Ademola K. Braimoh

Complex Land Systems: the Need for Long Time Perspectives to Assess their Future

The growing awareness about the need to anticipate the future of land systems focuses on how well we understand the interactions between society and environmental processes within a complexity framework. A major barrier to understanding is insufficient attention given to long (multidecadal) temporal perspectives on complex system behavior that can provide insights through both analog and evolutionary approaches. Analogs are useful in generating typologies of generic system behavior, whereas evolutionary assessments provide insight into site-specific system properties. Four dimensions of these properties: (1) trends and trajectories, (2) frequencies, thresholds and alternate steady states, (3) slow and fast processes, and (4) legacies and contingencies, are discussed. Compilations and analyses of past information and data from instruments and observations, palaeoenvironmental archives, and human and environmental history are now the subject of major international effort. The embedding of empirical information over multidecadal timescales in attempts to define and model sustainable and adaptive management of land systems is now not only possible, but also necessary.

Land change dynamics: insights from Intensity Analysis applied to an African emerging city

Abstract Land change in Kigali, Rwanda, is examined using Intensity Analysis, which measures the temporal stationarity of changes among categories. Maps for 1981, 2002 and 2014 were produced that show the land categories Built, Vegetated and Other, which is composed mainly of croplands and bare surfaces. Land change accelerated from the first time interval (1981–2002) to the second time interval (2002–2014), as increased human and economic activities drove land transformation. During the first interval, Vegetated showed net loss whereas Built showed net gain, in spite of a small transition directly from Vegetated to Built. During the second interval, Vegetated showed net gain whereas Built showed nearly equal amounts of gross loss and gross gain. The gain of Built targeted Other during both time intervals. A substantial portion of overall change during both time intervals consisted of simultaneous transitions from Vegetated to Other in some locations and from Other to Vegetated in other locations.

Global agriculture needs smart science and policies

Food insecurity and climate change, the twin crises that may define the future [1] have brought agriculture back into the spotlight of international debate. In spite of the growing threats of climate change to agricultural yields and livelihoods, global agriculture must produce additional food to feed a growing population [2]. Today, more than ever before, we understand the significance that climate has for agriculture. Major weather and food price shocks are becoming the new norm – the recent droughts in the horn of Africa, Russia, Australia, and United States markedly affected food production and prices, and increased the vulnerability of the poor. Agriculture’s direct reliance on the natural resource base is a defining characteristic of the sector, consuming 70% of global freshwater and occupying 40% of global land area. Conventional forms of agricultural production are often unsustainable, pollute the environment and deplete the natural resources on which production relies over time. Low agricultural productivity is often associated with poverty, food insecurity, and nutrient depletion in Africa, where just 4% of smallholder farmers use improved seeds, the average fertilizer application is 9 kg per hectare, and only 1% of arable land is under irrigation. In Asia, inappropriate irrigation practices lead to elevated methane emissions and salinization, and high nitrogen fertilizer levels to greenhouse gas emissions. Agriculture is the world’s leading source of methane and nitrous oxide emissions, a substantial source of carbon emissions, and the principal driver behind deforestation worldwide. Some 30% of global greenhouse gas emissions are attributable to agriculture and deforestation. The growing consensus on the need for a climate-smart agriculture (CSA) emerged largely out of awareness of the sector’s negative impacts. More recently, this perspective of agriculture as a source of greenhouse gas emissions and environmental pollution has become more balanced, with a growing understanding of the environmental services the sector can provide if production is well-managed. CSA

Increasing Agricultural Resilience through Better Risk Management in Zambia

A proper understanding of the risks faced by the agricultural sector and effective strategies to manage those risks is vital to creating a diversified and resilient economy for sustained growth and economic transformation. Increasing Agricultural Resilience through Better Risk Management in Zambia provides a rigorous analysis of the production, marketing, and enabling environment risks faced by Zambia’s agricultural sector and prioritizes solutions to manage the risks. In terms of the severity and frequency of adverse impacts, the analysis shows that droughts, floods, price volatilities, and trade restrictions are the principal risks affecting agriculture in the country. Exposure to the consequences of these and other risks can be effectively limited through risk management systems tailored to the country’s context. Three areas of risk management are found to warrant priority, with significant potential for synergizing actions undertaken across them: Strengthen early warning system to detect threats to food security; Develop climate-smart agriculture and increase resilience to climate-related shocks through diversification; and Develop the Zambian Commodity Exchange (ZAMACE) and build a shock-responsive safety net.