Risk transfer policies and climate-induced immobility among smallholder farmers

Climate change is anticipated to impact smallholder farmer livelihoods substantially. However, empirical evidence is inconclusive regarding how increased climate stress affects smallholder farmers’ deployment of various livelihood strategies, including rural–urban migration. Here we use an agent-based model to show that in a South Asian agricultural community experiencing a 1.5 oC temperature increase by 2050, climate impacts are likely to decrease household income in 2050 by an average of 28%, with fewer households investing in both economic migration and cash crops, relative to a stationary climate. Pairing a small cash transfer with risk transfer mechanisms significantly increases the adoption of migration and cash crops, improves community incomes and reduces community inequality. While specific results depend on contextual factors such as risk preferences and climate risk exposure, these interventions are robust in improving adaptation outcomes and alleviating immobility, by addressing the intersection of risk aversion, financial constraints and climate impacts

Dance movement therapy for depression

BACKGROUND: Depression is a debilitating condition affecting more than 350 million people worldwide (WHO 2012) with a limited number of evidence-based treatments. Drug treatments may be inappropriate due to side effects and cost, and not everyone can use talking therapies.There is a need for evidence-based treatments that can be applied across cultures and with people who find it difficult to verbally articulate thoughts and feelings. Dance movement therapy (DMT) is used with people from a range of cultural and intellectual backgrounds, but effectiveness remains unclear. OBJECTIVES: To examine the effects of DMT for depression with or without standard care, compared to no treatment or standard care alone, psychological therapies, drug treatment, or other physical interventions. Also, to compare the effectiveness of different DMT approaches. SEARCH METHODS: The Cochrane Depression, Anxiety and Neurosis Review Group's Specialised Register (CCDANCTR-Studies and CCDANCTR-References) and CINAHL were searched (to 2 Oct 2014) together with the World Health Organization's International Clinical Trials Registry Platform (WHO ICTRP) and ClinicalTrials.gov. The review authors also searched the Allied and Complementary Medicine Database (AMED), the Education Resources Information Center (ERIC) and Dissertation Abstracts (to August 2013), handsearched bibliographies, contacted professional associations, educational programmes and dance therapy experts worldwide. SELECTION CRITERIA: Inclusion criteria were: randomised controlled trials (RCTs) studying outcomes for people of any age with depression as defined by the trialist, with at least one group being DMT. DMT was defined as: participatory dance movement with clear psychotherapeutic intent, facilitated by an individual with a level of training that could be reasonably expected within the country in which the trial was conducted. For example, in the USA this would either be a trainee, or qualified and credentialed by the American Dance Therapy Association (ADTA). In the UK, the therapist would either be in training with, or accredited by, the Association for Dance Movement Psychotherapy (ADMP, UK). Similar professional bodies exist in Europe, but in some countries (e.g. China) where the profession is in development, a lower level of qualification would mirror the situation some decades previously in the USA or UK. Hence, the review authors accepted a relevant professional qualification (e.g. nursing or psychodynamic therapies) plus a clear description of the treatment that would indicate its adherence to published guidelines including Levy 1992, ADMP UK 2015, Meekums 2002, and Karkou 2006. DATA COLLECTION AND ANALYSIS: Study methodological quality was evaluated and data were extracted independently by the first two review authors using a data extraction form, the third author acting as an arbitrator. MAIN RESULTS: Three studies totalling 147 participants (107 adults and 40 adolescents) met the inclusion criteria. Seventy-four participants took part in DMT treatment, while 73 comprised the control groups. Two studies included male and female adults with depression. One of these studies included outpatient participants; the other study was conducted with inpatients at an urban hospital. The third study reported findings with female adolescents in a middle-school setting. All included studies collected continuous data using two different depression measures: the clinician-completed Hamilton Depression Rating Scale (HAM-D); and the Symptom Checklist-90-R (SCL-90-R) (self-rating scale).Statistical heterogeneity was identified between the three studies. There was no reliable effect of DMT on depression (SMD -0.67 95% CI -1.40 to 0.05; very low quality evidence). A planned subgroup analysis indicated a positive effect in adults, across two studies, 107 participants, but this failed to meet clinical significance (SMD -7.33 95% CI -9.92 to -4.73).One adult study reported drop-out rates, found to be non-significant with an odds ratio of 1.82 [95% CI 0.35 to 9.45]; low quality evidence. One study measured social functioning, demonstrating a large positive effect (MD -6.80 95 % CI -11.44 to -2.16; very low quality evidence), but this result was imprecise. One study showed no effect in either direction for quality of life (0.30 95% CI -0.60 to 1.20; low quality evidence) or self esteem (1.70 95% CI -2.36 to 5.76; low quality evidence). AUTHORS' CONCLUSIONS: The low-quality evidence from three small trials with 147 participants does not allow any firm conclusions to be drawn regarding the effectiveness of DMT for depression. Larger trials of high methodological quality are needed to assess DMT for depression, with economic analyses and acceptability measures and for all age groups

Navigating a Warming World: Rural-Urban Migration in the Context of Smallholder Farmer Climate Adaptation

Over the 21st century, climate change is likely to substantially threaten the viability of many of the world’s smallholder farmer livelihoods through increased risks of extreme droughts, floods, heatwaves, and other hazards. How farmers manage these risks will have significant consequences for several public policy issues, including rural-urban migration. In this dissertation, I employ a mixed-methods framework to explore the fundamental mechanisms by which climate risk and policy interventions shape the migration behavior of smallholder farmers. To do this, I integrate agent-based modelling, evolutionary game theory, survey research, and robust decision-making tools to investigate three multifaceted questions. First, how is climate change likely to affect the use of rural-urban migration by farming households, relative to other adaptation strategies like diversifying crops? Second, how do various decision-making factors, including risk aversion, loss aversion, and pro-social preferences, shape the climate adaptation strategies that are likely to be pursued by farmers? Third, how can policymakers at local and national governance scales design robust policies to improve smallholder farmer resilience to climate shocks? To address these questions, I focus on data and case studies from South Asia, a region that is characterized by a high dependence on small-scale farming, costly livelihood alternatives to subsistence farming (including migration), and high exposure to climate impacts. This dissertation finds that future climate change is likely to exacerbate poverty traps, both by directly reducing crop yields and by constraining farming households’ ability to pursue livelihood alternatives, including migration. Furthermore, while climate risks are already salient to farmers’ economic decision-making, these also increase the perceived riskiness of alternative livelihoods to farming, including international migration and off-farm wage labor. Complementary policy packages, such as pairing cash transfers with risk transfer mechanisms, and combining insurance subsidies with interventions cueing pro-social preferences, can be effective in providing farmers with the financial stability and capital to make effective adaptation investments. However, a lack of coordination across governance scales may impede the ability to meet key policymaking objectives across a range of climate futures. Therefore, effective adaptation interventions need to find complementarities across traditional policy spheres and bureaucratic divisions

Should Alberta upgrade oil sands bitumen?: an integrated life cycle framework to evaluate energy systems investment tradeoffs

Bibliography: p. 197-198

Prosocial preferences improve climate risk management in subsistence farming communities

Several governments have tested formal index-based insurance to build climate resilience among smallholder farmers. Yet, adoption of such programmes has generated concerns that insurance may crowd out long-established informal risk transfer arrangements. Understanding this phenomenon requires new analytic approaches that capture dynamics of human social behaviour when facing risky events. Here we develop a modelling framework, based on evolutionary game theory and empirical data from Nepal and Ethiopia, to demonstrate that insurance may introduce a new social dilemma in farmer risk management strategies. We find that while socially optimal risk management is achieved when all farmers pursue a combination of formal and informal risk transfer, a community of self-interested agents is unable to maintain this co-existence under rising climate risks. We find that a combination of prosocial preferences—moderate altruism and solidarity—helps farmers overcome these concerns and achieve the social optimum. In our model, behavioural interventions that cue such preferences can reduce farmer expected losses by 26% and save approximately 5% of community agricultural income through reduced premium subsidies under climate risk levels likely to emerge in the coming decades

COPTEM: A Model to Investigate the Factors Driving Crude Oil Pipeline Transportation Emissions

Previous transportation fuel life cycle assessment studies have not fully accounted for the full variability in the crude oil transport stage, for example, transporting a light crude through a high-diameter pipeline, vs transporting a heavy crude through a small-diameter pipeline. We develop a first-principles, fluid mechanics-based crude oil pipeline transportation emissions model (COPTEM) that calculates the greenhouse gas (GHG) emissions associated with pipeline transport as a function of crude oil parameters, pipeline dimensions, and external factors. Additionally, we estimate the emissions associated with the full life cycle of pipeline construction, maintenance, and disposal. This model is applied to an inventory of 62 major Canadian and U.S. pipelines (capacity greater than 100 000 barrels/day) to estimate the variability of GHG emissions associated with pipeline transportation. We demonstrate that pipeline GHG emissions intensities range from 0.23 to 20.3 g CO₂e/(bbl·km), exhibiting considerably greater variability than data reported in other studies. A sensitivity analysis demonstrates that the linear velocity of crude transport and pipeline diameter are the most impactful parameters driving this variability. To illustrate one example of how COPTEM can be used, we develop an energy efficiency gap analysis to investigate the possibilities for more efficient pipeline transport of crude oil