The art of adaptation: Living with climate change in the rural American Southwest

As adaptation has come to the forefront in climate change discourse, research, and policy, it is crucial to consider the effects of how we interpret the concept. This paper draws attention to the need for interpretations that foster policies and institutions with the breadth and flexibility to recognize and support a wide range of locally relevant adaptation strategies. Social scientists have argued that, in practice, the standard definition of adaptation tends to prioritize economic over other values and technical over social responses, draw attention away from underlying causes of vulnerability and from the broader context in which adaptive responses take place, and exclude discussions of inequality, justice, and transformation. In this paper, we discuss an alternate understanding of adaptation, which we label “living with climate change,” that emerged from an ethnographic study of how rural residents of the U.S. Southwest understand, respond to, and plan for weather and climate in their daily lives, and we consider how it might inform efforts to develop a more comprehensive definition. The discussion brings into focus several underlying features of this lay conception of adaptation, which are crucial for understanding how adaptation actually unfolds on the ground: an ontology based on nature–society mutuality; an epistemology based on situated knowledge; practice based on performatively adjusting human activities to a dynamic biophysical and social environment; and a placed-based system of values. We suggest that these features help point the way toward a more comprehensive understanding of climate change adaptation, and one more fully informed by the understanding that we are living in the Anthropocene.     

Nitrogen inputs to seventy-four southern New England estuaries: Application of a watershed nitrogen loading model

Excess nitrogen inputs to estuaries have been linked to deteriorating water quality and habitat conditions which in turn have direct and indirect impacts on aquatic organisms. This paper describes the application of a previously verified watershed loading model to estimate total nitrogen loading rates and relative source contributions to 74 small-medium sized embayment-type estuaries in southern New England. The study estuaries exhibited a gradient in nitrogen inputs of a factor of over 7000. On an areal basis, the range represented a gradient of approximately a factor of 140. Therefore, all other factors being equal, the study design is sufficient to evaluate ecological effects conceptually tied to excess nitrogen along a nitrogen gradient. In addition to providing total loading inputs rates to the study estuaries, the model provides an estimate of the relative contribution of the nitrogen sources from each watershed to each associated estuary. Cumulative results of this analysis reveal the following source ranking (means): direct atmospheric deposition (37%), ≈wastewater (36%), >indirect atmospheric deposition (16%) > fertilizer (12%). However, for any particular estuary the relative magnitudes of these source types vary dramatically. Together with scientific evidence on symptoms of eutrophication, the results of this paper can be used to develop empirical pressure-state models to determine critical nitrogen loading limits for the protection of estuarine water quality.     

Another Year of Record Heat for the Oceans

Changes in ocean heat content(OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum.According to IAP/CAS data, ...     

Tumbi Landslide, Papua New Guinea: rainfall induced?

On 24 January 2012, a fatal landslide with an estimated volume of 3 Mm³ hit villagers and infrastructure in the Tagali Valley, Southern Highlands Province, Papua New Guinea (PNG). Although a moderate event by PNG standards, the associated human casualties and infrastructure destruction give a human as well as a scientific need to review the potential causes for the event. PNG experiences numerous landslides annually, most of which are trigged either by rainfall events or seismic activity. Here, we review the short-term rainfall patterns leading up to the slope failure at Tumbi Quarry and compare the rainfall accumulations obtained over durations of 30, 60 and 90 days prior to the landslide, with comparable rainfall accumulations obtained for other failures observed in PNG over a 12-year period. Additionally, a review of long-term rainfall over a period of 6 months prior to the failure is completed as well as an assessment of seismic activity. Based on our analysis, we believe a seismic trigger to be very unlikely, while the increase in rainfall in the 2 weeks prior to the failure in conjunction with a high-intensity rainfall event at the end of October 2011 could have had a greater influence in enhancing rather than restraining slope failure. This, in addition to natural denudational processes, geological structure and the anthropogenic activity in the vicinity of the landslide, could all have served to affect slope stability.     

Evaluation of NLDAS‐2 evapotranspiration against tower flux site observations

The North American Land Data Assimilation System project phase 2 (NLDAS‐2) has run four land surface models for a 30‐year (1979–2008) retrospective period. Land surface evapotranspiration (ET) is one of the most important model outputs from NLDAS‐2 for investigating land–atmosphere interaction or to monitor agricultural drought. Here, we evaluate hourly ET using in situ observations over the Southern Great Plains (Atmospheric Radiation Measurement/Cloud and Radiation Testbed network) for 1 January 1997–30 September 1999 and daily ET u‐sing in situ observations at the AmeriFlux network over the conterminous USA for an 8‐year period (2000–2007). The NLDAS‐2 models compare well against observations, with the National Centers for Environmental Prediction's Noah land surface model performing best, followed, in order, by the Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic models. Daily evaluation across the AmeriFlux network shows that for all models, performance depends on season and vegetation type; they do better in spring and fall than in winter or summer and better for deciduous broadleaf forest and grasslands than for croplands or evergreen needleleaf forest. Copyright © 2014 John Wiley & Sons, Ltd.     

Toxicity of tributyltin in the marine mollusc Mytilus edulis

Our previous studies have demonstrated that tributyltin (TBT) is genotoxic to the early life stages of marine mussels and worms. Here, the toxicity of TBT to adult organisms was determined using a suite of biomarkers designed to detect cytotoxic, immunotoxic and genotoxic effects. Exposure of adult mussels, Mytilus edulis, to environmentally realistic concentrations of TBTO for 7 days resulted in a statistically significant decrease in cell viability at concentrations of 0.5 μg/l and above. TBT had no effect on phagocytic activity or antioxidant capacity (FRAP assay). There was a statistically significant increase in DNA damage detected using the comet and micronucleus assays between the controls and 0.5, 1 and 5 μg/l of TBTO (P > 0.0005). Furthermore there was a strong correlation between DNA strand breaks (comet assay) and formation of micronuclei (P = 0.0005; R² = 61.5%). Possible mechanisms by which TBT could damage DNA either directly or indirectly are discussed including the possibility that TBT is genotoxic due to its ability to disrupt calcium homeostasis.     

Acid leaching of ash and coal: Time dependence and trace element occurrences

The leaching of coal and coal/asphaltite/wood-ashes in sulfuric acid (pH 1.0, 25 °C, S/L, 1:10) was studied as a function of time; acid consumption and extracted metal concentrations are presented. Whole coals consumed acid rapidly during the first few minutes, followed by slow acid consumption. Wood-, lignite-, and asphaltite-ashes consumed acid in two stages, the rapid phase extending < 30 min and the slow phase extended up to 10 days. The rapid phase was dominated by the dissolution of Ca, K and Mg ions for wood-ash, by Ca, Al and Mg ions for lignite-ash and Ca and Mg ions for asphaltite-ash. The sulfur concentration in solution and the concentrations of Ca, Fe, K, Mg, Na, P, Al and Mn in the aqueous phase verified the neutralizing capacity of the untreated ashes as well as the formation of insoluble sulfates in the residues. The slow phase kinetics differed for different fuels and exhibited leaching of several abundant elements—Fe, Al, K, Na and Mn. Trace elements (Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Th, U, V, Zn) sometimes required up to 32 h for maximal extraction from ashes. Suggestions are presented regarding the chemical nature of trace elements in the untreated coals and ashes and suitable residence times for economical industrial processes. We think it possible to combine bacteriological oxidation of sulfidic concentrates of acid leaching from ash of various qualities or even whole coals.     

Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification

Satellite retrievals of atmospheric composition provide a wealth of data on a global scale. These complement results from atmospheric chemistry-transport models (CTMs), and can be combined using data assimilation. We present two assimilation schemes coupled to the Danish Eulerian Hemispheric Model (DEHM), a three-dimensional, off-line CTM with full photochemistry: a variant on the ensemble Kalman filter and the three-dimensional variational scheme. The aim of this paper is to describe the two schemes and present an initial assessment of their impacts on model skill. Retrievals of multiple atmospheric trace gases are assimilated, namely: NO₂ tropospheric column densities, CH₄ total column densities, and partial column concentrations of O₃, CO and CH₄; these data are retrieved from four satellite sensors. Data for each species are assimilated independently of one another, and other species are only adjusted indirectly via the model’s chemistry and dynamics. Assimilation results are compared with measurements from surface monitoring stations and other satellite retrievals, and preliminary validation results are presented.Reference simulations (without assimilation) grossly underestimate surface CO concentrations, and both assimilation schemes eliminate this large and systematic model bias. The assimilation improves the spatial correlation of modelled CO with surface observations, and improves the spatial correlation between forecasts and retrievals for CO, NO₂ and O₃. Results for CH₄ show a loss of skill due to a mismatch in model bias between two assimilated CH₄ data-sets. Finally, we discuss differences in methodology and results between this paper and a recent study on multi-species chemical data assimilation. Joint optimisation of initial conditions and emission rates offers a promising direction for improving modelled boundary-layer concentrations.     

Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high‐elevation catchment

In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km²). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.