Climate induced rural-to-urban migration in Working paper

Climate induced rural-to urban migration in Pakistan

January 2016 Fahad Saeed Kashif Majeed Salik Sadia Ishfaq

This report has been produced as part of a series of preliminary papers to guide the long-term research agenda of the Pathways to Resilience in Semi-arid Economies (PRISE) project. PRISE is a five-year, multi-country research project that generates new knowledge about how economic development in semi-arid regions can be made more equitable and resilient to climate change.

Front cover image: A tent city at sunset, Hahirpur district, province, Pakistan © Save the Children CC2.0 https://creativecommons.org/licenses/by-nc-nd/2.0/legalcode

2 Climate induced rural-to-urban migration in Pakistan

Acknowledgements The authors are thankful to a number of colleagues who have contributed to the development and finalisation of this paper. Special thanks are due to Dr. Abid Suleri and Dr. Vaqar Ahmed (Sustainable Development Policy Institute, SDPI) for providing their valuable insights. We are also grateful to Dr. Bara Guèye (IED Afrique) whose insightful comments helped us further refine our study. Thanks are also due to Waheed Zafar (SDPI) who provided support in data collection and data entry. This study would not have been possible without the financial support of the PRISE project, which is funded by IDRC and DFID.

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4 Climate induced rural-to-urban migration in Pakistan

Contents

Acknowledgements 3 Boxes and figures 7 Acronyms 8 Executive summary 9 1. Introduction 11 2. Link between migration and urbanisation: the role of climate change 13 3. Migration, urbanisation and climate change: the Pakistani context 15 4. Potential climate migrants in Pakistan 17 4.1 Data and methodology 18 4.2 Results 18 5. Discussion 23 6. Conclusions and recommendations 25 6.1 Way forward 26 References 27

Climate Climate induced induced rural -ruralto urban-to-urban migration migration in in PakistanPakistan 5

6 Climate induced rural-to-urban migration in Pakistan

Boxes and figures

Box 1 Rural-urban migration and urbanisation policies 14 Box 2 Map of Pakistan 16 Box 3 Cropping seasons 16 Box 4 Climate models 17 Box 5 Socioeconomic modelling scenarios 19

Figure 1 Mean maximum winter temperature over Pakistan (°C) for the period 18 1971-2000 from Swedish Meterological and Hydrological Institute’s (SMHI) regional climate model RCA Figure 2 Wintertime heatwaves over Pakistan as simulated by RCA 20 Figure 3 District-wise wheat production based on 2008-09 Census 21 Figure 4 Number of severely poor people living in rural areas of each district based 21 on Naveed and Ali (2012) and 1998 National Population Census data Figure 5 Number of severely poor people living in rural areas of each district based 21 on Naveed and Ali (2012) and 1998 National Population Census data, but only for the districts producing wheat above the average threshold of all the districts Figure 6 Semi-arid based on Pakistan Meteorological 22 Department's station data for the period 1991-2010 Figure 7 Same as Figure 5 but for the semi-arid areas of Pakistan 22 Figure 8 Percentage of urban to rural population in Pakistan based on IPCC SSP2 23 scenario Figure 9 The feedback loop 24

Climate induced rural-to-urban migration in Pakistan 7

Acronyms

ADB Asian Development Bank AR5 IPCC’s Fifth Assessment Report CMIP5 Coupled Model Intercomparison Project Phase 5 CORDEX Coordinated Regional Climate Downscaling Experiment DESA Department of Economic and Social Affairs ESMs Earth System Models GDP Gross Domestic Product GoP IOM International Organization for Migration IPCC Intergovernmental Panel on Climate Change KPK PMD Pakistan Meteorological Department PRISE Pathways to Resilience in Semi-arid Economies RCA Rossby Centre regional Atmospheric climate model RCMs Regional Climate Models RCP Representative Concentration Pathways SALs Semi-Arid Lands SSP Shared Socioeconomic Pathways UNDP Development Programme WB World Bank WMO World Meteorological Organization

8 Climate induced rural-to-urban migration in Pakistan

Executive summary

Over the past 20 years, new insights have been gained about climate–human interactions and their impact on human mobility and migration. The most significant of these is the conclusion the Intergovernmental Panel on Climate Change (IPCC) draws in its latest assessment report, namely that the magnitude of human displacement and migration may increase during the 21st century due to climate change. Quantitative research on the role of migration and climate change is limited, however, given the complexity and unpredictability of climate-induced migration patterns (Black et al., 2011) and the heterogeneity of individual and collective responses to climate change. Moreover, the uncertainty surrounding climate science itself presents a challenge to predicting precisely the impact on human settlements (Banerjee et al., 2011). For most developing countries, the problem of climate-induced migration is compounded by the challenge of urbanisation that seems to couple with it (ADB, 2012). While a substantial proportion of the population in developing countries live in rural areas, it remains largely unknown how many rural people migrate internally to urban and peri-urban centres in response to climate change. This is important to understand, because most rural livelihoods are based on agriculture, and climate-induced losses in agricultural productivity have been shown to alter livelihoods (Barnett and Adger, 2007; Mueller et al., 2014), and this can potentially scale up urbanisation. Thus, for the purpose of this study, we analyse climate-induced internal migration in a developing country that is largely semi-arid and faces development challenges of urbanisation, rural , and associated agricultural decline. Pakistan is a low-middle-income country of 188 million people that ranks low in human development, with rural-urban disparities in poverty, income and development infrastructure. is widespread but more pronounced in arid and semi-arid zones. The country’s urban economy contributes 78% to the national gross domestic product (GDP) although it is home to one third of the total population (World Bank (WB), 2014; Hussain, 2014). With an urbanisation rate of 3% per annum (Kugelman, 2014), many Pakistani cities have informally grown into large agglomerations with about 35% to 50% of urban population reportedly living in informal settlements (WB, 2014; Kugelman, 2014). Government projections suggest that by 2030 more than half of Pakistan’s population will be residing in urban areas (GoP, 2014). Such estimates do not take into account the effects of climate change – on urbanisation, rural-urban migration, and population growth. Agricultural productivity in rural areas is affected by variations in climate variables such as average temperature and precipitation. Heat stress in particular has shown to affect agricultural productivity of winter crops (Qin et al., 2014), such as wheat, a staple food grown in semi-arid and arid areas of Pakistan. According to a longitudinal study by Mueller et al. (2014), the benefits of migration outweigh the moving costs, especially following heat stress or heatwave in the winter season, which results in migration of all forms. Thus, to some extent, climate change may play a role, albeit marginal, in pushing up rural-to-urban migration, which presently constitutes 40% of total internal migration in the country (Arif, 2005). The results of this study indicate that climate change acts in combination with many other socioeconomic determinants of migration. Climate shocks and slow-onset changes impact ecological conditions in rural lands that trigger

Climate induced rural-to-urban migration in Pakistan 9

shifts in agricultural productivity, thus eroding incomes of poor and marginal cultivators. Migratory decisions may be taken to escape from losses in rural incomes, which are variably intensified by climatic stress. We predict that by 2030 such changes are likely to be magnified in arid and semi-arid areas of Pakistan that are important in terms of wheat production and are home to large rural populations. Given the sensitivity of wheat crop to heat stress, we anticipate that decline in wheat production will affect rural poor and marginal households, who will be forced to cope. When coupled with prospects for improved life in urban centres, this will incentivise poor rural populations to out-migrate. Thus, while variability in weather patterns plays a role in influencing migration patterns, the development deficit in Pakistan’s semi-arid rural areas, paralleled by higher investments in urban centres, together lure potential migrants from rural areas to urban settlements. Thus, following are some initial recommendations of the study: • Managing rapid urbanisation: Study results show that rural-urban migration may contribute to unplanned urbanisation and expansion of megacities like , Lahore, and , which may disrupt urban well-being. Therefore, one viable way to overcome this challenge is to develop intermediate cities or towns (Jamal and Ashraf, 2004), which can serve as pivots between large cities and rural areas by facilitating access to markets for agriculture outputs (Hussain, 2014). • Monitoring of internal migration: The dearth of adequate data on rural-urban migrants hinders monitoring of internal migration flows, which presents a challenge to informed decision-making. Therefore, this study proposes a National Registration System that can capture population mobility data across Pakistan. • Risk management in agriculture sector: Risk management in the agriculture sector needs innovative financial support mechanisms that improve poor farmers’ access to finance during climate shocks (e.g. crop insurance to protect against crop failures). • Improved rural and urban service delivery through decentralised governance: The revival of local governments under the 18th Constitutional Amendment is important for curbing rural-to-urban migration. Service delivery for rural and local populations is likely to increase; this would, however, need to be complemented by improved service provision in urban slums, which are likely to absorb the influx of informal rural migrants. • Integrated approach to ‘climate-proof’ development: Given Pakistan’s high vulnerability to climate change, and its existing level of development challenges, the country requires an integrated and multi- sectoral approach to climate-resilient economic development. Sectoral policies on population, agriculture and food security, environment, poverty alleviation and economic growth need to propose specific measures for climate resilience, as highlighted in National Climate Change Policy in 2012 and ‘Framework for Implementation of Climate Change Policy (2014-2030)’.

10 Climate induced rural-to-urban migration in Pakistan

1. Introduction

Over the past 20 years, new insights by socioeconomic and climate living conditions (environment, have been gained about climate- trends. sanitation, human security), and human interactions and their impact political stability. Recent studies Emerging literature identifies on human mobility and migration. have identified additional factors – migration patterns as either The most significant of these is the such as age, education, marital permanent or temporary (seasonal conclusion of the latest Inter- status, personal choices, community or cyclic) that may be internal (within governmental Panel on Climate perceptions and network a country) or international (across Change (IPCC) assessment report: connections (especially with earlier countries) (UN Department of that the magnitude of human migrants) – in framing migration Economic and Social Affairs (DESA), displacement and migration may rise patterns (Ketel, 2004; Reuveny, 2011). IPCC describes migration as during the 21st century due to 2007; Brown, 2008). a multi-causal phenomenon climate change. Estimates indicate characterised by a permanent or In order to understand the quantum that climate change effects – semi-permanent move by a person of migration, development including rainfall shifts, heat stress of at least one year that involves organisations have made concerted and water scarcity – may motivate crossing an administrative, but not efforts in recent years to monitor anywhere from 25 million to 1 billion necessarily a national border (Brown global migration. The World Bank people to migrate by 2050 (Myers, and Bean, 2005). Although has been publishing a yearly 2005; Parry, 2007; Lovell and historically humans migrated in Migration and Remittances London, 2007). Those most likely to response to variability in local Factbook since 2008, and the migrate will be populations living in conditions (Foresight, 2011), earlier International Organization for precarious and vulnerable conditions, streams of research have focused Migration (IOM) has annually especially in rural areas of arid and more exclusively on migration’s published World Migration Report semi-arid regions, where there is a socioeconomic determinants. since 2009. Yet although high dependency on climate- Recent migration literature has, international migration and internal sensitive, ecosystem-based however, examined migrant moves displacement has received livelihoods. Such mass movements in light of various causation factors, considerable interest in academic are likely to be from rural areas to which include access to capital, and development circles, research urban agglomerations, in line with finance, economic opportunities, on internal migration and climate- present trends (Qin et al., 2014). governance, social capital and induced migration has been slow to Presently, a major proportion of environmental conditions (Mazumdar, emerge. This is despite the global migration is internal (about 1987; Irfan, 1986; Etzo, 2008; Kolev, availability of some data at country 80%), most of it from rural areas to 2013). These can be broadly level on human mobility. Moreover, urban settlements (Qin et al., 2014). classified under two categories: although in developing countries a Based on these trends, global urban push factors and pull factors. substantial proportion of people live population is estimated to rise to in rural areas, it remains largely Push and pull factors arise due to 59% by 2030, as compared to 10% unknown how many rural people socio-political, environmental and/or in 1900 and 50% in 2009 (Grimm et migrate to urban and peri-urban economic conditions of a country, al., 2008). This implies that climate areas in response to climate change. that drive migrants to move from an change may not only alter migration This is important to understand, imbalanced place to a balanced patterns but also increase because most rural livelihoods are place (Black and Sward, 2008). urbanisation rates especially in based on agriculture, and climate- Push factors are generally related to developing economies. However, induced losses in agricultural the place of origin; examples include given the dearth of empirical productivity have shown to alter poverty, illiteracy, limited economic evidence, much of this research livelihoods in those countries opportunities, conflicts, natural remains speculative in nature, (Barnett and Adger, 2007; Mueller et disasters, and climate hazards, leaving the climate-migration al., 2014), which can potentially among others. Pull factors are discourse inconclusive (Black et al., intensify and scale up urbanisation. related to the place of migrant 2011). Picking from the Additionally, rural poverty, often destination, attracting people to recommendations of IPCC Fifth associated with landlessness and certain locations. Examples of pull Assessment Report (AR5), this study lack of access to assets (Naveed factors are access to better offers local insights on climate- and Ali, 2012), may also trigger rural- economic opportunities, basic induced internal migration in to-urban migration. Attempts to services (education, ) and Pakistan that is continually redefined escape from rural poverty may add Climate induced rural-to-urban migration in Pakistan 11

to urbanisation problems by exerting challenges of urbanisation, rural implications for urbanisation. Section pressure on urban services and poverty, and associated agricultural 3 reviews similar issues but in the infrastructure, exposing the urban decline. Another major aim of this national and sub-national context of residents to increased risks. study is to develop a methodology Pakistan. Section 4, based on to identify potential ‘hotspot’ regions robust research methodology, Based on these observations, this where future research on climate- provides scientific evidence on study, which serves as a Deep Dive induced migration can be carried out potential migrants of Pakistan. Lastly, for the Pathways to Resilience in during the course of the PRISE Section 5 expands upon the Semi-arid Economies (PRISE) project. discussion, and Section 6 draws project, focuses on how rural-to- conclusions, makes urban migration in Pakistan can best This study is structured into three recommendations, and points the be understood in the context of main sections. Section 2 reviews the way forward. long-term climate change. It role of climate change in influencing analyses climate-induced migration global patterns in rural-urban in the context of development migration, and the subsequent

12 Climate induced rural-to-urban migration in Pakistan

2. Link between migration and urbanisation: the role of climate change

Human migration has been (Barnett and Adger, 2007). Poverty, climate change will impact migrants occurring notwithstanding climate inequality, and market and in new settlements (e.g. cities) and change. However, scientific institutional failures have shown to what the direct impacts on human evidence suggests that be the major causes of migration, as mobility will be. It is particularly environmental change has played a indicated in the literature on famines challenging when the relation role in shaping human mobility and (Barnett and Adger, 2007). Not between climate change and settlement patterns since the surprisingly, growing scientific migration is not linear (McLeman and Holocene (McKone et al., 1998; research attributes migration as a Smit, 2006; Mueller et al., 2014) and Hughes and Brown, 1992; transformational adaptation to is dependent on a multitude of Richerson et al., 2001; Morgan, climate change (Qin et al., 2014; factors (Black and Sward, 2008; 2009). Temporal and spatial Massey et al., 2010; Warner, 2010; Black et al., 2011; Barnett and variation in resource productivity due McLeman and Hunter, 2010; Adger, 2007; Banerjee et al., 2011). to environmental variability Hoermann et al., 2010; Smith and Patterns in climate-induced compelled people (‘the hunter- McNamara, 2014), where people migration seem to couple with gatherer’) to migrate (Halstead, move out from high-risk areas to urbanisation (ADB, 2012), which 1989) and helped them to improve their access to most developing countries face agglomerate around intensified opportunities and livelihoods and today. In most developing countries, settlements for reduced exposure to minimise their vulnerability to risks overspending of development risks (Low, 1990; Morgan, 2009). (Tacoli, 2009). Indeed, many budget in urban areas increases the Even today, climate change developing countries (such as ‘pull’ factor, which combines with continues to trigger human Bangladesh, Eritrea, Ethiopia, Haiti, the ‘push’ of environmental displacement and migration (Parry, and Mali) officially recognise challenges in rural areas to influence 2007; Qin et al., 2014) by acting as migration and displacement as an people to out-migrate. Thus, urban a ‘macro driver of many kinds of adaptation option against climate areas become a ‘magnet’ for rural environmental changes’ that trigger disasters in their National Adaptation migrants and underemployed labour, shifts in local environmental and Programmes of actions (Banerjee et spurring urbanisation (Hussain, biophysical conditions (Barnett and al., 2011). However, other scholars 2014). Climate change can Adger, 2007). These changes may see migration as a failure to cope temporarily or permanently increase be slow-onset or sudden. The slow- with climate change (Warner, 2010), migration flows to cities (Adamo, onset environmental changes since the locals move out of rural 2010), which calls for policy include decline in biodiversity, places and into urban settings measures to accommodate migrant changes in water flows, degradation (transformative adaptation) instead influx. Apart from climate change, of ecosystems services, shifts in of adapting while staying in the rural-to-urban migration has been agricultural productivity, and soil same place (in situ adaptation). posing different challenges in the degradation (Hoermann et al., 2010). Quantitative research on the role of past, has resulted in the Sudden or rapid climatic changes migration and climate adaptation is, development of various policies at include increase in extreme events however, limited, given the national and sub-national levels. A such as extreme rainfall, flash floods, complexity and unpredictability of brief description of some of these glacial lake outburst floods, droughts, climate-induced migration patterns policies is presented in Box 1. heatwaves, etc. In response to such (Black et al., 2011), and the environmental changes, many While migration may hold economic heterogeneity of individual and populations out-migrate voluntarily potential for places of both migrant- collective responses to climate or by compulsion (Kalin, 2010; origin and destination (ADB, 2012), change. Moreover, the uncertainty Hoermann et al., 2010). urbanisation presents many surrounding climate science itself challenges, particularly in developing But climate change rarely acts alone presents a challenge to predicting countries (Özden and Enwere, 2012; to push out-migration. It couples precisely the impact on human Black et al., 2011). Large changes in with socioeconomic, political and settlements (Banerjee et al., 2011). mobility patterns have the potential ecological stresses to unsettle Making such a prediction includes to induce pressure on infrastructure human populations (Black et al., asking questions about how people and service delivery in destination 2011; McLeman and Smit, 2006) will migrate – and how many – as a areas, resulting in competition and through drastic social change result of climate change, how Climate induced rural-to-urban migration in Pakistan 13

Box 1: Rural-urban migration and urbanisation policies

Policies that directly and indirectly address migration and urbanisation issues can generally be classified into negative, manipulative and preventive policies (Mahmud et al., 2010). Negative policies refers to the use of force to limit the migration rate, such as enforced relocations from urban to rural areas, demolishing of unlawful settlements and prohibition of emigrant movement to cities (Parnwell, 1993). The manipulative approach seeks to redirect the migration flows, through policies facilitating urban, industrial and administrative decentralisation. This approach considers migration to be unavoidable for economic growth, and hence tries to capitalise the potential of value addition from the redirection of migration flows. The preventive approach generally involves creating more opportunities in the rural sector in order to prevent migration flows by reducing push and appeal to pull factors at home and destination place respectively. This is usually done by measures such as introduction of land reforms, agriculture intensification, agriculture extension, and rural infrastructural investment (Tacoli, 2003). The issue of migration receives little attention in Pakistan’s rural-urban development planning. For example, while the prevalence of poverty in rural and urban areas largely influences migration and urbanisation patterns, the Government’s Strategy Paper (PRSP) and recently approved Vision 2025 fail to provide any strategy relevant to current and future urban planning or migration. A draft National Emigration Policy exists, but it discusses international migration issues exclusively, with no focus on internal, rural-urban migration.

conflict (Locke, 2009; Barnett and vulnerable to climate change risks, In the case of Pakistan, which is the Webber, 2010). Although especially the informal urban fastest urbanising country in South urbanisation provides opportunities settlements or slums (Qin et al., , the phenomenon of rural-to- for growth, it also causes income 2014). The major climate risks to urban migration is emerging as a disparities within and between urban such areas include heat stress, major development challenge. and rural areas (Hussain, 2014). In extreme precipitation, storm surges, However, lack of research in this some places, newly arrived migrants inland and coastal flooding, area leaves a knowledge void that in urban localities may be as landslides, drought, increased aridity, hinders meaningful policy-making vulnerable to climate hazards as water and energy insecurity and air and its implementation. In light of they were in their places of origin pollution. These may cause this, the next section discusses the (Black et al., 2011). widespread negative impacts on relationship between urbanisation, human health, livelihood, property, rural-to-urban migration and climate The IPCC reports with medium and overall economy and change in the context of Pakistan. confidence, high agreement, and ecosystems. medium-level evidence that urban centres across the world are highly

14 Climate induced rural-to-urban migration in Pakistan

3. Migration, urbanisation and climate change: the Pakistani context

Pakistan is a low-middle-income A handful of scientific studies and 2010). Remarkably, a majority of country of 188 million people that grey literature have tried to explore rural migrants tend to move toward ranks low in human development, the relationship between these districts having high population with rural-urban disparities in poverty, interlinked factors. These suggest densities. For example, 63% of the income and development that agricultural productivity in rural people who migrated in the last ten infrastructure. The country is mainly areas is affected by variations in years moved to an urban area, with semi-arid, and the agriculture sector climate variables such as average 56% moving to the provincial or the is the largest employer, formally temperature and precipitation. Heat federal capital (Mahmud et al., 2010), engaging 44% of the workforce stress in particular has shown to mainly due to family networks and (68% in rural areas) (GoP, 2014). affect agricultural productivity of higher concentrated development in Subsistence agriculture is winter crops (Qin et al., 2014). For these areas. In a more focused predominant in rain-fed areas, example, the production of wheat internal migration study carried out whereas irrigation-based farming is crop, a staple food consumed by in Faisalabad district, Farooq et al. common in semi-arid zones that most , may decline by 5- (2005) found that 80% and 13% of have more sustainable access to 25% as a result of climate change the respondents were ‘pushed’ out water. Pastoralism is common in (Sultana et. al, 2009). Similar results due to poor economic and arid areas, where poorer were obtained by Majid and Zahir educational opportunities communities migrate seasonally for (2014) while studying climate change respectively. Such research food, water and fodder. Rural impacts on farm productivity and suggests that historically migration in poverty is widespread but is more socioeconomic vulnerabilities in Pakistan has been associated with pronounced in arid and semi-arid Punjab and Sindh. According to differential in rural-urban labour zones. It is often associated with them, drought is the most important productivity, human development, landlessness and exposure to climate phenomenon that urban investments, and climate risks and is accompanied by significantly impacts crop yields of technological advances (Irfan, 1986; insecure access to basic necessities wheat, rice, cotton and sugar cane. Khan et al., 2000; Mahmud et al., (Chun, 2014). Overall, about 50% of Decline in crop yields negatively 2010). the rural population is landless (WB, impacts tenant farmers, compelling It can be inferred from the 2002), whereas small farmers own them to seek alternative livelihoods discussion above that although there 86% of farms (farm size of less than and sometimes even to move to are studies focusing on climate 12 acres) (GoP, 2009). urban settlements (Majid and Zahir, change, food security, urbanisation 2014). This is similar to the seminal In contrast, Pakistan’s urban and migration, these issues are often work by Mueller et al. (2014), economy contributes 78% to the researched in isolation. In the discussed in more detail in later national GDP although it is home to following section, the link between sections, which finds that internal one-third of the total population (WB, migration and urbanisation in relation migration in Pakistan is caused to 2014; Hussain, 2014). With an with climate change will be some extent by heat stresses. There urbanisation rate of 3% per annum established. Moreover, in contrast to are other studies that independently (Kugelman, 2014), many Pakistani earlier studies, which focused on explore internal migration flows cities have informally grown into certain regions or districts, the across Pakistan. large agglomerations with about analysis presented in this study is 35% to 50% of the urban population In a pioneer study, Irfan (1986) carried out at the national scale. reportedly living in informal estimated that 42% of all migrants in settlements (WB, 2014; Kugelman, Pakistan moved within districts, 39% 2014). Government projections across districts, and 19% across suggest that by 2030 more than half provincial boundaries. A more recent of Pakistan’s population will be study by Arif (2005) estimates rural- residing in urban areas (GoP, 2014). to-urban migration to constitute Such estimates do not take into 40% of total internal migration. account the effects of climate Provincially, rural-to-urban migration change – on urbanisation, rural- is lowest in Sindh and Balochistan urban migration, and population followed by Punjab and Khyber growth. Pakhtunkhwa (KPK) (Mahmud et al., Climate induced rural-to-urban migration in Pakistan 15

Box 2: Map of Pakistan

Pakistan is a major country in having an area of 796,096 sq. km. The map below shows the topography of the country (in metres) which is a profound blend of plains, deserts, hills, forests, and plateaus ranging from coastal areas in the South to the mountains in the North. The administrative units of Pakistan consist of four provinces (Punjab, Sindh, Khyber-Pakhtunkhwa and Balochistan), two autonomous territories (Gilgit-Baltistan and Azad Kashmir), and a group of federally administrated tribal areas (FATA). Pakistan is bordered with People’s Republic of China to the north and India to the east while borders the country in the north-west and Iran to the west.

Source: author

Box 3: Cropping seasons

Pakistan has two major cropping seasons. Summer, or ‘kharif’, crops are sown from April to June and harvested from October to December; while winter, or ‘rabi’, crops are sown through October-December and harvested April-May. Winter crops generally include wheat and mustard.

16 Climate induced rural-to-urban migration in Pakistan

4. Potential climate migrants in Pakistan

Given the definitional issues and the regions of Pakistan. The study is for the poor, the benefits of dearth of reliable and consistent based on a 21-year longitudinal migration outweigh the moving costs, official data on internal mobility, survey conducted in rural Pakistan especially following extreme migration flows are difficult to (1991-2012) that explores the heatwaves / heat stress, which calculate without substantial error relationship between weather and results in migration of all forms. (Irfan, 1986; Mahmud et al., 2010). long-term migration. Mueller et al. This study by Mueller et al. (2014) is The last population census was analysed key weather variables at one of the few studies found in conducted seventeen years ago, in village level, including cumulative published, peer-reviewed literature 1998, and did not include any rainfall during monsoon (June- (with Impact Factor) that link human information on the place of birth. The September), average temperature migration with weather variables in government of Pakistan annually during winter (November-April) when Pakistan. We therefore make this publishes the Labour Force Survey wheat is grown, a 12-month study the basis of our present with modest information on labour moisture index, and flood intensity in research. Since the scope of the movement, but it fails to capture terms of number of deaths caused. above-mentioned study is conclusive data on inter- and intra- The study reveals that extreme high permanent migration, our study district migrations. Furthermore, temperatures in the winter season therefore also focuses on permanent despite the availability of sufficient are strongly correlated with internal (rural-to-urban) migration climate data, projecting the impacts migration, as compared to other that results from long-term climate of climate change on urbanisation variables. Further, high temperatures change rather than from sudden and internal migration trends is during winter season wipe out over climate disasters. difficult given the complex one third of agriculture yields, and interrelationship between these therefore the magnitude and In the sections below, the link multi-causal phenomena. Not statistical significance of the between migration, heat stress and surprisingly, very few studies estimates are most pronounced for climate change is established in focusing on climate-induced the land- and asset-poor, and their relevance with wheat production and migration in Pakistan can be found moves are mostly out-of-the village poverty in the national context. This in peer-reviewed literature, as moves. It is argued that the poor is followed by identification of semi- indicated above. may have more locational flexibility arid regions across Pakistan that are as they are not tied to land or assets, hotspots of potential migration, One such study, published in Nature which can be hard to sell and are at which is the main focus for future Climate Change, is by Mueller et al. risk of loss if unattended. Hence, PRISE studies on migration. (2014) and addresses the issue of Mueller et al. (2014) conclude that rural-to-urban migration in semi-arid

Box 4: Climate models

Today, climate models, or more specifically the Earth System Models (ESMs), are considered to be the state-of-the-art numerical tools to carry out global climate simulations. The general circulation of the atmosphere can be effectively simulated by ESMs. However, the resolution of these ESMs is coarse, typically of the order of 150-250 km. Therefore, many regional-scale climatic features go beyond the scope of ESMs. In lieu of this, a regional climate modelling technique was developed to downscale the coarse ESMs results to the regional scale. These models are called Regional Climate Models (RCMs). RCMs have a typical horizontal resolution of 50-10 km, and even down to 1 km in some instances, on time scales up to 150 years (Saeed et al., 2009, 2014).

Climate induced rural-to-urban migration in Pakistan 17

Figure 1: Mean maximum winter temperature over Pakistan (°C) for the period 1971-2000 from Swedish Meterological and Hydrological Institute’s (SMHI) regional climate model RCA

Source: author

4.1 Data and we define a heatwave in the winter 4.2 Results season as more than six methodology consecutive days with a daily Answers to the following questions In order to predict the pattern of maximum temperature that exceeds will be addressed in this section: (1) heatwaves over Pakistan till 2030 the average maximum temperature In which areas of Pakistan are (PRISE time frame), we used data of (of the winter season) by 5 °C. heatwaves projected to increase in a regional climate model. A brief Where this occurs, it is considered future? (2) Are these areas also the description of climate modelling is as a heatwave and applied to RCA4 major wheat-producing areas in the presented in Box 4. The data of the data. In order to be consistent with country? and finally (3) Do these Rossby Centre’s regional Mueller et al. (2014), the data of areas of the country also have a high Atmospheric model (RCA4) has winter months from November to incidence of severe poverty? Further, been analysed over CORDEX April has been analysed. we relate these linkages with (Coordinated Regional Climate incidence of severe poverty to Finally, to map the potential internal identify ‘hotspots’ for future climate- Downscaling Experiment) South climate migrants in Pakistan, the Asian Domain forced by EC-Earth induced migrants in Pakistan. estimates of district ranking over the Afterwards, an identification of model. It is worth mentioning here incidence of severe poverty, that CORDEX is an initiative by the hotspot regions for the PRISE developed by Naveed and Ali (2012), project’s future internal-migration World Climate Research Project to along with the total rural population downscale CMIP5 (Coupled Model study is also carried out, with a data of each district obtained from particular focus on semi-arid regions. Intercomparison Project Phase 5) 1998 Census, have been used in simulations using different RCMs this study. In addition, a district-wise Future trend of heatwaves over different domains around the map of wheat production has been The analysis of average maximum globe. For this study, we used developed based on data from temperature data for the base winter RCA’s data of control (1970-2000) Agriculture Census 2008-09. as well as future (2010-2030) period period (1970-2000) for Pakistan is using RCP8.5 concentration In order to further strengthen our presented in Figure 1. A high spatial scenario, also called a ‘business as research, we have also used IPCC’s variation in the map can be seen, usual’ scenario (Riahi et al., 2011). urbanisation scenarios. The recent with highest temperatures found in The data was obtained from the AR5 IPCC report is based on newly the province of Sindh as well as database of the Centre for Climate developed SSPs (Shared along the Arabian Sea coast, Change Research at the Indian Socioeconomic Pathways). Some followed by the plains of Punjab, and Institute of Tropical Meteorology, details about the SSPs are then in the provinces of Balochistan Pune.1 In line with WMO definition, presented in Box 5. In the study we and Khyber Pakhtunkhwa. Smallest use the urbanisation data from SSP2 values of maximum temperatures scenario, which is also called the are found in the northern areas of 1 http://cccr.tropmet.res.in/cordex/files/downloads.j ‘middle of the road’ scenario. the country characterised by high- sp elevation snow and glacier-fed

18 Climate induced rural-to-urban migration in Pakistan

catchments. In the top panel of more pronounced over the arid and Sindh where the number of Figure 2, the number of days where, semi-arid plains of the Punjab and heatwave days was less than 350 in intervals of at least 6 consecutive Sindh provinces, as well as parts of days in the decade 1971-80, the days, maximum temperature Balochistan adjoining Iran. number is likely to increase to more remains more than 5°C above the Furthermore, over the northern part than 425 by 2021-2030. Therefore, average maximum temperature data of the country, which is to answer the first question – In of Figure 1 is presented for the characterised by complex which areas of Pakistan are decades 1971-1980, 1981-1990 topography containing high peaks, heatwaves projected to increase in and 1991-2000 (control period). It this trend is least pronounced. future? – these results clearly show should be noted that Figure 2 that the trend in the occurrence of The bottom panels of Figure 2 show represents the number of days that heatwave days will be positive till the results for RCP8.5 for the fall within the criterion. For example, 2030, and the arid and semi-arid decades 2011-2020 and 2021-2030 if there are only 4 consecutive days regions will have the greatest (future period). These results are where maximum temperatures number of heatwave days. again obtained using the WMO’s remain more than 5°C above the definition described above, where average maximum, then these 4 Wheat growing districts the same base period from 1971- days do not fall under the mentioned in Pakistan 2000 is considered as reference as criterion and hence will not be shown in Figure 1. Unlike in the base In order to answer the second counted towards Figure 2. However, period, the increase over the question in subsection 4.2.1, if there are 8 consecutive days that northern areas is obvious from the regarding how much wheat is grown fulfill the criterion, then all of these 8 bottom panels of Figure 2. Generally in the areas showing an increase in days are counted as the heatwaves an increase in heatwave days can be heatwaves, district-wise wheat days. It can be seen from Figure 2 seen over the whole country, and, in production is plotted in Figure 3 that there is generally an increasing line with past trends, the increase is based on the Agriculture Census of trend of number of heatwave days likely to be most pronounced over 2008-09. Figure 3 shows that the throughout the country during the the arid and semi-arid plains of wheat production is highly areas control period. However, this trend is Punjab, Sindh and western where the heatwaves are projected not spatially consistent. A substantial Balochistan. It can also be noticed, to increase substantially in future as increase in the number of heatwave from the bottom panels of Figure 2, shown in Figure 2. days can be observed over the that over the areas of Punjab and whole country, but this increase is

Box 5: Socioeconomic modelling scenarios

In SSP scenarios, along with population and GDP scenarios developed by other institutes, the scenarios for future urbanisation trends are developed by the National Center for Atmospheric Research (NCAR) (https://secure.iiasa.ac.at/web-apps/ene/SspDb/static/download/ssp_suplementary%20text.pdf). For SSP, there were in total five story lines, with each one providing a brief narrative of the main characteristics of the future development path of an SSP (Kriegler et al., 2012). SSP2 scenario assumes the continuation of the present trends of urbanisation in all parts of the world, along with similar middle of the road assumptions about population growth, technological change and economic growth. In this scenario, it is assumed that the developed high-income countries continue their practices in urban development, whereas the developing countries generally follow the historical urbanisation experiences of the more developed countries.

Climate induced rural-to-urban migration in Pakistan 19

Figure 2: Wintertime heatwaves over Pakistan as simulated by RCA

Note: the legend shows the number of days per decade associated with heat waves in the winter seasons. The top panel shows the control period, whereas the bottom panel shows the future period using RCP8.5. Source: author Assuming that an increase in associated with agriculture but also The different colour scales indicate heatwaves will negatively impact those who generate incomes by the number of people living in wheat production, as reported in the providing goods and services to extreme poverty. The deeper the latest scientific literature and IPCC landowners. Therefore, in order to hue, the higher the number of AR5, this in turn will result in the map the potential number of extremely poor rural people living in reduction of farm and non-farm migrants due to climate change, we that district. It can be seen from income, thereby affecting the derive district-wise incidence of Figure 4 that although the north- livelihoods of the rural population. severe poverty estimates based on western province of Khyber Hence the future increase in poverty ratios developed by Naveed Pakhtunkhwa has a high number of heatwaves will be very critical to the and Ali (2012). Figure 4 shows the extremely poor rural people, the major wheat producing areas of the number of people living under severe occurrence of severe rural poverty country. poverty in rural areas based on interms of number of people is most estimates of Naveed and Ali obvious in central and southern Incidence of Severe (2012), where the total rural Punjab as well as in Sindh. Poverty population data is obtained from the Interestingly, with the exception of a 2 The answer to the third question, latest Population Census of 1998. few districts in KPK, this is the same region where the heatwaves are regarding whether the areas identified in subsections 4.2.1 and projected to increase substantially 2 It is important to mention here that the last due to climate change as shown in 4.2.2 correlate with the incidence of National Population Census was conducted in severe poverty, is very important, as 1998. Given this data limitation, we used recent Figure 2. Mueller et al. (2014) established that poverty estimates of Naveed and Ali (2012), which are based on the 2008-09 Pakistan Social and the magnitude and statistical Living standards Measurement (PSLM) survey. significance of migrants from rural to Thus, poverty percentages for each district are living standards. For more details, see chapter 2 of obtained from Naveed and Ali (2012) and applied the study. Since data was not available for urban is most pronounced for the to the total rural population of that district, as Federally Administered Tribal Areas and Gilgit- land- and asset-poor people. They obtained from data of 1998 Census. Naveed and Baltistan in Census 1998, and Rajanpur in Naveed argued that these people include not Ali (2012) estimate district-wise (extreme) poverty and Ali, 2012, these areas are omitted from the using a multidimensional approach that measures present study. Azad Jamu and Kashmir was also only those who are directly aggregate deprivation of a household in multiple omitted from the study since it falls outside arid indicators relating to wealth, health, education and and semi-arid zones. 20 Climate induced rural-to-urban migration in Pakistan

Figure 3: District-wise wheat production based on 2008-09 Agriculture Census

Source: author

Figure 4: Number of severely poor people living in rural areas of each district based on Naveed and Ali (2012) and 1998 National Population Census data

Source: author

Figure 5: Number of severely poor people living in rural areas of each district based on Naveed and Ali (2012) and 1998 National Population Census data, but only for the districts producing wheat above the average threshold of all the districts

Source: author

Climate induced rural-to-urban migration in Pakistan 21

Identification of hotspot tonnes. Further analysis reveals that 1991-2010. The figure shows that regions for migration 39 districts produce wheat crop semi-arid districts are located in greater than this value and Punjab, Khyber Pakhtunkhwa, Gilgit So far, we have identified areas that altogether account for 85% of total Baltistan and a couple in the show an increasing trend of wheat crop of the country. Figure 5 Balochistan province. Hence we heatwaves, have substantial wheat shows the number of people living plotted Figure 7, which is similar to production and contain a large under severe poverty in rural areas Figure 5 with the exception that it is number of extremely poor rural of these 39 districts. It is again over semi-arid districts of Figure 6 people. Yet there are certain districts obvious from Figure 5 that the and the cut-off is chosen to be having a large number of rural highest numbers of severely poor 150,000 tonnes instead of 207,000 people living in severe poverty that rural people, who are most tonnes. The cut-off is relaxed due to do not have a substantial wheat vulnerable to migration due to our proposed methodology for production base. Since one of the climate change, are located in the further research. The premise behind aims of the study is to identify the arid and semi-arid areas of Punjab this relaxation is that the map shown districts/regions that are most and Sindh provinces. in Figure 6 is based on station vulnerable to the impacts of climate observations. There are several change in terms of migration Identification of hotspots studies which show that station relevant to wheat production, we for PRISE project on density is not adequate in Pakistan. therefore have mapped extreme internal migration Therefore, in order to increase our rural poverty in those districts that potential number of districts where In order to identify the ‘hotspot’ produce wheat crop more than the the surveys can be conducted in areas in Pakistan where potential average district-level wheat coming years, we have relaxed the PRISE research may be carried out, production. Based on agriculture criteria a little. census data of 2008-09, the Figure 6 shows the semi-arid average wheat production per districts based on the data provided district is calculated to be 207,000 by Pakistan Meteorological Department (PMD) for the years

Figure 6: Semi-arid districts of Pakistan based Figure 7: Same as Figure 5 but for the on Pakistan Meteorological Department's semi-arid areas of Pakistan station data for the period 1991-2010

Source: author Source: author

22 Climate induced rural-to-urban migration in Pakistan

5. Discussion

Under normal circumstances, rural- economy (WB, 2014). An exception inconsistent improvement in to-urban migration is often here is the case of sub-Saharan development indicators. In Pakistan, considered as an adaptation Africa, where the rocketing pace of where the net rural-to-urban strategy, where a migrant moves to urbanisation does not seem to be in migration accounts for one fifth of an urban centre in search of line with improvements in economic the annual rise in urban population improved livelihood and better living wealth (Fay and Opal, 1999). For (Hussain, 2014), the high pace of standards. A dynamic urban centre sub-Saharan Africa, summertime urbanisation has raised concerns may be considered as a proxy for precipitation extremes have shown a about the capacity of the country’s development, as it is established strong link with rural-to-urban urban systems to absorb such that industrialisation and migration. The case of Pakistan is massive movements as well as the urbanisation are basic indicators of a somewhat similar to that of sub- impact on sustainable development. country’s transformation from a Saharan Africa, with its high pace of lower-income to a middle-income urbanisation that is paralleled by

Figure 8: Percentage of urban to rural population in Pakistan based on IPCC SSP2 scenario

80

70

60

% 50 40

30

20

10

0 1960 1980 2000 2020 2040 2060 2080 2100

Year Source: author

Given the country’s existing cities will result in an increased pull elsewhere in the developing world, sociopolitical and economic factor. Therefore, the simultaneous the most preferred destinations for challenges, the stress of climate occurrence of both of these factors these rural-to-urban migrant families change is likely to exacerbate will result in higher migratory flows are the peri-urban and urban slums development problems. From the towards the cities, adding to the of large cities, which results in results presented in the previous already existing problems of urban unplanned expansion that normally section, it can be inferred that the population explosion. Our results are is not a part of any city’s increasing trend of heatwaves under further complemented by Figure 8, development plan (Kugelman, 2014). a future climate change scenario which uses International Institute for Pakistan’s four large cities – Karachi, over wheat-producing districts will Applied System Analysis data of Lahore, , and Faisalabad negatively impact the wheat yields, SSP2 scenario, which shows that – together constitute about 50% of thus making the poor landless urbanisation will rise to 50% in urban slum population in Pakistan people more vulnerable to migration Pakistan by 2030/35 and 70% by (Ghani 2012). This unregulated towards the urban regions. Along the end of the 21st century. These expansion of urban areas results in with this push factor, the allocation findings are also in line with the the transformation of prime of more development funds and the UNDP’s World Urbanization agricultural lands into housing major share of investments in big Prospects: The 2014 Revision. As schemes and slums. For example, Climate induced rural-to-urban migration in Pakistan 23

94% of the total area of the Lahore food security and national economy, households out-migrate to add to district was under agricultural use in such drastic changes in the rural family incomes, female household 1972, which has reduced to 29.5% and urban landscapes will affect not members left behind are often in 2010 (Zaman, 2012). This loss of only the demographics of the sixth forced to undertake additional roles agricultural land will directly affect most populated country of the world that traditionally resided with men. the livelihoods of those associated but also the food security of a major Future climate extremes such as with agriculture, especially the global wheat exporter. However, this heatwaves are thus likely to affect poorest of the poor, and will result in empirical finding needs to be women in terms of (i) their traditional a feedback loop, depicted in Figure validated with more in-depth household chores (like securing 9. research studies. This will help in water and energy supplies); (ii) the identifying the different ways in additional male-dominated tasks While the above results indicate a which the rural and urban they acquire, such as farming, of strong correlation between a rise in economies may be transformed over which they may hold limited heatwaves and a decrease in wheat time as climate trends change. traditional knowledge; and (iii) their production, the scale and intensity at overall well-being, as their existing which this may occur is not Out-migration and declines in wheat socioeconomic vulnerabilities may indicated in the present study, given production are likely to affect women, be exacerbated during climate the limitations of predicting climate too, given their high socioeconomic shocks (e.g. due to low education trends using low-resolution data. vulnerability in rural Pakistan. Most status, lack of job opportunities, and Nevertheless, given the critical data in Pakistan indicate that while limited mobility). importance of wheat in Pakistan’s male members of poor farmer

Figure 9: The feedback loop

Climate Change: Increase in heatwaves

Reduction in Wheat Production

Loss of Agri Loss of Lands into Peri- Livelihoods for urban and Slums Severely Poor People

Rural to Urban Migration and Expansion of Urban Areas

Source: author

24 Climate induced rural-to-urban migration in Pakistan

6. Conclusions and recommendations

In line with existing climate-migration Based on the above findings, we study proposes a National discourse, this study argues that recommend a mix of adaptation Registration System that can climate change acts in combination measures, both manipulative and capture population mobility data with many other socioeconomic preventive measures that promote a across Pakistan. This needs to determinants of migration. The check on the accelerated flow of be supported by legislative development deficit in Pakistan’s masses from rural to urban areas. changes that make registration semi-arid rural areas is paralleled by mandatory for persons moving Following are some initial unequal investments in urban to formal and informal urban recommendations of the study: centres (such as in service provision areas. It will provide needed and infrastructure) that lures • Managing rapid information to the government potential migrants to urban urbanisation: Study results on flow and intensity of rural- settlements. However, the variability show that rural-urban migration urban migration to large cities. It in weather patterns (climate shocks may contribute to unplanned will also help formalise the urban such as heatwaves) also plays a role urbanisation and expansion of economy, which remains largely in influencing migration patterns. megacities like Karachi, Lahore, informal due to the large rural and Faisalabad, which may workforce that invisibly works Climate shocks and slow-onset disrupt urban well-being (see there. changes impact ecological section 5). Therefore, one viable conditions in rural lands that trigger Risk management in solution is to develop • shifts in agricultural productivity, thus agriculture sector: Given intermediate cities or towns eroding incomes of poor and Pakistan’s critical role as a major (Jamal and Ashraf, 2004), which marginal cultivators. Thus, migratory wheat exporter in the global can serve as pivots between decisions may be taken to escape economy, the agriculture sector large cities and rural areas by from losses in rural incomes, losses needs an innovative strategy that facilitating access to markets for which are variably intensified by can not only address existing agriculture outputs (Hussain, climatic stress. Using the latest climate-threats but also 2014). Such centres may climate modelling, we predict that capitalise on potential additionally take off burden from such changes are likely to be opportunities that climate large agglomerations by magnified by 2030 in arid and semi- change may present. For providing additional ‘pull factor’ arid areas of Pakistan that are example, the national policy on facilities, such as improved important in terms of wheat agriculture and food security access to education and health production and are home to large needs to innovate clear strategy care services. Markets in rural populations. Given the for coping with slow-onset intermediate cities may also help sensitivity of wheat crop to heat climatic impacts that may plug rural-urban income gaps by stress, we anticipate that a decline in consistently affect the agriculture providing opportunities for wheat production will affect rural sector. Moreover, risk seasonal employment to poor and marginal households, who management in the agriculture landless rural labour. While will be forced to cope. When sector needs innovative financial similar measures are also coupled with prospects for improved support mechanisms that proposed in the Ministry of life in urban centres, this will improve poor farmers’ access to Climate Change’s recently incentivise poor rural populations to finance during climate shocks launched ‘Framework for out-migrate. In cases where male (e.g. crop insurance to protect Implementation of Climate members out-migrate selectively, against crop failures). Change Policy (2014-2030)’, female household members will be they need to be materialised with • Improved rural and urban compelled to take over traditional a concrete action plan and service delivery through male roles in the rural agriculture necessary budgetary allocations. decentralised governance: sector. Thus, simultaneous The revival of local governments occurrences of push and pull factors • Monitoring of internal under the 18th Constitutional will set off rural-to-urban migration, migration: The dearth of Amendment is important for which will aggravate urbanisation adequate data on rural-urban curbing rural-to-urban migration challenges in Pakistan by exerting migrants hinders monitoring of for two reasons. Firstly, in the additional pressure on hard-pressed internal migration flows, which absence of local governments, it urban services and infrastructure. presents a challenge to informed is very likely that development decision-making. Therefore, this Climate induced rural-to-urban migration in Pakistan 25

funds would continuously be complemented by changes in • Under what circumstances does allocated to megacities and policy implementation as well, by climate change and variability provincial capitals (Mahmud et abolishment of structural barriers trigger migration? al., 2010), leaving only limited to inter-provincial coordination o What are the existing trends government decisions and and inter-departmental of migration patterns in the development funds to trickle communication (such as semi-arid lands (SALs) of down to district, tehsil, union between PMD, disaster Pakistan, Burkina Faso, and village levels. Secondly, the management authorities and Tanzania, and Kenya? balance distribution of power will water, power and irrigation o How are these migration allow local-level governments to departments), to ensure timely patterns likely to be affected make decisions and allocate communication of early warnings under future climate change funds that are directly relevant to to concerned institutions and in SALs? local problems. This is likely to (rural) communities (Saeed et al., increase service delivery for rural 2014; Salik et al., 2015). • How is affected by and local populations. However, climate-induced migration this would also need to be 6.1 Way forward patterns in ways that support complemented by improved The results of this study highlight the climate-resilient economic service provision in urban slums, need for more in-depth research on development? which are likely to absorb the different aspects of migration. This o How does migration affect influx of informal rural migrants. study has identified potential study welfare indicators like • Integrated approach to sites (Figure 7), where climate- income, health, education, ‘climate-proof’ induced rural-urban migration may etc., and to what extent development: Given be studied in Pakistan during the does migration shape Pakistan’s high vulnerability to course of PRISE project. Among the poverty, inequality, climate change, and its existing districts shown in Figure 7, we urbanisation, and conflicts level of development challenges, would select three districts (and over natural resources in the country requires an hence the study sites) according to SALs? integrated and multi-sectoral the high-, medium- and low-level o How is migration affecting approach to climate-resilient incidence of severe rural poverty in and likely to affect the economic development. Sectoral order to study how the decision- gender roles in SALs? policies on population, making in rural-urban migration is o How does understanding of agriculture and food security, affected by socioeconomic climate-induced migration environment, poverty alleviation vulnerability. PRISE countries in Asia patterns affect policies and and economic growth need to and Africa may use similar research institutions in terms of propose specific measures for methodology to identify potential adaptation? Conversely, climate resilience, as highlighted study sites according to their what are the direct and in National Climate Change research needs. Some of the key indirect linkages through Policy in 2012 and ‘Framework questions that will be investigated which policies and for Implementation of Climate during the course of the PRISE institutions affect migration Change Policy (2014-2030)’. project are the following: decisions of communities? Moreover, this needs to be

26 Climate induced rural-to-urban migration in Pakistan

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Walled city, Lahore, Pakistan © Guilhem Vellut CC2.0 https://creativecommons.org/licenses/by/2.0/le galcode

30 Climate induced induced rural rural-to-urban-to urban migration migration in Pakistan in Pakistan

Climate induced rural-to-urban migration in Pakistan 31

SDPI Sustainable Development Policy Institute 38, Main Embassy Road, G-6/3 Islamabad, Pakistan Tel. +92 51 2782134 www.sdpi.org www.sdpi.tv www.prise.odi.org Research for climate-resilient futures

This work was carried out under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA), with financial support from the UK Government’s Department for International Development (DfID) and the International Development Research Centre (IDRC), Canada. The views expressed in this work are those of the creators and do not necessarily represent those of DfID and IDRC or its Board of Governors.

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