Gaining Longitudinal Accounts of Carers' Experiences Using IPA and Photograph Elicitation.

Fluctuations in positive and negative caregiving experiences remain only partially explained as the significant variability over time of potential predictive factors themselves is understudied. The current study aims to gain considerable insight into caregiving experiences and perceptions over time by using photovoice methodology to support semi-structured interviews. A case study, longitudinal design is taken with three female caregivers who provide detailed insight into their caregivers' experiences over a 12 month period. The interview transcripts were analyzed using IPA- Interpretative Phenomenological Analysis. This innovative combination of methods resulted in the emergence of three related themes which included consuming the role, feeling consumed by the role, and letting go of the role. The idiographic approach taken allowed both within case differences to be examined over time, and also between carer differences to be highlighted. Implications of illness type and its characteristics, and of attachment and relationship quality with the care recipient were seen in terms of how and when the caregivers moved between the themes identified. The use of others' support or respite care is examined vis-a vis caregiver's own beliefs, emotions, relationship attachment and motivations to care. Caregivers self-efficacy beliefs also shifted over time and were influential in caregiver experience as the care recipient condition or needs changed. No previous studies have found that negative caregiving consequences are, in part, under volitional control and yet our data on the underlying reasons for consuming caregiving or allowing themselves to consume, would suggest this may in part be true. This is important because it suggests that interventions to support caregivers should address relational and motivational factors more fully.

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate.

Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root-mean-square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.

Exploring caregiving experiences: caregiver coping and making sense of illness.

OBJECTIVES: The current research explores how family caregivers (1) make sense of caregiving and (2) cope with their circumstance. METHOD: We analysed semistructured interviews of 13 caregivers of people with either stroke (n = 5) or dementia (n = 8) and used photographs that caregivers took exemplifying their caregiving experiences to elicit their description of how they made sense of caregiving. This enabled greater insight into caregivers' perspective of caregiving complementing our use of Interpretative Phenomenological Analysis (IPA) to analyse verbatim transcripts. RESULTS: Emerging themes included (1) making sense of illness including the implications of receiving a diagnosis, caregiving motivations and receiving support, and (2) coping with caregiving, with variance in coping depending on, in part, individual differences in sense making. Caregivers adopted active and information seeking techniques to deal with current problems and to increase their sense of control, but avoidant techniques when considering future logistics of caregiving and when feeling helpless due to the burden they faced. At times caregivers looked on the bright side and made downward comparisons. CONCLUSION: The combination of elicitation techniques and analysis using IPA established patterns across caregivers and individual differences between caregivers in the meaning they assigned to their caregiving experience. Differences in sense making were based on the context of the caregiving stressor, which in turn influenced the variability in caregiver's coping techniques adopted. The analysis detailed within this article provides evidence that information and service provision must be tailored to individual caregiver experiences.