Co-benefits of post-2012 global climate mitigation policies

This paper provides an analysis of co-benefits for traditional air pollutants made possible through global climate policies using the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model in the time horizon up to 2050. The impact analysis is based on projections of energy consumption provided by the Prospective Outlook for the Long term Energy System (POLES) model for a scenario without any global greenhouse gas mitigation efforts, and for a 2°C climate policy scenario which assumes internationally coordinated action to mitigate climate change. Outcomes of the analysis are reported globally and for key world regions: the European Union (EU), China, India and the United States. The assessment takes into account current air pollution control legislation in each country. Expenditures on air pollution control under the global climate mitigation regime are reduced in 2050 by 250 billion € when compared to the case without climate measures. Around one third of financial co-benefits estimated world-wide in this study by 2050 occur in China, while an annual cost saving of 35 billion (Euros) € is estimated for the EU if the current air pollution legislation and climate policies are adopted in parallel. Health impacts of air pollution are quantified in terms of loss of life expectancy related to the exposure from anthropogenic emissions of fine particles, as well as in terms of premature mortality due to ground-level ozone. For example in China, current ambient concentrations of particulate matter are responsible for about 40 months-losses in the average life expectancy. In 2050, the climate strategies reduce this indicator by 50 %. Decrease of ozone concentrations estimated for the climate scenario might save nearly 20,000 cases of premature death per year. Similarly significant are reductions of impacts on ecosystems due to acidification and eutrophication.     

Water quality in rice-growing watersheds in a Mediterranean climate

Rice (Oryza sativa L.) agriculture is estimated to cover 161 million ha of land on Earth, with 10% grown in temperate regions. Currently there are strong concerns about surface water nutrient pollution, and the purpose of this study was to determine the impacts of temperate rice cultivation on nutrient dynamics at the small watershed scale. Over the course of the 2008 growing season (May through September), bi-weekly grab samples were collected from outlets of 11 agricultural subwatersheds in California. Samples were analyzed for NO₃-N, NH₄-N, PO₄-P, K, and dissolved organic nitrogen (DON) concentrations, and the average values across all subwatersheds and sampling dates were 0.22, 0.031, 0.047, 1.36, and 0.32 mg L⁻¹, respectively. Linear mixed effects analysis was used to evaluate the magnitude of relationships between nutrient concentration and flux and subwatershed characteristics (i.e. percent soil clay and organic matter, percent rice area, irrigation water reuse, subwatershed discharge, irrigated area, and time, measured as the day in the growing season). For all nutrients, flux decreased over time and increased with discharge. Concentrations of K and DON were highest at the start and end of the growing season. Concentrations of NH₄-N were near non-detect levels, with the exception of a peak in mid-July, which corresponds to when many growers top-dress rice fields with N fertilizer. Nitrate-N concentration and flux decreased with percent rice area, whereas PO₄-P concentrations increased with percent rice area, indicating that rice area should be considered in future watershed-scale studies of nutrient discharge. In all subwatersheds, the discharge loads of K were smaller than surface water input loads, while NO₃-N, NH₄-N, PO₄-P, and DON discharge loads exceeded input loads when total growing season discharge was greater than 3500-6600 m³ ha⁻¹. This implies that the management of subwatershed discharge can be used to control nutrient export from rice-growing areas.     

Roost type influences torpor use by Australian owlet-nightjars

Australian owlet-nightjars (Aegotheles cristatus; ～50?g) are one of only a few avian species that roost in cavities year-round and regularly enter torpor. Cavity roosts act as thermal buffers, and roost type likely affects energy expenditure of small birds. We used radiotelemetry to locate diurnal winter roost sites of owlet-nightjars in central Australia and to measure body (T (b)) and skin (T (skin)) temperature. We also recorded ambient temperature inside (T (IN)) and outside roosts. Individual owlet-nightjars used one to seven different roosts (tracking time 3-10?weeks), selecting either rock crevices (four birds) or tree hollows (four birds), or switching between the two roost types (seven birds). Rock crevices (T (IN) +9°C to +33°C) were warmer and thermally more stable than tree hollows (T (IN) -4.0°C to +37°C). Torpor, often expressed by a reduction of T (skin)/T (b) by >10°C for 3-4?h at dawn, was influenced by roost selection; torpor use in tree hollows was almost twice that in rock crevices. Despite the potential energy savings accrued from roosting in well-insulated cavities, owlet-nightjars roosted in tree hollows more often (65% bird days, n?=?398) than in rock crevices (35% bird days, n?=?211). Lower costs of arousal from torpor via passive rewarming and basking and decreased risk of predation are two possible explanations for the preference to roost in tree hollows. We provide the first evidence for the influence of cavity roost selection on torpor use in a free-ranging bird and show that roost selection and thermal biology are strongly interrelated in determining energy expenditure.     

Torpor and activity in a free-ranging tropical bat: implications for the distribution and conservation of mammals?

Bats are most diverse in the tropics, but there are no quantitative data on torpor use for energy conservation by any tropical bat in the wild. We examined the thermal biology, activity patterns and torpor use of two tree-roosting long-eared bats (Nyctophilus geoffroyi, 7.8?g) in tropical northern Australia in winter using temperature telemetry. Bats commenced activity about 20?min after sunset, ended activity about 2.5?h before sunrise and entered torpor everyday in the early morning even when minimum ambient temperatures (T _a) were as high as 23°C. On average, bats remained torpid for almost 5?h, mean minimum skin temperature (T _skin) measured was 22.8?±?0.1°C and daily T _skin minima were correlated with T _a. Our study shows that even in the tropics, torpor is frequently employed by bats, suggesting that worldwide most bat species are heterothermic and use torpor for energy conservation. We propose that the ability of employing torpor and the resulting highly plastic energy requirements may partially explain why these small insectivorous bats can inhabit almost the entire Australian continent despite vastly different climatic and likely trophic conditions. Reduced energy requirements also may permit survival in degraded or modified habitats, reduce the need for foraging and reduce exposure to predators. Thus, the ability to employ torpor may be one important reason for why most Australian bats and other heterothermic mammals have not gone extinct whereas many obligatory homeothermic mammals that cannot employ torpor and have high energy and foraging requirements have suffered high rates of extinctions.     

Sensitivity of species-distribution models to error,bias, and model design: An application to resource selection functions for woodland caribou

Models that predict distribution are now widely used to understand the patterns and processes of plant and animal occurrence as well as to guide conservation and management of rare or threatened species. Application of these methods has led to corresponding studies evaluating the sensitivity of model performance to requisite data and other factors that may lead to imprecise or false inferences. We expand upon these works by providing a relative measure of the sensitivity of model parameters and prediction to common sources of error, bias, and variability. We used a one-at-a-time sample design and GPS location data for woodland caribou (Rangifer tarandus caribou) to assess one common species-distribution model: a resource selection function. Our measures of sensitivity included change in coefficient values, prediction success, and the area of mapped habitats following the systematic introduction of geographic error and bias in occurrence data, thematic misclassification of resource maps, and variation in model design. Results suggested that error, bias and model variation have a large impact on the direct interpretation of coefficients. Prediction success and definition of important habitats were less responsive to the perturbations we introduced to the baseline model. Model coefficients, prediction success, and area of ranked habitats were most sensitive to positional error in species locations followed by sampling bias, misclassification of resources, and variation in model design. We recommend that researchers report, and practitioners consider, levels of error and bias introduced to predictive species-distribution models. Formal sensitivity and uncertainty analyses are the most effective means for evaluating and focusing improvements on input data and considering the range of values possible from imperfect models.