Environmental Migration

Definition

Some key terms are important in the context of migration and environmental and climatic changes:

• Human mobility is “a generic term covering all the different forms of movements of persons.” In the context of environment drivers, human mobility is understood as encompassing the three forms of “climate change induced” movement from the Cancun Agreement namely, displacement, migration, and planned relocation (IOM, n.d.).
• Environmental migration is the “movement of persons or groups of persons [environmental migrants] who, predominantly for reasons of sudden or progressive changes in the environment that adversely affect their lives or living conditions, are forced to leave their places of habitual residence, or choose to do so, either temporarily or permanently, and who move within or outside their country of origin or habitual residence” (IOM, 2019).
• Climate migration is the movement of a person or groups of persons who, predominantly for reasons of sudden or progressive change in the environment due to climate change, are obliged to leave their habitual place of residence, or choose to do so, either temporarily or permanently, within a State or across an international border. (IOM, 2019). Climate migration is a subcategory of environmental migration; it defines a singular type of environmental migration, where the change in the environment is due to climate change.
• Climate refugees or environmental refugees: There is a growing consensus among concerned agencies, including IOM and UNHCR, that the use of these terms is to be avoided. These terms are misleading and fail to recognize a number of key aspects that define population movements in the context of climate change and environmental degradation, including that environmental migration is mainly internal and not necessarily forced, and the use of such terms could potentially undermine the international legal regime for the protection of refugees (IOM, n.d.)
• Environmentally displaced person refers to “persons who are displaced within their country of habitual residence or who have crossed an international border and for whom environmental degradation, deterioration or destruction is a major cause of their displacement, although not necessarily the sole one” (IOM, 2011:34 in IOM, 2014:13).
• Disaster displacement “refers to situations, where people are forced or obliged to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of disasters triggered by natural hazards. Such displacement may take the form of spontaneous flight or an evacuation ordered or enforced by authorities. Such displacement can occur within a country, or across international borders” (The Nansen Protection Agenda, 2015).
• Planned relocation “in the context of disasters or environmental degradation, including when due to the effects of climate change, [refers to] a planned process in which persons or groups of persons move or are assisted to move away from their homes or place of temporary residence, are settled in a new location, and provided with the conditions for rebuilding their lives. The term is generally used to identify relocations that are carried out within national borders under the authority of the State and denotes a long process that lasts until “relocated persons are incorporated into all aspects of life in the new setting and no longer have needs or vulnerabilities stemming from the Planned Relocation. (IOM, 2019 ; Georgetown University, UNHCR, and IOM, 2017).
• Trapped populations refers to populations “who do not migrate, yet are situated in areas under threat, […] at risk of becoming ‘trapped’ or having to stay behind, where they will be more vulnerable to environmental shocks and impoverishment” (IOM, 2019).

Data sources

Comprehensive datasets on environmental migration or planned relocation do not yet exist at the global level, but several initiatives have started to collect information across several countries. The following list provides an overview of the available information, including more qualitative research.

Primary data collection:

National authorities collect information on displacement and evacuations linked to disasters, in particular fast onset ones. Local-level disaster displacement data are available from (international and national) humanitarian agencies (NGOs, UN agencies) engaged in relief operations, which collect data in order to respond to the needs of affected populations. Planned relocation of communities in the context of environmental and climate change is increasingly implemented by governments. For a summary of relocation programmes, see Ionesco, Mokhnacheva and Gemenne, 2016; Benton, 2017 and Georgetown University, UNHCR and IOM, 2017).

Administrative data sources, such as the numbers of humanitarian visas (such as in the US, Brazil, Ecuador or Mexico) or residence permits granted (for instance, by Argentina) linked to disasters, can provide information on cross-border displacement and movements in the context of environmental events more generally.

IOM’s Displacement Tracking Matrix (DTM) is a system used to track and monitor disaster displacement and population mobility. Data, which can be disaggregated by gender and sex, are regularly captured, processed and disseminated to provide a better understanding of the movements and evolving needs of displaced populations and migrants, whether in situ or en route, before, during and in the aftermath of disasters. The data are presented in the DTM Data Portal. A study on how current DTM practices collect data on human mobility in the context of environmental degradation, climate change and disasters and draws also provides recommendations on how to improve current tools and practices. Recommendations include improving the focus of some DTM questions and increasing the amount of options available for respondents to provide more granular data on the migration, environment and climate nexus (IOM, 2020). 

DTM’s Transhumance Tracking Tool (TTT) is a tool developed by IOM to track transhumance movements and collect alerts related to agro-pastoral conflicts, in order to prevent and mitigate them.  

Innovative data sources include mobile phone-based sources such as call detail records (CDRs). Big data generated by mobile phone users before and after disasters, such as the 2010 earthquake in Haiti (Bengtsson et al., 2011) and several typhoons in the Philippines and Bangladesh (Lu et al., 2016), can indicate where displaced persons moved to and help deliver prompt and targeted humanitarian assistance or to understand internal movements (Laczko and Rango, 2014; GMG, 2017). This can be a means to collect complementary quantitative data on movements at small-scale and on seasonal patterns linked to adaptation to environmental change and disasters that are difficult to account for in traditional household survey tools (Lu et al., 2016). Other projects aim at using big data sources, such as satellite images or social media data, to identify early the environmental stressors that could lead to displacement (see for instance Isaacman et al., 2017).

Several research projects have and are collecting new data on the links between the environment and human mobility, but few with a comparative approach. There are three notable exceptions. First, the Migration, Environment and Climate Change: Evidence for Policy (MECLEP) project, implemented by IOM and six research partners in 2014-2017, and funded by the EU, conducted a comparative quantitative and qualitative study of six countries (Dominican Republic, Haiti, Kenya, Papua New Guinea, Mauritius and Viet Nam). The methodology developed for the project could easily be applied to other countries.

Second, the Pacific Climate Change and Migration (PCCM) project by ILO, UNESCAP and UNDP focused on Tuvalu, Nauru and Kiribati. The United Nations University Institute for Environment and Human Security (UNU-EHS) released findings detailing how climatic changes are impacting these Pacific island states.

Third, the HABITABLE project is a EU-funded project (2020-2024) aiming at significantly advancing our understanding of the current interlinkages between climate impacts and migration and displacement patterns, and to better anticipate their future evolution. Led by the Hugo Observatory, the project brings together 21 partners from 18 countries and focuses on four regions: West Africa, East Africa, Southern Africa and South-East Asia.  

Secondary data sources and research:

The Internal Displacement Monitoring Centre (IDMC) has compiled data on internal displacement in the context of disasters since 2008 globally through its online Global Internal Displacement Database (GIDD). The estimates are based on information by national authorities, UN agencies such as IOM, the International Federation of the Red Cross (IFRC) and the UN Office for the Coordination of Humanitarian Affairs (OCHA), non-governmental organizations and in particular media reports. Figures are published in the annual Global Report on Displacement (GRID), which also covers internal displacement due to conflict and violence. IDMC is developing methodologies to map and assess future disaster displacement risks and is starting to gather data on cross-border displacement.

The HELIX project (High-End Climate Impacts and Extremes) provided research on climate impacts and adaptation in relation to varying global warming scenarios (2, 4 and 6 degrees Celsius), using predictive analytics. Human migration was included in the impact studies. The recent Groundswell: Preparing for internal climate migration report (Rigaud et al., 2018) developed a model for future population distribution in 2050 in three regions (sub-Saharan Africa, South Asia and Latin America) if no action is taken.

The CLIMIG database of studies on environmental migration, both of qualitative and quantitative nature, was developed by the University of Neuchatel (Switzerland).

The Environmental Migration Portal by IOM, features a searchable research database, initially based on the People on the Move in a Changing Climate: A Bibliography, published by IOM in collaboration with University of Neuchatel. The database also includes migration and environment country assessments published by IOM.

The thematic working group on “Environmental change and migration” of the Global Knowledge Partnership on Migration and Development (KNOMAD) produced an annotated bibliography on Environmental Migration and developed a toolkit on planned relocation with many case study examples (Georgetown University, UNHCR and IOM, 2017).

The first “Atlas on Environmental Migration” was produced by IOM and Sciences Po, Paris (published with Routledge in 2017). The publication brings together, for the first time, existing knowledge on the links between migration and environmental change, presented through comprehensive maps, diagrams and case studies.

The Hugo Observatory at the University of Liège (Belgium) focuses on research on environmental changes and Migration.

The Platform on Disaster Displacement (a follow-up to the Nansen Initiative) provides a global dataset including preliminary findings from over 400 planned relocation cases. Last updated in 2021, it features characteristics including geographic location, spatial pattern, primary hazard and completion status.

Data strengths & limitations

Over the past decade, important advances on methodologies and data collection have been made. Academic researchers and specialized agencies are working on improved methodologies for comparative cross-country or cross-region studies, agent-based models and multi-factor simulators designed to predict future trends (such as drought-induced displacement modelling, Ginnetti and Franck, 2014, or IDMC’s Global Displacement Risk Model focused on sudden-onset disasters based on housing destructions), and hotspot identification triangulating environmental and social data, all of which can contribute greatly to improving current evidence and future projections of environmental migration trends so as to better inform policies and action.

Innovative data sources: Big data can provide opportunities that can further be strengthened in trying to estimate the extent of movements in contexts of disasters and degrading environments. These new methods can fill gaps in time series data, indicate where people have moved from and to and enhance the timeliness of this information. In some cases, these new methods could be used to inform life-saving early warnings. At the same time, privacy safeguards and ethical considerations need to be adhered to.

Nonetheless, difficulties remain.

• It is challenging to differentiate when the environment is the main factor triggering migration, rather than or in combination with other factors: In most cases, environmental factors are closely linked to socioeconomic, political, demographic, cultural and personal factors that play a role in leading to or preventing mobility (Laczko and Aghazarm, 2009; Foresight, 2011), which makes data collection beyond fast onset disasters leading to evacuations difficult. Information on people moving due to more gradual, so-called slow-onset processes like sea level rise or salinization, is scarce for methodological reasons.
   
• The most comprehensive data available do not capture duration of displacement: Thanks to IDMC’s work, data on internal displacement due to natural disastersare available for almost all countries. However, differing definitions used by data providers and a lack of reporting by countries remains a challenge, leading to media reports being an important source of events covered in the estimates. IDMC’s estimates reflect new displacements during a calendar year (and since 2019, the stock of IDPs due to disasters as of the end of the year) and does not capture the duration of people’s displacement, their return home or relocation elsewhere, those not sheltered in camps or people caught in long-term displacement, so-called protracted situations, from year to year. Data collection on cross-border movements after disasters is only starting and limited to localized case studies (IDMC, 2018 (a)).  Further research on disaster displacement is being supported as part of the work of the Data and Knowledge Working Group of the State-led Platform on Disaster Displacement.
   
• Underreporting: The quality and the availability of data on displacement vary between countries and from event to event: small-scale events or disasters that occur in isolated and marginalized areas are under-reported and thus not included in the available aggregate estimates (IDMC, 2017: 98; IDMC, 2018 (a)).
   
• Little information on links between conflict and disaster displacement: In cases where conflict is linked to disasters information on movements is lacking, in particular on displacement histories that could inform future predictions (IDMC data for instance are only available since 2008 but since 2017 include drought figures).
   
• Comprehensive datasets on environmental migration or planned relocation are needed: Data on environmental migration and planned relocation have improved in recent years, as an increasing number of studies have been conducted in affected areas. The research databases listed above are important tools providing an overview of the existing available information. However, comparable quantitative, longitudinal, disaggregated and georeferenced data are needed to assess how different forms of mobility can be a beneficial adaptation strategy and what potential risks need to be minimized. The majority of existing surveys focus mainly on the links between migration and the environment as a driver, and are mostly qualitative in nature. More information is needed on the impacts of those movements on adaptation to environmental and climate change.
   
• Few data on trapped populations: Some populations affected by environmental degradation and disasters may not be able to move due to a lack of financial resources, disability, social reasons (such as gender issues) or social networks. They are highly vulnerable populations, but data to inform action and protection are scarce.
   
• Better predictive analytics are needed: When it comes to predicting future trends, the disconnection between the environmental sciences and social sciences communities constitutes an additional challenge, in a context where environmental migration research would greatly benefit from multidisciplinary research and better integration of climate and population data.