Modeling the impacts of policy interventions from REDD+ in Southeast Asia: A case study in Indonesia

Reducing Emissions from Deforestation and Forest Degradation (REDD+) and enhancing “removals of greenhouse gas emissions by forests” in developing countries through positive incentives is regarded as an essential component of the post-2012 climate regime for stabilizing greenhouse gas emissions and an important way of engaging developing countries in global mitigation efforts. We aimed to evaluate the potential effectiveness of REDD+ by integrating it into a land use option framework. One of our goals was to develop scenarios for evaluating the impacts of land use changes on carbon and environmental processes. In addition, we aimed to quantify the potential economic benefits to society of compensated reductions and to identify hotspots for applying REDD+. Three land use change scenarios were examined: (I) business as usual (BAU), (II) economic development, and (III) REDD+. A case study in Indonesia was examined using these land use scenarios and policy interventions, evaluating their effects on carbon emissions, socioeconomics, and environmental features of a spatial system using land use models. Significant emissions and water erosion reductions were predicted to be achieved under the REDD+ scenario, due to reduced deforestation of <6% over the next decade; >0.14 Mt CO₂e reduction was predicted relative to the BAU scenario. Furthermore, the spatial land use model indicated that REDD+ payments of forest carbon credits in the compliance market would play a key role in compensating rural communities and plantation companies for their opportunity cost in ending deforestation. This study provides an example of integrating land use modeling with a scenario analysis framework to evaluate plausible future forecasts and to evaluate the potential impacts of REDD+.     

Orders of magnitude increase in soil erosion associated with land use change from native to cultivated vegetation in a Brazilian savannah environment

The Brazilian savanna (cerrado) is a large and important economic and environmental region that is experiencing significant loss of its natural landscapes due to pressures of food and energy production, which in turn has caused large increases in soil erosion. However the magnitude of the soil erosion increases in this region is not well understood, in part because scientific studies of surface runoff and soil erosion are scarce or nonexistent in the cerrado as well as in other savannahs of the world. To understand the effects of deforestation we assessed natural rainfall‐driven rates of runoff and soil erosion on an undisturbed tropical woodland classified as ‘cerrado sensu stricto denso’ and bare soil. Results were evaluated and quantified in the context of the cover and management factor (C‐factor) of the Universal Soil Loss Equation (USLE). Replicated data on precipitation, runoff, and soil loss on plots (5 × 20 m) under undisturbed cerrado and bare soil were collected for 77 erosive storms that occurred over 3 years (2012 through 2014). C‐factor was computed annually using values of rainfall erosivity and soil loss rate. We found an average runoff coefficient of ~20% for the plots under bare soil and less than 1% under undisturbed cerrado. The mean annual soil losses in the plots under bare soil and cerrado were 12.4 t ha^‐1 yr^‐1 and 0.1 t ha^‐1 yr^‐1, respectively. The erosivity‐weighted C‐factor for the undisturbed cerrado was 0.013. Surface runoff, soil loss and C‐factor were greatest in the summer and fall. Our results suggest that shifts in land use from the native to cultivated vegetation result in orders of magnitude increases in soil loss rates. These results provide benchmark values that will be useful to evaluate past and future land use changes using soil erosion models and have significance for undisturbed savanna regions worldwide. Copyright © 2015 John Wiley & Sons, Ltd.     

Deforestation of water‐repellent soils in Galicia (NW Spain): effects on surface runoff and erosion under simulated rainfall

At three adjacent sites in steeply sloping woodland in Galicia (NW Spain), surface runoff and associated erosion under simulated rainfall (64 mm h^?1) were measured on five occasions between June 1998 and July 1999. Two of the three sites had recently been deforested and topsoil added, and one of these two had been sown with grass, which was germinating at the onset of the study. Deforestation greatly increased runoff and erosion rates, and the recovery of plant cover reduced erosion. All three soils were very hydrophobic due to high levels of poorly humified organic matter, which led to higher runoff rates than expected, especially during dry periods. However, great structural stability prevented there being a significant correlation between runoff rate and soil erosion. Copyright © 2003 John Wiley & Sons, Ltd.     

Temporal dynamics and spatial scales: Modeling deforestation in the southern Yucatán peninsular region

Two spatially explicit econometric land use change models are presented, focusing on tropical deforestation caused by agricultural expansion in the southern Yucatán peninsula, Mexico. The two models developed are both based on conceptually similar theoretical models of farmer behavior. However, there are different empirical specifications of this theoretical model according to the scale of the analysis as well as the availability of temporal data on the observation of deforestation. For both models, the unit of observation for the dependent variable of deforestation is the TM pixel from satellite data. However, the socio-economic explanatory variables are derived from different sources. The first econometric model links the satellite data for the entire study region with aggregate census data at the village level. This model is estimated using a discrete choice logit model over a single time period. The second econometric model uses individual household survey data for a small random sample of the region, linked to satellite data for the plots of each household over multiple time periods. This model is estimated using a dynamic hazard model that estimates the risk of a specific pixel converting from forest to agricultural use. Both estimated models are used to predict deforestation and the results of the two modeling approaches are compared.     

Utility of Landsat 7 satellite data for continued monitoring of forest cover change in protected areas in Southeast Asia

Satellite instruments, particularly the Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) series of sensors, are important tools in the interdisciplinary study of tropical forests that are increasingly integrated into studies that monitor changes in vegetation cover within tropical forests and tropical protected areas, and also applied with other types of data to investigate the drivers of land cover change. However, further advances in the use of Landsat to study and monitor tropical forests and protected areas are threatened by the scan line corrector failure on the ETM+ sensor, as well as uncertainty about the continuity of the Landsat mission. Given these problems, this paper illustrates how ETM+ data were used in an interdisciplinary study that effectively monitored forest cover change in Gunung Palung National Park in West Kalimantan, Indonesian Borneo. Following 31 May 2003, when the ETM+ sensor's scan line corrector failed, we analysed how this failure impedes our ability to perform a similar study from this date onwards. This analysis uses six simulated post-scan line corrector failure (SLC-off) images and reveals that data gaps caused by SLC-off introduce maximum errors of 1.47 per cent and 4.04 per cent in estimates of forest cover and rates of forest loss, respectively. The analysis also demonstrates how SLC-off has transformed ETM+ data from a complete inventory dataset to a statistical sample with variable sample fraction, and notes how this data loss will confound the use of Landsat data to model land cover change in a spatially explicit manner. We discuss potential limited uses of SLC-off data and suggest alternative sensors that may provide essential remotely sensed data for monitoring tropical forests in Southeast Asia.     

The Expansion of Intensive Beef Farming to the Brazilian Amazon

Systems of intensive animal farming, such as the confinement of beef cattle, are widespread in the developed world. Such practices have been under scrutiny since the 1960s for animal welfare and pollution issues. Here, we document the expansion of intensive beef farming to the Brazilian Amazon in order to assess socio-environmental implications. Using a combination of data mining and field surveys, we developed a georeferenced dataset of 201 cattle confinements in the states of Mato Grosso (Cerrado and Amazon biomes), Pará and Rondônia (Amazon biome), collected in 2017. In Mato Grosso, the country’s agribusiness powerhouse, confinements are well established and account for ˜20% of the cattle slaughter. But rapid expansion in Pará and Rondônia remains largely unnoticed due to the absence of data since 2012. We used the new dataset to map cattle confinements across space and time. For the first time, (1) we document an expansion to the Amazon biome; (2) we also show that confinements are associated with substantially higher productivity rates, though intensified pasture-based systems can reach comparable yields; (3) that confinements have crop production levels 2-3 times higher than comparable properties, both in- and out-of-farm; and (4) that confinements tend to slow down on-property deforestation when compared to fattening ranches in the Amazon biome, although off-property effects could be substantial and need further study. Overall, the implications of intensive beef farming for animal welfare and local waste generation in Brazil require attention as pressure to avoid deforestation continues to stimulate the practice.     

The implications of ignoring smallholder agriculture in climate-financed forestry projects: empirical evidence from two REDD+ pilot projects

ABSTRACT

Changes in agricultural practices can play a pivotal role in climate change mitigation by reducing the need for land use change as one of the biggest sources of GHG emissions, and by enabling carbon sequestration in farmers’ fields. Expansion of smallholder and commercial agriculture is often one of the main driving forces behind deforestation and forest degradation. However, mitigation programmes such as REDD+ are geared towards conservation efforts in the forestry sector without prominently taking into account smallholder agricultural interests in project design and implementation. REDD+ projects often build on existing re- and afforestation projects without major changes in their principles, interests and assumptions. Informed by case study research and interviews with national and international experts, we illustrate with examples from Ethiopia and Indonesia how REDD+ projects are implemented, how they fail to adequately incorporate the demands of smallholder farmers and how this leads to a loss of livelihoods and diminishing interest in participating in REDD+ by local farming communities. The study shows how the conservation-based benefits and insecure funding base in REDD+ projects do not compensate for the contraction in livelihoods from agriculture. Combined with exclusive benefit-sharing mechanisms, this results in an increased pressure on forest resources, diverging from the principal objective of REDD+. We note a gap between the REDD+ narratives at international level (i.e. coupling development with a climate agenda) and the livelihood interests of farming communities on the ground. We argue that without incorporating agricultural interests and a review of financial incentives in the design of future climate finance mechanisms, objectives of both livelihood improvements and GHG emission reductions will be missed.

Key policy insights

• REDD+ is positioned as a promising tool to meet climate, conservation and development targets. However, these expectations are not being met in practice as the interests of smallholder farmers are poorly addressed.

• REDD+ policy developers and implementers need more focus on understanding the interests and dynamics of smallholder agriculturalists to enable inclusive, realistic and long-lasting projects.

• For REDD+ to succeed, funders need to consider how to better ensure long-term livelihood security for farming communities.

     

Land Cover Changes on Ambergris Caye,Belize: A Case Study of Unregulated Tourism Development

Measuring land-use, land-cover change in biodiverse, tropical countries is critical for conservation management and sustainable planning because it provides quantifiable data regarding broad environmental changes. This project uses Landsat satellite imagery to document vegetation cover change on Ambergris Caye, Belize, from 2000 to 2017. The close proximity of the Belize Barrier Reef Reserve System has made Ambergris Caye the most popular tourist destination and economic hub in Belize. As a result, the region has undergone intense commercial and residential development coupled with rapid population growth over the past two decades. Understanding general trends in landscape dynamics is critical for the natural resource–based tourism industry of Belize to continue to thrive. Unsupervised classification methods and a per pixel postclassification comparison were used with Landsat imagery to estimate loss in vegetation cover and increases in urban and barren land. The results indicate a 10.85 percent decrease in vegetation and a 39 percent increase in urban and barren land during the seventeen-year study period with an annual forest loss rate of 0.67 percent per year using a compound interest rate formula. The results of this analysis represent a baseline study of vegetation change on Ambergris Caye to inform management and conservation efforts.     

Population Pressure,Deforestation, and Land Degradation: A Case Study from the Dominican Republic

Population pressure, deforestation, and land degradation are major ecological concerns in developing countries. This research investigates causal linkages among interrelated physical and social processes in a case study conducted within the Plan Sierra resource management region of the Cordillera Central, Dominican Republic. Results of bivariate regression analysis, based on a sample of 450 traditional hillslope farms, support a linear relationship between population pressure and deforestation at two spatial scales. However, the strength of the relationship between population pressure and forest cover change decreases over a twenty-year time frame. Results also confirm a positive relationship between deforestation and land degradation. This case study contributes to an understanding of the precise nature of these relationships at sub-national scales of analysis.     

Impact of land-use changes on snow in a forested region with heavy snowfall in Hokkaido,Japan

Abstract

We simulated snow processes in a forested region with heavy snowfall in Japan, and evaluated both the regional-scale snow distribution and the potential impact of land-use changes on the snow cover and water balances over the entire domain. SnowModel reproduced the snow processes at open and forested sites, which were confirmed by snow water equivalent (SWE) measurements at two intensive observation sites and snow depth measurements at the Automated Meteorological Data Acquisition System sites. SnowModel also reproduced the observed snow distribution (from the MODIS snow cover data) over the simulation domain during thaw. The observed SWE was less at the forested site than at the open site. The SnowModel simulations showed that this difference was caused mainly by differences in sublimation. The type of land use changed the maximum SWE, onset and duration of snowmelt, and the daily snowmelt rate due to canopy snow interception.

Citation Suzuki, K., Kodama, Y., Nakai, T., Liston, G. E., Yamamoto, K., Ohata, T., Ishii, Y., Sumida, A., Hara, T. & Ohta, T. (2011) Impact of land-use changes in a forested region with heavy snowfall in Hokkaido, Japan. Hydrol. Sci. J. 56(3), 443–467.