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Present findings from STEPS project on uncertainty and introduce elements that we are looking at in current project funding by NRC>.. Most of authors here.. Upasona defending her thesis.. And most of project team also here..
Climate shocks and stressors such as cyclones, floods and droughts, changing rainfall patterns and glacial movements as well as the unexpected spread of vector borne diseases are some examples of uncertainties that planners, resource managers and local people in the global South are confronted with regularly. Climate science informs us about impacts like temperature rise, unpredictability of precipitation, flash floods, sea level rise, disease vectors / cycles, emissions, resource depletion
Box TS.1 | Treatment of Uncertainty Based on the Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties, this WGI Technical Summary and the WGI Summary for Policymakers rely on two metrics for communicating the degree of certainty in key findings, which is based on author teams’ evaluations of underlying scientific understanding: • Confidence in the validity of a finding, based on the type, amount, quality and consistency of evidence (e.g., mechanistic understanding, theory, data, models, expert judgement) and the degree of agreement. Confidence is expressed qualitatively. • Quantified measures of uncertainty in a finding expressed probabilistically (based on statistical analysis of observations or model results, or expert judgement).
Ecological uncertainty has usually been theorized from ‘above’ by experts, natural scientists, and modellers who measure and make prognoses about water availability and variability, glacier movements as well as changes in temperature and their impacts on the soils, water and food systems. Social scientists have also contributed to theorizing about uncertainty. But the focus on models, diagrams and scenarios may have very little to do with how everyday men and women (poor or rich, urban or rural especially in the global South) live with, understand and cope with uncertainty and rarely have uncertainty from ‘above’ and uncertainty from ‘below’ been brought together.
While a rich literature has documented how herders, cultivators and local resource users live with uncertainty and scarcity, this literature has rarely made its way to the meccas of uncertainty and rarely do analyses of uncertainty from ‘above’ and ‘below’ come together. Climate change is a good case in point. The rich ethnographic material on seasonality, coping with floods, droughts, scarcity and local uncertainties and how these are socially differentiated rarely finds its way to the mainstream climate change literature on extreme events, climate change and resource patterns and their impacts on water, agriculture and the soils. There is emerging research on how local perspectives on adaptation can be incorporated in more mainstream perspectives and it would be important to examine the processes of this incorporation. This is why there is growing criticism of doomsday portrayals of rapid climate change impacts in some parts of Asia and Africa which often can be out of sync with local realities where uncertainty, crises often appear to be the norm and where coping strategies have emerged. Of course, it is true that many coping mechanisms may no longer be resilient to extreme events and major political and economic drivers of change and we must not romanticize ‘living with uncertainty. ’ Still, ignoring uncertainty from ‘below’ misses out on important opportunities to create synergies across different knowledge domains. Another related problem is that uncertainty from ‘above’ rarely captures all the narratively rich diverse storylines around uncertainty and resilience which capture diverse imaginaries, alternative futures and scenarios. Furthermore, resilience debates are often static and may not look at the political ecology and economy of resilience (i.e. resilience for what purpose and for whom? Similarly, thresholds, tipping points and limits are rarely viewed as socially mediated and constructed, instead they are viewed as universalist and absolute, leading to ‘perfect storm’ narratives and justifying acts of brutal and extreme power (e.g. forced resettlement). Similarly, modellers and others rarely bring together their analyses with those concerning political economy and macro economic and political changes which also have impacts that may be more drastic than climate change (e.g. land grabs in Africa, changes in technology etc.).
Part of disquiet with CC literature – everything CC and ignoring traditions that came before..
Study whether and to what extent the discrepancy between uncertainty (of cc) understandings is a barrier to social transformation necessary to adapt to climate change (HOW, WHY AND WHO); Explore and develop approaches & methodologies to bridge uncertainty from above and below in order to foster productive and socially just ways of dealing with uncertainties and social transformation.
Uncertainty is usually defined as a situation characterised by indeterminancies. It is a situation where not enough is known about the probabilities of a particular set of outcomes and where they cannot be calculated (cf. Knight 1921; Douglas 1985). It has its roots in many disciplines (from physics to psychology, economics and science technology studies, STS). While the economistic definition focuses on the outcomes of decision making and the inability to assign probabilities to a certain outcome, uncertainty can also refer to a cognitive or emotive state of being that is discomforting and uneasy, which however is either reduced or escalated by the passage of time and changes in perceptions of circumstances (see Penrod 2007). Unlike risk where we know the odds and the scientific proclivity to contain it (cf. Wynne 1992), uncertainty is where one does not know the odds and probabilities cannot be calculated. Thus anthropologists and social scientists distinguish between manageable risks and unknowable sources of uncertainty and perhaps even fear (due to so called apocalyptic situations in the future), see Hastrup 2013.
Uncertainty has much to do with incomplete knowledge or degrees of knowledge and Funtowicz and Ravetz (1990) argue that uncertainty is a situation of inadequate information of three types (inexactness, unreliability and border with ignorance). The STEPS centre (see Leach et al 2010 and Stirling et al 2007) has focused on four types of incertitude or incomplete knowledge (risk; ambiguity; uncertainty and ignorance). In the case of uncertainty where probability doesn’t exist, subjective judgements and multiple interpretations are the best way forward, instead of a singular value or recommendation.
Walker et al. (2003:5) define uncertainty as ‘any deviation from the unachievable ideal of completelydeterministic knowledge of the relevant system’. They distinguish between epistemic uncertainty (arising due to the imperfection of our knowledge) and ontological or variability uncertainty (due to inherent variability in human and natural systems concerning social, economic and technological developments). Both will be framed and interpreted differently by different actors and these framings (i.e. the process of selecting, organising, interpreting cf. Rein and Schoen 1993) will be linked to relations of power and justify different institutional practices and responses. Following Walker et al., Brugnach et al. (2008) add another dimension by way of ambiguity, which emanates from multiple framings about a certain phenomenon. This may be due to different interpretations and different normative judgments (Klinke & Renn, 2002; Weick, 1995)
There is however, growing recognition that the global, national and sub-national responses to uncertainty have been inadequate (Wynne 1992; Stirling et al. 2007). Despite the increasing recognition of growing complexity, dynamism and uncertainties, there is also a constant search for technically driven managerialist solutions - solutions that may either falter in the face of local social dynamics and uncertainties or end up harming certain groups, usually the poor (Mehta et al. 1999; Leach et al. 2010; Scoones 1995). Conceptualisations of uncertainties are varied and are embedded in different realms of knowledge and disciplinary traditions, The largely northern focused literature of Science, Technology Studies (STS) has been critical in elucidating the narrow ways in which uncertainty is often conceptualised by modelers, scientists, and planners (e.g. Wynne 1992; Nowotny et al. 2001; Stirling et al. 2007). Other literatures from an anthropological and sociological tradition and from the perspective of complex ecologies have demonstrated how local people live with uncertainty and how practices have evolved to deal with it (e.g. Scoones 1995; Berkes & Berkes 2009; Vasavi 1999; Mehta et al 1999; Marschke & Berkes 2006; Adger et al. 2001). A growing literature has focused on the importance of local knowledge in adapting to climate change (e.g. Green & Raygorodetsky 2010; Newsham & Thomas 2011; Naess 2013).
Computer models remain largely though the most important tool of climate science which tend to distance their efforts from situated contexts (cf. Edwards 2001). However, in recent times, several modellers have acknowledged the limits to these predictions (Curry & Webster, 2011; Hulme, 2013; Kandlikar, Risbey, & Dessai, 2005; Shackley & Wynne, 1996; Stainforth, Allen, Tredger, & Smith, 2007). These models can be imperfect and inadequate as there is limited understanding of the climate system and no model can be ‘structurally identical’ to the actual system (Stainforth et al., 2007).
They exercise considerable epistemic authority but how do they build their social authority? By social authority Hulme refers to the “interactions between scientific practices, cultural performances, and political interests, interactions which endow models with the status of trustworthy “witnesses” to the truth-or not”(Hulme, 2013:32).
It is for these reasons that Hastrup (2012) calls climate models as “fluid objects” to where scientific uncertainty becomes a rhetorical resource which can and will be employed by different actors towards their strategic ends.
Climate change and modelling are about anticipating nature practically and scientifically to make the world work and to make sense of the world. Models are about substituting missing empirical data which is a socially embedded act. Interpretations of models gain a social life of their own – models can never stand alone. They are never more than approximations (Hastrup 2013).
This is why General Circulation Models (GCMs) have limitations and they may not be able to capture extreme rare events and simulating shifts between climatic states. (ibid)
Above: Experts, technocrats and state institutions.. Deliberations// policy formulations / mechanism/ politically influenced.. Most powerful constitutences
Below : Communities with all their heterogeneity/ social and gender dynamics.. At present remain primarily silent participants// some mere spectators with their non expert knowledge.. Developed coping strategies and patterns of resilience over decades and centuries.. Range from victims to villians to passive specators to active agents reshaping their lives and future..
It is not necessarily played out at the verbal or articulated level but instead is a more ‘practical’ form of knowledge which could also be tacit (cf. Bourdieu, 1977).
Middle : The knowledge brokers.. Uncertainty professionals who often seek to bridge the gulf between above and below.. Street level bureacrats, district level officials, scholars, NGOs, media.. They have their own politics and constraints.. Sometimes squeezed by above and below..
Provide discursive and critical analysis , frameworks to develop bridges between people and decision makers .. Also value laden, ideological, shaped by power and politics, funding agendas etc..
Most often many of the human activities and livelihood practices that intersect with climate change remain unrepresented in these climate simulation models, discourse and policy.
Here the narrow frame of uncertainty needs to be broadened and diversified to encompass varieties of uncertainties emanating from, and exacerbated by livelihood practices, social differentiation (of caste, class, region, religion and gender), access to information and networks.
The interconnections between social meanings and their relationship with ecological worlds have been studied effectively in the tradition of political ecology and anthropology . This rich body of work elucidates how people attach meaning and significance to the world they inhabit, and in turn gain meanings from the natural world to understand and live with change.
Anthropologists have long been concerned with how local people make sense of weather patterns, variability in weather and also permanent climate change. fruitful interdisciplinary interactions between anthropologists, modellers etc seeking to bring together the social and physical realities of climate change. The book The Social Life of Models is a good case in point (see Hastrup and Skrydstrup 2013). The Waterworld project focussed on how people in particular places understand the local implications of climate change and what this means for their lives and future. Here again climate change is often one of the many causes that brings about manifold changes and deeply located in particular places. Climate change calls for multiple responses and changes social life in dramatic ways due to the sharp entanglements between social and natural processes. (Hastrup and Rubow 2014). While our work has a lot in common with the Waterworlds project, we perhaps take more of a normative position and are interested in what explicitly happens to poor, marginalised and disenfranchised people.
many indigenous knowledge (IK) systems evolve through adaptive learning based on developing a complex knowledge base of the environment and lessons from past mistakes – a version of postnormal science (cf. Funtowicz & Ravetz 1993). Both kinds of knowledge are desirable because they have different relative strengths and a potential for complementarity (Berkes and Berkes 2009).
could end up undermining adaptation by ignoring local understandings of ways of learning, experimenting and innovating critical for transformation. Thus, IK can also complement more macro perspectives by filling in the local scale. The project views both IK and ‘expert knowledge’ as culturally and socially embedded in local institutions, practices and social, gender and power relations (Thompson & Scoones 1994; Agarwal 1995; Jasanoff 2010). For example, recent historical work by Carey (2010) demonstrates how scientific knowledge about glacial changes in the Andes is moulded by power dynamics, economic outcomes, local worldviews and social relations. We also recognise some of the limits to local knowledge in the face of large-scale environmental uncertainties due to climate change (Marin 2010; Rudiak-Gould 2011) and concede that even if people are able to adapt, such processes can involve major trade-offs and losses that they must endure (Roncoli et al. 2001). Neither are scientists nor local people homogeneous. This dynamic view of the nature of uncertainty from ‘below’ and ‘above’ opens up the possibility of identifying convergences between certain actors and perspectives in local and scientific worlds (hence our focus on translations). Institutional arrangements are key in managing uncertainty (Mehta et al. 1999). Usually, local people adapt to risks and uncertainties amidst a mix of institutional types and arrangements which transcend formal/ informal divides and tend to be messy, overlapping and power-ridden (see Cleaver 2011; Mehta et al. 1999). Thus, it’s important to focus on the political economy of climate change uncertainty and the implications for social justice across multiple scales (Tanner & Allouche 2011). Uncertainty (like scarcity, cf. Mehta 2005) can be manufactured to meet certain political ends. Uncertainty can be used as an excuse to do ‘nothing’ (Dessai et al. 2007). Who benefits from certain discourses of uncertainty and social transformation, and who carries the costs?
This also brings us to the practices of anticipation (cf. Hastrup, 2013) where people attempt to predict, forecast and prepare for both immediate and distant futures. Anticipation is a tactic employed both by above and below. Climate change from below - for many ordinary people around the world climate change is not something abstract or about a particular way of modelling or prediction. It is instead a ‘lived reality. The changes are felt, embraced, feared and prepared for … Their impingement on lived experience induces humans to respond , first by seeking to understand them and assess their range, and then to anticipate their future course so as to prepare to meet the new world’ (see Hastrup and Rubow 2014:4 ). Practices of anticipation are part and parcel of climate change and in anticipating the climate and its changes, people are confronted by all kinds of uncertainties (cf Hastrup 2013) – range from forecasts of daily weather patterns to extreme events and range of future scenarios and as we move from Halocene to the Anthropocene... According to Hastrup, anticipation is also about trying to diminish uncertainties for the future which makes it possible for people to act and assert agency in the here and now.
India: As an emerging economy, India is often in a difficult position when it comes to addressing global obligations around climate change as well as domestic priorities of continued economic growth and poverty reduction (Atteridge et al. 2012). In 2008 India developed a National Action Plan on Climate Change (NAPCC) which acknowledges that climate change is likely to alter the distribution and quality of India’s natural resources and adversely affect people’s livelihoods. Since the economy is predominantly natural resource based, the country has large populations who are highly vulnerable to the impacts of climate variability and change. Water resources and health are particularly at risk from climate-related shocks and stressors, and coastal areas are facing the most severe challenges (issues to be addressed in our case studies). The NAPCC has however been criticised for not making any commitment to equity or redistribution, given the huge disparity in income and access to natural resources in India (Bidwai 2012). Of relevance to our research is that state-specific climate policies are being designed to deliver state-level development agendas that may have co-benefits for climate, growth and environment objectives. For example, Gujarat, which is highly industrialised, has focused on mitigation actions while in the Sunderbans the focus is clearly on livelihoods, adaptation and perhaps even planned exit.
The Sunderbans: The Sunderbans are increasingly understood in terms of climate change and the need to invest in adaptation strategies. However, do the strategies adopted take into account the experiences and perspectives of the people who are living with and adapting to climate change? This component will explore the perceptions of climate-related challenges and resilience from the perspective of residents of the Sunderbans, informal health workers who provide health services and members of local NGOs. It will also explore the tensions between short-term coping mechanisms and longer term adaptation both in terms of appropriate health system development and livelihood strategies (including out migration).
Climate change and urban India: This component will build on the Phase I mini project. It will combine historical and ethnographic research on CC and cities and forground the relationships between different kinds of uncertainties in selected domains, e.g. natural calamities, water, energy, waste and housing. It will critically examine the relationship between mitigation and adaptation strategies at the urban level. It will interrogate the way the meanings and implications of such policies and practices are unfolding on the ground in the context of an uncertain future of climate change impacts amongst diverse set of people.
Kutch: This component will build on Lyla’s long term research and engagement with Kutch, a dryland in western India known for scarcity and ecological uncertainty. Official perceptions of scarcity tend to be universalist and absolute, not taking into account uncertainty and local people’s own knowledge systems and strategies. Decades of programmes and strategies to mitigate uncertainty and scarcity have not led to improvements for local people and their livelihoods. Climate change is now an omnipresent discourse and adds to ongoing scarcity politics and issues. This component will examine official policies, models, scientific practices and discourses of climate change, adaptation and mitigation and contrast them with local practices and knowledges. It will also examine the rapid socio, economic and political drivers of change that are shaping the region and Gujarat more generally and look at the accompanying imaginaries, politics and political economies of injustices that are shaping the region and its future. The work will be executed by GUIDE and Satvik and the areas of focus will be agreed at the workshop.
Global (?) and National perspectives: This component will do a mini ethnography of the world of scientists, modellers and their perspectives of uncertainty and what it means for local people. Here we will interview and engage with scientists from IIT, Tehri etc. Global and European perspectives would also be desirable but the feasibility in terms of the budget and time will have to be worked out and probably will be done with separate funding. We will aim to look at both adaptation and mitigation issues and also question some of the inherent distinctions.
Science, Technology Studies (STS; narrow ways in which uncertainty is often conceptualized by experts (e.g. Wynne; Nowotny et al; Pahl-Wostl et al; Stirling). Anthropological and sociological tradition: local knowledges and practices around uncertainty (e.g. Scoones; Berkes and Berkes; Vasavi; Mehta) Climate change, risk, adaptation, disasters in India and beyond Resilience and transformation
We are concerned with how a range of framings lead to diverse discourses of uncertainty from ‘above’ and ‘below’, as well as how they are translated. Discourses can both constrain and enable particular ways of acting (cf. Foucault 1980) making it important to examine how discourses travel across institutional and national boundaries (see e.g. Skocpol 1985). Framings and discourses lead to different practices and cultures to deal with uncertainty. The standard approach for conceptualising uncertainty is to quantify it in terms of probabilities (e.g. Groves et al. 2008; Sigel et al. 2010). Statistical models accommodate sophisticated data with multiple variables across a range of spatial and temporal scales. By contrast, many indigenous knowledge (IK) systems evolve through adaptive learning based on developing a complex knowledge base of the environment and lessons from past mistakes – a version of postnormal science (cf. Funtowicz & Ravetz 1993). Both kinds of knowledge are desirable because they have different relative strengths and a potential for complementarity (Berkes and Berkes 2009). In climate change, there tends to be an ‘intensively scientific primary framing’ and ‘intensively economistic imagination’ (Wynne 2010: 291) which could end up undermining adaptation by ignoring local understandings of ways of learning, experimenting and innovating critical for transformation. Thus, IK can also complement more macro perspectives by filling in the local scale. The project views both IK and ‘expert knowledge’ as culturally and socially embedded in local institutions, practices and social, gender and power relations (Thompson & Scoones 1994; Agrawal 1995; Jasanoff 2010). For example, recent historical work by Carey (2010) demonstrates how scientific knowledge about glacial changes in the Andes is moulded by power dynamics, economic outcomes, local worldviews and social relations. We also recognise some of the limits to local knowledge in the face of large-scale environmental uncertainties due to climate change (Marin 2010; Rudiak-Gould 2011) and concede that even if people are able to adapt, such processes can involve major trade-offs and losses that they must endure (Roncoli et al. 2001). Neither are scientists nor local people homogeneous. This dynamic view of the nature of uncertainty from ‘below’ and ‘above’ opens up the possibility of identifying convergences between certain actors and perspectives in local and scientific worlds (hence our focus on translations).
Finally, institutional arrangements are key in managing uncertainty (Mehta et al. 1999). Usually, local people adapt to risks and uncertainties amidst a mix of institutional types and arrangements which transcend formal/ informal divides and tend to be messy, overlapping and power-ridden (see Cleaver 2011; Mehta et al. 1999). Our research will also focus on the political economy of climate change uncertainty and the implications for social justice across multiple scales (Tanner & Allouche 2011). Uncertainty (like scarcity, cf. Mehta 2005) can be manufactured to meet certain political ends. Uncertainty can be used as an excuse to do ‘nothing’ (Dessai et al. 2007). Who benefits from certain discourses of uncertainty and social transformation, and who carries the costs? Here the literature on environmental justice (e.g. Agyeman et al. 2003 and Schlosberg 2007) as well as diverse literatures on justice (cf. Sen 2009; Rawls 1971) are key to examine how justice is perceived and practised in contexts of high uncertainty.
discourse and textual analysis of key scientific texts and portrayals of uncertainty from a wide range of actors; semi-structured interviews and focus group discussions with experts, planners, scientists, local women and men, participant observation, “learning by doing” accompanying women and men on their daily tasks, and finally small scale surveys.
Vulnerablity and hazard mapping – Sunderbans..
The Sundarbans, literally ‘beautiful forest’ in Bengali, delta in both India and Bangladesh. largest remaining natural habitat of the Royal Bengal Tiger.
The Sunderbans, a coastal delta, is characterised by tremendous ecological uncertainty and geo-climatic challenges (e.g. mangrove forest, islands affected by rising sea levels, erratic rainfall, cyclones as well as tidal waves forming and eroding islands) as well as government neglect (CSE 2012). The Indian Sunderbans is home of about 4.5 million people and is in two district
The 54 islands are spread over 19 administrative blocks and though the area is less than 100 kilometres away from Kolkata, it is marked by poverty, deprivation and is considered to be “very remote”. These forest islands were largely uninhabited by humans until the 18th century
leads to livelihood uncertainty and difficulties in maintaining traditional livelihoods plus health impacts; survival uncertainty re shelter
# Scientists focussing on climatic issues (e.g. rainfall, sea level rise.. # One group saying that there are dramatic changes and others saying it’s natural in a delta ) #scientific uncertainty around CC; Uncertainty re attribution (is it due to CC or other anthropogenic changes e.g. waterways etc. / irrigation etc. ) # Policy inertia #Institutional complexities cause uncertainties for Sunderbans residents #Lack of coordination
#Middle has a good grasp of the different scientific debates – taking actions e.g. conserve mangroves; high awareness #Disconnect between awareness and action – dependent on funding agendas – climate funds/ DDR/ #Lack of coordination amongst NGOs, #Predomination of strong conservation agenda #Sympathetic and aware of uncertainties facing below.. Researchers/ journalists – trying to bridge gap and facilitate dialogue but no real role for them.. Lonely critical voices
BELOW #Uncertainty increasing #Struggle for survival #CC interacts with lots of other social and economic factors #Life is uncertain – uncertainty key dimension of their life #They realise they have to live with it.
Politics of embankments..
Gora mora …
Kutch, a large district and dryland in western Gujarat, is known for scarcity and ecological uncertainty. Official perceptions of scarcity tend to be universalist and absolute, not taking into account uncertainty and local people’s own knowledge systems and strategies (Mehta 2005). The district is characterized by high aridity, deficient soil moisture, over-extraction of groundwater, rapid salinity and also rapid land use changes due to industrial development as well as changing agricultural and grazing patterns. Uncertainty associated with climatic variability (namely erratic rainfall, high temperature and wind velocity) is part and parcel of life in Kutch. More recently, Kutch has become Asia’s most rapidly industrializing zone, leading to massive economic growth for some but also the uneven spread of development, rising inequalities as well as environmental costs. Pastoralism, agro-pastoralism and rain-fed agriculture are the dominant livelihood systems and local people have developed local knowledges and strategies to harness and make use of the variability and uncertainty that permeates this dryland ecosystem (see Mehta 2005). Three villages in Kutch were studies to represent three major ecosystems and parts of the district, namely Kanmer village (predominantly agriculture), the Banni region (Asia’s largest Grassland ) and Jakhau village (coastal port located in western).
Kutch receives an average of 335 mm of rainfall between June and September. The peak rainfall used to be in July but there has been a shift in recent years with maximum rainfall now falling in September. As with most drylands, rainfall is highly erratic and variable across the district. This is why villagers in the three sites reported huge differences. While residents of Kanmer reported a decrease in rainfall, in Banni they reported that in recent times rain has increased. The analysis of rainfall data (Bhuj-Rudramata Weather Station, Observatory, Bhuj Taluka) also shows that rainfall is increasing (see Figures, Source: GUIDE).
The rainfall rarely comes when we expect it. It is either early or delayed and the amount is really variable. Sometimes there is formation of very good cloud but with very little or no rains. Earlier, at the onset of monsoon dust storms used to form and make the surroundings totally dark. This has not been happening since last few years which may be attributed to the spread of vegetative cover of Prosopis juliflora”
However even if rainfall has increased, the gap between the showers and their intensity has also increased affecting agricultural crops and grass productivity, leading to crops failures. Another change is the occurrence of heavy rainfall in a single day which has also increased drastically during recent years (GUIDE 2014). In 2011, there was a massive flood in Bhuj which is highly unusual for a dryland usually plagued by droughts. While heavy rain, if harnessed properly, can help store water in ponds, check dams etc, it can also cause a lot of damage to crops. The changes in rainfall patterns have made both agricultural livelihoods more risky but also made local level predictions more difficult. I
## No follow up and very little monitoring after the project is over #Middle understand the dimensions and what government is doing and not doing; They are an intermediary..
#NGOs making noise about specific issues (e.g. water, pastoralism, migration etc.. )
#Middle understand the dimensions and what government is doing and not doing; They are an intermediary..
#NGOs making noise about specific issues (e.g. water, pastoralism, migration etc.. )
BELOW #Aware of different dimensions of uncertainty and have a range of coping strategies – #Village heads decides and can prevent implementation
#Coping in multiple ways and and also severely affected
# Urban heat island effects # Dwindling water resources # Generation of waste # Demand for energy # Concretization # (landslides, soil erosion – Mumbai) # Floods – both #Sea level rise
# All these interact with unregulated, complex urban. Interface between ecology, political economy , institutions
# Key decision makers and planners # Overconfident about plans and not taking uncertainty seriously.. ‘we’ll bring water and energy from XX, technological fixes; help people create behavioural change and awareness; # Currently more mitigation efforts in Mumbai; # Business as usual scenario,..uncertainy not taken very seriously.. # More around disaster management rather than long term congnisacen of CC..; # No predictions or models.. Only through TERI coming up with prognoses of sea-level rise.. nothing on vulnerability mapping # Lots of plans re mitigation and drought control: (CC dept and agricultural #committees at national, state and district levels)
# MIDDLE: problematises and helps categorize / look at multiple perspectives / informs about knowledge uncertainties
#focussing on environmental history – e/g/ around river and waste management in cities.. # challenging the development paradigm of consumption / unfettered growth; challenging top down modes of decisions making
# (calling for right to city / urban nature..) #Middle understand the dimensions and what government is doing and not doing; They are an intermediary..
BELOW Face the vulnerablity, need to build resilience; #individual responsibility/ coping (differentiated by class, caste, gender
# Below of the below: Severe attack from institutions; forced to move, not rights.. (slums and pavement dwellers – more than 50% of both cities) # Middle class.. shifting to new technologies (e.g. water purification,) # Elite : ignoring uncertainty.. not caring.. Disdainful of state but not keen to make any significant lifestyle changes.. Feel that the next generation will somehow have to manage and cope.. 'long time away’
- Far wider changes in power, gender, distributive/ procedural and recognisational justice …
Why transformation, not revolution? Emancipation/ liberational politics.. Systemic changes to issues concerning consumtpion/ Production/ distribution/ knowledge politics..
This of course arises the question…what is desireable or not…who decides and what perspective matters (everyone in this room might have a different idea)
In Moussini– use islands as example – progressive stages of social and economic adaptation…from abandoning fishing to diversification…migration…but as in he case of ghoramara – what tranformation possible if island disappearing?
Whatever the case may be there is an agreement that transformation should be radical, non incremental and non business as usual
MOVE TO PHOTO VOICE…
Mehta et al - Climate change and uncertainty from below and above
Climate change and uncertainty
from below and above
Lyla Mehta, Alankar, Shibaji Bose, Upasona
Ghosh and Vijay Kumar
• Impacts and knowledges of climate change are
characterised by uncertainty
•Integration in CC decision making disputed
•Ecological uncertainty usually conceptualised
from ‘above’ by experts
• How attuned are these with how local people
live with and understand uncertainty?
The project examined :
• Uncertainty from ‘below’ (and ‘above’)
• Storylines of uncertainty, climate change,
histories of scarcity, flooding etc.
• A range of pathways (both dominant and
alternative) from a range of stakeholders
• Patterns of resilience and coping
• Path dependency - major drivers of social
and political change in conjunction with
patterns of uncertainty
What is uncertainty?
• a situation of indeterminancies where not
enough is known about the probabilities of a
particular set of outcomes and they cannot be
calculated (Knight, 1921; Douglas, 1985)
• Roots in many disciplines - incomplete
knowledge / incertitude
•Epistemological and ontological uncertainties
(Walker et al)
• Official responses to uncertainty have been
inadequate (Wynne ; Stirling) and tendency
to control uncertainty/ treat it as risk
Uncertainties in CC
• Uncertainties in CC projections high and
local level impacts difficult to predict
• IPCC : uncertainties around spatial and
temporal patterns of rainfall; intensification
of present climatic variability
• ‘Monster’ or ‘super-wicked’ problem
• Quantitative assessment based on
‘probabilities’ and problems with
• Primacy of computer models and their
Uncertainty from above: the framings of
experts, modelers, planners, the State,
politicians, markets and scientists (stratified,
heterogenous, powerful ). The ‘official’
Uncertainty from below: the framings of lay
and local people (stratified, heterogeneous,
power) in the global South. Considered to be
‘experiential’ non-official knowledge.
The Middle Or Translators: knowledge
brokers, intermediaries, street level
bureaucrats, activists, academics, media
etc. who often bridge ‘above’ and ‘middle’
Climate change from below?
• Jasanoff: Need to synchronise scientific
framings with ‘mundane rhythms of lived lives
and specificities of human experience’
• CC uncertainties exacerbated by livelihood
practices, social difference and multiple drivers
• Social meanings/ interactions with ecological
worlds (e.g. political )
• Role of different kinds of knowledges
• Institutional arrangements
• Practices of anticipation (Hastrup 2013)
• Wetlands – Sunderbans
• Drylands – Kutch:
• Urban India: (Delhi/ Mumbai)
• Global / national: (Ethnography
of scientists, experts, modellers )
• Ethnographies of knowledges
•Practices and cultures
•Implications for social justice /
Methodology and methods
• Mixed methods
• Discourse and textual analysis
• Semi structured interviews and FGDs
• Ethnographic engagement
• Historical analysis
• Photovoice and embedded comms
• Methodologies for appraisal/
• Uncertainty omnipresent in daily life
(cyclones/ sea level rise/ tidal waves/ floods)
•Political economy – So close yet so far/
poverty and government neglect
•Increasing livelihood uncertainty/ migration
•Uncertainties in science (e.g. around
embankments/ river siltation/ island loss)
Dominant pathways: Focus on planned exist
/ embankments / mangrove restoration/
•Local people left out or ‘blamed’ –
Sunderbans not for people – www.steps-centre.org
• Local people used to living with
• Still: reporting extreme events and
changes (e.g. changes in rainfall pattern/
• Lots of official measures but no reduction
• CC one of many changes (e.g. pollution/
industrialisation/ commodification of
• Island heat effect
• Sea level rise
• Provision of water /
new politics of
• Expansion over
• Floods / soil
Delhi / Mumbai
• Above overconfident and not taking
uncertainty seriously (technological fixes)
• Business and usual and profit oriented
• Middle problematizes issues and provides
• Poor face vulnerabilities and differentiated
by class, caste and gender
• Attack from elites (evictions etc.. )
Issues/ conclusions/ questions
•Scientists struggling with uncertainty – but
despite limits won’t let go of models. Unclear how
to deal with situated contexts & multiple drivers
• Diverse experiences of uncertainty and how it
interacts with lives/ livelihoods
• Uncertainty not new; CC one additional
dimension – ‘ Life is uncertain’
•CC as all pervasive discourse in urban areas –
less so in Sunderbans / Kutch
• Political economy and politics of uncertainty
•Institutional complexities and lack of coordination
• Diverse roles of ‘above’, ‘middle’ and ‘below’
Thoughts on pathways
• Range between top down capitalist driven
development (Kutch/ cities)/ complete
marginalisation and neglect (Sunderbans)
• Official neglect of uncertainty has increased
local level insecurities and illbeing
• Scope to urge ‘above’ to be more attuned with
local rhythms of uncertainty
• Local histories highlight long history of
adaptation and indigenous patterns of coping
• Alternatives exist across the sites
• In the face of growing CC threats, some may not
be viable ; some hybrids emerging.. but how
feasible are options such as ‘planned exit’?
Gaps/ focus of current project
• Various dimensions of scientific
• Focus on ‘Above’ / expert notions of
uncertainty and differences in ‘above’
• Translations across above and below
• Transformations and radical changes
in development pathways