2.4 Expanding Causal Association: Beyond Theory Building
2.4.2 Vulnerability, Scarcity and Migratory Adaptation
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Climate change is likely to influence the food-producing capacity in many areas. While some areas may experience a reduction in crop yields, others are likely to benefit. One important factor is temperature. While an increase in temperature of a few degrees is projected to generally increase crop yields in temperate areas, greater warming may reduce agricultural output. In tropical areas, where dry land agriculture dominates, even minimal increases in temperature may be detrimental to food production (Raleigh and Urdal, 2007:
677).
He points out however that although degradation of soil and water resources is likely to be intensified by adverse changes in temperature and precipitation, the nature of adaptation strategies and interventions may help in mitigating the impacts of these changes (ibid: 677).
How then does vulnerability transform into violent conflicts?
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the place of origin caused by among other things, lack of economic opportunities and access to resources on the one hand, and on the other hand, by pull functions at the point of destination due to the availability of better opportunities, access to resources, etc. According to Dingle and Drake (2007), migration often “serves as a pre-emptive strategy to adaptation in response to resources that fluctuate spatio-temporally either seasonally or less predictably”
(Dingle and Drake, 2007: 113). Their study highlights four elements as characteristic of environment-induced migration: (1) as a type of persistent and defined “locomotory” activity, (2) characterised by the involvement of a large scale relocation of the subject moving on a longer duration as against patterns arising in its routine daily activities, (3) which may involve a seasonal to-and-fro movement of the affected population between alternately favourable and/unfavourable regions, and (4) resulting in a spatial redistributive movements in the extended population (Dingle and Drake, 2007: 113-114).
Oliver-Smith and Shen (2009: 12) predict that climate change when combined with depletion of ecosystems, overuse of natural resources and environmental degradation, will impact adversely on the habitability of large areas of the planet. In 1990, an Intergovernmental Panel on Climate Change report noted that human migration may be the “greatest single impact of climate change”, opening the floodgate of research on the climate change adaptation and migration nexus (IPCC, 1990: 20). While mobility is historical in human nature, scholars agree that environmental deterioration and the attendant depletion of ecosystem’s capacity to support life have been major influences on human migration (Gupta et al., 2006, Gomez, 2013; McLeman, 2011; Steiner, 2008).
Another study identifies three distinct ways by which climate change will significantly affect migration: (1) human vulnerability in dry regions which will witness a reduction in agricultural output and other ecosystems services such as availability of clean water and fertile land; (2) increase in the number and intensity of extreme weather events such as heavy precipitation resulting in flooding and mass displacement; and (3) its effect on coastal areas such as displacements in coastal habitats through rising sea-level which will permanently destroy extensive range of productive low-lying coastal areas and deprive millions of their homes (Brown, 2008).
As a 2001 IPCC report points out, since rising sea levels implies aggravated risks of flooding in vulnerable regions, “climate change is expected to contribute to migration from coastal and riverine settlements” (IPCC, 2001: 36). The report notes further that some patterns of changes
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in the environment that are associated with climatic changes such as extreme weather events and coastal flooding are likely to cause population displacement in varying degrees and the most dramatic changes will are expected to occur in patterns of human settlement as rise in sea-level unfolds gradually just as the process of freshwater and soil degradation.
Raleigh, Jordan and Salehyan (2008: 6-8) identify different migration responses which correspond to specific forms of vulnerability. Temporary and circular labour migration has been associated with chronic drought. This is in contrast to enduring disaster events which often compels relatively long-term or permanent change of location. Similarly, they explain that floods and slides which are recurrent in nature and are ‘known risks’ for the victims, often resulting in direct localized temporary out-migration to relief sites. Within this characterisation of event-migration forecast, cyclones and hurricanes will likely result in short-term distress migration allowing populations to return and rebuild. Similarly, Munshi (2003) draws a link between movements into, and within the United States to changes in rainfall patterns particularly in regions relying on rain-fed livelihood systems. Reuveny (2008) also refers to the movement of about 2.5 million people displaced by drought and dust storms. During the 1930s, storms, forced over 300,000 people from the Mid West United States to neighbouring states like California in the world’s first case of eco-migration.
A similar migration scenario according to Fritz (2010) was the year 2000 floods which saw the displacement of about a million people in Mozambique. Building upon experiences from this event, Fritz points out that sudden and collective displacement are common in the face of such events but mostly result in temporary forms of migration as a survival strategy, stressing that the patterns of migration from weather events will be proportional to the degree or intensity of impact. He notes however that movements may become permanent if the disaster renders the habitation unsuitable for resettlement, or damages the prospects of re-establishing an economic base upon return as was the case in certain parts of Southeast Asia. A particular case Fritz notes was the 2004 tsunami which altered the patterns of fish-stock farming and resulted in the loss of shrimp farms thereby forcing an inland movement of shrimp farmers for alternative livelihoods.
Small, Van der Meer, and Upshur (2001) also draw attention to the displacement of about 100,000 people as a result of severe environmental crisis in the Aral Sea region in 1996.
Similarly, environmental degradation in Central Asia caused a multi-year drought beginning in the late 1990s which led to widespread unemployment in Karakalpakstan, a downstream
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autonomous region in Uzbekistan (Glantz, 2005). About 273,000 people (20% of the region’s total population) migrated to Kazakhstan and to the Russian Federation in search of better economic opportunities during the period of extreme drought in Uzbekistan between 1999 and 2001 (Glantz 2005). Small, Van der Meer, and Upshur (2001) observe that the level of vulnerability of the local population and the tendency to migrate was further heightened by poverty and ineffective governance with 48.8% of respondents preferring to migrate elsewhere in response to the loss of livelihood opportunities and inadequate institutional support.
Piguet, Pecoud and de Guchteneire (2011) note evidence in the literature that “drought and desertification are historically associated with population movements”. Environmental factors, the authors argue, ranked highly in the first systematic theories of migration with classical studies. Ravenstein (1889) for example explained that unattractive climate, in combination with other socio-political and economic factors resulted in a continuous migration current (Ravenstein cited in Piguet, Pecoud and de Guchteneire, 2011). The authors further identified a number of factors which are predicted to increase in significance due to climate change, as well as impact on human migration: (1) an increase in the intensity and frequency of tropical cyclones, heavy floods and rainfall, (2) increase in the incidence of drought and desertification, as well as (3) sea level rise (p. 2-3).
In line with Piguet et al, (2011) above, Rebetez (2011) identified certain climate parameters in which serious changes will likely impact human migration. These in the authors view, include temperature change and the longer term global warming; a reduction in melt-water, snowfall, melt and altitude which could adversely affect seasonal dynamics as seen in the Peruvian Andes where seasonal precipitation have declined for example; sea level rise;
changes in the general patterns of precipitation, as well as the frequency and intensity of hurricanes (Rebetez, 2011: 38-44).
Given the localized and location-specific nature of climate change impacts and adaptation requirements, a number of case studies on links between environmental variability and migration emphasize contextual factors as underpinning the level of exposure to events and the response generated among the populace (Downs, 1972; Ereaut and Segnit, 2006). Many agree that migration is often adopted as a mechanism for coping with environmental challenges in Bangladesh (Afsar 2005; Alam 2003; Asian Development bank, 2009;
Samaddar 1999; Siddiqui 2005). Asian Development Bank (2009) observes that international
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migration of unskilled labour have increased in Bangladesh substantially in recent years, with only 40% of migrant workers originating from just 5 of 64 districts44 in the flood-prone south.
In a controlled study on environment-related out-migration in Nepal, Bohra-Mishra and Massey (2011) found a strong and consistent correlation between environment-related population pressure and the likelihood of population movement. They noted that this linkage is in response to a growing difficulty of accessing and exploiting environmental resources such as firewood, fodder as well as declining agricultural yield. Echoing Suhrke (1994), they identify land degradation, desertification, flooding as a result of rising sea levels, and deforestation among the most important elements of environmental change which ultimately leads to out-migration (Bohra-Mishra and Massey, 2011: 74-75). It is against this backdrop that Raleigh and Urdal (2007: 678) warned that “while abrupt displacements may happen, we primarily expect to see climate change resulting in a gradual migration by people in search of more fertile land”.
2.4.2.1 Socio-economic Factors in Environment-induced Migration
With regards to predicting human migration in relation to environmental stress, studies are cautious enough to stress that migratory response to climate change does not occur in isolation. Socio-economic and political factors play important roles in shaping population responses to environmental stress hence the variation in adaptive capacity across cases:
individual, communal, and regional when exposed to similar environmental stressors (see Ngigi, 2009; Schmidt-Verkerk, 2009). The high vulnerability of the developing world is linked therefore, to the low systemic capacity to support adaptation resulting in high vulnerability in poor regions where large scale migration will occur due to high reliance on climate-sensitive natural resources amidst low political or institutional capacity for mediated adaptation (IPCC, 2012; Oliver-Smith and Shen, 2009).
Some studies also maintain that certain conditions of exposure constrain the possibility of migration (See for example, Henry, Schoumaker and Beauchemin (2004) on Burkina Faso, and Findley, 1994 on Mali), suggesting a reverse relationship in which declines in resources results in a reduction in the capacity for migration (Black et al., 2008). Attention is therefore
44 The 5 districts affected by large scale workers migration as a result of flooding risks in Bangladesh include Dhaka, Chittagong, Comilla, Tangail and Brahmanbaria.
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paid to other factors which, acting alongside environment-related vulnerabilities, result in migration. ACCES puts this succinctly thus:
[I]t cannot be assumed that climate change alone will lead to migration or displacement. Climate change plays an indirect role in such movements, by exacerbating existing vulnerabilities. Low “adaptive capacity” is an essential element of vulnerability to climate change, whether it is at the level of the individual, the family, the community/region, or the state. Adaptive capacity depends on factors such as demographic pressure, poverty, level of development (e.g. state provision of social safety net, basic services), weak or inequitable governance (land tenure being a key aspect), each of which can be important “drivers” of migration or displacement. At the level of the individual, and in addition to the above, other factors such as information/education, social networks, and physical condition can also influence the potential for environmental migration (ACCES, 2010: 18).
In the same vein, Schmidt-Verkerk, (2009) for example, argues that the relationship between environment and migration is a complex one which cannot be explained using a linear causal relation between for example, drought and population migration because a host of factors inform how people respond to environmental stress. Bronen, et al. (2009: 12) similarly observes that “diverse environmental events and conditions at multiple scales may cause and contribute to human migration and displacement”. Indeed, regardless of the levels of predictive confidence by scientists on the environmental change and migration nexus, causal analysis is acknowledged as “far from [being] a straightforward analysis” (Oliver-Smith, and Shen, 2009: 10).
In far-flung international migrations unlike local migration or cross-border movements, the role of socio-economic factors are particularly noted. Examining links between environment and international migration into Europe for example, Black et al. (2008: 6) argue that “It is difficult to imagine that people whose livelihoods are undermined by climate change will immediately embark on a journey to Europe or to North America as refugees in need of protection”. This is because the poor are regarded as lacking the capacity to migrate overseas due to the cost-intensive nature of international migration (Castles, 2000; De Hann, 2000;
Haug 2002; Meze-Hausken 2004; Schmidt-Verkerk, 2009; Skeldon, 2002).
Highlighting the need for case-based analyses of links between climate change and human migration, studies have warned against the tendency to present migration as a necessarily response to environmental variability and stress (Haug, 2002; Meze-Hausken, 2004; Schmidt- Verkerk, 2009). Schmidt-Verkerk (2009) for example, maintains that populations’ response
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to environmental stress will be informed by a variety of factors including the socioeconomic circumstance of the people, or the availability of, and capacity to sequentially deploy a range of coping strategies among which migration is often considered as a last resort. In sum, given the complex intervening factors including social and economic variables which influence the migration decision, it is important to avoid an over-simplification of the environmental change-migration nexus (Oliver-Smith and Shen, 2009: Schmidt-Verkerk, 2009).
2.4.2.2 Estimating Climate-induced Migration
Statistical estimate is an important component of modern policy decision making. The challenge of statistical evaluation therefore poses a major problem in social policy formulation in many areas of policy planning. This challenge manifests clearly in climate change-migration studies. As a phenomenon subject to multiple contingencies, isolating and estimating cases of migration informed by environmental factors in order to accurately quantify the affected populations poses a huge challenge. Indeed, it remains one of the most controversial aspects of environmental migration research (Black et al. 2008; Gomez, 2013;
IPCC, 2012). The complexity of variables which influence populations’ vulnerability, capacity to adapt, or the impetus to move is combined with the absence of empirical data in constraining statistical accuracy in this regard. Some analysts have put it categorically that
“long term, empirical data on migration patterns in response to environmental hazards does not exist” (Raleigh, Jordan and Salehyan, 2008: 8).
Estimates are further constrained by definitional issues since “figures for the number of environmental refugees worldwide vary depending on the definition and the source of data”
(Kolmannskog, 2008: 8). The result is low confidence in the ability to assign direct causality to climatic impacts, or to the numbers of people affected (IPCC, 2012 cited in Gomez, 2013:
5). Similarly, Black et al. notes that “different causes of migration cannot be isolated from each other, since migration is a multi-causal phenomenon in which a range of factors are inter-related” (Black et al, 2008: 7). The inter-related nature of causal factors underlies the divergence of estimates and projections on environment-related migration.
Researchers advance different methods in attempts at deriving estimates of affected populations. McGranahan and Anderson (2007) quantify the number of people and the land area at risk as a result of sea level rise using a 10 meter scenario. Their study focused on density of areas such as China, India, Bangladesh, Vietnam and Indonesia, or by the share of
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the population, using Bahamas, Suriname, Netherlands, Vietnam and Guyana, and noted that migration appears to be increasing into more vulnerable places such as China and Bangladesh.
Based on EM-DAT data on previous disaster events, Raleigh Jordan and Salehyan (2008) attempted a representation using value mean percentages of an affected country’s population, including those killed or made homeless by seven of the most common chronic and sudden disasters.45 Their method involves tabulation of these disasters over time and regions and across countries, sampling them by income levels and political instability.
As a result of the divergence of scales, results vary extensively. Estimates given since the mid-1990s in a number of studies are often criticized by scholars who question the reliability of the data upon which such estimates were based.46 Studies such as McGregor (1994), Suhrke (1994), Kibreab (1997), and Black (2001) for example, have argued that Myers over- simplified the causal relation between migration and environmental factors, and that his study failed to provide data that sufficiently substantiates his predictions on the numbers of people to be affected.
Focus Migration (2009), puts the figure of persons that will likely be affected by environment-induced migration through events such as flooding, famine and desertification and similar threats at 24 million. Similarly, the German Advisory Council on Global Change (WBGU, 2008) estimates that climate-induced migration and its secondary impacts accounts for between 10-25%, of human migration globally—a number which according to Forced Migration (2009: 1), could amount to between 25-60 million migrants. Similarly, the United Nations University – Institute for Environment and Human Security (UNU-EHS) in Bonn puts the number of migrants displaced by environmental factors up to 2010 to be in the range of 50 million (UNU-EHS, cited in Forced Migration, 2009).
Other high-level policy actors have also given projections. For example, the Intergovernmental Panel on Climate Change (IPCC) projects a total of up to 150 million climate change migrants by 2050 (Acketoft, 2008). Another exhaustive study—the Stern
45 Emergency Events Database (EM-DAT) is a database maintained since 1988 by the Centre for Research on the Epidemiology of Disasters. It was supported initially by the World Bank and the Belgian Government. Its aim is to provides information and humanitarian support at national and international levels. See more at http://www.emdat.be
46 See Myers and Kent 1995, Myers 1986, 1993, 2001, and 2002.
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Review, working from a larger review of data and forecasts, submitted that there may be 200 million environmental migrants across the globe by 2050 (Stern Review, 2006). In its analysis, the Inter-Agency Standing Committee (IASC) (2008) also reviewed common estimates and projected that environmental degradation is likely to have displaced between 25 million to one billion people by the year 2050.
The inconsistency in projections and estimates on climate change-induced migration points not only to a dearth of accurate statistics and reliable climate-migration data, but also to the complexity of the challenge given variations in patterns across and within regions. It raises therefore, the imperative that more case-specific research is carried out on the subject in order to give a more accurate representation of localized experiences, and to also provide adequate data which may then be combined to arrive at a holistic picture of climate-related migration flows.
2.4.2.3 International Dimensions to Climate-induced Migration
Migration, including those occurring across nations, is one of the widely accepted consequences of climate change (Brown, 2008). Although scholars believe that climate is unlikely to bring about large scale wars between nations, it is acknowledged to play important roles in aggravating both national and international conflicts over distribution or access, heightening the likelihood of violence that may expand across national boundaries (WBGU, 2008). It is also argued that climate change results in significant numbers of cross- border movements, explaining calls for international legal measures to cater for environmentally displaced persons (Lopez, 2007; McAdam and Saul, 2010; Myers, 2002;
Naude, 2008; Norwegian Refugee Council, 2008; Onuoha, 2010).
There is some agreement among scholars that threats to human livelihoods within vulnerable nations will likely increase the number of livelihood induced out-migrations and influx risks especially into proximate regions (Siddiqui, 2005; Black et al, 2008). From this point of view, it is speculated that populations’ livelihood will be threatened by the effects of climate change such as desertification, sea level rise, coastal flooding, and heat waves especially in poor regions. All of these events, it is argued, will increase vulnerability in weak or fragile states, and amplify the impetus to move (WBGU, 2014). It is in this context that climate- related migration is recognized as a security concern in international security circles. In this