Development impacts of global environmental change in drylands
Introduction
Where human development is the process of enlarging people’s choices by expanding human capabilities and functioning (Alkire, 2010; UNDP, 2010), human security is a variable condition under which people and communities have the capacity to manage stresses according to their needs, rights and values (Barnett et al., 2010). In this sense, the concept of human security complements the concept of human development by focusing on basic human needs and addressing the concern for steady fulfillment of these needs. Reframing environmental change as an issue of human security requires analyzing environmental change within the wider context of the co-occurring economic, social, institutional, political, cultural, and technological changes taking place in the world today (O’Brien, 2006).
Human security is influenced by slowly evolving and interrelated changes in population, in economic development and in the environment. Unmitigated global environmental change, including climate change, land degradation and water scarcity, increase pressure on the well-being of especially the poor (MA, 2005; IPCC, 2007; UNEP, 2007; World Bank, 2008). As some of these environmental changes will only become apparent in the longer term, they increasingly may backlash on progress already made. Therefore, to ensure that development is achieved in a sustainable manner, these changes need to be taken into account in designing development policies (Bourguignon et al., 2008).
This chapter assesses the role of the environment as an important precondition for human security. Two distinct but complementary analysis and related methodologies are used, with child and infant mortality as indicators of human security. To examine long-term prospects for human security, we focus on future developments in access to food, clean drinking water, basic sanitation and modern energy sources, and their implications for child mortality. This analysis is done on a largely aggregated regional scale, using the Global Integrated Sustainability Model (GISMO) (Hilderink et al., 2008). As this global analysis only broadly provides insight into the underlying health risks, we complement the analysis by assessing the mechanisms that contribute to increasing vulnerability. This analysis is done on a more disaggregated subnational scale, using the methodology of archetypical patterns of vulnerability (UNEP, 2007; Kok and Jager, 2009). This methodology is based on the notion that there are similar vulnerability situations around the world that also share similar features in terms of mechanisms that drive them. We focus on the vulnerability of small-holder farmers in dryland areas, as these are amongst the most critical, from a development and environmental perspective, with high infant mortality rates and a fragile environment (Levy et al., 2005).
Methodology
Global Integrated Sustainability Model (GISMO)
The Global Integrated Sustainability Model (GISMO1.0) operationalizes the concept of sustainable development by interlinking global environmental change and human development (Hilderink et al., 2008). It addresses quality of life that results from changes in human, economic and environmental domains, using the systems approach to describe these complex dynamic systems and their interrelations. We applied the model in combination with the IMAGE model (Bouwman et al., 2006), to address a broad range of global environmental change issues related to human development.
Quality of life is modeled focusing on poverty, education, human health and their underlying dynamics, linked through a cohort-component population model. Here, we focus on the role of food (malnutrition), water (access to safe drinking water and basic sanitation) and energy (use of solid fuels for cooking and heating) with respect to human health (child mortality).
The occurrence of malnutrition is determined by food availability, women’s education and status relative to that of men, and access to save drinking water (Smith and Haddad, 2000). Access to safe drinking water and basic sanitation are determined by per-capita income, levels of urbanization and population densities, distinguishing between no access, access to an improved source and household connection (Cairncross and Valdmanis, 2006). For solid fuel use, a simple function using per-capita income as an explanatory variable is used (Mehta et al., 2006). Child mortality is determined according to the causal chain, from health-risk factors towards disease and eventually death (WHO, 2002), based on socio-economic (e.g., poverty, education) and environmental health risks (e.g., child malnutrition, unsustainable access to safe drinking water, basic sanitation and solid fuel use).
Archetypical patterns of pulnerability
The analysis of the prospects for child mortality provides us with insights into trends in world regions under different scenarios. This, however, does not tell us much about the dynamics within specific human-environment systems. Vulnerability analysis is a valuable tool for a better understanding of these dynamics and for identifying potential impacts on human security caused by socio-economic and environmental changes. Such an analysis contributes to a better understanding of local conditions as it examines exposures and sensitivities of people to these changes, and their ability to cope with or adapt to the potential impacts (Turner et al., 2003).
Recognizing the need and potential for looking at similarities between related situations around the globe, a method was developed to identify and analyze “archetypical patterns of vulnerability” (Jäger and Kok, 2007: 317), which generalizes the outcomes of local vulnerability studies (here we primarily use meta-studies) and builds on global assessment insights and tools. The method looks for common vulnerability creating mechanisms in a multitude of cases that, in that sense, are archetypical. It flags the most vulnerable groups, and provides regional perspectives and connections between regions within a global context. A pattern of vulnerability is defined as: “a specific representative pattern of the interactions between environmental change and human well-being” (Jäger and Kok, 2007: 317). The method not only looks at environmental changes but also includes the wider socio-economic context in which these changes take place, addressing the integrated human-environment system from a global perspective.
Taking the most important common properties and dynamics from case studies and meta-studies, the core mechanisms that cause specific vulnerabilities are derived. Next, these core mechanisms are quantified using indicators from global Integrated Assessment Models, here GISMO and the IMAGE model. In the final step, different manifestations of the patterns (so called vulnerability profiles) and their geographic locations are identified through cluster analysis (Janssen et al., 2012). See Kok et al. (2010) for a further elaboration of the methodology and its application on different human-environment systems.
Prospects in child mortality
Child mortality is an important indicator of human security. Sustainable access to food, safe drinking water and basic sanitation (water) and modern energy sources (energy) may decrease child mortality significantly (PBL, 2009). Of the estimated 8.8 million annual child deaths in 2008, the vast majority were related to preventable and treatable infectious diseases and conditions that are related to their environment, including the use of solid fuels (fuel wood, dung, coal and charcoal) for cooking and heating (pneumonia) and unsafe drinking water and the lack of basic sanitation (diarrhea) (Black et al., 2010) with malnutrition (underweight) being an important underlying factor responsible for about 35 percent of child deaths (Black et al., 2008). Here, we assess future development in access to food, water and energy and the related impacts on child mortality. Reducing child mortality is also one of the eight Millennium Development Goals (MDGs): reduce by two-thirds, between 1990 and 2015, the under-five mortality rate.
In general, future projections are based on a range of related developments, all encompassing major uncertainties. To assess future developments in child mortality and progress towards achieving the related MDG target, we used three scenario variants, mainly differing in economic growth and food availability. Variant I is based on FAO projections (FAO, 2006) that uses data on economic growth from the World Bank (2005) that shows medium economic growth compared to the other variants. Variant II is based on the baseline scenario of the OECD Environmental Outlook (MNP/OECD, 2008), which shows the highest economic growth. Variant III is based on the reference scenario of the International Assessment of Agricultural Science and Technology for Development (IAASTD, 2009), which shows the lowest economic growth. In all three variants, the population is calibrated on the UN medium projection (UNDESA, 2007).
For the three variants child malnutrition (food), access to safe drinking water and basic sanitation (water), and access to improved energy sources (energy) are projected to increase significantly, with main improvements in East Asia and the Pacific. However, in absolute terms, improvements are much less, particularly in Sub-Saharan Africa and South Asia, and especially with respect to energy, as the relative improvements in access levels are largely compensated by large population growth rates. As a result of the improvements overall child mortality is projected to decrease significantly (as is shown in Figure 8.1, for Variant I). Nevertheless, in Sub-Saharan Africa and South Asia a lack of these basic services is still responsible for many child deaths. In Variant I, by 2030, about 65 in every 1,000 children are still expected to die before the age of five, with more than 45 percent of these deaths related to inadequate access to food, water and energy.
Figure 8.2 presents child mortality for 2015 and 2030, in all three variants. It clearly shows that, although substantial improvements are projected, the improvements in access levels are far from enough to reach the MDG target. Furthermore, only a few regions are projected to reach this target by 2015. High food prices in Variant III with low economic growth have a huge impact on overall child mortality, especially in Sub-Saharan Africa, while the much stronger economic growth in Variant II remains insufficient for reducing child mortality by two-thirds, by 2030.
The analysis of child mortality prospects is exemplary of the entry points where global environmental change may have an impact on human security. Global environmental change may potentially affect future access to food, water and energy, thereby undermining human security. The following section explores the dynamics of environmental change and human security, in more detail, by focusing on small-holder farmers in dryland areas.
Vulnerability of small-holder farmers in dryland areas
The analysis above addresses human security by projecting child mortality on a largely aggregated regional scale. However, the impact of socio-economic and environmental changes on human security is dependent on a wide range of conditions, including social structures and the biophysical system. Furthermore, these changes are not evenly distributed across world regions. To unpack the regional analysis, we used the methodology of archetypical patterns of vulnerability to assess specific vulnerability creating mechanisms, i.e. potential risks to human security, on a more local scale. Here, we assess the vulnerability of smallholder farmers in dryland areas. In dryland areas, the link between environment, development and human security is highly relevant as is indicated by their relatively high levels of infant mortality (Levy et al., 2005).
Current literature suggests that there are typical and common mechanisms that influence the vulnerability of farmers in dryland areas, especially in developing countries (Geist and Lambin, 2004; Jäger and Kok, 2007; Reynolds et al., 2007; Sietz et al., 2011). Dryland areas are hot spots with respect to the challenges and trade-offs of improving human development in a fragile environment with limited natural resources and high risks of overexploitation. Dryland areas are characterized by low levels of precipitation and high rates of evaporation. They occupy 41 percent of the earth’s land area and are home to half of all people living in poverty (Dobie, 2001). Most dryland countries have a large proportion of their labor force working in the agricultural sector, with the poor highly dependent on environmental services. Land degradation and climate change endanger agricultural production and environmental sustainability.
The pattern of vulnerability is characterized by increasing pressures on natural resources from a growing population, limited and insecure access to water and fertile soils, and soil degradation resulting from overuse. Combined with the breakdown of traditional coping mechanisms and barriers to alternative livelihoods (Geist and Lambin, 2004; Safriel et al., 2005; UNEP, 2007) this drives a negative feedback on agricultural production and income generation (e.g. Safriel and Adeel, 2008). Poor infrastructure impedes market access (e.g. Shiferaw et al., 2008), which together with the unavailability of capital influences the improvement of agricultural productivity (Twomolow et al., 1999; Thomas, 2008). All these factors lead to situations in which rural households potentially become enmeshed in poverty traps.
A set of seven global indicators has been identified, as proxies for the basic vulnerability creating mechanisms and their impacts on human security. For the sake of availability, sub-national data on infant mortality were used instead of those on child mortality (CIESIN, 2005). Cluster analysis of these indicators has distinguished eight vulnerability profiles, six of which relate to dryland areas in developing countries (Figure 8.3).1 These vulnerability profiles define different vulnerability patterns, i.e. combinations of indicator values that shape specific vulnerabilities in different dryland areas. Below we discuss the different vulnerability patterns and their spatial distribution (Figure 8.4), supplemented with relevant case studies taken from the work of Sietz et al. (2011).
The two resource-poor vulnerability patterns identify the most resource-constrained and isolated areas of the world. The harsh dryland conditions explain the still relatively low levels of soil degradation, as agricultural and grazing practices are not favored. The very limited renewable water resources pose the risk of groundwater overuse. The two profiles differ mainly in level of human well-being (income and infant mortality). Severe poverty occurs in areas dominated by pastoral land use. More moderate poverty occurs in zones between pastoral and sporadic, sparse forms of agriculture on the desert fringes and in areas where national economies allow for improved living conditions, for example, because of fossil-fuel exploitation. A good illustration of the severe poverty pattern is the case study of Le Sage and Majid (2002) in Somalia. The poorest people there are not able to benefit from occasionally better rainfall due to the depleted asset base and war-related constraints on access to productive resources. Even though better situated people may produce more crops, debt repayment and recurrent droughts continue to exhaust their livelihood assets.
The two poor water, better soils vulnerability patterns are less resource-constrained, but are confronted with much higher soil degradation. They differ mainly in agricultural conditions and population densities. More favorable agricultural conditions are combined with higher population densities, but also with higher soil degradation, while poverty levels are similar. These patterns are found in parallel areas, neighboring deserts, with the less populated areas closer to the desert, corresponding with a land-use gradient from pastoral to agro-pastoral. The more populated pattern is illustrated by Kassahun et al. (2008) in East Ethiopia, where rangeland degradation has increased in severity and magnitude since the 1970s. Overgrazing and overexploitation of woody plants accelerate the pace of soil degradation, while also water bodies were affected by agricultural activities. This ongoing overuse of natural resources induces declining agricultural yields, food insecurity and increased poverty, and generates conflicts over grazing areas and water resources.
The better endowed vulnerability patterns are least resource-constrained. However, differences are more distinct than in the previous two groups of patterns. Although, the resource situation is best in the extremely overused vulnerability pattern, the human well-being is comparable to the poor water, better soils patterns. Furthermore, soils have been extremely degraded by a very dense population, also putting future generations under increased pressure. In contrast, the river vulnerability pattern is best endowed with water resources, while soil degradation is moderate in comparison. However, the pattern combines relatively high income levels with relatively high infant mortality rates, suggesting a very uneven distribution of income opportunities, probably due to differences in access to irrigation and grassland. The former pattern dominates the arid areas of India, but is also found in north-eastern China and on the African Mediterranean coast. The latter pattern is found around the lower reaches of the Indus, Euphrates, Tigris and Volga rivers, and in other irrigation areas, such as around the Aral Sea. A good illustration of the extremely overused pattern is the case study of Ram et al. (1999) describing the situation in Khabra Kalan (Rajasthan). The study shows increasing population, shrinking land holdings and shortfall of food on small farms which results in the deterioration of the land productivity. Mustafa and Qazi (2007) verify the conclusions drawn from the river vulnerability pattern with a case study from Balochistan (part of the Indus basin). They show how the transition from a sustainable, traditional irrigation system (“karez”) to groundwater pumping leads to increasing social disparities and degradation of environmental resources.
Increasing vulnerability due to global environmental change
Unsustainable use and increasing competition over natural resources (including land, water and fossil energy sources), as well as global environmental changes (including climate change and biodiversity loss) increase the pressure on already stressed livelihoods and will increase vulnerabilities – especially in dryland areas where the resource situation is generally constrained. Countries facing the most serious environmental degradation are also making the slowest progress toward achieving the MDGs (MA, 2005). Furthermore, deteriorating environmental conditions can lead to fewer opportunities for generating income, and exhaust survival strategies (Oxfam, 2006). Finally, resource scarcities increase the pressure on available resources, putting upward pressure on prices of especially food and energy (PBL, 2011).
Climate change eventually reduces crop yields and increases the likelihood of short-term crop failure and long-term production declines (IPCC, 2007). The most vulnerable are poor and food-insecure countries at lower latitudes, especially in seasonally dry and tropical regions that largely depend on rain-fed farming (IPCC, 2007). In drylands, this is especially the case for the resource poor pattern for Sub-Saharan Africa and the extremely overused pattern for South Asia, but people in the poor water, better soils pattern also should take these future changes into account.
Increased land use and industrial activities impact water quality, while climate change may reduce water availability through shrinking glaciers, more frequent dry seasons, increased evapotranspiration and water quality deterioration (Bates et al., 2008). In 2006, 1.2 billion people experienced physical water scarcity, and another 1.6 billion people economic water scarcity (Comprehensive Assessment of Water Management in Agriculture, 2007). Physical water scarcity mainly results in competition between different uses and is a major concern for future agricultural opportunities in the resource poor and poor water, better soils patterns for North Africa, the Middle East and Central Asia. Economic water scarcity includes underdeveloped water infrastructure with high vulnerability to droughts that not only impact on agriculture but also on access to save drinking water. People that will be most affected are those living in already water-stressed basins, while problems will be most critical in economically depressed areas, where water stress is increased by socio-economic factors. This mainly includes the resource poor and poor water, better soils patterns for Sub-Saharan Africa and the extremely overused pattern for South Asia.
Although fertility rates are dropping all over the world, population increase is projected to remain high in underdeveloped areas in Sub-Saharan Africa and South Asia (UNDESA, 2007). This is especially a challenge for the extremely overused pattern for South Asia where population pressure is already very high. In the resource poor and poor water, better soils patterns for Sub-Saharan Africa resource availabilities seem to limit opportunities for improving human well-being on the basis of agricultural production, let alone with an increasing population. Combined population and environmental pressures may force people to migrate to better endowed areas, impacting on the development opportunities there, or drive them towards cities that not necessarily provide good income opportunities for these migrants.
Entry points to strengthen human security in drylands
The variety in vulnerability patterns suggests that there is no single set of options for improving human security in dryland areas. Unsustainable use of natural resources, increasing competition over fertile land and water resources, and unmitigated global changes increase the pressure on already stressed livelihoods, as is shown in the previous section. Some of these pressures will only become apparent in the long term – after 2015 or even 2030 – potentially having a backlash on development progress. Therefore, policies fostering increased access to food, water and improved energy sources should address the human-environment system as a whole, while also taking environmental changes into account in development strategies.
The resource poor, severe poverty pattern requires attention in almost all vulnerability dimensions. As people in these areas are extremely poor, agriculture is the single most important source of income. Improving water-use efficiency could create positive effects in agricultural production, although immediate interventions to improve basic livelihood conditions are also required to reduce the very high incidence of poverty.
To relieve the pressure in the poor water, better soils patterns, land-use intensity should be decreased through more sustainable resource management, but when resources are more constrained, intensities can also be decreased through diversified livelihoods. This requires moving water-intensive agriculture to more water rich areas, as well as creating off-farm income opportunities. It should be noted that decreasing poverty through more sustainable resource management is more realistic in cases where population growth is limited. The same holds for areas with the extremely overused pattern, where only a very small income can be generated from relatively good natural resources due to very high population densities. The pressure is unlikely to be relieved by more sustainable agricultural practices alone. Therefore, pressure on production also has to be reduced.
The most promising situation for development is in the rivers pattern, where the natural resource situation is good, population pressure is intermediate, and average income is the highest of all patterns. Here, institutional processes, such as land reform and measures to improve the position of smallholder farmers, could relieve pressures from unequal access to natural resources.
Conclusions
In this chapter we have addressed future developments in human security on an aggregated regional scale, focusing on the impact on child mortality caused by inadequate access to food, safe drinking water, basic sanitation, and improved energy sources. In addition, we have analyzed specific vulnerability creating mechanisms that impose potential risks to human security for small-holder farming in dryland areas, due to global change, on a more local scale. Dryland areas are hot spots with respect to the challenges and trade-offs in improving human security in a fragile environment with limited natural resources and high risks of overexploitation.
The regional analysis concludes that, although access to food, water and energy is expected to increase significantly, related health risks remain substantial; even by 2030. If current trends continue, the MDG 4 target for reducing child mortality is far out of reach, even with higher economic growth and greatly improved agricultural productivity. Furthermore, the sub-national scale analysis of drylands concludes that there is no single set of options for improving human security in dryland areas. Unsustainable use of natural resources, increasing competition over land and water resources, and unmitigated global environmental changes increase the pressure on already stressed livelihoods. As some of these pressures will only become apparent in the long term – after 2015 or even 2030 – they may backlash on development progress.
Therefore, to improve human security, and with child mortality as our main indicator, accelerated growth in access to food, improved drinking water and basic sanitation, and improved energy sources is key. Furthermore, policies should address the human-environment system as a whole, while also taking expected global changes into account. In this way, the MDG4 child mortality target may not only be achieved, but the achievement may also become more sustainable beyond this target year.
Note
1 See Kok et al. (2010) for a more detailed discussion on the vulnerability creating mechanism and the data used, and Sietz et al. (2011) for a similar dryland analysis using a slightly different data set.
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