Rapid assessment of rivers using macroinvertebrates: A procedure based on habitat-specific sampling,family level identification and a biotic index

Abstract This paper describes a simple and inexpensive procedure for the rapid biological assessment of water quality in rivers and streams in eastern Australia. The procedure involves the standardized collection of samples of 100 macroinvertebrates from defined habitat types within a water body. Specimens are identified to family level only and a biotic index is calculated. Proposed future testing and evaluation are described, and the limitations of the rapid approach are discussed.     

A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

Food security and water scarcity have become two major concerns for future human''s sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security.     

水文情势与盐分变化对湿地植被的影响研究综述

湿地植被是湿地生态系统的重要组成部分。水文情势与盐分变化直接影响到湿地植被的分布与演替。目前,全球气候变化和人类活动导致的水文情势改变与盐分聚集已造成大面积的湿地退化和盐渍化,已严重威胁全球淡水湿地生态系统的稳定和健康。系统总结了水文情势与盐分变化单一环境变量及其交互作用对湿地植物生理生态、物种多样性、群落结构与演替和植被动态等诸多方面的影响研究进展,并探讨了湿地水文动态-盐分变化-植被响应的综合模型研究现状,认为发展湿地综合模型预测未来水文情势与盐分变化情景下湿地演变,是应对气候变化湿地水盐管理和生态保护的重要工具,最后指出今后亟需加强的研究方向。     

Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross‐validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland‐dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross‐validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross‐validation results were correlated with extrapolation results, the use of cross‐validation performance metrics to guide modeling choices where knowledge is limited was supported.     

Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.     

Progress and opportunities in advancing near-term forecasting of freshwater quality

Near-term freshwater forecasts, defined as sub-daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near-term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms) and ecosystem services (e.g., water-related recreation and tourism). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past 5 years. We found that freshwater forecasting is currently dominated by near-term forecasts of water quantity and that near-term water quality forecasts are fewer in number and in the early stages of development (i.e., non-operational) despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed and that near-term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end-user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events 5 days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts will require substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.     

New method and criteria for national assessments of threatened habitat types

Consistent information on threatened habitat types is needed for land use planning and for prioritizing conservation, management, and restoration actions. However, detailed background data for assessing extinction risks of habitat types exists only in few countries. We present a new, flexible procedure for assigning habitat types into Red List Categories similar to those used for species by the World Conservation Union (IUCN). The procedure allows variation in the character or scale of assessment units and it is applicable even with incomplete data. The assessment protocol consists of two primary criteria: the change in the quantity and the change in the quality of the habitat type. The criteria are analyzed by expert groups with a transparent and repeatable stepwise procedure. The quantitative and qualitative changes in habitat types over the last 50 years serve as a starting point for the assessment, and the status is adjusted by assessing sub-criteria that address earlier changes, predicted future change, and the overall commonness or rarity of the habitat type. We also report the main results of the first assessment of threatened habitat types in Finland, and illustrate the application of the criteria by two case studies.     

Impact of climatic change on bog ecosystems,with special reference to sub-oceanic raised bogs

The relation between climatic conditions and type of peatland ecosystem in the different climate zones in Europe is discussed. Special attention is given to the hydrology of raised bogs in the sub-oceanic region. Possible effects of climatic change on such raised bog systems are discussed in terms of changes in water discharge, ground-water table, rate of peat accumulation, and flora and vegetation. It is concluded that future changes, as suggested by the more widely accepted scenarios for climatic change, will seriously disrupt the ecological functioning of these peatland ecosystems, and it is doubtful whether at least the most southerly examples of sub-oceanic raised bogs will at all survive. Finally, suggestions are given for future research on the impact of climatic change on peatland ecosystems.     

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long‐term (20–56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40–60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C₃ than C₄ grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.     

Climate change‐induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands

Drylands occur worldwide and are particularly vulnerable to climate change because dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability and change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding. We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change‐induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation. Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change‐induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, that is, leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water‐limited ecosystems.     

Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one‐third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population‐level plant‐plant, plant‐herbivore, and predator‐prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant‐plant), (2) herbivory, neutralism, or mutualism (plant‐herbivore), or (3) neutralism and predation (predator‐prey), as water availability crosses physiological, behavioural, or population‐density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top‐down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems.     

气候变化对大豆影响的研究进展

工业革命以来,全球大气中CO₂等温室气体浓度急剧升高,导致全球气温升高和降水格局发生变化.大气CO₂ 浓度升高、全球变暖、水分状况的变化将对大豆的生长发育、产量、品质等产生影响,未来气候变化下大豆生产将发生很大变化.大豆是世界及我国重要的粮食和油料作物之一,未来气候变化下大豆生产的变化将会影响全球粮油安全.本文从大气CO₂浓度升高、温度升高、水分胁迫三方面综述了气候变化对大豆影响的研究,并对未来的相关研究做了展望,为了解未来大豆的生产情况以及制定应对气候变化对大豆生产影响的相关政策提供依据.     

Simulation of watershed hydrology and stream water quality under land use and climate change scenarios in Teshio River watershed,northern Japan

Quantitative prediction of environmental impacts of land-use and climate change scenarios in a watershed can serve as a basis for developing sound watershed management schemes. Water quantity and quality are key environmental indicators which are sensitive to various external perturbations. The aim of this study is to evaluate the impacts of land-use and climate changes on water quantity and quality at watershed scale and to understand relationships between hydrologic components and water quality at that scale under different climate and land-use scenarios. We developed an approach for modeling and examining impacts of land-use and climate change scenarios on the water and nutrient cycles. We used an empirical land-use change model (Conversion of Land Use and its Effects, CLUE) and a watershed hydrology and nutrient model (Soil and Water Assessment Tool, SWAT) for the Teshio River watershed in northern Hokkaido, Japan. Predicted future land-use change (from paddy field to farmland) under baseline climate conditions reduced loads of sediment, total nitrogen (N) and total phosphorous (P) from the watershed to the river. This was attributable to higher nutrient uptake by crops and less nutrient mineralization by microbes, reduced nutrient leaching from soil, and lower water yields on farmland. The climate changes (precipitation and temperature) were projected to have greater impact in increasing surface runoff, lateral flow, groundwater discharge and water yield than would land-use change. Surface runoff especially decreased in April and May and increased in March and September with rising temperature. Under the climate change scenarios, the sediment and nutrient loads increased during the snowmelt and rainy seasons, while N and P uptakes by crops increased during the period when fertilizer is normally applied (May through August). The sediment and nutrient loads also increased with increasing winter rainfall because of warming in that season. Organic nutrient mineralization and nutrient leaching increased as well under climate change scenarios. Therefore, we predicted annual water yield, sediment and nutrient loads to increase under climate change scenarios. The sediment and nutrient loads were mainly supplied from agricultural land under land use in each climate change scenario, suggesting that riparian zones and adequate fertilizer management would be a potential mitigation strategy for reducing these negative impacts of land-use and climate changes on water quality. The proposed approach provides a useful source of information for assessing the consequences of hydrology processes and water quality in future land-use and climate change scenarios.     

Impacts of climate change on virtual water content of crops in China

Looming water scarcity and climate change pose big challenges for China's food security. Previous studies have focus on the impacts of climate change either on agriculture or on water resources. Few studies have linked water and agriculture together in the context of climate change, and demonstrated how climate change will affect the amount of water used to produce per unit of crop, or virtual water content (VWC). We used a GIS-based Environmental Policy Integrated Climate (GEPIC) model to analyze the current spatial distribution of VWC of various crops in China and the impacts of climate change on VWC in different future scenarios. The results show that C4 crops (e.g. irrigated maize with a VWC of 0.73 m³ kg^− 1 in baseline) generally have a lower VWC than C3 crops (e.g. irrigated wheat with a VWC of 1.1 m³ kg^− 1 in baseline), and the VWC of C4 crops responds less sensitively to the CO₂ concentration change in future climate scenarios. Three general change trends exist for future VWC of crops: continuous decline (for soybean and rice without considering CO₂ concentration changes) and continuous increase (for rice with considering CO₂ concentration changes) and first-decline-then-increase (other crop-scenario combinations). The trends reflect the responses of different crops to changes in precipitation, temperature as well as CO₂ concentration. From south to north along the latitude, there is a high-low-high distribution trend of the aggregated VWC of the crops. Precipitation and temperature changes combined can lead to negative effects on crop yield and higher VWC particularly in the far future e.g. the 2090s, but when CO₂ concentration change is taken into consideration, it is likely that crop yield will increase and crop VWC will decrease for the whole China. Integrated effects of precipitation, temperature and CO₂ concentration changes will benefit agricultural productivity and crop water productivity through all the future periods till the end of the century. Hence, climate change is likely to benefit food security and help alleviate water scarcity in China.     

Incorporating the effects of changes in vegetation functioning and CO2 on water availability in plant habitat models

The direct effects of CO2 level changes on plant water availability are usually ignored in plant habitat models. We compare traditional proxies for water availability with changes in soil water (fAWC) predicted by a process-based ecosystem model, which simulates changes in vegetation structure and functioning, including CO2 physiological effects. We modelled current and future habitats of 108 European tree species using ensemble forecasting, comprising six habitat models, two model evaluation methods and two climate change scenarios. The fAWC models' projections are generally more conservative. Potential habitats shrink significantly less for boreo-alpine and alpine species. Changes in vegetation functioning and CO2 on plant water availability should therefore be taken into account in plant habitat change projections.     

The hydroclimatic and ecophysiological basis of cloud forest distributions under current and projected climates

Background

Tropical montane cloud forests (TMCFs) are characterized by a unique set of biological and hydroclimatic features, including frequent and/or persistent fog, cool temperatures, and high biodiversity and endemism. These forests are one of the most vulnerable ecosystems to climate change given their small geographic range, high endemism and dependence on a rare microclimatic envelope. The frequency of atmospheric water deficits for some TMCFs is likely to increase in the future, but the consequences for the integrity and distribution of these ecosystems are uncertain. In order to investigate plant and ecosystem responses to climate change, we need to know how TMCF species function in response to current climate, which factors shape function and ecology most and how these will change into the future.

Scope

This review focuses on recent advances in ecophysiological research of TMCF plants to establish a link between TMCF hydrometeorological conditions and vegetation distribution, functioning and survival. The hydraulic characteristics of TMCF trees are discussed, together with the prevalence and ecological consequences of foliar uptake of fog water (FWU) in TMCFs, a key process that allows efficient acquisition of water during cloud immersion periods, minimizing water deficits and favouring survival of species prone to drought-induced hydraulic failure.

Conclusions

Fog occurrence is the single most important microclimatic feature affecting the distribution and function of TMCF plants. Plants in TMCFs are very vulnerable to drought (possessing a small hydraulic safety margin), and the presence of fog and FWU minimizes the occurrence of tree water deficits and thus favours the survival of TMCF trees where such deficits may occur. Characterizing the interplay between microclimatic dynamics and plant water relations is key to foster more realistic projections about climate change effects on TMCF functioning and distribution.     

Temperature-dependent growth rates of larval midges (Diptera: Chironomidae) from a southeastern U.S. stream

Inland aquatic ecosystems and their biodiversity in Asia represent a wide spectrum along a complex continuum of interacting ecological, economic, socio-cultural and political gradients all of which determine their present and future. Whereas the diversity of biophysical environments ensures a rich inland aquatic biodiversity, their present status has been greatly influenced by human societies that have depended on them for millennia. Besides high population densities and developmental pressures, socio-cultural factors, economic considerations and various policies concerning land and water resources are major factors responsible for the degradation of habitats and loss of biodiversity. The looming global climate change may only worsen the situation unless remedial measures are taken on a large scale and urgently. The future of aquatic biodiversity in Asian countries will depend upon a radical change in national policies on water, and upon research that can support the development of appropriate policies.     

Climate Change Impacts on the Upper Indus Hydrology: Sources,Shifts and Extremes

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21^st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin’s water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members.     

Student's tutorial on bloom hypotheses in the context of phytoplankton annual cycles

Phytoplankton blooms are elements in repeating annual cycles of phytoplankton biomass and they have significant ecological and biogeochemical consequences. Temporal changes in phytoplankton biomass are governed by complex predator–prey interactions and physically driven variations in upper water column growth conditions (light, nutrient, and temperature). Understanding these dependencies is fundamental to assess future change in bloom frequency, duration, and magnitude and thus represents a quintessential challenge in global change biology. A variety of contrasting hypotheses have emerged in the literature to explain phytoplankton blooms, but over time the basic tenets of these hypotheses have become unclear. Here, we provide a “tutorial” on the development of these concepts and the fundamental elements distinguishing each hypothesis. The intent of this tutorial is to provide a useful background and set of tools for reading the bloom literature and to give some suggestions for future studies. Our tutorial is written for “students” at all stages of their career. We hope it is equally useful and interesting to those with only a cursory interest in blooms as those deeply immersed in the challenge of understanding the temporal dynamics of phytoplankton biomass and predicting its future change.     

Dynamic logistic regression and dynamic model averaging for binary classification

We propose an online binary classification procedure for cases when there is uncertainty about the model to use and parameters within a model change over time. We account for model uncertainty through dynamic model averaging, a dynamic extension of Bayesian model averaging in which posterior model probabilities may also change with time. We apply a state-space model to the parameters of each model and we allow the data-generating model to change over time according to a Markov chain. Calibrating a "forgetting" factor accommodates different levels of change in the data-generating mechanism. We propose an algorithm that adjusts the level of forgetting in an online fashion using the posterior predictive distribution, and so accommodates various levels of change at different times. We apply our method to data from children with appendicitis who receive either a traditional (open) appendectomy or a laparoscopic procedure. Factors associated with which children receive a particular type of procedure changed substantially over the 7 years of data collection, a feature that is not captured using standard regression modeling. Because our procedure can be implemented completely online, future data collection for similar studies would require storing sensitive patient information only temporarily, reducing the risk of a breach of confidentiality.