Current Ethiopian policies and laws recognize the importance of equitable benefit-sharing mechanisms for natural resource management. The question of ‘what is fair’ is often unclear in practice. We pursue this question in the context of benefit sharing for Reducing Emissions from Deforestation and Forest Degradation (REDD+) in Ethiopia. We present findings from interviews conducted in 2017 with 33 national REDD+ actors, and a review of national policies and laws until 2020 to understand Ethiopia’s policy and legal framework, and vision for a REDD+ benefit-sharing mechanism. Our findings show that Ethiopia is progressing in developing a benefit-sharing mechanism (BSM) for REDD+. Government policies on benefit sharing are pro-poor with an emphasis on legal rights. Among the various concepts of fairness, more stakeholders agreed that benefits should be shared according to efforts made to reduce deforestation and forest degradation rather than being based on poverty or legal rights. Left unattended, we believe this divergence of opinion on ‘what is fair’ opens the potential for questions regarding the legitimacy of the REDD+ BSM among stakeholders in general and can pose practical implementation challenges. We suggest that establishing open dialogue, learning mechanisms and inclusive processes can lead to regulations, policies and procedures that clarify and harmonize the different views on fairness over time.
Tag: deforestation
Multidimensional tropical forest recovery
Tropical forests disappear rapidly because of deforestation, yet they have the potential to regrow naturally on abandoned lands. We analyze how 12 forest attributes recover during secondary succession and how their recovery is interrelated using 77 sites across the tropics. Tropical forests are highly resilient to low-intensity land use; after 20 years, forest attributes attain 78% (33 to 100%) of their old-growth values. Recovery to 90% of old-growth values is fastest for soil (<1 decade) and plant functioning (12 decades). Network analysis shows three independent clusters of attribute recovery, related to structure, species diversity, and species composition. Secondary forests should be embraced as a low-cost, natural solution for ecosystem restoration, climate change mitigation, and biodiversity conservation. © 2021 American Association for the Advancement of Science. All rights reserved.
Land Cover and Land Use Change Decreases Net Ecosystem Production in Tropical Peatlands of West Kalimantan, Indonesia
Deforested and converted tropical peat swamp forests are susceptible to fires and are a major source of greenhouse gas (GHG) emissions. However, information on the influence of land-use change (LUC) on the carbon dynamics in these disturbed peat forests is limited. This study aimed to quantify soil respiration (heterotrophic and autotrophic), net primary production (NPP), and net ecosystem production (NEP) in peat swamp forests, partially logged forests, early seral grasslands (deforested peat), and smallholder-oil palm estates (converted peat). Peat swamp forests (PSF) showed similar soil respiration with logged forests (LPSF) and oil palm (OP) estates (37.7 Mg CO2 ha−1 yr−1, 40.7 Mg CO2 ha−1 yr−1, and 38.7 Mg CO2 ha−1 yr−1, respectively), but higher than early seral (ES) grassland sites (30.7 Mg CO2 ha−1 yr−1). NPP of intact peat forests (13.2 Mg C ha−1 yr−1) was significantly greater than LPSF (11.1 Mg C ha−1 yr−1), ES (10.8 Mg C ha−1 yr−1), and OP (3.7 Mg C ha−1 yr−1). Peat swamp forests and seral grasslands were net carbon sinks (10.8 Mg CO2 ha−1 yr−1 and 9.1 CO2 ha−1 yr−1, respectively). In contrast, logged forests and oil palm estates were net carbon sources; they had negative mean Net Ecosystem Production (NEP) values (−0.1 Mg CO2 ha−1 yr−1 and −25.1 Mg CO2 ha−1 yr−1, respectively). The shift from carbon sinks to sources associated with land-use change was principally due to a decreased Net Primary Production (NPP) rather than increased soil respiration. Conservation of the remaining peat swamp forests and rehabilitation of deforested peatlands are crucial in GHG emission reduction programs
Advances in Amazonian Peatland Discrimination With Multi-Temporal PALSAR Refines Estimates of Peatland Distribution, C Stocks and Deforestation
There is a data gap in our current knowledge of the geospatial distribution, type and extent of C rich peatlands across the globe. The Pastaza Marañón Foreland Basin (PMFB), within the Peruvian Amazon, is known to store large amounts of peat, but the remoteness of the region makes field data collection and mapping the distribution of peatland ecotypes challenging. Here we review methods for developing high accuracy peatland maps for the PMFB using a combination of multi-temporal synthetic aperture radar (SAR) and optical remote sensing in a machine learning classifier. The new map produced has 95% overall accuracy with low errors of commission (1–6%) and errors of omission (0–15%) for individual peatland classes. We attribute this improvement in map accuracy over previous maps of the region to the inclusion of high and low water season SAR images which provides information about seasonal hydrological dynamics. The new multi-date map showed an increase in area of more than 200% for pole forest peatland (6% error) compared to previous maps, which had high errors for that ecotype (20–36%). Likewise, estimates of C stocks were 35% greater than previously reported (3.238 Pg in Draper et al. (2014) to 4.360 Pg in our study). Most of the increase is attributed to pole forest peatland which contributed 58% (2.551 Pg) of total C, followed by palm swamp (34%, 1.476 Pg). In an assessment of deforestation from 2010 to 2018 in the PMFB, we found 89% of the deforestation was in seasonally flooded forest and 43% of deforestation was occurring within 1 km of a river or road. Peatlands were found the least affected by deforestation and there was not a noticeable trend over time. With development of improved transportation routes and population pressures, future land use change is likely to put South American tropical peatlands at risk, making continued monitoring a necessity. Accurate mapping of peatland ecotypes with high resolution (<30 m) sensors linked with field data are needed to reduce uncertainties in estimates of the distribution of C stocks, and to aid in deforestation monitoring.
Allometric equations for estimating on-farm fuel production of Gliricidia sepium (Gliricidia) shrubs and Cajanus cajan (pigeon pea) plants in semi-arid Tanzania
Background: Fuelwood is considered to be the primary source of cooking energy in Tanzania and, due to ongoing deforestation, access to fuelwood is becoming more cumbersome. On-farm agroforestry systems can reduce dependency on off-farm fuel; however, the output of on-farm produced fuel is typically uncertain as production potentials are often not known. In this paper, we have developed allometric equations to model the above-ground woody biomass (AGWB) production from intercropped Gliricidia sepium (Jacq.) Kunth ex Walp (Gliricidia) shrubs and Cajanus cajan (L.) Millsp. (pigeon pea) plants. Methods: We used a destructive sampling approach, for measuring the dendrometric characteristics, such as the root collar diameter at a 20 cm stem height (RCD20) and the stem height to estimate the AGWB production. The models are based on 112 Gliricidia and 80 pigeon pea observations from annually pruned plants. Seven allometric equations were fitted to derive the best-fit models for the AGWB production. Results: We found that using a natural log-transformed linear model with RCD20 as a single predictor variable provides the highest explanatory value to estimate the AGWB production (Gliricidia: R2 = 95.7%, pigeon pea: R2 = 91.4%) while meeting Ordinary Least Square (OLS) estimator requirements. Adding stem height as an additional variable to predict the AGWB production does not improve model accuracy enough to justify the extra work for including it. Conclusions: While on-farm pigeon pea plants produced a stable amount of woody biomass per annum, annual fuelwood production from Gliricidia shrubs increased over the years. Compared to the annual fuelwood consumption data from the literature, our results show that on-farm produced fuelwood can substantially offset the demand for off-farm fuel, potentially resulting in household fuelwood autarky. © 2021, The Author(s).
Transformational change to reduce deforestation and climate change impacts – A review of definitions, concepts and drivers in scientific and grey literature
Addressing enormous challenges from environmental and climate change requires a transformational change in how we use land and natural resources. This study, jointly undertaken by FAO and CIFOR, investigates how transformational change is understood in the scientific literature. We screened 111 scientific articles, published between 2000 and 2018 on transformational change in health, business and land use, natural resources, and climate change. TC is well articulated in the health, education and business management literature, but less so – only 22 papers – in agriculture, forestry, land use and climate change. Definitions of transformational change converge in that it represents a movement away from the current status; that the transformations should focus on root causes to be sustained; and of a key role of knowledge as driver and indicator of change. Critical elements of TC comprise collective, interdisciplinary and transdisciplinary learning and reflection; managing risks; engaging in on-linear thinking; participation, ownership, and finance. Transformational change is influenced by four groups of drivers: processes; resources; norms; and legitimacy. There are trade-offs between the three dimensions of transformational change: scale, speed (fast) and depth (deep). Indicators of transformational change are complex and difficult to measure. Further reflections and scientific analysis are needed on drivers of transformational change at the intersection between land use and climate change.
FTA Highlight No.11 – REDD+: Combating Climate Change with Forest Science
The climate change battle has many fronts; protecting the world’s remaining forests is a major one. Land-use change, including deforestation, contributes 10–12% of global emissions (IPCC 2019), and the REDD+ framework (reducing emissions from deforestation and forest degradation) has been seen as a way to promote both climate and sustainable development benefits. Now enshrined in the Paris Agreement, the central offer of REDD+ consists of results-based payments to forest-rich countries for protecting forests and avoiding carbon emissions. The challenges associated with this approach are large, and a diversity of actors is needed to make it a success, including researchers. Could science contribute to make REDD+ more efficient, more effective and more equitable? Scientists with CIFOR’s Global Comparative Study on REDD+ (GCS REDD+) have been analyzing REDD+ for the past 12 years. GCS REDD+ is the largest global research program of its kind and a major component of the CGIAR Research Program on Forests, Trees and Agroforestry (FTA). With dozens of national and subnational REDD+ initiatives and several hundred local projects underway, GCS REDD+ has looked at the range of approaches, analyzed conditions — from policy to land rights to forest monitoring capacity — and produced a bedrock of evidence and analysis across 22 countries. This ensures that policymakers and practitioner communities have the evidence they need to design and implement REDD+ with effective, cost-efficient and equitable outcomes.
Turning the Tide on Deforestation: Flagship initiatives of the Collaborative Partnership on Forests
This brochure presents flagship initiatives and programmes designed by members of the Collaborative Partnership on Forests to contribute to the common goal formulated by UN Secretary-General António Guterres of “turning the tide on deforestation”. The brochure reaffirms the call for action by leaders to accelerate efforts at UNFCCC COP26 to halt deforestation.
Effects of household-level attributes and agricultural land-use on deforestation patterns along a forest transition gradient in the Miombo landscapes, Zambia
Dry forests in tropical and subtropical areas continue to experience high deforestation rates that affect households’ dependence on forest resources. Little remains understood about the relationship between household factors and deforestation patterns in Zambia. We integrate remotely sensed data with surveys of 1123 households collected in the Miombo areas between 2017 and 2019 to better understand the effects of household attributes on regional deforestation patterns along a forest transition gradient. We found, in early-to-mid-transition, deforestation patterns systematically decreased further from settlements (homesteads), but this was reversed in regions with advanced forest transition. The socio-demographic attributes, land and non-land-based attributes, and location factors differently affected deforestation across provinces. Although agricultural land-use was significantly associated with deforestation, no distinct patterns emerged across distance categories or along the forest transition. Furthermore, increases in non-farm income reduced the likelihood of high deforestation, but the impact was not always significant across provinces. Our results indicate that economic effects of distance in Miombo areas complement the forest transition, but are not exclusively related to crop productivity. We assume that different aspects of livelihoods can explain the deforestation patterns in the Miombo areas. Thus, forest management should be regional-specific, such as improving access to financial incentives in North-Western, and reforestation and agroforestry in Copperbelt and the Eastern Province.
Coronavirus, macroeconomy, and forests: What likely impacts?
Much uncertainty persists about how the coronavirus (COVID-19) and its derived crisis effects will impact both the economy and forests. Here we conceptualize a recursive model where an initial COVID-19 supply-side shock hits first the Global North that, mediated by country-specific epidemic management strategies and other (fiscal, monetary, trade) policy responses feeds through to financial markets and the real economy. Analytically we distinguish two stylized scenarios: an optimistic V-shaped recovery where effective policy responses render most economic damages transitory, versus a pessimistic pathway of economic depression, where short-run pandemic impacts are dwarfed by the subsequent economic breakdown. Economic impacts are transitioned from the global North to the South through trade, tourism, remittances and investment/capital flows. As for impacts on tropical forests, we compare the effects of past economic crises to early indicators for incipient trends. We find national income and commodity price effects to be torn between three forces: a contractive-inflationary supply-side shock, deflationary pandemic demand-side effects, and expansive-inflationary monetary and fiscal policy responses. We discuss how global forest outcomes will depend on how these macroeconomic battles are resolved, but also on geographical differences in deforestation dynamics. Reviewing recent fire and deforestation alerts data, as well as annual tree-cover loss data, we find that deforestation-curbing and -enhancing factors so far just about neutralized each other. Yet, country impacts vary greatly. Changing macroeconomic scenarios, such as fading out of huge economic stimulus packages, could change the picture significantly, in line with what our model predicts.