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Migration is often conceptualised as a failure to adapt to environmental risks and change, while new research suggests migration is an effective front-line response to environmental degradation. This thesis investigates the social and environmental mechanisms that lead to individuals adopting migration as an adaptation to environmental change. It argues that the use of migration as a response to environmental change depends on the ecosystem services available at location, the mobility characteristics of the individual and the degree to which ecosystem contribute to place utility. I interpret place utility as a function of both instrumental and affective bonds to place. The research tests these ideas in a highland migrant sending area in a small coastal valley of Peru, geographically and culturally connected to the capital city Lima but predominantly rural in nature. The area has established rural-urban migration networks and a complex social-ecological system vulnerable to climate change. Data on mobility characteristics, contributors to place utility and use of ecosystem services in the rural sending area were collected through household surveys and semi-structured interviews. Four settlements were sampled along an altitudinal transect representing different ecological zones as well as different access to off-farm employment and other opportunities. Analysis of the primary data shows that individuals gain utility from non-provisioning ecosystem services independently of reliance on provisioning ecosystem services. These impacts of climate change that previously only had a cultural significance take on significance in terms of migration. The data show that individuals remain in location because of positive place utility or low mobility potential. I conclude that a likely result of environmental change is an increase in dissatisfaction with no significant changes in the composition of the population. Low mobility potential, a function of affective bonds to place, prevents dissatisfied people from migrating. The thesis shows that populations are likely to be persistent in the face of environmental change. Understanding why individuals remain in location reveals the viability of migration as an adaptation to environmental change.

Many studies have estimated empirical relationships between dengue, weather, and El Ni˜no in several regions of the world. Some of these studies used their model estimations to predict the potential impacts of climate change on the future distribution of dengue. Often, these studies have sidestepped elements that are key to the estimation of the effects of climate variables on dengue with statistical confidence. For example, they fail to incorporate covariates that may confound the empirical associations between dengue, weather, El Ni˜no, and climate undermining their model estimations. Additionally, several studies used nationally or supra-nationally aggregated data which remove the spatial variability in all variables making it difficult to detect complex associations between dengue and climate variables. Other studies were conducted in small geographical areas with the problem of having low numbers of disease cases posing problems for their analysis with statistical confidence. Here, we used the most comprehensive dengue-related datasets analysed to date and several statistical methods to investigate the effects of weather, climate, and El Ni˜no on dengue incidence. We demonstrate that such effects are robust to the confounding effects of socioeconomic development and other non-climatic factors such as seasonal trends and inter-annual variability. Our results reveal that the effects weather and El Ni˜no are significantly heterogeneous between provinces influenced by the underlying climate. With the exception of access to piped water, we could not identify significant effects of socioeconomic status on dengue occurrence. This result is likely related to human behaviour or the lack of protective measures against mosquitoes. We used our model estimations to project the potential impacts of climate change on dengue incidence by 2030, 2050 and 2080 with greater statistical confidence than previous studies. Our projections indicate that climate change is likely to increase dengue incidence mainly in already endemic areas.

Atmospheric measurements of carbon dioxide (CO2) and oxygen (O2) are a valuable tool to better understand the global carbon cycle. Technological improvements have resulted in near-real-time continuous measurements of both O2 and CO2 becoming viable. The increased time resolution of continuous measurements compared to discrete flask samples provides greater insight into atmospheric variations and short-term processes. These measurements will become even more relevant as the research focus shifts from the global to regional scale, for example anthropogenic emissions verification. This thesis presents a 4.5 year record of atmospheric CO2 and O2 measurements made at Weybourne Atmospheric Observatory (WAO) on the north Norfolk coast in the United Kingdom. In situ, continuous measurements cover the period October 2007 to April 2012. Data for the tracer ‘Atmospheric Potential Oxygen’ (APO) are also presented. The analytical methodology is described in detail and the data are examined on interannual, seasonal, synoptic and diurnal timescales. The precision of ambient air measurements is about ±0.03 ppm for CO2 and ±2.0 per meg for O2. The average amplitude of the WAO seasonal cycle is 14.9 ppm for CO2, 134.2 per meg for O2 and 59.0 per meg for APO, similar to other stations at similar latitudes. Interannual variability in the seasonal cycle amplitude is also investigated. Growth rates over the 4.5 year period are 2.4 ppm yr-1 for CO2, -25 per meg yr-1 for O2 and -13 per meg yr-1 for APO, also similar to other nearby stations. Short-term analyses reveal clear diurnal cycles in both CO2 and O2 that vary seasonally throughout the year. No diurnal cycle is observed in APO. A number of short-term events are explored and confirm that WAO experiences both clean marine air masses from the Arctic and North Atlantic, as well as fossil fuel pollution signals from the UK and continental Europe.