The recent interest in multi-functional agricultural landscapes has not been matched with formal assessment of the roles that trees play across the spectrum of ecosystem services (ESs) provided in Sub-Saharan Africa (SSA). A structured literature review (1995–2014) assessed 350 journal articles about provision of one or more ESs by trees on farms and in agricultural landscapes in SSA. This revealed information on 15 ESs from studies in 23 countries covering arid (1% of studies), semi-arid (49%), sub-humid (26%) and humid (24%) agro-ecological zones. The majority of the studies reported provisioning (39%) and supporting (35%) followed by regulating (26%) ESs while studies on cultural services were scarce. Beneficial impacts of trees were dominating (58%), in particular in semi-arid zones where they were associated with enhancing water and nutrient cycling. A decline in some ESs was reported in 15% of the studies, while 28% found no effect of trees. Although the effects of trees were mainly positive, a decline in crop production was noted as a key trade-off against the provisions of ESs, such as modification of microclimate. This highlights the need to manage trade-offs among impacts of trees on ES provision to reduce competition and increase complementarity between trees and crops. © 2016 Informa UK Limited, trading as Taylor & Francis Group.
Tag: agricultural land
Through their eyes: Indigenous film making in western China
Interactive Session on Reciprocal Learning and Knowledge Exchange
Diversification and intensification of agricultural adaptation from global to local scales
Biodiversity Monitoring for Agricultural Landscapes. A protocol using biodiversity metrics to monitor agricultural sustainability under Aichi Target 7
Aichi Target 7 requires that by 2020 agricultural areas, forests and aquatic resources are managed sustainably ensuring conservation of biodiversity. To date, for agricultural land only subjective indicators, such as the area under “sustainable management”, have been proposed and there is an urgent need to develop a framework of objective metrics. This framework should provide a robust system for monitoring agricultural sustainability and its contribution to biodiversity conservation at national scales for reporting to the CBD.
Trees now part of a global crop modeling framework
Until now global models of crop production have ignored trees, despite significant tree cover on much of the world’s agricultural land. This is now changing thanks to a new tree-crop modeling initiative. ICRAF and partners in the ACIAR-funded project ‘Trees-for-Food Security’ have just published a landmark paper reviewing the modeling of tree-crop interactions at field scale (Luedeling et al 2016).
Grazing lands in Sub-Saharan Africa and their potential role in climate change mitigation: What we do and don’t know
In 2014, the USAID project ‘Grazing lands, livestock and climate resilient mitigation in Sub-Saharan Africa’ held twoworkshops, hosted by the Colorado State University, which brought together experts from around the world. Two reportsresulted from these workshops, one an assessment of the state of the science, and the other an inventory of related activitiesin the region to date.. In this short communication we summarize the main points of the first report – The state of thescience (Milne and Williams, 2015). A second report is in preparation.
Relating plant diversity to biomass and soil erosion in a cultivated landscape of the eastern seaboard of Thailand
Plant diversity can affect ecological processes through effects on biomass and soil condition. A study was carried out in an agricultural watershed of Thailand to document plant species richness of different agricultural land uses and to assess its relationship with biomass and soil erosion. A nested sampling design of 20 x 20 m, 10 x 10 m, 5 x 5 m and 1 x 1 m quadrats was employed to study species richness of three categories of plants: herbaceous plants, shrubs and trees. Interviews were conducted with farmers who owned the cultivated fields where sampling plots were located. Plant diversity was assessed by computing Shannon index, Simpson index, and Species richness. Species utility index, which is the percentage of species identified as useful, was also estimated for each land use. Biomass was estimated using methodology recommended by FAO and soil erosionwas estimated using the universal soil loss equation (USLE). From among the different land use types, mixed orchard ranked first in terms of plant diversity while paddy ranked last. Land uses with monocropping of shrubs, such as cassava, pineapple and sugarcane had lower plant diversity than land uses with monocropping of trees, such as coconut and para rubber. Monocropping of eucalyptus was an exception. Rotations of monocrops, namely pineapplecassava and sugarcanecassava, or intercropping, namely coconutcassava, also had a higher plant diversity as compared to monocropping of shrubs. The highest species utility index of 61 was found in orchards, the lowest of 9 was found in Eucalyptus plantations. Plant diversity was found to have a significant positive correlation with biomass and a negative, though non-significant, correlation with soil erosion.
Updating legacy soil maps for climate resilient agriculture: A case of kilombero valley, Tanzania
Since the first documented soil survey in Tanzania by Milne (J Ecol 35:192-265, 1936), a number of other soil inventory exercises at different scales have been made. The main challenge has been the fragmented nature of the often outdated detailed soil maps and small-scale less-informative country-wide soil maps. Recent advances in information and computational technology have created vast potential to collect, map, harness, communicate and update soil information. These advances present favorable conditions to support the already popular shift from qualitative (conventional) to quantitative (digital) soil mapping (DSM). In this study, two decision tree machine learning algorithms, J48 and Random Forest (RF), were applied to digitally predict k-means numerically classified soil clusters to update a soil map produced in 1959. Predictors were derived from 1 arc SRTM digital elevation data and a 5 m RapidEye satellite image. J48 and RF predicted the soil units of the legacy maps with greater detail. However, RF showed superiority for predicting clusters J48 could not predict and for showing higher pixel contiguity. No significant difference (P = 0.05) was observed between the soil properties of the predicted soil clusters and the actual field validation points. Young soils (Entisols and Inceptisols) were found to occupy about 56 % of the study site’s 30,000 ha followed by Alfisols, Mollisols and Vertisols at 31, 9 and 4 %, respectively. This study demonstrates the usefulness of DSM techniques to update conventionally prepared legacy maps to offer soil information at improved detail to agricultural land use planners and decision makers of Tanzania to make evidence-based decisions for climate-resilient agriculture and other land uses. © Springer International Publishing AG 2016.
Greenhouse gas fluxes from agricultural soils of Kenya and Tanzania
Knowledge of greenhouse gas (GHG) fluxes in soils is a prerequisite to constrain national, continental, and global GHG budgets. However, data characterizing fluxes from agricultural soils of Africa are markedly limited. We measured carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) fluxes at 10 farmer-managed sites of six crop types for 1 year in Kenya and Tanzania using static chambers and gas chromatography. Cumulative emissions ranged between 3.5–15.9 Mg CO2-C ha−1 yr−1, 0.4–3.9 kg N2O-N ha−1 yr−1, and −1.2–10.1 kg CH4-C ha−1 yr−1, depending on crop type, environmental conditions, and management. Manure inputs increased CO2 (p = 0.03), but not N2O or CH4, emissions. Soil cultivation had no discernable effect on emissions of any of the three gases. Fluxes of CO2 and N2O were 54–208% greater (p < 0.05) during the wet versus the dry seasons for some, but not all, crop types. The heterogeneity and seasonality of fluxes suggest that the available data describing soil fluxes in Africa, based on measurements of limited duration of only a few crop types and agroecological zones, are inadequate to use as a basis for estimating the impact of agricultural soils on GHG budgets. A targeted effort to understand the magnitude and mechanisms underlying African agricultural soil fluxes is necessary to accurately estimate the influence of this source on the global climate system and for determining mitigation strategies.