Palm oil, land rights and ecosystem services in Gbarpolu County, Liberia

As part of the rebuilding efforts following the long civil war, the Liberian government has renegotiated long-term contracts with international investors to exploit natural resources. Substantial areas of land have been handed out in large-scale concessions across Liberia during the last five years. While this may promote economic growth at the national level, such concessions are likely to have major environmental, social and economic impacts on local communities, who may not have been consulted on the proposed developments. This report examines the potential socio-economic and environmental impacts of a proposed large-scale oil palm concession in Bopolu District, Gbarpolu County in Liberia. The research provided an in-depth mapping of current resource use, livelihoods and ecosystems services, in addition to analysis of community consultation and perceptions of the potential impacts of the proposed development. This case study of a palm oil concession in Liberia highlights wider policy considerations regarding large-scale land acquisitions in the global South: • Formal mechanisms may be needed to ensure the process of Free, Prior, Informed Consent takes place effectively with affected communities and community land rights are safeguarded. • Rigorous Environmental and Social Impact Assessments need to be conducted before operations start. Accurate mapping of customary land rights, community resources and cultural sites, livelihoods, land use, biodiversity and ecosystems services is a critical tool in this process. • Greater clarity and awareness-raising of land tenure laws and policies is needed at all levels. Good governance and capacity-building of key institutions would help to ensure effective implementation of relevant laws and policies. • Efforts are needed to improve basic services and infrastructure in rural communities and invest in food crop cultivation in order to enhance food security and poverty alleviation. Increasing access to inputs, equipment, training and advice is especially important if male and female farmers are no longer able to practice shifting cultivation due to the reduction/ loss of customary land and the need to farm more intensively on smaller areas of land.

Quantifying uncertainty in remotely sensed land cover maps

Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

PERSiST: a flexible rainfall-runoff modelling toolkit for use with the INCA family of models

Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis

Cashew cultivation, access to land and food security in Brong-Ahafo Region, Ghana: Preventing the intergenerational transmission of poverty

This research aimed to investigate the implications of changing agricultural land use from food production towards increased cashew cultivation for food security and poverty alleviation in Jaman North District, Brong-Ahafo Region of Ghana. Based on qualitative, participatory research with a total of 60 participants, the research found that increased cashew production had led to improvements in living standards for many farmers and their children over recent years. Global demand for cashew is projected to continue to grow rapidly in the immediate future and cashew-growing areas of Ghana are well placed to respond to this demand. Cashew farmers however were subject to price fluctuations in the value of Raw Cashew Nuts (RCN) due to unequal power relations with intermediaries and export buyer companies and global markets, in addition to other vulnerabilities that constrained the quality and quantity of cashew and food crops they could produce. The expansion of cashew plantations was leading to pressure on the remaining family lands available for food crop production, which community members feared could potentially compromise the food security of rural communities and the land inheritance of future generations.

Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data

The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

Struggles over family land? Tree crops, land and labour in Ghana's Brong-Ahafo region

Agricultural land use in much of Brong-Ahafo region, Ghana has been shifting from the production of food crops towards increased cashew nut cultivation in recent years. This article explores everyday, less visible, gendered and generational struggles over family farms in West Africa, based on qualitative, participatory research in a rural community that is becoming increasingly integrated into the global capitalist system. As a tree crop, cashew was regarded as an individual man's property to be passed on to his wife and children rather than to extended family members, which differed from the communal land tenure arrangements governing food crop cultivation. The tendency for land, cash crops and income to be controlled by men, despite women's and young people's significant labour contributions to family farms, and for women to rely on food crop production for their main source of income and for household food security, means that women and girls are more likely to lose out when cashew plantations are expanded to the detriment of land for food crops. Intergenerational tensions emerged when young people felt that their parents and elders were neglecting their views and concerns. The research provides important insights into gendered and generational power relations regarding land access, property rights and intra-household decision-making processes. Greater dialogue between genders and generations may help to tackle unequal power relations and lead to shared decision-making processes that build the resilience of rural communities.

Bayesian analysis of uncertainty in the GlobCover 2009 land cover product at climate model grid scale

Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those required for climate models, such spatial modelling can be difficult. Also, computer models often require land cover proportions at sites larger than the original map scale as inputs, and it is the uncertainty in these proportions that this article discusses. This paper describes a Monte Carlo sampling scheme that generates realisations of land cover proportions from the posterior distribution as implied by a Bayesian analysis that combines spatial information in the land cover map and its associated confusion matrix. The technique is computationally simple and has been applied previously to the Land Cover Map 2000 for the region of England and Wales. This article demonstrates the ability of the technique to scale up to large (global) satellite derived land cover maps and reports its application to the GlobCover 2009 data product. The results show that, in general, the GlobCover data possesses only small biases, with the largest belonging to non–vegetated surfaces. In vegetated surfaces, the most prominent area of uncertainty is Southern Africa, which represents a complex heterogeneous landscape. It is also clear from this study that greater resources need to be devoted to the construction of comprehensive confusion matrices.