Climate Action

Living Edition
| Editors: Walter Leal Filho, Anabela Marisa Azul, Luciana Brandli, Pinar Gökcin Özuyar, Tony Wall

Climate Refugees: Why Measuring the Immeasurable Makes Sense Beyond Measure

  • Johannes M. LuetzEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-71063-1_81-1

Synonyms

Definition

Climate change-related human movement typically occurs within a complex web of commingled contributory causative factors. Hence the multicausality inherent in human movement makes attribution or disaggregation of causality an almost intractable problem. Nevertheless, climate change is now widely recognized as a key contributing migration push factor. Moreover, there is agreement among experts that its contribution to migration, relative to other causes, is growing. This suggests a possible, if not probable, influx in “climate refugees” (Reeves and Jouzel 2010), although this term is contested in the literature (cf. Zetter 2017; Ahmed 2018; see Box 1). Adopting a posture of “preparedness” emerges as an important priority for effective adaptation to climate change, where “migration” is seen not as a “failure to adapt” but rather as a “strategy to survive”. This discourse argues that quantitative scenarios of “climate refugees” are an essential prerequisite for anticipatory adaption to climate change.

Introduction

This chapter explores the topic of climate change and human migration (CCHM) within the broader framework of the United Nations Sustainable Development Goal (SDG) 13: Climate Action: Take urgent action to combat climate change and its impacts (UN 2019). More specifically, Targets 1 and 3 explicitly emphasize the need for anticipatory adaptation to climate change, envisaging progress as follows:
  • “Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries” (Target 1).

  • “Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning” (Target 3).

Situated within this context, discourses about CCHM typically comprise theoretical, practical, empirical, analytical, and computational challenges, among others. Importantly, adaptation to climate change in the global migration arena is a strategic human development and policy concern, which typically envisages a forward-thinking posture of “preparedness.” In short, safeguarding equitable sustainable development (Luetz and Walid 2019) makes the proactive engagement in the CCHM space a strategic and fertile undertaking (EC 2019).

In terms of content arrangement, this chapter is divided into three sections and organized as follows. Section “Multicausality and Disaggregational Difficulties” introduces the multicausality inherent in climate change-related human migration and discusses arising attribution challenges and disaggregational difficulties. Thereafter, section “Numerical Projections, Predictions, and Predicaments” outlines prediction problems in respect of making, proving, or disproving numerical projections of future CCHM. Finally, section “Concluding Synthesis: Catalyzing Anticipatory Climate Change Adaptation” provides a synthesis of the state of the art, concluding that in terms of promoting preparedness and anticipatory adaptation to climate change, measuring the immeasurable makes sense beyond measure.

Multicausality and Disaggregational Difficulties

The nexus between climate change and human migration is intricate, since cause-and-effect relationships can be difficult to establish. Any migrant’s decision to move is invariably influenced by numerous and often interrelated factors. Attempts to dissect a migrant’s resolve to leave, and disaggregating the mix of factors that underlie that decision into “environmental” and “non-environmental,” “climate related” and “non-climate related,” or “forced” and “voluntary” categories, can be daunting, if not outright impossible. To what extent is a migrant “pushed” out of his or her human habitat by environmental degradation – or “pulled” away from it by the promise of a better life elsewhere? And to what extent is climate change implicated, identifiable, and quantifiable as a driver in the environmental degradation that precedes the migration? And, how might the mixture of perceived causal factors be disentangled, proven, and substantiated (Myers and Kent 1995; Renaud et al. 2007; Brown 2008a, b; Laczko and Aghazarm 2009; McAdam 2010; Luetz and Havea 2018)? Moreover, the classifications are interconnected and interrelated: environmental degradation may trigger migration, but migration may also trigger environmental degradation (Myers and Kent 1995; Laczko and Aghazarm 2009). Goffman (2006) aptly articulates that “[o]ne classification may cause the other or, more likely, each drives the other in a vicious cycle of reinforcing degradations” (p. 6; cf. Brown 2007, p. 29). Expressed in simple language, it is very difficult to draw a clear dividing line between “forced” and “voluntary” migration in relation to environmental degradation or slow-onset climatic changes. While this may be possible theoretically or conceptually (e.g., “migration, [is] voluntary, and displacement … is forced” [ADB 2012, p. 9; linked to Foresight 2011]), it appears to be impossible, practically. Instead, in the view of the International Organization for Migration (Laczko and Aghazarm 2009), it is more expedient to imagine the issue of climate-related migration on a continuum, “ranging from clear cases of forced to clear cases of voluntary movement, with a grey zone in between” (IOM 2018, para 10).

Seeing that it is difficult to establish a “direct causal link” of linear nature between environmental degradation and population displacement, demonstrating “relative causal attributions” seems to be an even more vexing challenge (Foresight 2011). Moreover, causality may be further obscured by statistical “noise” as all people movements take place within the wider context of global trends, including population growth, urbanization, sprawl of slums, and globalization, among others (Foresight 2011; Hugo 2011; WBGU 2011; Ehrlich and Ehrlich 2013; UN 2017). Ascribing the entire urban drift to climate change-derived environmental degradation would be untenable, but dismissing climate change as a causal factor seems equally absurd. On the contrary, while commingled contributory causes cannot be uncoupled or neatly divided asunder, there is a clear sense that the “evidence for a distinctively anthropogenic ‘climate change signal’ in forced migration […] is mounting” (Brown 2007, p. 18). Hence there is widespread agreement among experts that climate change will increasingly emerge as a driver of environmental degradation, compounding existing pressures, exacerbating vulnerabilities, and leading to potentially fast-swelling numbers of displaced people (e.g., Brown 2007, 2008a, b; UN-OCHA 2009; Foresight 2011, p. 9). Even so, accepting climate change as one migration cause among numerous others should not be seen as problematic, given that most migration literature argues for multiple causes (e.g., Hugo 1996, 2010; Luetz and Havea 2018).

In summary, while aggregated migration causality is not easily disaggregated, the role of climate change in inducing or enhancing human migration – relative to other contributing causes – is both perceptible and growing, and the fallout in numerical terms may be both significant and unprecedented (WBGU 2007; Schellnhuber 2008; IPCC 2018). Relatedly and importantly, adaptation to climate change is predicated on an anticipatory posture of “preparedness,” which in turn implies the need for a state of “readiness” before ultimate certainties can be empirically proven “beyond doubt” (Luetz 2018). Hence, there is an argument that “conceiving the inconceivable,” “estimating the inestimable,” and “quantifying the unquantifiable” are invaluable for promulgating a more robust and future-oriented agenda for anticipatory adaptation to climate change. This seems to be of far greater benefit to migration-affected individuals and communities than debating whether “climate refugees” exist (Box 1). Possible quantitative scenarios are sketched next (section “Numerical Projections, Predictions, and Predicaments”).

Box 1 Do Climate Refugees Exist?

The concept of “climate refugees” is contested in the literature (cf. Zetter 2017; Ahmed 2018). In point of fact, climate-related human displacement is subject to well-known conceptual and practical challenges, scholarly debates, and terminological contestations, which are elaborated in the chapter entitled “Climate Change and Human Migration as Adaptation: Conceptual and Practical Challenges and Opportunities.” Relatedly, debates surrounding the definitional or associational appropriateness of different terminologies appear to have broadly divided academics into two camps (Brown 2008a, pp. 13–15), namely, those favoring the term “refugee” (e.g., Docherty and Giannini 2009) and those favoring the term “migrant” (e.g., IOM 2018). Importantly, the words “refugees” and “migrants” conjure up vastly different mental images and associations which seem to be, more often than not, indicative of the writers’ normative preferences, institutional or ideological allegiances, or underlying agendas (Zetter 2007; Cournil 2011, pp. 359–360). Hence, there is no consensus definition on people who are displaced (in full or in part) by the adverse environmental effects brought on by progressive climate change (ADB 2012), leaving a situation that has been described as “confusing” and “unhelpful” (Dun and Gemenne 2008, p. 10). Instead, different normative approaches and agendas have led scholars to propose a vast array of competing conceptualizations and dissimilar definitions.

Even so, pilot research on atoll islands in Bougainville/Papua New Guinea (Luetz and Havea 2018) has proposed a shift away from treating climate migrants (however they are to be conceptually classified) as passive consignees of “scholarly labels,” to placing them more firmly at the center of the definitional debate. There seem to be at least two reasons for a stronger local-level involvement of individuals and communities who migrate for reasons that may implicate climate change. First, there is a sense that some islanders may resist the categorization of “climate refugees” (McNamara and Gibson 2009; Luetz and Havea 2018). Second, there are suggestions that “local contexts, dialects and expressions (e.g., ‘Turangu’) have much to contribute terminologically with respect to more appropriately informing the definitional and conceptual constructs of policy and research discourses” (Luetz and Havea 2018, p. 23). Inclusivity in coining conceptualizations has already made advances in discourses about disability, and there is the hope that “inclusion” may be similarly normalized in the climate migration domain: “The ‘nothing about us, without us’ (Charlton 2000) cry within the disability discourse, calling for representation in a bureaucratic system of oppression and disempowerment, is hauntingly relevant” (Luetz et al. 2019, p. 120). Furthermore, inclusivity seems to be all the more pivotal as “consulting the unconsulted” is increasingly identified in the international development arena as a key concern and success factor for global poverty reduction, social justice, and environmental sustainability education (cf. Chambers 1997; Luetz et al. 2018, 2019; Luetz and Walid 2019).

NB: Pertinent conceptual and practical challenges and opportunities arising from CCHM are elaborated in the chapter entitled “Climate Change and Human Migration as Adaptation: Conceptual and Practical Challenges and Opportunities.”

Numerical Projections, Predictions, and Predicaments

Several researchers have published projections about possible numbers of people who may migrate on account of climate-related environmental changes. Estimates vary significantly, ranging from dozens to hundreds of millions of people. This section is limited in scope to 12 selected numerical prognoses and/or studies.

First, Myers and Kent (1995) posited:

[A]s increasing numbers of impoverished people press ever harder on over-loaded environments [and] if predictions of global warming are borne out … as many as 200 million people [could be] put at risk of displacement. (p. 1)

Subsequently, Myers (2006) increased his projection to 250 million (cited in Walker 2007, p. 14; Christian Aid 2007, p. 48, endnote 10; cf. Biermann and Boas 2010, p. 68).

Second, a World Bank Report (Dasgupta et al. 2007) estimated that:

[…] global warming could well promote SLR [sea level rises] of 1 m–3 m in this century, and unexpectedly rapid breakup of the Greenland and West Antarctic ice sheets might produce a 5 m SLR. […] [T]he overall magnitudes for the developing world are sobering: Within this century, hundreds of millions of people are likely to be displaced by SLR; accompanying economic and ecological damage will be severe for many. The world has not previously faced a crisis on this scale, and planning for adaptation should begin immediately. (pp. 2, 44)

Third, Rajan (2008) cautioned that:

as many as 120 million people could be rendered homeless by 2100 in both countries of India and Bangladesh. Given the proximity of Bangladesh to India and the large land area that would be inundated, it is also likely that the bulk of these people will end up being migrants in India, particularly in large cities in the interior that are already likely to face resource stress due to climate change and over-exploitation of groundwater and other ecosystem services. (p. 10)

Two snapshots (2050 and 2100) are excerpted from Rajan’s (2008) tabular presentation of potential future forced migrants (Fig. 1). In the event of sea level rises of 1 m, 3 m, or 5 m, 65.6 million, 91.9 million, or 118.2 million people, respectively, could be rendered homeless in Bangladesh and India by 2100 (Rajan 2008, p. 10; cf. Byravan and Rajan 2008, pp. 13–20).
Fig. 1

Estimates of migrants displaced by sea level rise from Bangladesh and India

Fourth, UNDP (2007) stated:

Sea levels could rise rapidly with accelerated ice sheet disintegration. Global temperature increases of 3–4 °C could result in 330 million people being permanently or temporarily displaced through flooding. Over 70 million people in Bangladesh, 6 million in Lower Egypt and 22 million in Viet Nam could be affected. […] The 1 billion people currently living in urban slums on fragile hillsides or flood-prone river banks face acute vulnerabilities. (p. 9)

Fifth, Sachs (2007) cautioned:

As global warming tightens the availability of water, prepare for a torrent of forced migrations. Human-induced climate and hydrological change is likely to make many parts of the world uninhabitable, or at least uneconomic. Over the course of a few decades, if not sooner, hundreds of millions of people may be compelled to relocate because of environmental pressures. […] We are just beginning to understand these phenomena in quantitative terms. Economists, hydrologists, agronomists and climatologists will have to join forces to take the next steps in scientific understanding of this human crisis. (p. 43)

Sixth, Schellnhuber (2009) speculated:

When we talk about a one metre rise in global sea level we are also talking about 500 million people who are going to have to look for new homes. And so far we do not have any instruments to manage this. (p. 77; cited in Luetz 2013, p. 42)

Seventh, the Stern Review surmised:

By the middle of the century, 200 million more people may become permanently displaced due to rising sea levels, heavier floods, and more intense droughts, according to one estimate. (Stern 2006, p. 56; attributed to Myers and Kent 1995)

Eighth, the Intergovernmental Panel on Climate Change (IPCC) also repeated Myers’ quantitative assessment:

If such projections [of extreme vulnerabilities] prove true, climatic change will create ‘environmental refugees.’ Even without the worst projected impacts, problems of both domestic and international migration are likely to be exacerbated. Myers (1993, 1994) cites estimates that there are about 10 million environmental refugees at present, and on the basis of a survey of projected impacts in vulnerable regions, estimates that this figure could rise to 150 million by the middle of the next century as a result of climate change. He sketches the immense social, economic, and political costs implicit in such movements, ‘pushing the overall cost far beyond what we can realistically envisage in the light of our experience to date … it requires a leap of imagination to envisage 150 million destitutes abandoning their homelands, many of them crossing international borders.’ Again, the poor seem most likely to suffer, though clearly such movements might also trigger broader ethnic or even international conflicts that could envelop whole societies. (IPCC 1995, p. 98; cf. p. 199)

Furthermore, in AR4, the IPCC (2007) concedes that:

[c]limate change may contribute to destabilising unregulated population movements in the Asia-Pacific region, providing an additional challenge to national security (Dupont and Pearman 2006; Preston et al. 2006). Population growth and a one metre rise in sea-level are likely to affect 200–450 million people in the Asia-Pacific region (Mimura 2006). An increase in migrations from the Asia-Pacific region to surrounding nations such as New Zealand and Australia is possible (Woodward et al. 2001). Displacement of Torres Strait Islanders to mainland Australia is also likely. (attributed to Green 2006; in Hennessy et al. 2007, p. 522)

Ninth, the NGO Christian Aid offered a prediction on the high end of the scale:

We estimate that, unless strong preventative action is taken, between now and 2050 climate change will push the number of displaced people globally to at least 1 billion. (Christian Aid 2007, p. 22, cf. pp. 1, 5)

Tenth, in 2010 the Global Forum on Migration and Development duly noted that:

exact impacts of climate change on migration and development are difficult to predict because of the wide variation in estimates of global numbers of people that could potentially be affected, and because of terminological differences. For example, estimates of people affected by climate-induced disasters between 2000 and 2004 mention some 240 million or 62 million a year. Another prediction suggests that up to 1 billion people may be forced to move between 2007 and 2050, which sounds a lot but, at some 23 million a year, is fewer than the estimates of 62 million a year for the period 2000–2004. (GFMD 2010, p. 38)

Eleventh, according to Brown (2011):

The most vulnerable country is China, with 144 million potential climate refugees. India and Bangladesh are next, with 63 million and 62 million respectively. Viet Nam has 43 million vulnerable people, and Indonesia 42 million. Also in the top 10 are Japan with 30 million, Egypt with 26 million, and the United States with 23 million. Some of the refugees could simply retreat to higher ground within their own country. Others—facing extreme crowding in the interior regions of their homeland—would seek refuge elsewhere. (p. 75; attributed to McGranahan et al. 2007).

Twelfth, the Foresight report criticized numerical projections of future climate migrants, cautioning that:

[e]xisting estimates of ‘numbers of environmental migrants’ tend to be based on one or two sources [referring to Jacobsen (1988; 10 million) and Myers and Kent (1995; 150 million)]. […] Furthermore, the methodology used in Myers [and Kent] (1995) has been criticised [Castles 2002; Castles 2011; Gemenne 2011] [because] it seems to negate the ability of those in low-income countries to cope with environmental events, presenting a relatively deterministic connection between risk and migration. […] By trying to count those who move, those who stay behind or are trapped in the context of environmental change may be overlooked […]. (Foresight 2011, p. 28)

The above discussion of selected numerical projections is admittedly incomplete (Luetz 2013, pp. 39–48). Even so, two observations emerge. First, numbers, authorities, methodologies, typologies, and conditionalities are divergent. Second, the numbers are all rather large (Fig. 2). In a paper for the United Nations High Commissioner for Refugees (UNHCR), migration researcher Richard Black (2001) observed: “At first glance, the data available on environmental refugees appears quite impressive, […but] the strength of the academic case put forward is often depressingly weak” (p. 2). Other scholars make similar observations: “[e]stimates […] are divergent and controversial” (Warner et al. 2009, p. 2; cf. Gemenne 2011).
Fig. 2

Selected commonly quoted projections

There seem to be at least four reasons why predictions of future climate change-related human movements are fraught with problems. First, human mobility takes place within the wider context of global megatrends, including population growth, urbanization, coastward migration, and sprawl of slums (McGranahan et al. 2007; Hugo 2011; WBGU 2011), which makes it virtually impossible to isolate the “climate-change-only” contribution to consequent human movement. With rapid urbanization continuing unabated, the United Nations Human Settlements Programme projects that by 2030 five billion people could be living in cities, with slum populations expected to double from one billion to two billion (UN Habitat 2006). Much of this growth takes place within the context of coastward migration (Cohen et al. 1997; UN 2016), which sees more and more people being concentrated in coastal megacities (e.g., Nicholls and Small 2002; WBGU 2006; UN 2017). According to the United Nations (2016), “[e]ight of the top ten largest cities in the world are located by the coast” (para 1), and according to Gommes et al. (1998), “21 per cent of the world’s human population live less than 30km from the sea” (cited in WBGU 2006, p. 40). According to the UN (2017), coastal communities “represent 37 per cent of the global population in 2017” (p. 1). With coastal population growth rates given at approximately “twice the global average” (WBGU 2006, p. 40; attributed to Bijlsma et al. 1996; cf. UN 2016), researchers synthesize that by the year 2030, about half of the world’s population could be living within 100 km of the sea (Small and Nicholls 2003; cited in WBGU 2006, p. 40; cf. UN 2016, 2017). In short, ascribing the entire urban and/or coastal drift to climate change would be absurd, but arguing that climate change is therefore not implicated as a major contributory migration enhancing determinant seems similarly untenable.

Second, demographic data are often old, poor, or incomplete, and most census data in developing country contexts are rarely detailed enough to provide nuanced insights into population displacements, especially those that are internal and/or induced by slow-onset causes (Myers and Kent 1995; Brown 2008a, b; Luetz 2017, 2018). Relatedly, the views and local realities of people affected by CCHM are often not sufficiently solicited and reflected in research studies even though “local contexts, dialects and expressions … have much to contribute [to] policy and research discourses” (Luetz and Havea 2018, p. 23). “There is therefore an argument that better data are urgently needed. This must include an unequivocal focus on "consulting the unconsulted” (Luetz et al. 2019, p. 115).

Third, dealing with future scenarios invariably involves elements of speculation and uncertainty. Brown (2007, 2008a, b) asserts that computer modelling techniques may not conclusively account for the combined impact of individual choice, variable future emissions, meteorological scenarios, and international climate change action. Stated differently, the multiplicity of issues involved creates a challenge for quantitative data collection and modelling, including data management, analysis, and synthesis. Precisely, how is multidimensional human vulnerability (or resilience) to be measured, quantified, compared, and computed across vastly divergent developing country contexts? How are computer models to manage the massive compound mix of data and variables, comprising climates, local communities, economies, inequalities, cultural customs, religious traditions, social classes, colonial legacies, gender relations, changeable adaptive capacities (e.g., ongoing learning), and evolving policy formulations, to name just a few (Piguet 2013, p. 157; attributed to Tacoli 2009)? Moreover, how are their interdependent relationships to one another to be understood or computed?

Fourth and, finally, the scope and scale of future climate change-related migration depends largely on actions taken today (e.g., mitigation), wherefore estimates of future climate migrants would necessarily be subject to caveats, conditionalities, and evolutionary changes. Since the future is hard to foresee and non-static, the question arises whether time-bounded numerical predictions are useful, especially if scenarios involve more distant futures which are naturally subject to greater uncertainty (Brown 2008a, p. 25). In short, and as the Danish physicist Niels Bohr (1885–1962) famously said, “[p]rediction is very difficult, especially about the future” (cited in Brown 2008a, p. 21). Notwithstanding, infinite possible future scenarios and infinitesimal certainties seem to converge around the following lowest common denominator consensus, namely, that:

[t]he avalanche of statistics above translates into a simple fact—that on current trends the ‘carrying capacity’ of large parts of the world, i.e. the ability of different ecosystems to provide food, water and shelter for human populations, will be compromised by climate change [and] that the international community has to face up to the prospect of large-scale displacement caused by climate change. (Brown 2008a, pp. 17, 41)

Or to synthesize the situation in the understated words of the United Nations Office for the Coordination of Humanitarian Affairs (UN-OCHA 2009), “[c]limate change is likely to lead to increasing rates of displacement” (p. 15). Given the apparent prediction problems discussed above, it seems to be essentially impossible to make, defend, prove, or disprove any accurate, verifiable, and robust projections of future climate change-related people movements. Notwithstanding, the figures nevertheless seem to serve an important purpose as they demonstrate that, concurrent with global megatrends (Hugo 2011; WBGU 2011), climate-related human migration may progressively evolve and manifest as a significant challenge in this century (Brown 2008a, pp. 17, 41; Schellnhuber 2008, 2009; IPCC 2018). Furthermore, the overall problem analysis does not imply that best “guesstimates” are superfluous or do not have an important role to play in alerting policymakers to prepare for potentially extraordinary and unprecedented impending sociodemographic changes. Relatedly and importantly, promoting “preparedness” should not be confused with encouraging or accommodating “alarmism,” as advocated in a study on migration in Bangladesh (Luetz 2018, pp. 73–74):

While accurate prognoses of future migrations are inherently difficult, if not impossible to make, this researcher measuredly rejects the use of the term “alarmist” on the grounds that its use seems to [incorrectly] insinuate exaggeration, a point corroborated by dictionary definitions of this word: “alarmist […] someone who is considered to be exaggerating a danger and so causing needless worry or panic” (McKean 2005, p. 36). In light of the growing body of evidence linking climate change to the erosion of livelihoods the notion of “exaggeration” appears not only scientifically ill-informed but also runs counter to the premise of preparedness which seeks to pre-empt problems before they materialise beyond reasonable hopes of resolution. Therefore, the mere possibility (not probability or certainty) of humanitarian scale displacements and resultant human suffering is seen here to be reason enough to invoke a response of preparation, irrespective of whether or not large displacements will ultimately materialise. While gargantuan challenges can lead to torpidity, inaction or so-called “paralysis of analysis”, the point bears repeating that the very notion of preparedness implies readiness before both need and certainty arise. As the United Nations has advocated regarding climate change adaptation: “Hoping—and working—for the best while preparing for the worst, serves as a useful first principle for adaptation planning.” (UNDP 2007, p. 198; in Luetz 2018, pp. 73–74)

Hence it is argued here that in terms of activating or maximizing anticipatory adaptation to climate change, measuring what seems to be essentially immeasurable still makes immeasurably more sense than running the risk that laissez-faire non-engagement may spawn unforeseen situations of violence and chaos. The “climate change-collective violence” nexus is well established in the literature, and there are indications that recent humanitarian-scale refugee movements have been, at least in part, fuelled by climate change-related causality (Breisinger et al. 2013; Wendle 2016; Levy et al. 2017; cf. Ahmed 2018). Hence the case to assist early, proactively, and preemptively remains clear and compelling.

Concluding Synthesis: Catalyzing Anticipatory Climate Change Adaptation

Climate change and human migration (CCHM) typically takes place within a complex context of commingled contributory causative factors. Hence the multicausality inherent in human movement makes attribution or disaggregation of causality an almost intractable problem. Discourses about CCHM are therefore commonly characterized by theoretical, practical, empirical, analytical, and computational challenges, among others. The challenges are well known (Brown 2008a, b; Gemenne 2009; Luetz 2013) and include deterministic constraints, compound cause-and-effect interrelationships, entanglement of “push” and “pull” factors, overlapping “forced” and “voluntary” categories, and intransigent difficulties involved in determining direct causal links of linear nature between environmental degradation and population displacement. Even so, the challenges also point to untapped opportunities for adaptation to climate change. As Myers and Kent (1995) have pointed out, if a migrant is:

putatively driven 60 percent by environmental factors and 40 percent by economic factors, or the other way round, this issue is not nearly so important as the fact that he or she is impelled to migrate and to seek refuge elsewhere—whereupon society at large should feel inclined if not obliged to do something about his or her plight rather than to debate the precise factors in the underlying motivation. (p. 29)

In synthesis, while the manifold and unsearchable motivations of a migrant’s decision to move will invariably remain impossible to discern, dissect, and/or compute, the question what to do about it is clearly of far greater consequence to the global climate change adaptation agenda than misguidedly expecting to first meet quasi-perfect scientific conditions for research that simply do not exist outside of hermetically sealed laboratories.

In respect of preparing for future scenarios of CCHM, section “Numerical Projections, Predictions, and Predicaments” discussed 12 selected quantitative prognoses. Further, the section also outlined pertinent prediction problems inherent in making, proving, or disproving numerical projections of future climate change-related human movement. To summarize, there is very little agreement among scholars on how to collate, analyze, and synthesize data into widely acceptable numerical model projections of future CCHM. Even so, this limitation needs to be kept in perspective of what can and cannot be conclusively established, both in terms of epistemological considerations and available empirical evidence. As Myers and Kent (1995) have pointed out:

In a situation of uncertainty where not all factors can be quantified to conventional satisfaction, let us not become preoccupied with what can be precisely counted if that is to the detriment of what ultimately counts […] absence of evidence about a problem does not imply evidence of absence of a problem. (p. 33)

Finally, there are indications that the preparedness paradigm long embraced by the disaster management community, which values proaction over reaction and preparing over repairing (Luetz 2008, 2013; IPCC 2012; UNISDR 2011, 2015), is also increasingly gaining currency in CCHM discourse, as evidenced by case study research in the Maldives (Luetz 2017) and Bangladesh (Luetz 2018; Luetz and Sultana 2019) and a “toolbox” for planned relocations (UNHCR 2017). Given that Targets 1 and 3 of SDG 13 explicitly envisage anticipatory adaptation to climate change (see section “Introduction”) corroborates the point that proactive engagement in the CCHM space is a fertile albeit underappreciated climate change adaptation priority. This opportunity offers development actors clear benefits in respect of supporting climate change-related migration as a favorable, underrated and comparatively benign form of adaptation to climate change (IOM 2010; Luetz 2013, 2017).

To recapitulate and to conclude, there are no agreed mechanisms to attribute or disaggregate conglomerate causality and no agreed projections in terms of future fallout. Even so, the adaptation potential remains clear, compelling, and underutilized. Expressed in simple preparedness prose, action or proaction is inherently preferable to inaction or reaction. Hence to catalyze anticipatory adaption to climate change, measuring the immeasurable indeed makes sense beyond measure. Or stated differently, preparedness presumes informedness, and informedness presupposes that accommodating approximation may be necessary where exactness is impossible. As the ancient philosopher wisely said, “It is the mark of an educated mind to rest satisfied with the degree of precision which the nature of the subject admits and not to seek exactness where only an approximation is possible” (Aristotle, Greek philosopher and scientist; 384–322 BC). Or to put it in the words of the well-known physicist and Nobel Prize winner, “Not everything that counts can be counted, and not everything that can be counted counts” (Attributed to Albert Einstein; cited in Garfield 1986, pp. 156, 311).

Postscript

Climate Migration: Bangladesh on the Move (Case Study)

A video documentary on case study field research conducted in Bangladesh (communities of origin and destination) was published by UNSW Sydney on 18 February 2015 and illustrates sociocultural and environmental issues and complexities. It is publicly available at https://youtu.be/PBJeelgnadU.

Cross-References

Notes

Acknowledgments

Grateful acknowledgment for essential support is made to the University of New South Wales (UNSW) and the development organization World Vision International (WVI).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.CHC Higher EducationBrisbane/CarindaleAustralia
  2. 2.University of New South Wales (UNSW)SydneyAustralia

Section editors and affiliations

  • S. Jeff Birchall
    • 1
  1. 1.School of Urban and Regional Planning, Department of Earth and Atmospheric SciencesUniversity of AlbertaEdmontonCanada