West Africa constitutes a hotspot region for both land use change and climate change. Land use change, and high climate variability in this region negatively affect tree growth dynamics, ecosystem functioning and services. In the present study, we assessed the impacts of climate variability on tree growth of Detarium microcarpum Guill. & Perr. and Tamarindus indica L., two Fabaceae woody species with high socio-economic significance in West Africa. In total, we collected 18 stem discs from dead trees of the two species in the South-Sudanian phytogeographic zone in Burkina Faso. The studied species showed well-defined growth ring-boundaries demarcated by marginal parenchyma bands. Cross-dating was successful within disc and within species, and enabled the construction of statistically robust tree-ring index chronologies. The chronologies spanned 45 years (1974 − 2019) and 30 years (1990 − 2019) for D. microcarpum and T. indica, respectively. We found a significant variation in tree growth rates (p-value < 0.05) between D. microcarpum (1.711 ± 0.491 mm year−1) and T. indica (2.613 ± 0.473 mm year−1). Pearson correlation analyses showed that the standard ring-width index for both species positively correlated with total annual precipitation amounts (p-value < 0.05) and major seasonal precipitation (p-value = 0.05). However, no significant correlation was found between ring-width index and temperature related variables. These findings support that precipitation controls tree growth of D. microcarpum and T. indica in the semi-arid savannas of West Africa. Consequently, a decrease in mean annual rainfall in West African region may negatively affect tree growth rate and stand dynamics of the studied species.
Tag: semiarid zones
Seasonal rainfall patterns affect rainfed maize production more than management of soil moisture and different plant densities on sandy soils of semi-arid regions
In semi-arid regions, rainfed maize production is constrained by erratic rainfall and water loss through percolation, especially on sandy soils. This study evaluated the effects of sub-surface water retention technology (SWRT) and varying plant densities on maize performance over four cropping seasons in Mutare, Zimbabwe. SWRT increased grain yield by 21% and biomass by 13%, though seasonal rainfall variation had a greater impact. Rainwater use efficiency (RWUE) improved with higher plant density, particularly in dry years. These findings highlight the need for integrated soil moisture management and optimized planting densities, alongside investments in water harvesting and irrigation infrastructure, to stabilize and enhance maize yields in semi-arid smallholder systems.
Development of an integrated assessment framework for agroforestry technologies: assessing sustainability, barriers, and impacts in the semi-arid region of Dodoma, Tanzania
This study examines agroforestry as a solution to land degradation in Tanzania, highlighting both its benefits for food production and the challenges hindering widespread adoption. Using an integrated assessment framework that combines MESMIS (a sustainability assessment tool) and ScalA (a scaling-up evaluation method), researchers assess the sustainability and barriers to agroforestry implementation in semi-arid regions. The study focuses on three key objectives: identifying agroforestry technologies adopted by smallholder farmers, evaluating farmers’ perceptions of sustainability across environmental, economic, and social dimensions, and pinpointing constraints to broader adoption. Findings indicate that farmers view four agroforestry techniques as the most sustainable: (i) tied ridge + tree intercropping, (ii) contour planting + tree intercropping, (iii) Chololo pits + tree intercropping, and (iv) tree intercropping alone. Despite positive perceptions, adoption is influenced by climate conditions, socio-economic factors, and institutional support. The study underscores that favorable perceptions alone do not guarantee widespread adoption, emphasizing the need to consider contextual influences. Researchers advocate for further testing and application of this framework in similar settings to provide holistic insights into agroecosystem sustainability.
An exploratory survey of long horn beetle damage on the dryland flagship tree species Boswellia papyrifera (Del.) Hochst
Challenges to the sustainable use of water resources in the Ili River basin of Central Asia
Water is a scarce resource in Central Asia, and many catchments span international boundaries, among them that of the Ili River, which is shared by China and Kazakhstan. Since 1970, the natural hydrological regime of the Ili River, both absolute flow rates and cycles, has changed due to construction of reservoirs such as that at Kapchagai, as well as natural climatic cycles and the growth of water consumption in the basin. Using data from Kazhydromet, we calculated that flow rates below Kapchagai dam averaged 468 m3/sec before construction of the dam, 366 m3/sec while the reservoir was being filled, and 489 m3/sec between 1988 and 2013. The dam has profoundly altered the annual cycle of flows in the river, with reductions in the summer and increases in the winter, when water is released to produce hydropower. The effects of these changes are being heightened by China’s increasing diversion of the river’s water. The sustainable use of decreasing water resources to conserve the biodiversity of the Ili-Balkhash basin’s ecosystems mandates a solution to the water allocation challenge between China and Kazakhstan. This will require a basin-wide approach that includes modernization of water distribution systems and careful consideration to relative priority needs for food, hydropower, and communal uses in both countries.
Soil-water and root dynamics under hedgerow intercropping in semiarid Kenya
Competition for growth resources between woody and crop species is said to be the main reason for failure of hedgerow intercropping (alleycropping) in semiarid tropics, but the mechanisms of competition are not clearly understood. In this study, conducted in the semiarid highlands of Kenya, soil-water changes and root dynamics were monitored during two rainy seasons from a long-term, replicated, alleycropping experiment. The treatments were (i) maize (Zea mays L.) grown alone, without fertilizer; (ii) maize, without fertilizer, intercropped between hedgerows of leucaena [Leucaena leucocephala (Lam.) de Wit], with hedgerow prunings returned to the alleys; and (iii) maize grown alone, with fertilizer at 40 kg N and 18 kg P ha-1. Available water in 1.25 m of soil depth under alleycropping was lower than with maize alone. Depletion of soil water by hedgerows continued after maize harvest and carried water deficits in alleycropping from one season to the next. Leucaena provided 1.45 Mg ha-1 leaf biomass, which contained 41.6 kg N and 2.5 kg P ha-1; moreover, it added 0.51 Mg ha-1 season-1 of root biomass to the soil, equivalent to 7 kg N and 0.2 kg P ha-1. Therefore, N contributed through the alleycropping system was equivalent to the recommended fertilizer level; the system, however, did not meet the P requirements of the crop. Maize did not respond to fertilizer in both seasons, and the alleycropped maize yielded lower than the unfertilized maize.
Resilience and Livelihood Benefits of Climate Smart Agroforestry Practices in Semi-arid Tanzania
The agricultural sector in Tanzania is an important driver for economic growth, poverty alleviation, food security and rural development. However, high dependence on rainfall makes the sector vulnerable to the impacts of climate change. Economic losses due to climate change are estimated at US$200 million per year. The scaling up of climate-smart agriculture practices such as agroforestry can reduce such losses, build resilience in the sector, improve productivity and farmer incomes while restoring ecosystem functions that contribute to climate change mitigation. Agroforestry technologies build a healthy agro-ecosystem and foster greater climate resilience of farm households through restoration of land productivity and diversification of production and income options. However, evidenced-based information on the resilience and livelihood benefits of semi-arid agroforestry systems as a climate smart practice is limited.
Increasing DryDev’s effectiveness and efficiency through probabilistic decision modelling
This working paper describes the Decision Analysis work done on the Drylands Development Programme (DryDev) in Sub-Saharan Africa. The programme was designed to address water management, food security and rural economic development in the drylands of Kenya, Ethiopia, Burkina Faso, Mali and Niger. The initiative was geared towards supporting the transition of smallholder households from subsistence farming and reliance on emergency aid towards more sustainable agribusiness enterprises. Decision Analysis was used as a quantitative ex-ante impact assessment tool to prioritize interventions based on their projected impacts. The assessment simulated the potential of four interventions in six project sites of Eastern Kenya, incorporating risk and uncertainty in decision modelling. The result delivered to the decision makers was a range of plausible outcomes from a cost benefit analysis and a description of the variables with the highest critical uncertainties whose measurement would most facilitate decision-making. This paper describes the modelling process, which was both participatory and probabilistic, for each intervention. It gives details on the quantitative approach used for each of the four interventions separately, highlighting the benefit, cost and risk variables and the interactions between them. It then discusses the results of each decision model and from these makes recommendations to the decision makers. The penultimate section highlights the limitations and constraints faced by the analysis, and this is followed by general conclusions. The DryDev Programme is funded by the Netherlands’ Ministry of Foreign Affairs, with ICRAF as the lead implementing agency and SNV, CARITAS, ADRA and World Vision as implementing partners.
Stakeholder Approach to Risk Informed and Evidence Based Decision Making (SHARED) for Resilience
Decision-makers from the household to state level frequently have to make decisions within a context of risks, uncertainties, multiple possible outcomes and stakeholder groups with varied interests. It is therefore reasonable for them to be concerned about the risk that an investment or intervention could fail to achieve its objectives. This happens because the uncertainties surrounding the impacts of a proposed development intervention during project assessment are usually not addressed. These uncertainties can be high where information on the parameters of interest and how they will evolve under future change is scarce. For instance, there is a severe lack of data on the ecological, socioeconomic, cultural and political parameters that would influence the complex dynamics of environmental systems.Decision analysis aims to assist decision-makers in making rational decisions in situations where they are faced with imperfect information. It is concerned with identifying the most promising course of action, while recognizing risks and uncertainties. Initially, analyses are based on the current state of knowledge about particular variables of interest, before any measurements are taken. This knowledge is used for probabilistic simulations of the full range of plausible system outcomes of particular interventions, which aid in prioritizing decision options based on their likely outcomes or impacts. This is achieved by including decision-makers, various stakeholders and end-users in conducting ex-ante impact assessments using quantitative impact pathways and probabilistic estimates of all relevant benefits, costs, risks and uncertain variables. Business decision analysis methods offer a promising way forward, because they have been designed for aiding businesses in making decisions on risky projects with limited research budgets. To achieve this, a key objective of decision analysis is capturing the current state of uncertainty.
Resource use and growth in semi-arid agroforestry systems
The work reported here aimed to provide a comprehensive database of core information to support the development and validation of process-based models of resource capture and growth in the semi-arid overstorey agroforestry systems. Intensive field studies were carried out in Kenya over a 30 month period and the results obtained were combined with data from a previous project to produce a dataset spanning a 4.5 year period. This dataset was then used to verify output from the HyPAR model. Allometric procedures developed from the pipe model theory (Lott et al., 1998) were used to estimate tree growth non-destructively throughout the observation period. Significant differences in tree size between the sole (Td) and dispersed agroforestry (CTd) treatments were established during the first 130 days after planting, probably because of competition with the associated crops. The above-ground biomass and trunk length and taper characteristics of the CTd trees remained inferior to those of Td trees throughout the observation period, seriously undermining the economic potential of this agroforestry system. Comparison of output from the HyPAR model against the observed results provided information pertinent to future model development. The model proved to be insufficiently flexible for end-users wishing to simulate the growth of different crops during the same simulation cycle, or to use model output to aid management decisions such as the timing of pruning. The allometric procedures used by the model to estimate canopy size from trunk diameter at breast height also proved incapable of accounting for reductions in canopy size resulting from pruning. Estimates of tree height are rounded to the nearest metre within the model, representing a potentially serious loss of resolution when annual increments often do not exceed 2 m. In addition, the numerous parameters required by the model would force most end-users to rely heavily on published information, potentially undermining the reliability of simulations.