 2010–2020. Globally, the number of countries monitoring forest area using RS at good to very good capacities increased from 55 in FRA 2005 to 99 in FRA 2020. Likewise, the number of countries with good to very good NFI capacities increased from 48 in FRA 2005 to 102 in FRA 2020. This corresponds to ∼85% of the global forest area monitored with one or more nationally-produced up-to-date RS products or NFI in FRA 2020. For large proportions of global forests, the highest quality data was used in FRA 2020 for reporting on forest area (93%), growing stock (85%), biomass (76%), and carbon pools (61%). Overall, capacity improvements are more widespread in the tropics, which can be linked to continued international investments for forest monitoring especially in the context of reducing emissions from deforestation and forest degradation in tropical countries (REDD+). More than 50% of the tropical countries with targeted international support improved both RS and NFI capacities in the period 2010–2020 on top of those that already had persistent good to very good capabilities. There is also a link between improvements in national capacities and improved governance measured against worldwide governance indicators (WGI). Our findings—the first global study—suggest an ever-improving data basis for national reporting on forest resources in the context of climate and development commitments, e.g. the Paris Agreement and Sustainable Development Goals.

Disturbed African tropical forests and woodlands have the potential to contribute to climate change mitigation. Therefore, there is a need to understand how carbon stocks of disturbed and recovering tropical forests are determined by environmental conditions and human use. In this case study, we explore how gradients in environmental conditions and human use determine aboveground biomass (AGB) in 1958 national forest inventory (NFI) plots located in forests and woodlands in mainland Tanzania. Plots were divided into recovering forests (areas recovering from deforestation for −1yr−1 during the first 20 years following establishment. Our results can serve as the basis of carbon sink estimates in African recovering tropical forests and woodlands, and aid in forest landscape restoration planning.

According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) contributes roughly a quarter ( ∼ 10–12 Pg CO2e yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice, and livestock. In spite of the importance of this sector, it is unclear where the regions with hotspots of AFOLU emissions are and how uncertain these emissions are. Here we present a novel, spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°) for the tropics for the period 2000–2005. Our data highlight the following: (i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; (ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (69 %) and to their uncertainties (98 %); (iii) higher gross fluxes from forests, which coincide with higher uncertainties, making agricultural hotspots appealing for effective mitigation action; and (iv) a lower contribution of non-CO2 agricultural emissions to the total gross emissions (ca. 25 %), with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions of 8.0 (5.5–12.2) were in the range of other databases (8.4 and 8.0 Pg CO2e yr−1 in FAOSTAT and the Emissions Database for Global Atmospheric Research (EDGAR) respectively), but we offer a spatially detailed benchmark for monitoring progress in reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties will assist national policy makers, investors, and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.

We evaluated the annual stocks and decay rates of leaf litter, green foliage, and fine roots at a multiple-species afforestation site using the litterbag technique over 3 years. During the course of each year the decomposition of all residue types exhibited a pattern of initially rapid loss of mass over winter followed by decomposition rates that were effectively zero for the rest of the year. Depending on the year of measurement and tree species, decay constants defined by the asymptotic function (k a ) for foliar materials ranged between 3 and 16 year−1, with 55–74 % of the initial mass remaining after 1 year of field exposure. The greatest amount of mass remaining was observed in the third year when topsoil salinity increased to a point (11–18 dS m−1) that it inhibited decomposition, superseding the influences of species characteristics and soil moisture. For foliar materials, the remaining stable fraction was smaller in Elaeagnus angustifolia that also showed a slower decay rate than other species. Fine roots (at a depth of 30 cm) degraded faster in all species, with 33–38 % of the initial mass remaining. The decay rates were lowest for Ulmus pumila roots, which were characterized by relatively dense tissue. The greater production and decomposition of nitrogen-rich residue might explain the superior performance of E. angustifolia in improving saline soil productivity. Irrespective of species, the carbon returns through the relatively fast decomposition of fine roots benefit soil fertility, whereas large inputs of slowly decomposing foliar residues represent carbon sequestration in the aboveground litter pool.

Although REDD+ is approaching its 10th anniversary, major impacts in terms of reduced forest loss are hard to document. Conservation practitioners and scholars are therefore increasingly asking why REDD+ has not delivered more tangible results. A recent Comment in Conservation Biology by Fletcher et al. (2016) addresses this question. We agree with Fletcher et al. that REDD+ has been hyped in some circles, which has created unrealistic expectations among policy makers and forest dwellers alike. Yet, we argue that Fletcher et al. put forward an incomplete interpretation of the evolving REDD+ concept and practice and wrongly place the responsibility for lack of progress on the principles of payment for environmental services (PES) and on reliance on market-based instruments (MBIs), in part based on their misunderstanding of the PES concept.Potential answers to the question of why REDD+ has not delivered more tangible results fall into 4 categories: REDD+ has not yet been implemented at the scale needed to make a difference, REDD+ has evolved from the initial PES vision to a modified version of previous and largely ineffective conservation efforts, REDD+ has been blocked by powerful actors interested in maintaining the status quo, and REDD+ is conceptually flawed in its design as a PES and MBI scheme. Fletcher et al. fail to fully appreciate the first 3 problems, overemphasize the presumed flaws in REDD+ as a PES design, and prepare the ground for the rise and fall of the next conservation fad (Redford et al. 2013). We believe that REDD+, although troubled, is not dead.

This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis (VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis (MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was characterised by an external input =12 kg/ha/yr inorganic fertilizer with/without the addition of manure in rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20, 50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows: (1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b) benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services) were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental performance of the scenarios are compared to maize production systems in other developing regions in order to put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and sustainability of agricultural production systems at farm and regional scales, as well as in connecting the management planning level and regional development considerations.

Mangrove organic carbon is primarily stored in soils, which contain more than two-thirds of total mangrove ecosystem carbon stocks. Despite increasing recognition of the critical role of mangrove ecosystems for climate change mitigation, there is limited understanding of soil organic carbon sequestration mechanisms in undisturbed low-latitude mangroves, specifically on organic carbon burial rates and sources. This study assessed soil organic carbon burial rates, sources and stocks across an undisturbed coastal mudflat and mangrove hydrogeomorphological catena (fringe mangrove and interior mangrove) in Bintuni Bay, West Papua Province, Indonesia. 210Pb radionuclide sediment dating, and mixing model of natural stable isotope signatures (δ 13C and δ15N) and C/N ratio were used to estimate organic carbon burial rates and to quantify proportions of allochthonous (i.e., upland terrestrial forest) and autochthonous (i.e., on-site mangrove forest) organic carbon in the top 50 cm of the soil. Burial rates were in the range of 0.21–1.19 Mg C ha−1 yr−1. Compared to the fringe mangroves, organic carbon burial rates in interior mangroves were almost twice as high. Primary productivity of C3 upland forest vegetation and mangroves induced soil organic carbon burial in interior mangroves and this was consistent with the formation of the largest organic carbon stocks (179 ± 82 Mg C ha−1). By contrast, organic carbon stored in the fringe mangrove (68 ± 11 Mg C ha−1) and mudflat (62 ± 10 Mg C ha−1) soils mainly originated from upland forests (allochthonous origin). These findings clearly indicate that carbon sequestered and cycling in mangrove and terrestrial forest ecosystems are closely linked, and at least a part of carbon losses (e.g., erosion) from terrestrial forests is buried in mangrove ecosystems.