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Detecting and understanding disturbance is a challenge in ecology that has grown more critical with global environmental change and the emergence of research on social–ecological systems. We identify three areas of research need: developing a flexible framework that incorporates feedback loops between social and ecological systems, anticipating whether a disturbance will change vulnerability to other environmental drivers, and incorporating changes in system sensitivity to disturbance in the face of global changes in environmental drivers. In the present article, we review how discoveries from the US Long Term Ecological Research (LTER) Network have influenced theoretical paradigms in disturbance ecology, and we refine a framework for describing social–ecological disturbance that addresses these three challenges. By operationalizing this framework for seven LTER sites spanning distinct biomes, we show how disturbance can maintain or alter ecosystem state, drive spatial patterns at landscape scales, influence social–ecological interactions, and cause divergent outcomes depending on other environmental changes.

Uncertainties in ecophysiological responses to environment, such as the impact of atmospheric and soil moisture conditions on plant water regulation, limit our ability to estimate key inputs for ecosystem models. Advanced statistical frameworks provide coherent methodologies for relating observed data, such as stem sap flux density, to unobserved processes, such as canopy conductance and transpiration. To address this need, we developed a hierarchical Bayesian State-Space Canopy Conductance (StaCC) model linking canopy conductance and transpiration to tree sap flux density from a 4-year experiment in the North Carolina Piedmont, USA. Our model builds on existing ecophysiological knowledge, but explicitly incorporates uncertainty in canopy conductance, internal tree hydraulics and observation error to improve estimation of canopy conductance responses to atmospheric drought (i.e., vapor pressure deficit), soil drought (i.e., soil moisture) and above canopy light. Our statistical framework not only predicted sap flux observations well, but it also allowed us to simultaneously gap-fill missing data as we made inference on canopy processes, marking a substantial advance over traditional methods. The predicted and observed sap flux data were highly correlated (mean sensor-level Pearson correlation coefficient = 0.88). Variations in canopy conductance and transpiration associated with environmental variation across days to years were many times greater than the variation associated with model uncertainties. Because some variables, such as vapor pressure deficit and soil moisture, were correlated at the scale of days to weeks, canopy conductance responses to individual environmental variables were difficult to interpret in isolation. Still, our results highlight the importance of accounting for uncertainty in models of ecophysiological and ecosystem function where the process of interest, canopy conductance in this case, is not observed directly. The StaCC modeling framework provides a statistically coherent approach to estimating canopy conductance and transpiration and propagating estimation uncertainty into ecosystem models, paving the way for improved prediction of water and carbon uptake responses to environmental change.

The impact of stored water on estimates of transpiration from scaled sap flux measurements was assessed in mature Pinus taeda (L.) at the Duke Free-Air CO(2) Enrichment (FACE) site. We used a simple hydraulic model with measurements of sap flux (J) at breast height and the base of the live crown for 26 trees over 6 months to examine the effects of elevated CO(2) (eCO(2)) and fertilization (N(F)) treatments, as well as temporal variation in soil moisture (M(()(t)())), on estimates of the hydraulic time constant (κ). At low M(()(t)()), there was little (12%) difference in κ of different treatments. At high M(()(t)()), differences were much greater, with κ reductions of 27, 52 and 34% in eCO(2), N(F) and eCO(2) × N(F) respective to the control. Incorporating κ with these effects into the analysis of a larger data set of previous J measurements at this site (1998-2008) improved agreement between modeled and measured values in 92% of cases. However, a simplified calibration of κ that neglected treatment and soil moisture effects performed more dependably, improving agreement in 98% of cases. Incorporating κ had the effect of increasing estimates of reference stomatal conductance at 1 kPa vapor pressure deficit (VPD) and saturating photosynthetic active radiation (PAR) an average of 12-14%, while increasing estimated sensitivities to VPD and PAR. A computationally efficient hydraulic model, such as the one presented here, incorporated into a hierarchical model of stomatal conductance presents a novel approach to including hydraulic time constants in estimates of stomatal responses from long-term sap flux data sets.

This paper examines Block's (2001) claim that whereas the notion of method no longer plays a significant role in the thinking of applied linguists, it still plays a vital role in the thinking of teachers. In order to assess Block's claim, four sources of data on teachers' beliefs were examined—two direct sources of data: (1) interviews with questions directly addressing teachers' opinions on the concept of method and (2) discussion board postings on the topic of post-method, and two indirect sources: (3) language learning/teaching autobiographies and (4) teaching journals. The evidence from the data suggests that teacher interest in methods is determined by how far methods provide options in dealing with particular teaching contexts. Rather than playing a vital role in teacher thinking, teacher attitude towards methods is highly pragmatic. In the light of this evidence, implications for teacher education are considered.

Extending the useful life of antimicrobial drugs through appropriate use-that is, use that maximizes therapeutic impact while minimizing toxicity and the development of resistance-is an important component of efforts to prevent and control the emerging threat of antimicrobial resistance. The major paradigms of antimicrobial drug use involve acute infections in outpatients, acute infections in inpatients, chronic infections, and agriculture/veterinary medicine. The factors that influence drug use and the challenges that need to be addressed in promoting more appropriate use are different in each of these paradigms. For acute respiratory infections in outpatients, data from intervention trials suggest that concurrent multifaceted interventions may be effective in promoting appropriate drug prescribing. The next challenge is to extend these interventions to larger populations by incorporating them into routine medical practice.