Agroforestry (AF)-based adaptation to global climate change can consist of (1) reversal of negative trends in diverse tree cover as generic portfolio risk management strategy; (2) targeted, strategic, shift in resource capture (e.g. light, water) to adjust to changing conditions (e.g. lower or more variable rainfall, higher temperatures); (3) vegetation-based influences on rainfall patterns; or (4) adaptive, tactical, management of tree-crop interactions based on weather forecasts for the (next) growing season. Forty years ago, a tree physiological research tradition in aboveground and belowground resource capture was established with questions and methods on climate-tree-soil-crop interactions in space and time that are still relevant for today’s challenges. After summarising early research contributions, we review recent literature to assess current levels of uncertainty in climate adaptation assessments in and through AF. Quantification of microclimate within and around tree canopies showed a gap between standard climate station data (designed to avoid tree influences) and the actual climate in which crop and tree meristems or livestock operates in real-world AF. Where global scenario modelling of ‘macroclimate’ change in mean annual rainfall and temperature extrapolates from climate station conditions in past decades, it ignores microclimate effects of trees. There still is a shortage of long-term phenology records to analyse tree biological responses across a wide range of species to climate variability, especially where flowering and pollination matter. Physiological understanding can complement farmer knowledge and help guide policy decisions that allow AF solutions to emerge and tree germplasm to be adjusted for the growing conditions expected over the lifetime of a tree.

/pdf/climate-change-adaptation-in-and-through-agroforestry-four-ztbtl27nt7.pdf

Climate change adaptation in and through agroforestry: four decades of research initiated by Peter Huxley

Inclusive and adaptive business models for climate-smart value creation

Some of the measures to be taken to reduce greenhouse gas emissions are related to agricultural activities. Climate-smart agriculture (CSA) is a method allowing implementation of agricultural practices in compliance with the efforts to combat climate change. CSA is an approach guiding agricultural systems under changing climate conditions to provide sustainable development and food safety. The targets of this approach included sustainable increase in agricultural production, resistance and adaptation to climate change and reduction of greenhouse gas emissions. Farmer participation and level of consciousness play a significant role in successful implementation of CSA. The present study was conducted to put forth farmers’ adaptation of climate change. Farmer perceptions or approaches to CSA were taken into consideration. In the study, the literature was examined to analyze the adoption of CSA and the typology of CSA applications was developed. The typology consists of five categories: (1) soil management, (2) water management, (3) chemical input management, (4) crop diversification and (5) planting trees/agroforestry. Household survey data were used to create and test hypotheses about farmers’ adoption of CSA. Nonparametric tests were used to estimate the socioeconomic variables that were effective in the adoption of CSA categories. The results generally show that CSA categories have high application potential among farmers. The factors influencing farmer decisions on these issues were identified as education, participation into agricultural meetings, land size and agricultural income. Such factors may guide policymakers while taking measures against climate change.

Farmers’ adaptation to climate-smart agriculture (CSA) in NW Turkey

/pdf/transforming-agriculture-in-southern-africa-constraints-3mchrqyyqv.pdf

Transforming Agriculture in Southern Africa : Constraints, Technologies, Policies and Processes

Review of agricultural production systems in eastern Africa in relation to food and nutrition security and climate change

Climate-smart agriculture (CSA) has three goals—productivity, resilience and mitigation. Rarely are these accounted for in CSA programming or the scientific evidence that supports it. Here, we evaluate the climate smartness of CSA-based agroforestry practices in Tabora and Dodoma, Tanzania using unpublished data from earlier studies. Firstly, a study of on-farm wood production and its use with the improved cook stove (ICS) was used to ascertain the productivity and mitigation effects of CSA. Next, intercropping experiments of maize or cassava with pigeonpea and/or G. sepium provided information on the production and resilience benefits of CSA. It was found that agroforestry practices (shelterbelt, trees on contours and intercropping) supplied up eight tons per hectare (t ha−1) of wood—enough to support a five-member family for up to 6 years when using ICS. Employing ICS also reduced the time spent in cooking (20%) and fuelwood collection (32%), and reduced gas emissions by 62%. Generally, intercropping pigeonpea or G. sepium enhanced farm production (as noted by a land equivalent ratio greater than 1) and agroecosystem resilience through crop diversification by using suitable intercropping arrangements and including a drought-resistant crop. Using the latter two in semi-arid Dodoma enhanced crop production across seasons and sites. Our analysis shows that adopting CSA-based agroforestry and intercropping practices is beneficial. However, these benefits are not universal. It also illustrates other key principles for understanding multidimensionality of CSA objectives, including the need to: select appropriate indicators, ensure designs are robust for heterogeneity, examine trade-offs, and conduct participatory evaluation of CSA.

https://link.springer.com/content/pdf/10.1007%2F978-3-319-92798-5_13.pdf

Understanding the Multidimensionality of Climate-Smartness: Examples from Agroforestry in Tanzania

The intensification of agricultural systems in sub-Saharan Africa is necessary to reduce poverty and improve food security, but increased nutrient applications in smallholder systems could have negative consequences for water quality, greenhouse gas emissions, and air quality. We tracked nitrogen (N) inputs and measured maize (Zea mays) biomass, grain yields, N leaching, and nitric oxide and nitrous oxide fluxes from a clayey soil in Yala, Kenya and a sandy soil in Tumbi, Tanzania, with application rates of 0, 50, 75, 100, 150, and 200 kg N ha-1 yr-1 over two cropping seasons. Maize yields were 4.5 times higher in Yala than Tumbi, but yields plateaued at both sites with fertilizer applications at or above 100 kg N ha-1 yr-1. Partial N budgets in Yala were typically negative, meaning more N was exported in maize biomass plus grain or lost from the system than was added in fertilizer. In Tumbi, N budgets were negative at lower fertilizer levels but positive at higher fertilizer levels. At both sites most (96%) of the N was lost through maize biomass/grain removal and N leaching. Fertilizer additions at or less than 50 kg N ha-1 yr-1 on these two contrasting sites resulted in minor gaseous N losses, and fertilizer additions less than 200 kg N ha-1 yr-1 caused relatively little change to N leaching losses. This indicates that the modest increases in fertilizer use required to improve maize yields will not greatly increase cropland N losses. 

The fate of nitrogen during agricultural intensification in East Africa: Nitrogen budgets in contrasting agroecosystems

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Understanding the Multidimensionality of Climate-Smartness: Examples from Agroforestry in Tanzania

The fate of nitrogen during agricultural intensification in East Africa: Nitrogen budgets in contrasting agroecosystems