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This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant. [ABSTRACT FROM AUTHOR]

This paper offers new high-resolution oxygen and carbon isotope data from Stalagmite S1 from Mavri Trypa Cave, SW Peloponnese. Our data provide the climate background to the destruction of the nearby Mycenaean Palace of Nestor at Pylos at the transition from Late Helladic (LH) IIIB to LH IIIC, ~3150–3130 years before present (before AD 1950, hereafter yrs BP) and the subsequent period. S1 is dated by 24 U-Th dates with an averaged precision of ±26 yrs (2σ), providing one of the most robust paleoclimate records from the eastern Mediterranean for the end of the Late Bronze Age (LBA). The δ18O record shows generally wetter conditions at the time when the Palace of Nestor at Pylos was destroyed, but a brief period of drier conditions around 3200 yrs BP may have disrupted the Mycenaean agricultural system that at the time was likely operating close to its limit. Gradually developing aridity after 3150 yrs BP, i.e. subsequent to the destruction, probably reduced crop yields and helped to erode the basis for the reinstitution of a central authority and the Palace itself. [ABSTRACT FROM AUTHOR]

Over the 20th century, urbanization has substantially shaped the surface of Earth. With population rapidly shifting from rural locations towards the cities, urban areas have dramatically expanded on a global scale and represent crystallization points of social, cultural and economic assets and activities. This trend is estimated to persist for the next decades, and particularly the developing countries are expected to face rapid urban growth. The management of this growth will require good governance strategies and planning. By threatening the livelihoods, assets and health as foundations of human activities, another major global change contributor, climate change, became an equally important concern of stakeholders. Based on the climate trends observed over the 20th century, and a spatially explicit model of urbanization, this paper investigates the impacts of climate change in relation to different stages of development of urban areas, thus evolving a more integrated perspective on both processes. As a result, an integrative measure of climate change trends and impacts is proposed and estimated for urban areas worldwide. We show that those areas facing major urban growth are to a large extent also hotspots of climate change. Since most of these hotspots are located in the Global South, we emphasize the need for stakeholders to co-manage both drivers of global change. The presented integrative perspective is seen as a starting point to foster such co-management, and furthermore as a means to facilitate communication and knowledge exchange on climate change impacts. [ABSTRACT FROM AUTHOR]

Background: Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods: We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results: The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions: From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. [ABSTRACT FROM AUTHOR]

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. A promising option is eco-functional intensification through organic farming, an approach based on using and enhancing internal natural resources and processes to secure and improve agricultural productivity, while minimizing negative environmental impacts. In this concept an active soil microbiota plays an important role for various soil based ecosystem services such as nutrient cycling, erosion control and pest and disease regulation. Several studies have reported a positive effect of organic farming on soil health and quality including microbial community traits. However, so far no systematic quantification of whether organic farming systems comprise larger and more active soil microbial communities compared to conventional farming systems was performed on a global scale. Therefore, we conducted a meta-analysis on current literature to quantify possible differences in key indicators for soil microbial abundance and activity in organic and conventional cropping systems. All together we integrated data from 56 mainly peer-reviewed papers into our analysis, including 149 pairwise comparisons originating from different climatic zones and experimental duration ranging from 3 to more than 100 years. Overall, we found that organic systems had 32% to 84% greater microbial biomass carbon, microbial biomass nitrogen, total phospholipid fatty-acids, and dehydrogenase, urease and protease activities than conventional systems. Exclusively the metabolic quotient as an indicator for stresses on microbial communities remained unaffected by the farming systems. Categorical subgroup analysis revealed that crop rotation, the inclusion of legumes in the crop rotation and organic inputs are important farming practices affecting soil microbial community size and activity. Furthermore, we show that differences in microbial size and activity between organic and conventional farming systems vary as a function of land use (arable, orchards, and grassland), plant life cycle (annual and perennial) and climatic zone. In summary, this study shows that overall organic farming enhances total microbial abundance and activity in agricultural soils on a global scale. [ABSTRACT FROM AUTHOR]

The cotton mealybug, Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae), is a serious invasive species that significantly damages plants of approximately 60 families around the world. It is originally from North America and has also been introduced to other continents. Our goals were to create a current and future potential global distribution map for this pest under climate change with MaxEnt software. We tested the hypothesis of niche conservatism for P. solenopsis by comparing its native niche in North America to its invasive niches on other continents using Principal components analyses (PCA) in R. The potentially suitable habitat for P. solenopsis in its native and non-native ranges is presented in the present paper. The results suggested that the mean temperature of the wettest quarter and the mean temperature of the driest quarter are the most important environmental variables determining the potential distribution of P. solenopsis. We found strong evidence for niche shifts in the realized climatic niche of this pest in South America and Australia due to niche unfilling; however, a niche shift in the realized climatic niche of this pest in Eurasian owing to niche expansion. [ABSTRACT FROM AUTHOR]

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. [ABSTRACT FROM AUTHOR]

This paper aims to describe the spatial-temporal variability in catch of the main fishery resources of the Amazon River and floodplain lakes of the Lower Amazon, as well as relating the Catch per Unit of Effort with anomalies of some of the Amazon River, atmosphere and Atlantic Ocean system variables, determining the influence of the environment on the Amazonian fishery resources. Finfish landings data from the towns and villages of the Lower Amazon for the fisheries of three sites (Óbidos, Santarém and Monte Alegre), were obtained for the period between January 1993 and December 2004. Analysis of variance, detrended correspondence analysis, redundancy analysis and multiple regression techniques were used for the statistical analysis of the distinct time series. Fisheries production in the Lower Amazon presents differences between the Amazon River and the floodplain lakes. Production in the Amazon River is approximately half of the one of the floodplain lakes. This variability occurs both along the Lower Amazon River region (longitudinal gradient) and laterally (latitudinal gradient) for every fishing ground studied here. The distinct environmental variables alone or in association act differently on the fishery stocks and the success of catches in each fishery group studied here. Important variables are the flooding events; the soil the sea surface temperatures; the humidity; the wind and the occurence of El Niño-Southern Oscillation events. Fishery productivity presents a large difference in quantity and distribution patterns between the river and floodplain lakes. This variability occurs in the region of the Lower Amazon as well as laterally for each fishery group studied, being dependent on the ecological characteristics and life strategies of each fish group considered here. [ABSTRACT FROM AUTHOR]

This article builds on the premise that human consumption of goods, food and transport are the ultimate drivers of climate change. However, the nature of the climate change problem (well described as a tragedy of the commons) makes it difficult for individuals to recognise their personal duty to implement behavioural changes to reduce greenhouse gas emissions. Consequently, this article aims to analyse the climate change issue from a human-scale perspective, in which each of us has a clearly defined personal quota of CO2 emissions that limits our activity and there is a finite time during which CO2 emissions must be eliminated to achieve the “well below 2°C” warming limit set by the Paris Agreement of 2015 (COP21). Thus, this work’s primary contribution is to connect an equal per capita fairness approach to a global carbon budget, linking personal levels with planetary levels. Here, we show that a personal quota of 5.0 tons of CO2 yr-1 p-1 is a representative value for both past and future emissions; for this level of a constant per-capita emissions and without considering any mitigation, the global accumulated emissions compatible with the “well below 2°C” and 2°C targets will be exhausted by 2030 and 2050, respectively. These are references years that provide an order of magnitude of the time that is left to reverse the global warming trend. More realistic scenarios that consider a smooth transition toward a zero-emission world show that the global accumulated emissions compatible with the “well below 2°C” and 2°C targets will be exhausted by 2040 and 2080, respectively. Implications of this paper include a return to personal responsibility following equity principles among individuals, and a definition of boundaries to the personal emissions of CO2. [ABSTRACT FROM AUTHOR]

Climate warming and organic matter decomposition are connected in a recursive manner; this recursion can be described by temperature sensitivity. We conducted a multifactorial laboratory experiment to quantify the temperature sensitivity of organic carbon (C) and nitrogen (N) decomposition processes of common boreal organic soils. We incubated 36 mor and 36 slightly decomposed Carex-Sphagnum peat samples in a constant moisture and ambient temperature for 6 months. The experiment included three temperature and two moisture levels and two food web manipulations (samples with and without fungivore enchytraeid worms). We determined the release of carbon dioxide (CO2) and dissolved organic carbon (DOC) in seven molecular size classes together with ammonium N and dissolved organic N in low molecular weight and high molecular weight fractions. The temperature sensitivity function Q10 was fit to the data. The C and N release rate was almost an order of magnitude higher in mor than in peat. Soil fauna increased the temperature sensitivity of C release. Soil fauna played a key role in N release; when fauna was absent in peat, the N release was ceased. The wide range of the studied C and N compounds and treatments (68 Q10 datasets) allowed us to recognize five different temperature sensitivity patterns. The most common pattern (37 out of 68) was a positive upwards temperature response, which was observed for CO2 and DOC release. A negative downward pattern was observed for extractable organic nitrogen and microbial C. Sixteen temperature sensitivity patterns represented a mixed type, where the Q10function was not applicable, as this does not allow changing the sign storage change rate with increasing or decreasing temperature. The mixed pattern was typically connected to intermediate decomposition products, where input and output fluxes with different temperature sensitivities may simultaneously change the storage. Mixed type was typical for N processes. Our results provide useful parameterization for ecosystem models that describe the feedback loop between climate warming, organic matter decomposition, and productivity of N-limited vegetation. [ABSTRACT FROM AUTHOR]

We use agent-based computer simulation to test the effect of environmental conditions (available biomass/carrying capacity and environmental risk) on the development of wealth inequality and patron-client herding networks in nomadic pastoral economies. Our results show that 1) wealth inequality reaches very high levels when carrying capacity is high and risk is low, and 2) patron-client contract herding networks increase in size and duration when carrying capacity is high and risk is low. We compare empirical data from the Mongol (1206–1368 CE) and Xiongnu (209 BCE– 48 CE) empires with simulation results to develop an explanatory mechanism for the apparent correlation between nomadic empire creation and positive environmental conditions. We argue that the internal dynamics of nomadic pastoral societies are sufficient to produce high degrees of inequality and hierarchical herding networks. Nomadic empires are more likely to form during key periods of increased biomass and decreased environmental risk. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is an important component of the global carbon cycle due to the large permafrost carbon pool and its vulnerability to climate warming. The Tibetan Plateau has experienced a noticeable warming over the past few decades and is projected to continue warming in the future. However, the direction and magnitude of carbon fluxes responses to climate change and elevated CO2 concentration under Representative Concentration Pathways (RCP) scenarios in the Tibetan Plateau grassland are poorly known. Here, we used a calibrated and validated biogeochemistry model, CENTURY, to quantify the contributions of climate change and elevated CO2 on the future carbon budget in the alpine grassland under three RCP scenarios. Though the Tibetan Plateau grassland was projected a net carbon sink of 16 ~ 25 Tg C yr-1 in the 21st century, the capacity of carbon sequestration was predicted to decrease gradually because climate-driven increases in heterotrophic respiration (Rh) (with linear slopes 0.49 ~ 1.62 g C m-2 yr-1) was greater than the net primary production (NPP) (0.35 ~ 1.52 g C m-2 yr-1). However, the elevated CO2 contributed more to plant growth (1.9% ~ 7.3%) than decomposition (1.7% ~ 6.1%), which could offset the warming-induced carbon loss. The interannual and decadal-scale dynamics of the carbon fluxes in the alpine grassland were primarily controlled by temperature, while the role of precipitation became increasingly important in modulating carbon cycle. The strengthened correlation between precipitation and carbon budget suggested that further research should consider the performance of precipitation in evaluating carbon dynamics in a warmer climate scenario. [ABSTRACT FROM AUTHOR]

Climate-related studies have generally focussed upon physiologically well-defined ‘mechanistic’ traits rather than ‘functional’ ones relating indirectly to resource capture. Nevertheless, field responses to climate are likely to typically include both ‘mechanistic’ specialization to climatic extremes and ‘functional’ strategies that optimize resource acquisition during less climatically-severe periods. Here, this hypothesis was tested. Seventeen traits (six ‘functional’, six ‘mechanistic’ and five ‘intermediate’) were measured from 19 populations of oleaster (wild olive) along a climatic gradient in Morocco. Principal components analysis of the trait dataset identified size and the ‘worldwide leaf economics spectrum’ as PCA axes 1 and 2. However, contrary to our prediction, these axes, and commonly-measured ‘functional’ traits, were little correlated with climate. Instead, PCA 3, perhaps relating to water-use and succulence, together stomatal density, specific leaf water content and leaf shape, patterned with altitude, aridity, rainfall and temperature. We concluded that, at least for slow-growing species, such as oleaster, ‘mechanistic’ traits are key to identifying mechanisms of climatic restriction. Meaningful collaboration between ‘mechanistic’ and ‘functional’ disciplines provides the best way of improving our understanding of the global impacts of climate change on species distribution and performance. [ABSTRACT FROM AUTHOR]

Reliable population estimates are fundamental to the conservation of endangered species. We evaluate here the use of photo-identification (photo-ID) and mark-recapture techniques for estimating the population size of the endangered Saimaa ringed seal (Phoca hispida saimensis). Photo-ID data based on the unique pelage patterns of individuals were collected by means of camera traps and boat-based surveys during the molting season in two of the species' main breeding areas, over a period of five years in the Pihlajavesi basin and eight years in the Haukivesi basin. An open model approach provided minimum population estimates for these two basins. The results indicated high survival rates and site fidelity among the adult seals. More accurate estimates can be obtained in the future by increasing the surveying effort both spatially and temporally. The method presented here proved effective for evaluating population size objectively, whereas the results of the current snow lair censuses are dependent on varying winter conditions, for instance. We therefore suggest that a photo-ID-based non-invasive mark-recapture method should be used for estimating Saimaa ringed seal abundances in order to ensure reliable, transparent population monitoring under changing climatic conditions. [ABSTRACT FROM AUTHOR]

Many systems in various scientific fields like medicine, ecology, economics or climate science exhibit so-called critical transitions, through which a system abruptly changes from one state to a different state. Typical examples are epileptic seizures, changes in the climate system or catastrophic shifts in ecosystems. In order to predict imminent critical transitions, a mathematical apparatus called early warning signals has been developed and this method is used successfully in many scientific areas. However, not all critical transitions can be detected by this approach (false negative) and the appearance of early warning signals does not necessarily proof that a critical transition is imminent (false positive). Furthermore, there are whole classes of systems that always show early warning signals, even though they do not feature critical transitions. In this study we identify such classes in order to provide a safeguard against a misinterpretation of the results of an early warning signal analysis of such systems. Furthermore, we discuss strategies to avoid such systematic false positives and test our theoretical insights by applying them to real world data. [ABSTRACT FROM AUTHOR]

Climate change in recent decades has been identified as a significant threat to natural environments and human wellbeing. This is because some of the contemporary changes to climate are abrupt and result in persistent changes in the state of natural systems; so called regime shifts (RS). This study aimed to detect and analyse the timing and strength of RS in Estonian climate at the half-century scale (1966−2013). We demonstrate that the extensive winter warming of the Northern Hemisphere in the late 1980s was represented in atmospheric, terrestrial, freshwater and marine systems to an extent not observed before or after the event within the studied time series. In 1989, abiotic variables displayed statistically significant regime shifts in atmospheric, river and marine systems, but not in lake and bog systems. This was followed by regime shifts in the biotic time series of bogs and marine ecosystems in 1990. However, many biotic time series lacked regime shifts, or the shifts were uncoupled from large-scale atmospheric circulation. We suggest that the latter is possibly due to complex and temporally variable interactions between abiotic and biotic elements with ecosystem properties buffering biotic responses to climate change signals, as well as being affected by concurrent anthropogenic impacts on natural environments. [ABSTRACT FROM AUTHOR]

Analysing the effect water temperature has on Daphnia magna is essential in anticipating the impact climate change will have on this freshwater zooplanktonic keystone species. While many authors have followed this line of research, few have covered an extensive temperature range or complex temperature change scenarios. Global warming is mostly associated with increased extreme temperature events, such as heat waves, as well as earlier and more intense thermal stratification. Both of these events may directly influence D. magna fitness, especially in those populations performing diel vertical migration (DVM). We analysed the effect water temperatures, ranging from 11 to 29°C, have on the filtration capacity (FC) of D. magna, to anticipate the effects of acclimation, temperature change rate (TCR) and potential reversibility of responses to such conditions. Results show that sudden temperature changes have an immediate negative impact on the FC of D. magna and is more severe at higher temperatures and higher TCRs. However, D. magna individuals have shown themselves to be capable of quasi-acclimating to temperatures ranging from 11 to 25°C in around a week and achieving much higher FCs; albeit never reaching the optimal FC achieved at 20°C. That said, 29°C is lethal for D. magna individuals within approximately five days. Finally, non-optimal temperature acclimated individuals can recover maximal FC within 2–4 days of the optimal long-term acclimation temperature (20°C) being re-established, thus proving temperature responses to be reversible. [ABSTRACT FROM AUTHOR]

Intraspecific trait variation has been singled out as an important mechanism by which individuals can cope with environmental variations and avoid local extinctions. Here we evaluate variation in metamer traits (i.e., traits associated with internodes, petioles and their corresponding leaves) and parameters of chlorophyll fluorescence within and among populations of a neotropical tree, Copaifera langsdorffii. We also evaluated phenotypic plasticity in natural settings comparing traits between shade and sun-exposed metamers. We selected six populations along a climatic gradient ranging from semi-arid to humid and representing three different biomes (Caatinga, Cerrado, and Atlantic Forest). Local climatic conditions significantly affected the morphological and physiological traits of populations. Trait variation among populations was explained mainly by aridity index and evapotranspiration. Individuals from drier regions had lower specific leaf area (SLA), lower investment in leaf area per total dry mass of metamer (LARm), lower specific petiole length (SPL) and lower potential quantum yield (Fv/Fm, only for sun-exposed metamers). Populations from locations with greater environmental heterogeneity (interannual variation) had greater plasticity in response to light for Fv/Fm and electron transport rate (ETR) and morphological traits related to the hydraulic and biomechanical aspects of the leaves (petiole length, internode length and SPL). High intraspecific variation in metamer traits in C. langsdorffii coupled with its ability to modify these traits in response to different climate conditions can explain the success of the species over a range of different habitats and represent important factors for the persistence of this species in the face of climate change. [ABSTRACT FROM AUTHOR]

Riparian habitats have been frequently identified as priority areas for conservation under climate change because they span climatic gradients and have cool, moist microclimates relative to surrounding areas. They are therefore expected to act as dispersal corridors for climate-induced species range shifts and to provide microclimatic refugia from warming. Despite recognition of these values, rigorous methods to identify which riparian areas are most likely to facilitate range shifts and provide refugia are currently lacking. We completed a novel analysis across the Pacific Northwest, USA, that identifies potential riparian corridors featuring characteristics expected to enhance their ability to facilitate range shifts and provide refugia. These features include large temperature gradients, high canopy cover, large relative width, low exposure to solar radiation, and low levels of human modification. These variables were used to calculate a riparian climate-corridor index using a multi-scale approach that incorporates results ranging in scale from local watersheds to the entire Pacific Northwest. Resulting index values for potential riparian corridors in the Pacific Northwest were highest within mountainous areas and lowest within relatively flat, lowland regions. We also calculated index values within ecoregions, to better identify high-value riparian climate corridors within the relatively flat, degraded areas where they may most contribute to climate adaptation. We found that high-value riparian climate-corridors are least protected in flat, lowland areas, suggesting that such corridors should be high priorities for future conservation effort. Our analysis provides critical information on valuable riparian climate-corridors to guide climate adaptation efforts (and riparian management and restoration efforts) in the Pacific Northwest, while offering a novel approach that may be applied to similar efforts in other geographies. [ABSTRACT FROM AUTHOR]

Knowledge about the relative importance of influencing-factors on rice yield gap is crucial to rice production, especially in southwestern China where topography is extremely complicated. In the current study, the data of rice yield from a total of 76 experiments were collected in 2008 and 2009 in Chongqing, southwest China. For each location, two treatments with fertilizer and without fertilizer were carried out, each treatment was performed with three replications, and yield gap was calculated using fertilized yield minus unfertilized yield. Seventeen influencing-factors including variety, fertilization, climate, terrain, and soil properties were obtained at each location. Regression tree (RT) model were employed to investigate relative important of influencing-factors to rice yield gap variability. The result of Pearson correlation analysis suggested yield gap of rice was positively correlated with sunshine hours, phosphorous and potassium fertilizers, while negatively correlated with soil available nitrogen content. The results of RT showed that the selected influencing-factors explained about 74.1% of rice yield gap variation. Meanwhile, the result also indicated variety followed by others had more influence on rice yield gap variation. Our findings analyzed by regression model at a regional scale suggested that more precise fertilization recommendation should be formulated based on comprehensive factors (e.g., soil, climate, terrain, variety), which reasonably guided farmer and government for rice production. [ABSTRACT FROM AUTHOR]

Climate change is affecting the growth, phenology, and distribution of species across northeastern United States. In response to these changes, some species have been adversely impacted while others have benefited. One species that has benefited from climate change, historically and in response to experimental treatments, is common ragweed (Ambrosia artemisiifolia), a widely distributed annual weed and a leading cause of hay fever in North America. To better understand how climate change may affect the distribution of common ragweed, we built a maximum entropy (Maxent) predictive model using climate and bioclimatic data and over 700 observations across the eastern U.S. Our model performed well with an AUC score of 0.765 using four uncorrelated variables, including precipitation seasonality, mean diurnal temperature range, August precipitation, and January maximum temperature. After building and testing our model, we then projected potential future common ragweed distribution using a suite of 13 global climate models (GCMs) under two future greenhouse gas scenarios for mid and late-century. In addition to providing georeferenced hot spots of potential future expansion, we also provide a metric of confidence by evaluating the number of GCMs that agree. We show a substantial contraction of common ragweed in central Florida, southern Appalachian Mountains, and northeastern Virginia and areas of potential expansion at the northern margins of its current distribution, notably in northeastern U.S. However, the vast majority of this increase is projected to occur by mid-century and may be moderated somewhat by the 2070s, implying that common ragweed may be sensitive to climatic variability. Although other factors and modeling approaches should be explored, we offer preliminary insight into where common ragweed might be a new concern in the future. Due to the health impacts of ragweed, local weed control boards may be well advised to monitor areas of expansion and potentially increase eradication efforts. [ABSTRACT FROM AUTHOR]

Emerald Basin on the Scotian Shelf off Nova Scotia, Canada, is home to a globally unique aggregation of the glass sponge Vazella pourtalesi, first documented in the region in 1889. In 2009, Fisheries and Oceans Canada (DFO) implemented two Sponge Conservation Areas to protect these sponge grounds from bottom fishing activities. Together, the two conservation areas encompass 259 km2. In order to ascertain the degree to which the sponge grounds remain unprotected, we modelled the presence probability and predicted range distribution of V. pourtalesi on the Scotian Shelf using random forest modelling on presence-absence records. With a high degree of accuracy the random forest model predicted the highest probability of occurrence of V. pourtalesi in the inner basins on the central Scotian Shelf, with lower probabilities at the shelf break and in the Fundian and Northeast Channels. Bottom temperature was the most important determinant of its distribution in the model. Although the two DFO Sponge Conservation Areas protect some of the more significant concentrations of V. pourtalesi, much of its predicted distribution remains unprotected (over 99%). Examination of the hydrographic conditions in Emerald Basin revealed that the V. pourtalesi sponge grounds are associated with a warmer and more saline water mass compared to the surrounding shelf. Reconstruction of historical bottom temperature and salinity in Emerald Basin revealed strong multi-decadal variability, with average bottom temperatures varying by 8°C. We show that this species has persisted in the face of this climatic variability, possibly indicating how it will respond to future climate change. [ABSTRACT FROM AUTHOR]

Potato blackleg and soft rot caused by Pectobacterium and Dickeya species are among the most significant bacterial diseases affecting potato production globally. In this study we estimate the impact of future temperatures on establishment of non-indigenous but confirmed Pectobacterium and Dickeya species in Great Britain (GB). The calculations are based on probabilistic climate change data and a model fitted to disease severity data from a controlled environment tuber assay with the dominant potato blackleg and soft rot-causing species in GB (P. atrosepticum), and three of the main causative agents in Europe (P. carotovorum subsp. brasiliense, P. parmentieri, Dickeya solani). Our aim was to investigate if the European strains could become stronger competitors in the GB potato ecosystem as the climate warms, on the basis of their aggressiveness in tubers at different temperatures. Principally, we found that the tissue macerating capacity of all four pathogens will increase in GB under all emissions scenarios. The predominant Pectobacterium and Dickeya species in Europe are able to cause disease in tubers under field conditions currently seen in GB but are not expected to become widely established in the future, at least on the basis of their aggressiveness in tubers relative to P. atrosepticum under GB conditions. Our key take-home messages are that the GB potato industry is well positioned to continue to thrive via current best management practices and continued reinforcement of existing legislation. [ABSTRACT FROM AUTHOR]

Many studies have focused on the interactive effects of temperature increases due to global warming and nutrient enrichment on phytoplankton communities. Recently, non-temperature effects of climate change (e.g., decreases in wind speed and increases in solar radiation) on large lakes have received increasing attention. To evaluate the relative contributions of both temperature and non-temperature effects on phytoplankton communities in a large eutrophic subtropical shallow lake, we analyzed long-term monitoring data from Lake Taihu, China from 1997 to 2016. Results showed that Lake Taihu’s spring phytoplankton biovolume and composition changed dramatically over this time frame, with a change in dominant species. Stepwise multiple linear regression models indicated that spring phytoplankton biovolume was strongly influenced by total phosphorus (TP), light condition, wind speed and total nitrogen (TN) (radj2 = 0.8, p < 0.01). Partial redundancy analysis (pRDA) showed that light condition accounted for the greatest variation of phytoplankton community composition, followed by TP and wind speed, as well as the interactions between TP and wind speed. Our study points to the additional importance of non-temperature effects of climate change on phytoplankton community dynamics in Lake Taihu. [ABSTRACT FROM AUTHOR]

Climate change communication efforts grounded in the information deficit model have largely failed to close the gap between scientific and public understanding of the risks posed by climate change. In response, simulations have been proposed to enable people to learn for themselves about this complex and politically charged topic. Here we assess the impact of a widely-used simulation, World Climate, which combines a socially and emotionally engaging role-play with interactive exploration of climate change science through the C-ROADS climate simulation model. Participants take on the roles of delegates to the UN climate negotiations and are challenged to create an agreement that meets international climate goals. Their decisions are entered into C-ROADS, which provides immediate feedback about expected global climate impacts, enabling them to learn about climate change while experiencing the social dynamics of negotiations. We assess the impact of World Climate by analyzing pre- and post-survey results from >2,000 participants in 39 sessions in eight nations. We find statistically significant gains in three areas: (i) knowledge of climate change causes, dynamics and impacts; (ii) affective engagement including greater feelings of urgency and hope; and (iii) a desire to learn and do more about climate change. Contrary to the deficit model, gains in urgency were associated with gains in participants’ desire to learn more and intent to act, while gains in climate knowledge were not. Gains were just as strong among American participants who oppose government regulation of free markets–a political ideology that has been linked to climate change denial in the US–suggesting the simulation’s potential to reach across political divides. The results indicate that World Climate offers a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science. [ABSTRACT FROM AUTHOR]

Climate change projections show that temperature and precipitation increases can alter the exchange of greenhouse gases between the atmosphere and high latitude landscapes, including their freshwaters. Dissolved organic carbon (DOC) plays an important role in greenhouse gas emissions, but the impact of catchment productivity on DOC release to subarctic waters remains poorly known, especially at regional scales. We test the hypothesis that increased terrestrial productivity, as indicated by the normalized difference vegetation index (NDVI), generates higher stream DOC concentrations in the Stordalen catchment in subarctic Sweden. Furthermore, we aimed to determine the degree to which other generic catchment properties (elevation, slope) explain DOC concentration, and whether or not land cover variables representing the local vegetation type (e.g., mire, forest) need to be included to obtain adequate predictive models for DOC delivered into rivers. We show that the land cover type, especially the proportion of mire, played a dominant role in the catchment’s release of DOC, while NDVI, slope, and elevation were supporting predictor variables. The NDVI as a single predictor showed weak and inconsistent relationships to DOC concentrations in recipient waters, yet NDVI was a significant positive regulator of DOC in multiple regression models that included land cover variables. Our study illustrates that vegetation type exerts primary control in DOC regulation in Stordalen, while productivity (NDVI) is of secondary importance. Thus, predictive multiple linear regression models for DOC can be utilized combining these different types of explanatory variables. [ABSTRACT FROM AUTHOR]

Background: Climate change is likely to further worsen ozone pollution in already heavily polluted areas, leading to increased ozone-related health burdens. However, little evidence exists in China, the world's largest greenhouse gas emitter and most populated country. As China is embracing an aging population with changing population size and falling age-standardized mortality rates, the potential impact of population change on ozone-related health burdens is unclear. Moreover, little is known about the seasonal variation of ozone-related health burdens under climate change. We aimed to assess near-term (mid-21st century) future annual and seasonal excess mortality from short-term exposure to ambient ozone in 104 Chinese cities under 2 climate and emission change scenarios and 6 population change scenarios.Methods and Findings: We collected historical ambient ozone observations, population change projections, and baseline mortality rates in 104 cities across China during April 27, 2013, to October 31, 2015 (2013-2015), which included approximately 13% of the total population of mainland China. Using historical ozone monitoring data, we performed bias correction and spatially downscaled future ozone projections at a coarse spatial resolution (2.0° × 2.5°) for the period April 27, 2053, to October 31, 2055 (2053-2055), from a global chemistry-climate model to a fine spatial resolution (0.25° × 0.25°) under 2 Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs): RCP4.5, a moderate global warming and emission scenario where global warming is between 1.5°C and 2.0°C, and RCP8.5, a high global warming and emission scenario where global warming exceeds 2.0°C. We then estimated the future annual and seasonal ozone-related acute excess mortality attributable to both climate and population changes using cause-specific, age-group-specific, and season-specific concentration-response functions (CRFs). We used Monte Carlo simulations to obtain empirical confidence intervals (eCIs), quantifying the uncertainty in CRFs and the variability across ensemble members (i.e., 3 predictions of future climate and air quality from slightly different starting conditions) of the global model. Estimates of future changes in annual ozone-related mortality are sensitive to the choice of global warming and emission scenario, decreasing under RCP4.5 (-24.0%) due to declining ozone precursor emissions but increasing under RCP8.5 (10.7%) due to warming climate in 2053-2055 relative to 2013-2015. Higher ambient ozone occurs under the high global warming and emission scenario (RCP8.5), leading to an excess 1,476 (95% eCI: 898 to 2,977) non-accidental deaths per year in 2053-2055 relative to 2013-2015. Future ozone-related acute excess mortality from cardiovascular diseases was 5-8 times greater than that from respiratory diseases. Ozone concentrations increase by 15.1 parts per billion (10-9) in colder months (November to April), contributing to a net yearly increase of 22.3% (95% eCI: 7.7% to 35.4%) in ozone-related mortality under RCP8.5. An aging population, with the proportion of the population aged 65 years and above increased from 8% in 2010 to 24%-33% in 2050, will substantially amplify future ozone-related mortality, leading to a net increase of 23,838 to 78,560 deaths (110% to 363%). Our analysis was mainly limited by using a single global chemistry-climate model and the statistical downscaling approach to project ozone changes under climate change.Conclusions: Our analysis shows increased future ozone-related acute excess mortality under the high global warming and emission scenario RCP8.5 for an aging population in China. Comparison with the lower global warming and emission scenario RCP4.5 suggests that climate change mitigation measures are needed to prevent a rising health burden from exposure to ambient ozone pollution in China. [ABSTRACT FROM AUTHOR]

Background: Climate change negatively impacts human health through heat stress and exposure to worsened air pollution, amongst other pathways. Indoor use of air conditioning can be an effective strategy to reduce heat exposure. However, increased air conditioning use increases emissions of air pollutants from power plants, in turn worsening air quality and human health impacts. We used an interdisciplinary linked model system to quantify the impacts of heat-driven adaptation through building cooling demand on air-quality-related health outcomes in a representative mid-century climate scenario.Methods and Findings: We used a modeling system that included downscaling historical and future climate data with the Weather Research and Forecasting (WRF) model, simulating building electricity demand using the Regional Building Energy Simulation System (RBESS), simulating power sector production and emissions using MyPower, simulating ambient air quality using the Community Multiscale Air Quality (CMAQ) model, and calculating the incidence of adverse health outcomes using the Environmental Benefits Mapping and Analysis Program (BenMAP). We performed simulations for a representative present-day climate scenario and 2 representative mid-century climate scenarios, with and without exacerbated power sector emissions from adaptation in building energy use. We find that by mid-century, climate change alone can increase fine particulate matter (PM2.5) concentrations by 58.6% (2.50 μg/m3) and ozone (O3) by 14.9% (8.06 parts per billion by volume [ppbv]) for the month of July. A larger change is found when comparing the present day to the combined impact of climate change and increased building energy use, where PM2.5 increases 61.1% (2.60 μg/m3) and O3 increases 15.9% (8.64 ppbv). Therefore, 3.8% of the total increase in PM2.5 and 6.7% of the total increase in O3 is attributable to adaptive behavior (extra air conditioning use). Health impacts assessment finds that for a mid-century climate change scenario (with adaptation), annual PM2.5-related adult mortality increases by 13,547 deaths (14 concentration-response functions with mean incidence range of 1,320 to 26,481, approximately US$126 billion cost) and annual O3-related adult mortality increases by 3,514 deaths (3 functions with mean incidence range of 2,175 to 4,920, approximately US$32.5 billion cost), calculated as a 3-month summer estimate based on July modeling. Air conditioning adaptation accounts for 654 (range of 87 to 1,245) of the PM2.5-related deaths (approximately US$6 billion cost, a 4.8% increase above climate change impacts alone) and 315 (range of 198 to 438) of the O3-related deaths (approximately US$3 billion cost, an 8.7% increase above climate change impacts alone). Limitations of this study include modeling only a single month, based on 1 model-year of future climate simulations. As a result, we do not project the future, but rather describe the potential damages from interactions arising between climate, energy use, and air quality.Conclusions: This study examines the contribution of future air-pollution-related health damages that are caused by the power sector through heat-driven air conditioning adaptation in buildings. Results show that without intervention, approximately 5%-9% of exacerbated air-pollution-related mortality will be due to increases in power sector emissions from heat-driven building electricity demand. This analysis highlights the need for cleaner energy sources, energy efficiency, and energy conservation to meet our growing dependence on building cooling systems and simultaneously mitigate climate change. [ABSTRACT FROM AUTHOR]

Individuals must have a quantitative understanding of the carbon footprint tied to their everyday decisions to make efficient sustainable decisions. We report research of the innumeracy of individuals as it relates to their carbon footprint. In three studies that varied in terms of scale and sample, respondents estimate the quantity of CO2 released when combusting a gallon of gasoline in comparison to several well-known metrics including food calories and travel distance. Consistently, respondents estimated the quantity of CO2 from gasoline compared to other metrics with significantly less accuracy while exhibiting a tendency to underestimate CO2. Such relative absence of carbon numeracy of even a basic consumption habit may limit the effectiveness of environmental policies and campaigns aimed at changing individual behavior. We discuss several caveats as well as opportunities for policy design that could aid the improvement of people’s quantitative understanding of their carbon footprint. [ABSTRACT FROM AUTHOR]

Systematic conservation planning is a framework for optimally locating and prioritizing areas for conservation. An often-noted shortcoming of most conservation planning studies is that they do not address future uncertainty. The selection of protected areas that are intended to ensure the long-term persistence of biodiversity is often based on a snapshot of the current situation, ignoring processes such as climate change. Scenarios, in the sense of being accounts of plausible futures, can be utilized to identify conservation area portfolios that are robust to future uncertainty. We compared three approaches for utilizing scenarios in conservation area selection: considering a full set of scenarios (all-scenarios portfolio), assuming the realization of specific scenarios, and a reference strategy based on the current situation (current distributions portfolio). Our objective was to compare the robustness of these approaches in terms of their relative performance across future scenarios. We focused on breeding bird species in Israel’s Mediterranean region. We simulated urban development and vegetation dynamics scenarios 60 years into the future using DINAMICA-EGO, a cellular-automata simulation model. For each scenario, we mapped the target species’ available habitat distribution, identified conservation priority areas using the site-selection software MARXAN, and constructed conservation area portfolios using the three aforementioned strategies. We then assessed portfolio performance based on the number of species for which representation targets were met in each scenario. The all-scenarios portfolio consistently outperformed the other portfolios, and was more robust to ‘errors’ (e.g., when an assumed specific scenario did not occur). On average, the all-scenarios portfolio achieved representation targets for five additional species compared with the current distributions portfolio (approximately 33 versus 28 species). Our findings highlight the importance of considering a broad and meaningful set of scenarios, rather than relying on the current situation, the expected occurrence of specific scenarios, or the worst-case scenario. [ABSTRACT FROM AUTHOR]

The sinking properties of three strains of Emiliania huxleyi in response to temperature changes were examined. We used a recently proposed approach to calculate sinking velocities from coccosphere architecture, which has the advantage to be applicable not only to culture samples, but also to field samples including fossil material. Our data show that temperature in the sub-optimal range impacts sinking velocity of E. huxleyi. This response is widespread among strains isolated in different locations and moreover comparatively predictable, as indicated by the similar slopes of the linear regressions. Sinking velocity was positively correlated to temperature as well as individual cell PIC/POC over the sub-optimum to optimum temperature range in all strains. In the context of climate change our data point to an important influence of global warming on sinking velocities. It has recently been shown that seawater acidification has no effect on sinking velocity of a Mediterranean E. huxleyi strain, while nutrient limitation seems to have a small negative effect on sinking velocity. Given that warming, acidification, and lowered nutrient availability will occur simultaneously under climate change scenarios, the question is what the net effect of different influential factors will be. For example, will the effects of warming and nutrient limitation cancel? This question cannot be answered conclusively but analyses of field samples in addition to laboratory culture studies will improve predictions because in field samples multi-factor influences and even evolutionary changes are not excluded. As mentioned above, the approach of determining sinking rate followed here is applicable to field samples. Future studies could use it to analyse not only seasonal and geographic patterns but also changes in sinking velocity over geological time scales. [ABSTRACT FROM AUTHOR]

Objective: Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China. Method: Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation. Result: The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa. Conclusion: The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management. [ABSTRACT FROM AUTHOR]

Future hydrological extremes, such as floods and droughts, may pose serious threats for the livelihoods in the upstream domains of the Indus, Ganges, Brahmaputra. For this reason, the impacts of climate change on future hydrological extremes is investigated in these river basins. We use a fully-distributed cryospheric-hydrological model to simulate current and future hydrological fluxes and force the model with an ensemble of 8 downscaled General Circulation Models (GCMs) that are selected from the RCP4.5 and RCP8.5 scenarios. The model is calibrated on observed daily discharge and geodetic mass balances. The climate forcing and the outputs of the hydrological model are used to evaluate future changes in climatic extremes, and hydrological extremes by focusing on high and low flows. The outcomes show an increase in the magnitude of climatic means and extremes towards the end of the 21st century where climatic extremes tend to increase stronger than climatic means. Future mean discharge and high flow conditions will very likely increase. These increases might mainly be the result of increasing precipitation extremes. To some extent temperature extremes might also contribute to increasing discharge extremes, although this is highly dependent on magnitude of change in temperature extremes. Low flow conditions may occur less frequently, although the uncertainties in low flow projections can be high. The results of this study may contribute to improved understanding on the implications of climate change for the occurrence of future hydrological extremes in the Hindu Kush–Himalayan region. [ABSTRACT FROM AUTHOR]

Critical transitions of complex systems can often be predicted by so-called early-warning signals (EWS). In some cases, however, such signals cannot be detected although a critical transition is imminent. Observing a relation of EWS-detectability and the network topology in which the system is implemented, we simulate and investigate scale-free networks and identify which networks show, and which do not show EWS in the framework of a two state system that exhibits critical transitions. Additionally, we adapt our approach by examining the effective state of the system, rather than its natural state, and conclude that this transformation can reveal hidden EWS in networks where those signals are otherwise obscured by a complex topology. [ABSTRACT FROM AUTHOR]

Reduced seawater pH and changes in carbonate chemistry associated with ocean acidification (OA) decrease the recruitment of crustose coralline algae (CCAcf.), an important coral-reef builder. However, it is unclear whether the observed decline in recruitment is driven by impairment of spore germination, or post-settlement processes (e.g. space competition). To address this, we conducted an experiment using a dominant CCA, Porolithon cf. onkodes to test the independent and combined effects of OA, warming, and irradiance on its germination success and early development. Elevated CO2 negatively affected several processes of spore germination, including formation of the germination disc, initial growth, and germling survival. The magnitude of these effects varied depending on the levels of temperature and irradiance. For example, the combination of high CO2 and high temperature reduced formation of the germination disc, but this effect was independent of irradiance levels, while spore abnormalities increased under high CO2 and high temperature particularly in combination with low irradiance intensity. This study demonstrates that spore germination of CCA is impacted by the independent and interactive effects of OA, increasing seawater temperature and irradiance intensity. For the first time, this provides a mechanism for how the sensitivity of critical early life history processes to global change may drive declines of adult populations of key marine calcifiers. [ABSTRACT FROM AUTHOR]

A warming climate increases thermal inputs to lakes with potential implications for water quality and aquatic ecosystems. In a previous study, we used a dynamic water column temperature and mixing simulation model to simulate chronic (7-day average) maximum temperatures under a range of potential future climate projections at selected sites representative of different U.S. regions. Here, to extend results to lakes where dynamic models have not been developed, we apply a novel machine learning approach that uses Gaussian Process regression to describe the model response surface as a function of simplified lake characteristics (depth, surface area, water clarity) and climate forcing (winter and summer air temperatures and potential evapotranspiration). We use this approach to extrapolate predictions from the simulation model to the statistical sample of U.S. lakes in the National Lakes Assessment (NLA) database. Results provide a national-scale scoping assessment of the potential thermal risk to lake water quality and ecosystems across the U.S. We suggest a small fraction of lakes will experience less risk of summer thermal stress events due to changes in stratification and mixing dynamics, but most will experience increases. The percentage of lakes in the NLA with simulated 7-day average maximum water temperatures in excess of 30°C is projected to increase from less than 2% to approximately 22% by the end of the 21st century, which could significantly reduce the number of lakes that can support cold water fisheries. Site-specific analysis of the full range of factors that influence thermal profiles in individual lakes is needed to develop appropriate adaptation strategies. [ABSTRACT FROM AUTHOR]

Background: Increasing climate variability as a result of climate change will be one of the public health challenges to control infectious diseases in the future, particularly in sub-Saharan Africa including Ethiopia. Objective: To investigate the effect of climate variability on childhood diarrhea (CDD) and identify high risk periods of diarrheal diseases. Methods: The study was conducted in all districts located in three Zones (Awi, West and East Gojjam) of Amhara Region in northwestern parts of Ethiopia. Monthly CDD cases for 24 months (from July 2013 to June 2015) reported to each district health office from the routine surveillance system were used for the study. Temperature, rainfall and humidity data for each district were extracted from satellite precipitation estimates and global atmospheric reanalysis. The space-time permutation scan statistic was used to identify high risk periods of CDD. A negative binomial regression was used to investigate the relationship between cases of CDD and climate variables. Statistical analyses were conducted using SaTScan program and StataSE v. 12. Results: The monthly average incidence rate of CDD was 11.4 per 1000 (95%CI 10.8–12.0) with significant variation between males [12.5 per 1000 (95%CI 11.9 to 13.2)] and females [10.2 per 1000 (95%CI 9.6 to 10.8)]. The space-time permutation scan statistic identified the most likely high risk period of CDD between March and June 2014 located in Huletej Enese district of East Gojjam Zone. Monthly average temperature and monthly average rainfall were positively associated with the rate of CDD, whereas the relative humidity was negatively associated with the rate of CDD. Conclusions: This study found that the most likely high risk period is in the beginning of the dry season. Climatic factors have an association with the occurrence of CDD. Therefore, CDD prevention and control strategy should consider local weather variations to improve programs on CDD. [ABSTRACT FROM AUTHOR]

Ecological niche models (ENMs) have increasingly been used to estimate the potential effects of climate change on species’ distributions worldwide. Recently, predictions of species abundance have also been obtained with such models, though knowledge about the climatic variables affecting species abundance is often lacking. To address this, we used a well-studied guild (temperate North American quail) and the Maxent modeling algorithm to compare model performance of three variable selection approaches: correlation/variable contribution (CVC), biological (i.e., variables known to affect species abundance), and random. We then applied the best approach to forecast potential distributions, under future climatic conditions, and analyze future potential distributions in light of available abundance data and presence-only occurrence data. To estimate species’ distributional shifts we generated ensemble forecasts using four global circulation models, four representative concentration pathways, and two time periods (2050 and 2070). Furthermore, we present distributional shifts where 75%, 90%, and 100% of our ensemble models agreed. The CVC variable selection approach outperformed our biological approach for four of the six species. Model projections indicated species-specific effects of climate change on future distributions of temperate North American quail. The Gambel’s quail (Callipepla gambelii) was the only species predicted to gain area in climatic suitability across all three scenarios of ensemble model agreement. Conversely, the scaled quail (Callipepla squamata) was the only species predicted to lose area in climatic suitability across all three scenarios of ensemble model agreement. Our models projected future loss of areas for the northern bobwhite (Colinus virginianus) and scaled quail in portions of their distributions which are currently areas of high abundance. Climatic variables that influence local abundance may not always scale up to influence species’ distributions. Special attention should be given to selecting variables for ENMs, and tests of model performance should be used to validate the choice of variables. [ABSTRACT FROM AUTHOR]

The ability of species to track their climate niche is dependent on their dispersal potential and the connectivity of the landscape matrix linking current and future suitable habitat. However, studies modeling climate-driven range shifts rarely address the movement of species across landscapes realistically, often assuming “unlimited” or “no” dispersal. Here, we incorporate dispersal rate and landscape connectivity with a species distribution model (Maxent) to assess the extent to which the Cunningham’s skink (Egernia cunninghami) may be capable of tracking spatial shifts in suitable habitat as climate changes. Our model was projected onto four contrasting, but equally plausible, scenarios describing futures that are (relative to now) hot/wet, warm/dry, hot/with similar precipitation and warm/wet, at six time horizons with decadal intervals (2020–2070) and at two spatial resolutions: 1 km and 250 m. The size of suitable habitat was projected to decline 23–63% at 1 km and 26–64% at 250 m, by 2070. Combining Maxent output with the dispersal rate of the species and connectivity of the intervening landscape matrix showed that most current populations in regions projected to become unsuitable in the medium to long term, will be unable to shift the distance necessary to reach suitable habitat. In particular, numerous populations currently inhabiting the trailing edge of the species’ range are highly unlikely to be able to disperse fast enough to track climate change. Unless these populations are capable of adaptation they are likely to be extirpated. We note, however, that the core of the species distribution remains suitable across the broad spectrum of climate scenarios considered. Our findings highlight challenges faced by philopatric species and the importance of adaptation for the persistence of peripheral populations under climate change. [ABSTRACT FROM AUTHOR]

Extreme heat events will become more frequent under anthropogenic climate change, especially in Mediterranean ecosystems. Microhabitats can considerably moderate (buffer) the effects of extreme weather events and hence facilitate the persistence of some components of the biodiversity. We investigate the microclimatic moderation provided by two important microhabitats (cavities formed by the leaves of the grass-tree Xanthorrhoea semiplana F.Muell., Xanthorrhoeaceae; and inside the leaf-litter) during the summer of 2015/16 on the Fleurieu Peninsula of South Australia. We placed microsensors inside and outside these microhabitats, as well as above the ground below the forest canopy. Grass-tree and leaf-litter microhabitats significantly buffered against high temperatures and low relative humidity, compared to ground-below-canopy sensors. There was no significant difference between grass-tree and leaf-litter temperatures: in both microhabitats, daily temperature variation was reduced, day temperatures were 1–5°C cooler, night temperatures were 0.5–3°C warmer, and maximum temperatures were up to 14.4°C lower, compared to ground-below-canopy sensors. Grass-tree and leaf-litter microhabitats moderated heat increase at an average rate of 0.24°C temperature per 1°C increase of ambient temperature in the ground-below-canopy microhabitat. The average daily variation in temperature was determined by the type (grass-tree and leaf-litter versus ground-below-canopy) of microhabitat (explaining 67%), the amount of canopy cover and the area of the vegetation fragment (together explaining almost 10% of the variation). Greater canopy cover increased the amount of microclimatic moderation provided, especially in the leaf-litter. Our study highlights the importance of microhabitats in moderating macroclimatic conditions. However, this moderating effect is currently not considered in species distribution modelling under anthropogenic climate change nor in the management of vegetation. This shortcoming will have to be addressed to obtain realistic forecasts of future species distributions and to achieve effective management of biodiversity. [ABSTRACT FROM AUTHOR]

Water-use efficiency (WUE), defined as the ratio of net primary productivity (NPP) to evapotranspiration (ET), is an important indicator to represent the trade-off pattern between vegetation productivity and water consumption. Its dynamics under climate change are important to ecohydrology and ecosystem management, especially in the drylands. In this study, we modified and used a late version of Boreal Ecosystem Productivity Simulator (BEPS), to quantify the WUE in the typical dryland ecosystems, Temperate Eurasian Steppe (TES). The Aridity Index (AI) was used to specify the terrestrial water availability condition. The regional results showed that during the period of 1999–2008, the WUE has a clear decreasing trend in the spatial distribution from arid to humid areas. The highest annual average WUE was in dry and semi-humid sub-region (DSH) with 0.88 gC mm-1 and the lowest was in arid sub-region (AR) with 0.22 gC mm-1. A two-stage pattern of WUE was found in TES. That is, WUE would enhance with lower aridity stress, but decline under the humid environment. Over 65% of the region exhibited increasing WUE. This enhancement, however, could not indicate that the grasslands were getting better because the NPP even slightly decreased. It was mainly attributed to the reduction of ET over 70% of the region, which is closely related to the rainfall decrease. The results also suggested a similar negative spatial correlation between the WUE and the mean annual precipitation (MAP) at the driest and the most humid ends. This regional pattern reflected the different roles of water in regulating the terrestrial ecosystems under different aridity levels. This study could facilitate the understanding of the interactions between terrestrial carbon and water cycles, and thus contribute to a sustainable management of nature resources in the dryland ecosystems. [ABSTRACT FROM AUTHOR]

Several studies have projected increases in drought severity, extent and duration in many parts of the world under climate change. We examine sources of uncertainty arising from the methodological choices for the assessment of future drought risk in the continental US (CONUS). One such uncertainty is in the climate models’ expression of evaporative demand (E0), which is not a direct climate model output but has been traditionally estimated using several different formulations. Here we analyze daily output from two CMIP5 GCMs to evaluate how differences in E0 formulation, treatment of meteorological driving data, choice of GCM, and standardization of time series influence the estimation of E0. These methodological choices yield different assessments of spatio-temporal variability in E0 and different trends in 21st century drought risk. First, we estimate E0 using three widely used E0 formulations: Penman-Monteith; Hargreaves-Samani; and Priestley-Taylor. Our analysis, which primarily focuses on the May-September warm-season period, shows that E0 climatology and its spatial pattern differ substantially between these three formulations. Overall, we find higher magnitudes of E0 and its interannual variability using Penman-Monteith, in particular for regions like the Great Plains and southwestern US where E0 is strongly influenced by variations in wind and relative humidity. When examining projected changes in E0 during the 21st century, there are also large differences among the three formulations, particularly the Penman-Monteith relative to the other two formulations. The 21st century E0 trends, particularly in percent change and standardized anomalies of E0, are found to be sensitive to the long-term mean value and the amplitude of interannual variability, i.e. if the magnitude of E0 and its interannual variability are relatively low for a particular E0 formulation, then the normalized or standardized 21st century trend based on that formulation is amplified relative to other formulations. This is the case for the use of Hargreaves-Samani and Priestley-Taylor, where future E0 trends are comparatively much larger than for Penman-Monteith. When comparing Penman-Monteith E0 responses between different choices of input variables related to wind speed, surface roughness, and net radiation, we found differences in E0 trends, although these choices had a much smaller influence on E0 trends than did the E0 formulation choices. These methodological choices and specific climate model selection, also have a large influence on the estimation of trends in standardized drought indices used for drought assessment operationally. We find that standardization tends to amplify divergences between the E0 trends calculated using different E0 formulations, because standardization is sensitive to both the climatology and amplitude of interannual variability of E0. For different methodological choices and GCM output considered in estimating E0, we examine potential sources of uncertainty in 21st century trends in the Standardized Precipitation Evapotranspiration Index (SPEI) and Evaporative Demand Drought Index (EDDI) over selected regions of the CONUS to demonstrate the practical implications of these methodological choices for the quantification of drought risk under climate change. [ABSTRACT FROM AUTHOR]

The interspecific abundance-occupancy relationship (AOR) is a widely used tool that describes patterns of habitat utilization and, when evaluated over time, may be used to identify large-scale changes in community structure. Our primary goal for this research was to validate the utility of AORs as temporal indicators of community state. We used long-term survey data in four regions of the northwest Atlantic coastal shelf (NWACS) to estimate the diversity of spatial behaviors in each community, which we modeled with negative binomial (NB) distributions. NB parameters were used to generate time series data for simulated communities, from which AORs were then estimated and evaluated for temporal trends. We found that AORs from simulated communities were similar in year-to-year variation to empirical relationships. In order to further understand the role of spatial diversity in the generation of AOR trends, we did additional simulations where NB parameters were manually manipulated. In one instance, we ran simulations while holding species’ parameters constant over time. This treatment effectively removed trends, suggesting that temporal change in community relationships was the result of genuine variation in intraspecific spatial use. In another set of simulations, we conducted a case study to evaluate the impact of a select group of schooling and spatially aggregating species on an especially rapid shift in AORs in the Gulf of Maine from 1973 to 1983. Removals of these species reduced the magnitudes of most trends, demonstrating their importance to observed community changes. This research directly links variation in AORs to distribution and density-related processes and provides a potentially powerful framework to identify community-level change and to test ecological and mechanistic hypotheses. [ABSTRACT FROM AUTHOR]

Global warming accelerates water cycle with features of regional difference. However, little is known about the physical mechanism behind the phenomenon. To reveal the links between water cycle and climatic environment, we analyzed the changes of water cycle elements and their relationships with climatic and environmental factors. We found that when global warming was significant during the period of 1986-2003, the precipitation in Tarim mountains as well as Xinjiang increased rapidly except for Tarim plains, which indicated that there existed a signal of acceleration for water cycle in Xinjiang. The speed of water cycle is mainly affected by altitude, latitude, longitude, slope direction, and the most fundamental element is temperature. Moreover, according to Clausius-Kela Bai Lung relation, we found that the climate change induced the increase of temperature and accelerated the local water cycle only for the wet places. Our results provide a possible physical mechanisms of water cycle and thus well link the climate change to water circulation. [ABSTRACT FROM AUTHOR]

Human-induced climate change is considered a conspicuous threat to biodiversity in the 21st century. Species’ response to climate change depends on their exposition, sensitivity and ability to adapt to novel climates. Exposure to climate change is however uneven within species’ range, so that some populations may be more at risk than others. Identifying the regions most exposed to climate change is therefore a first and pivotal step on determining species’ vulnerability across their geographic ranges. Here, we aimed at quantifying mammal local exposure to climate change across species’ ranges. We identified areas in the Brazilian Amazon where mammals will be critically exposed to non-analogue climates in the future with different variables predicted by 15 global circulation climate forecasts. We also built a null model to assess the effectiveness of the Amazon protected areas in buffering the effects of climate change on mammals, using an innovative and more realistic approach. We found that 85% of species are likely to be exposed to non-analogue climatic conditions in more than 80% of their ranges by 2070. That percentage is even higher for endemic mammals; almost all endemic species are predicted to be exposed in more than 80% of their range. Exposure patterns also varied with different climatic variables and seem to be geographically structured. Western and northern Amazon species are more likely to experience temperature anomalies while northeastern species will be more affected by rainfall abnormality. We also observed an increase in the number of critically-exposed species from 2050 to 2070. Overall, our results indicate that mammals might face high exposure to climate change and that protected areas will probably not be efficient enough to avert those impacts. [ABSTRACT FROM AUTHOR]

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. [ABSTRACT FROM AUTHOR]

Studying the influence of climatic and/or site-specific factors on soil organic matter (SOM) along an elevation gradient is important for understanding the response of SOM to global warming. We evaluated the composition of SOM and structure of humic acids along an altitudinal gradient from 600 to 1400 m in moso bamboo (Phyllostachys edulis) plantations in central Taiwan using NMR spectroscopy and photometric analysis. Total organic C and total nitrogen (N) content increased with increasing elevation. Aromaticity decreased and ΔlogK (the logarithm of the absorbance ratio of humic acids at 400 and 600 nm) increased with increasing elevation, which suggests that SOM humification decreased with increasing elevation. High temperature at low elevations seemed to enhance the decomposition (less accumulation of total organic C and N) and humification (high aromaticity and low ΔlogK). The alkyl-C/O-alkyl-C (A/O-A) ratio of humic acids increased with increasing elevation, which suggests that SOM humification increased with increasing elevation; this finding was contrary to the trend observed for ΔlogK and aromaticity. Such a discrepancy might be due to the relatively greater remaining of SOM derived from high alkyl-C broadleaf litter of previous forest at high elevations. The ratio of recalcitrant C to total organic C was low at low elevations, possibly because of enhanced decomposition of recalcitrant SOM from the previous broadleaf forest during long-term intensive cultivation and high temperature. Overall, the change in SOM pools and in the rate of humification with elevation was primarily affected by changes in climatic conditions along the elevation gradient in these bamboo plantations. However, when the composition of SOM, as assessed by NMR spectroscopy and photometric analysis was considered, site-specific factors such as residual SOM from previous forest and intensive cultivation history could also have an important effect on the humic acid composition and humification of SOM. [ABSTRACT FROM AUTHOR]

Climate change may affect the ability of soil-based onsite wastewater treatment systems (OWTS) to treat wastewater in coastal regions of the Northeastern United States. Higher temperatures and water tables can affect treatment by reducing the volume of unsaturated soil and oxygen available for treatment, which may result in greater transport of pathogens, nutrients, and biochemical oxygen demand (BOD5) to groundwater, jeopardizing public and aquatic ecosystem health. The soil treatment area (STA) of an OWTS removes contaminants as wastewater percolates through the soil. Conventional STAs receive wastewater from the septic tank, with infiltration occurring deeper in the soil profile. In contrast, shallow narrow STAs receive pre-treated wastewater that infiltrates higher in the soil profile, which may make them more resilient to climate change. We used intact soil mesocosms to quantify the water quality functions of a conventional and two types of shallow narrow STAs under present climate (PC; 20°C) and climate change (CC; 25°C, 30 cm elevation in water table). Significantly greater removal of BOD5 was observed under CC for all STA types. Phosphorus removal decreased significantly from 75% (PC) to 66% (CC) in the conventional STA, and from 100% to 71–72% in shallow narrow STAs. No fecal coliform bacteria (FCB) were released under PC, whereas up to 17 and 20 CFU 100 mL-1 were released in conventional and shallow narrow STAs, respectively, under CC. Total N removal increased from 14% (PC) to 19% (CC) in the conventional STA, but decreased in shallow narrow STAs, from 6–7% to less than 3.0%. Differences in removal of FCB and total N were not significant. Leaching of N in excess of inputs was also observed in shallow narrow STAs under CC. Our results indicate that climate change can affect contaminant removal from wastewater, with effects dependent on the contaminant and STA type. [ABSTRACT FROM AUTHOR]

Tropical cyclones are extreme random meteorological events that can have profound implications to coastal biodiversities. Given that the frequency, intensity and duration of these events are poised to increase due to the global climate change, understanding the ecological impacts of such erratic occurrences becomes imperative to devise better management strategies. The eventful passage of the tropical cyclone, Phyan, along the northwestern coast of India in November 2009, coupled with the availability of historical data presented a rare opportunity to elucidate the consequences on the polychaete assemblages of the Malvan Marine Sanctuary and their subsequent recovery. This was achieved by comparison of the pre- and post-Phyan seasonal data from four different sites in and around the Sanctuary. MDS analyses and polychaete community parameters suggested conspicuous cyclone related effects on the polychaete community characteristics in the three outer stations off Malvan, whereas the relatively protected bay station remained more or less unscathed. Impacts, attributable to the cyclone apart from seasonal variations, included changes in polychaete composition, reductions in total polychaete density, species diversity, evenness and functional groups. Dominance of the opportunistic polychaete, Paraprionospiopatiens was all pervasive just after Phyan, resulting in poor diversity and evenness values. In the outer stations, diverse feeding modes present prior to the cyclone were replaced by microphagous feeders post the disturbance. However, the study also observed complete recovery as substantiated by the improvement inpolychaete density, diversity indices and re-instatement of multiple feeding guilds in affected areas. This resilience of the coastal waters off Malvan is attributed to its marine protected status, implying that reduced human interference aided rapid revival of damaged ecosystems. [ABSTRACT FROM AUTHOR]