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Prioritising local action for water quality improvement using citizen science; a study across three major metropolitan areas of China
Abstract
Streams in urban areas are prone to degradation. While urbanization-induced poor water quality is a widely observed and well documented phenomenon, the mechanism to pinpoint local drivers of urban stream degradation, and their relative influence on water quality, is still lacking. Utilizing data from the citizen science project FreshWater Watch, we use a machine learning approach to identify key indicators, potential drivers, and potential controls to water quality across the metropolitan areas of Shanghai, Guangzhou and Hong Kong. Partial dependencies were examined to establish the direction of relationships between predictors and water quality. A random forest classification model indicated that predictors of stream water colour (drivers related to artificial land coverage and agricultural land use coverage) and potential controls related to the presence of bankside vegetation were found to be important in identifying basins with degraded water quality conditions, based on individual measurements of turbidity and nutrient (N-NO3 and P-PO4) concentrations.
... In particular, Shupe [122] analysed data collected by citizens along with auxiliary data related to land cover patterns (i.e., urban, agricultural, and forestry areas) in order to estimate seasonal variations in water quality and their relation to certain activities, e.g., intense agricultural activities, fertilization, urban expansion, etc. Under the same concept, Thornhill et al. [123] utilised the CS water quality measurements (e.g., N-NO3, P-PO4 and turbidity) of the FreshWater Watch (FWW) project, and established a scalable approach that could facilitate the identification of regional or local key drivers that contribute to the degradation of freshwater quality. Last, the Citclops CS project was introduced by Garaba et al. [124], in which the low-cost and easy to use Forel-Ule colour index (FUI) method was explored along with RS observations of the MERIS multispectral instrument, to collect watercolour measurements, related to pollutant concentrations (e.g., algal density, etc.) [28]. ...
... The CTI, also known as Topographic Wetness Index (TWI), is a product of upslope areas, flow slope, and geometry functions [129], and therefore a good indicator for runoff risk assessment [130]. Additional environmental studies related to freshwater degradation (n = 1| [123]), road trace identification (n = 1| [116]), urban LC (n = 1| [90]) and forest plantations mapping (n = 1| [81]) were chosen to exploit the above topographic indicators. A noteworthy case was found in Venter et al. [120], in which both DTM and the Digital Surface Model (DSM) were produced from LiDAR airborne laser scanning (ALS) mission, in order to extract the vegetation canopy height model (CHM), and additional variables corresponding to terrain's ruggedness. ...
... More information on the LCZ classification schema are available in Steward and Oke [137]. Finally, LULC was used to reveal information regarding the land cover/urban objects (e.g., [95,96,112]), and specifically considering the effect of the agriculture activities on water quality [122,123], or the signal loss due to dense vegetation presence [116]. ...
Recent advances in Earth Observation (EO) placed Citizen Science (CS) in the highest
position, declaring their essential provision of information in every discipline that serves the SDGs, and the 2050 climate neutrality targets. However, so far, none of the published literature reviews has investigated the models and tools that assimilate these data sources. Following this gap of knowledge, we synthesised this scoping systematic literature review (SSLR) with a will to cover this limitation and highlight the benefits and the future directions that remain uncovered. Adopting the SSLR guidelines, a double and two-level screening hybrid process found 66 articles to meet the eligibility criteria, presenting methods, where data were fused and evaluated regarding their performance, scalability level and computational efficiency. Subsequent reference is given on EO-data,
their corresponding conversions, the citizens’ participation digital tools, and Data Fusion (DF) models that are predominately exploited. Preliminary results showcased a reference in the multispectral satellite sensors, with the microwave sensors to be used as a supplementary data source. Approaches such as the “brute-force approach” and the super-resolution models indicate an effective way to overcome the spatio-temporal gaps and the so far reliance on commercial satellite sensors. Passive crowdsensing observations are foreseen to gain a greater audience as, described in, most cases as a
low-cost and easily applicable solution even in the unprecedented COVID-19 pandemic. Immersive platforms and decentralised systems should have a vital role in citizens’ engagement and training process. Reviewing the DF models, the majority of the selected articles followed a data-driven method with the traditional algorithms to still hold significant attention. An exception is revealed in the smaller-scale studies, which showed a preference for deep learning models. Several studies enhanced their methods with the active-, and transfer-learning approaches, constructing a scalable model. In the end, we strongly support that the interaction with citizens is of paramount importance to achieve
a climate-neutral Earth.
... However, the perception that volunteer-generated data would not be well received by the scientific community contributes to a prejudice against its use (Crall et al, 2011;Dickinson et al., 2010;Foster-Smith & Evans, 2003;Riesch & Potter, 2013). In contrast, numerous studies have shown that volunteers are capable of collecting data of equal quality to that of professional scientists, provided they are given the proper training and resources, and provided the study design matches the collectors' abilities, and many validation studies to date have reported the high standard of water quality data collected by citizen scientists (Dyer et al. 2014;Herman-Mercer et al., 2018;Levesque et al., 2017;Loiselle et al., 2016;Loperfido et al., 2010;McGoff et al., 2017;Muenich et al., 2016;Safford & Peters, 2017;Scott & Frost, 2017;Shelton, 2013;Thornhill et al., 2017;Thornhill et al., 2018;Wilderman & Monismith, 2016). Water quality and water resource management within EU Member States is governed by the Water Framework Directive (WFD), a piece of European Commission legislation, that requires the incorporation of public participation in its implementation, mainly through public consultation and information supply (Hadj-Hammou et al., 2017;Van der Heijden & Ten Heuvelhof, 2013). ...
... Results of citizen testing of Orthophosphate, Nitrate and Electrical Conductivity proved reasonably accurate based on the percentages of results in agreement with laboratory analyses for these parameters (Table 5a-b & 5e). This was partly expected for both nutrient tests given the positive conclusions drawn by other researchers who have used the Kyoritsu PackTest water chemistry kits provided through FreshWater Watch to allow citizen scientists to measure Orthophosphate and Nitrate (Levesque et al., 2017;Loiselle et al., 2016;McGoff et al., 2017;Scott & Frost, 2017;Shupe, 2017;Thornhill et al., 2017;Thornhill et al., 2018;Xu et al., 2017). Two of these studies (Levesque et al., 2017;Thornhill et al., 2017) noted that between 65.8% and 81% of results obtained by citizen scientists for both parameters were in agreement with laboratory results, a J o u r n a l P r e -p r o o f 15 slightly higher level of agreement than was noted in this investigation. ...
... This was partly expected for both nutrient tests given the positive conclusions drawn by other researchers who have used the Kyoritsu PackTest water chemistry kits provided through FreshWater Watch to allow citizen scientists to measure Orthophosphate and Nitrate (Levesque et al., 2017;Loiselle et al., 2016;McGoff et al., 2017;Scott & Frost, 2017;Shupe, 2017;Thornhill et al., 2017;Thornhill et al., 2018;Xu et al., 2017). Two of these studies (Levesque et al., 2017;Thornhill et al., 2017) noted that between 65.8% and 81% of results obtained by citizen scientists for both parameters were in agreement with laboratory results, a J o u r n a l P r e -p r o o f 15 slightly higher level of agreement than was noted in this investigation. Interest level has been identified as an important motivational variable in a student's academic performance and an influencing factor in how much attention is paid to a particular activity (Hidi & Harackiewicz, 2000;Schiefele, 1991Schiefele, , 1996. ...
Citizen science (CS) may be described as research carried out by members of the public with the aim of gathering scientific information for the purpose of aiding in scientific projects. It has many potential advantages, including data collection at a scale not possible by professional scientists alone. The United Nations (UN) has recently recognized citizen science as a potential source of data that may contribute to the UN Sustainable Development Goals (SDGs). The availability of relatively inexpensive water quality monitoring field equipment suitable for CS suggests great potential for increased spatial coverage far beyond that of traditional, laboratory-based monitoring networks for water quality. In support of work towards the achievement of Sustainable Development Goal 6: “Clean Water and Sanitation”, this study tested the use of such field equipment by citizen scientists for SDG Indicator 6.3.2: “Proportion of bodies of water with good ambient water quality”. Data generated by 26 citizen scientists were compared with the results produced by an accredited laboratory. The results compared well for most parameters, suggesting that citizen science may be able to contribute towards monitoring ambient water quality for the Sustainable Development Goals.
... This comparison included simultaneous measurements at the same sites by scientists or monitoring agencies (e.g. environmental protection agencies) (Fore et al., 2001;Thornhill et al., 2017;Valois et al., 2019), comparison of the measurements from the kits with laboratory analyses of samples (Lévesque et al., 2017;Quinlivan et al., 2020a;Xu et al., 2017), or comparison with gauge data or remote sensing measurements (Au et al., 2000;Bos et al., 2019;Canfield et al., 2002;Flores Rojas and Huamantinco Araujo, 2017;Fore et al., 2001;Herman-Mercer et al., 2018;Mitroi et al., 2020;Nicholson et al., 2002;Wilson et al., 2018). ...
... Typical ranges for nitrate test strips are, for example, five classes between 0.05 and 0.8 mg/L nitrate-nitrogen (SHMAK kit) or six classes between 0.2 to >10 mg/L (Kyoritsu Pack Test kit). Thus, although the colorimetric method is lowcost and easy use for almost anyone, the method is mainly useful to provide a baseline of water quality conditions (Ali et al., 2019;Quinlivan et al., 2020b,a;Win et al., 2019) or to find pollution hotspots (e.g., Thornhill et al., 2017;Ulloa et al., 2020;Zhang et al., 2017). Other factors that affect the reliability of these data include the subjectivity in interpreting and choosing the concentration range by the participants (Quinlivan et al., 2020a). ...
Citizen science has become a widely used approach in water quality studies. Although there are literature reviews about citizen science and water quality assessments, an overview of the most commonly used methods and their strengths and weaknesses is still lacking. Therefore, we reviewed the scientific literature on citizen science for surface water quality assessments and examined the methods and strategies used by the 72 studies that fulfilled our search criteria. Special attention was given to the parameters monitored, the monitoring tools, and the spatial and temporal resolution of the data collected in these studies. In addition, we discuss the advantages and disadvantages of the different approaches used in water quality assessments and their potential to complement traditional hydrological monitoring and research.
... Lambers et al. (2019) also reported on using contributions from citizen scientists to improve the results of a multi-class archeological object detection based on CNN. In their project, FreshWater Watch Predict water quality using a regression model (Thornhill et al., 2017) High-level Well-structured Prediction ...
... volunteers participated in field expeditions to validate archeological objects detected by the algorithm, and the results were used to tune the algorithm object detection results. In other fields, computational technologies such as random forest classification (Thornhill et al., 2017), stacked ensemble model (Lim et al., 2019), and generalized linear model (Kumagai et al., 2018) have been used on data collected by citizen scientists and environmental or urban data collected by scientists, to predict water quality, air quality, and coral bleaching respectively. A CNN has been used to model the distribution of species in biodiversity research, such as the White-tailed Ptarmigan distribution over Vancouver Island (Jackson et al., 2015) or the Asian bush mosquito distribution area (Kerkow et al., 2020). ...
The field of citizen science involves the participation of citizens across different stages of a scientific project; within this field there is currently a rapid expansion of the integration of humans and AI computational technologies based on machine learning and/or neural networking-based paradigms. The distribution of tasks between citizens (“the crowd”), experts, and this type of technologies has received relatively little attention. To illustrate the current state of task allocation in citizen science projects that integrate humans and computational technologies, an integrative literature review of 50 peer-reviewed papers was conducted. A framework was used for characterizing citizen science projects based on two main dimensions: (a) the nature of the task outsourced to the crowd, and (b) the skills required by the crowd to perform a task. The framework was extended to include tasks performed by experts and AI computational technologies as well. Most of the tasks citizens do in the reported projects are well-structured, involve little interdependence, and require skills prevalent among the general population. The work of experts is typically structured and at a higher-level of interdependence than that of citizens, requiring expertize in specific fields. Unsurprisingly, AI computational technologies are capable of performing mostly well-structured tasks at a high-level of interdependence. It is argued that the distribution of tasks that results from the combination of computation and citizen science may disincentivize certain volunteer groups. Assigning tasks in a meaningful way to citizen scientists alongside experts and AI computational technologies is an unavoidable design challenge.
... Table 4 synthesizes the information from citizen science studies applied to agriculture and its relation to the application of ICTs, citizen participation techniques and benefits generated. It can also be observed that the same article can make use of more than three ICT applications [6], [7], [8], [9], [17], participation techniques [7], [9], [10], [11], [14], [15], [20] and more than three benefits [12], [13], [18]. From this it follows that the study conducted by Rahman et al. [7] and Romani et al. [9], have a greater number of ICT application criteria as well as citizen participation techniques, while the article by Thornhill et al [18] presents a greater number of benefits, such as environmental and meteorological monitoring, flood control and learning systems. ...
... It can also be observed that the same article can make use of more than three ICT applications [6], [7], [8], [9], [17], participation techniques [7], [9], [10], [11], [14], [15], [20] and more than three benefits [12], [13], [18]. From this it follows that the study conducted by Rahman et al. [7] and Romani et al. [9], have a greater number of ICT application criteria as well as citizen participation techniques, while the article by Thornhill et al [18] presents a greater number of benefits, such as environmental and meteorological monitoring, flood control and learning systems. ...
The constant evolution of citizen science in recent years- where the participation of citizens in scientific projects is applied with the use of information technologies- has been able to solve different problems in different areas of knowledge. In the same way, when we deal with the issue of agriculture, together with the support of information technologies, these are applied to increase productivity, automate processes and train farmers to make decisions. There are different processes in agriculture that can be implemented with ICT solutions. This work is focused on carrying out a process of systematic mapping of research which will include a search, study selection, analysis and identification of potential relationships on citizen science in agriculture through ICTs. With the application of systematic mapping, the frequency of indexed publications that has existed on this topic will be evaluated, since no statistical studies on citizen science have been found that account for the number of existing projects on agriculture and technology.
... Data were collected by 120 trained citizen scientists (from >8000 total trained) using standardized methods. Quality control against standard methods was conducted with approximately 10% of the samples [27,28]. Measurements and observations of algal blooms were also checked automatically and by local partner scientists. ...
... General ecosystem conditions included Data were collected by 120 trained citizen scientists (from >8000 total trained) using standardized methods. Quality control against standard methods was conducted with approximately 10% of the samples [27,28]. Measurements and observations of algal blooms were also checked automatically and by local partner scientists. ...
The involvement of volunteers in the monitoring of the environment holds great potential to gather information on a wider temporal and spatial scale than is currently possible. However, the mass involvement of citizens in monitoring freshwater health is a relatively new field and subject to uncertainty. Here, we examine 1192 samples collected across 46 temperate ponds (< 2 ha) and 29 temperate lakes (> 2 ha) by 120 volunteers trained through the FreshWater Watch citizen science programme to consider if the approach is able to (a) identify well established patterns in water quality and biological indicators (i.e., fish), and (b) provide a potentially useful basis for the identification of pollution sources in urban or peri-urban landscapes. Seasonal patterns observed agreed well with established principles of nutrient dynamics, algal bloom seasonality, and broad biological trends between ponds and lakes. Further, observational data collected by the volunteers suggested plausible links between the presence of residential discharge and water level fluctuation and significant increases in algal bloom observations between peri-urban and urban sites. We suggest that citizen science can have a role to play in complementing regulatory monitoring efforts and that local citizens should be empowered to become stewards of their local freshwater resources.
... A recent study by Ballard, Dixon and Harris (2017) demonstrated that involving local people in information gathering for the purpose of conservation initiatives capacitates them for future conservation efforts. The tools developed can enable communities to act; hence people must be able to understand them with minimal input from the specialists, and must be able to produce reliable data (Thornhill, Ho, Zhang, Li, Ho, Miguel-Chinchilla & Loiselle, 2017). Citizen science is an approach to environmental education that allows the public to be on par with the specialists with regard to the data collected (Ghilardi-Lopes, 2015). ...
... Wetland management plays a crucial role in conservation and the wise use of wetlands (Farrier & Tucker, 2000). One of the major challenges for wetland management is that a vast amount of data over a large spatial area is required to clearly understand the state of wetlands (Bonney, Cooper, Dickinson, Kelling, Phillips, Rosenberg & Shirk, 2009;Thornhill et al., 2017). ...
More than half of the wetlands in South Africa have been degraded or lost due to economic activities, urban developments and poor wetland management. Reversing the trend would require the participation of a wide range of actors in addition to scientists. A case has been made for a citizen science approach in order to empower the public with
skills and knowledge that would enable them to understand environmental issues without depending on specialists. However, the wetland health assessment tools used in South Africa are highly technical, rendering them largely inaccessible to non-specialists. Recently, Kotze (2015) developed a tool which seeks to address this gap by involving the wider community in monitoring the health of wetlands in South Africa. The aim of the present study was to test the extent to which the new wetland health tool can be used by local people to better understand their surrounding wetlands. The study’s findings indicated that the tool enabled non-specialists to generate information about wetlands that was not significantly different from that produced by specialists.
... Supervised learning algorithms, such as RF, are increasingly being used in SW pollution modelling (e.g., Thornhill et al 2017, Jamei et al 2022. RF is an assemblage of a large number of classification or regression trees, which uses a sample of the data to build a model. ...
Aquifer-stream interactions affect the water quality in Mediterranean areas; therefore, the coupling of surface water and groundwater models is generally used to solve water-planning and pollution problems in river basins. However, their use is limited because model inputs and outputs are not spatially and temporally linked, and the data update and fitting are laborious tasks. Machine learning models have shown great potential in water quality simulation, as they can identify the statistical relationship between input and output data without the explicit requirement of knowing the physical processes. This allows the ecological, hydrological, and environmental variables that influence water quality to be analyzed with a holistic approach. In this research, feature selection (FS) methods and algorithms of artificial intelligence— random forest (RF) and eXtreme Gradient Boosting (XGBoost) trees—are used to simulate nitrate concentration and determine the main drivers related to nitrate pollution in Mediterranean streams. The developed models included 19 inputs and sampling of nitrate concentration in 159 surface water quality-gauging stations as explanatory variables. The models were trained on 70 percent data, with 30 percent used to validate the predictions. Results showed that the combination of FS method with local knowledge about the dataset is the best option to improve the model’s performance, while RF and XGBoost simulate the nitrate concentration with high performance (r=0.93 and r=0.92, respectively). The final ranking, based on the relative importance of the variables in the RF and XGBoost models, showed that, regarding nitrogen and phosphorus concentration, the location explained 87 percent of the nitrate variability. RF and XGBoost predicted nitrate concentration in surface water with high accuracy without using conditions or parameters of entry, and enabled the observation of different relationships between drivers. Thus, it is possible to identify and delimit zones with a spatial risk of pollution and approaches to implementing solutions.
... In urban areas, freshwater bodies are exposed to several risks such as impermeability, population density, habitat fragmentation and degradation (such as rectification and channeling of water bodies) in addition to low water quality. Due to this gradual loss of quality and the scarcity of resources, the concept of sustainability has been strengthened and several development models have been proposed in order to guarantee environmental quality, highlighting the use of future generations (Lacerda & Cândido, 2013;Thornhil et al., 2017). ...
The risks of scarcity have forced several countries to change their water resources management. In Brazil, the Paraíba do Sul River has a great importance as it supplies water for many cities of the Southeast region. Thus, the management of water and wastewater systems demands a more sustainable and efficient scenario. The study's objective was to evaluate, through sustainability indicators, the urban water management system in Volta Redonda (Rio de Janeiro state, Brazil). The selection of sustainability indicators was done through Delphi technique: a group of eight specialists selected the indicators used to evaluate sustainability, its dimension and level of importance. The six criteria for the classification of indicators according to the dimensions of sustainability were: (1) Environmental / Ecological, (2) Economic, (3) Social / Cultural, (4) Technological (5) Ethical and (6) Political / Institutional. Most of the indicators were considered "very important" or just "important". Regarding the dimension of sustainability, 93% of indicators contemplated more than three dimensions. However, 13 indicators contemplated all the six dimensions as they were multidimensional indicators, analyzed according to the municipal data. The chosen method for the indicator's selection was considered quite satisfactory, since they were able to generate a set of key indicators to show the current municipal water and wastewater scenario. The city has shown satisfactory conditions regarding fresh water supply index. However, some indicators pointed a not sustainable system due to the low wastewater treatment index, precarious state of the river's life and divergences between the basin plan and the municipal director plan.
... Citizen science has been widely used to monitor aquatic environments throughout the world (Hughes et al., 2014;Hyder et al., 2017;Loiselle et al., 2016;Thornhill et al., 2019). Studies in the northern hemisphere have reported the high standard of data acquired (Lévesque et al., 2017;Loperfido et al., 2010;McGoff et al., 2017;Muenich et al., 2016;Thornhill et al., 2017), but few validation studies have been performed in Africa. Spatial and temporal changes in turbidity, nitrate and water level in rivers and groundwater were successfully determined using citizen science Wand a et al., 2017;Weeser et al., 2018), but the feasibility of using this approach in African Great lakes has yet to be clearly demonstrated (Bishop et al., 2020). ...
Several studies in Lake Tanganyika have effectively employed traditional methods to explore changes in water quality in open waters; however, coastal monitoring has been restricted and sporadic, relying on costly sample and analytical methods that require skilled technical staff. This study aims in validating citizen science water quality collected data (nitrate, phosphate and turbidity) with those collected and measured by professional scientists in the laboratory. A second objective of the study is to use citizen scientist data to identify the patterns of seasonal and spatial variations in nutrient conditions and forecast potential changes based on expected changes in population and climate (to 2050). The results showed that the concentrations of nitrate and phosphate measured by citizen scientists nearly matched those established by professional scientists, with overall accuracy of 91% and 74%, respectively. For total suspended solids measured by professional and turbidity measured by citizen scientists, results show that, using 14 NTU as a cut-off, citizen scientist measurements of Secchi tube depth to identify lake TSS below 7.0 mg/L showed an accuracy of 88%. In both laboratory and citizen scientist-based studies, all measured water quality variables were significantly higher during the wet season compared to the dry season. Climate factors were discovered to have a major impact on the likelihood of exceeding water quality restrictions in the next decades (2050), which could deteriorate lake conditions. Upscaling citizen science to more communities on the lake and other African Great Lakes would raise environmental awareness, inform management and mitigation activities, and aid long-term decision-making.
... The most common parameters measured by citizen scientists are nitrate, phosphate, water clarity and turbidity [36,41,[55][56][57]. Also, citizens can be trained to make observations on shore vegetation and litter [55,58]. In addition, citizens can survey river geomorphic features and dynamics (for ex. ...
Human changes on the Danube River have transformed it into a heavily engineered river, severely threatening its ecological status. The status and management strategies vary significantly between regions of the Danube River Basin. Citizen science approach can be the bridge in harmonizing water management practices across the Danube Basin and in recording large water quality datasets. This chapter reviews citizen science actions in the Lower Danube Basin and the available tools for citizens in this region. The study has shown that the activities with public involvement in this region have been supported by non-governmental organizations (NGOs) or independent citizen science platforms. Citizen science activities in this region are scarce and infrequent, and most of them without supervision from professional researchers or involvement from local authorities. Limited access to funds, lack of trust between participating groups and the restricted power of communities to voice concerns have been found as factors influencing citizen science activities. The scientists may be the missing link between policy makers, water managers and citizens, while providing the optimal tools and knowledge to all sectors. Professional scientists can collaborate with NGOs and build upon their extensive expertise and success in engaging with citizens and authorities.
... Three nearby measurements in each site (within 10 m from each other) were made to compare spatial heterogeneity; An estimate of dissolved nutrients (nitrate and phosphate) from the filtrate of the samples taken above using standard colorimetric methods [11]. Nitrate and phosphates were tested in enclosed reagent tubes and compared with corresponding colors [12]. ...
The largest blue-green infrastructures in industrialized, urbanized and developed regions in China are often multiuse wetlands, located just outside growing urban centers. These areas have multiple development pressures while providing environmental, economic, and social benefits to the local and regional populations. Given the limited information available about the tradeoffs in ecosystem services with respect to competing wetland uses, wetland managers and provincial decision makers face challenges in regulating the use of these important landscapes. In the present study, measurements made by citizen scientists were used to support a comparative study of water quality and wetland functions in two large multiuse wetlands, comparing areas of natural wetland vegetation, tourism-based wetland management and wetland agriculture. The study sites, the Nansha and Tianfu wetlands, are located in two of the most urbanized areas of China: the lower Yangtze River and Pearl River catchments, respectively. Our results indicated that the capacity of wetlands to mitigate water quality is closely related to the quality of the surrounding waters and hydrological conditions. Agricultural areas in both wetlands provided the lowest sediment and nutrient retention. The results show that the delivery of supporting ecosystem services is strongly influenced by the location and use of the wetland. Furthermore, we show that citizen scientist-acquired data can provide fundamental information on quantifying these ecosystem services, providing needed information to wetland park managers and provincial wetland administrators.
... However, these two parameters are highly correlated with each other (Table S2). Regional population and residential land together have a significant influence on water quality (Thornhill et al., 2017). Fig. 6 shows that the population density is positively correlated with the water quality parameters in the first phase where the population density is less than 3000 people per km 2 , above which, however, the SHAP values only marginally increase. ...
A systematic understanding of spatial distribution of water quality is critical for successful watershed management; however, the limited number of physical monitoring stations has restricted the evaluation of spatial water quality distribution and the identification of features impacting the water quality. To fill this gap, we developed a modeling process that employed the random forest regression (RFR) to model the water quality distribution for the Taihu Lake basin in Zhejiang Province, China, and adopted the Shapley Additive exPlanations (SHAP) method to interpret the underlying driving forces. We first used RFR to model three water quality parameters: permanganate index (CODMn), total phosphorus (TP), and total nitrogen (TN) based on 16 watershed features. We then applied the built models to generate water quality distribution maps for the basin, with CODMn ranging from 1.39 to 6.40 mg/L, TP from 0.02 to 0.23 mg/L, and TN from 1.43 to 4.27 mg/L. These maps showed generally consistent patterns among CODMn, TN, and TP with minor differences in the spatial distribution. The SHAP analysis showed that TN was mainly affected by agricultural non-point sources, while CODMn and TP were affected by agricultural and domestic sources. Due to differences in sewage collection and treatment between urban and rural areas, the water quality in highly populated urban areas was better than that in rural areas, which led to an unexpected positive relationship between water quality and population density. Overall, with the RFR models and SHAP interpretation, we obtained a continuous distribution pattern of the water quality and identified its driving forces in the basin. These findings provided important information to assist water quality restoration projects.
... Photographs showed cloudy, frothy discharge from pipes into the river, while citizen scientists noted evidence of eutrophication and floating mats of algal growth in these locations, some of which correlated with high nitrate and phosphate results during periods without rainfall. Many studies have cited the presence of algal blooms as an indicator of the degradation of water quality based on measurements of nutrient (nitrate and/or phosphate) concentrations (Cunha et al., 2017;Thornhill et al., 2017). Frothy discharge from pipes, meanwhile, is indicative of drainage system misconnections; indeed, as noted above, some participants recorded witnessing a smell of detergent at some locations. ...
This study investigates water quality along the river Liffey in Dublin city with the help of citizen scientists, including the community of river users such as paddle boarders and those accessing the river from the bank. The primary objective was to evaluate water quality near sources of pollution observed by citizens, while filling data gaps for the United Nations (UN) Sustainable Development Goal (SDG) 6, Indicator 6.3.2. The participants used field chemistry kits to measure nitrate (NO₃-N) and phosphate (PO₄-P) at 19 locations on a monthly basis over the course of nine months, recording the results on a smartphone app. 10% of nitrate samples were indicative of low quality water values while 35.6% of phosphate samples were indicative of low quality water. Rainfall over the study period was analysed to investigate the impact of run-off from rainwater on the river. Results indicated that excessive rainfall was not a factor in lower water quality in this area. Citizen scientists’ observational notes and photographs entered onto the database, with accompanying test results were key to highlighting pollution sources at specific locations which correlated with high levels of nitrate and phosphate resulting in low quality water. Land use was a factor in these areas of recent housing development indicating possible domestic misconnections. Citizen scientist data has the potential to fulfil UN SDG 6, in contributing to Indicator 6.3.2 while detecting contamination.
... Finally, the overall water clarity was classified as clear, cloudy, or turbid. These categorical variables were added in consideration of citizen scientist studies where these and similar variables were found to be significant predictors of water quality (65)(66)(67). ...
The presence of human enteric pathogens, stemming from fecal pollution, is a serious environmental and public health concern in recreational waters. Accurate assessments of fecal pollution are therefore needed to properly assess exposure risks and guide water quality policies and practices. In this study, the absence of a direct correlation between enterococci and source-specific human and animal markers disputes the utility of enterococci as an indicator of fecal pollution in urbanized subtropical bays. Moreover, the inverse correlation between enterococci and the human-specific marker HF183 indicates that recreational beach advisories, triggered by elevated enterococcus concentrations, are a misleading practice. This study clearly demonstrates that a multiparameter approach that includes the quantitation of host-specific markers, as well as analyses of microbial diversity, is a more effective means of assessing water quality in urbanized subtropical bays.
... Although most citizen-science water quality programs collect data in the form of water samples (Breuer et al., 2015;Good et al., 2014), others involve in situ monitoring of parameters like turbidity and nutrient concentrations or ecosystem health indicators such as macroinvertebrates or Escherichia coli (Latimore and Steen, 2014;Scott and Frost, 2017;Thornhill et al., 2017). Various methods and techniques have been reported for different programs. ...
Hydrological monitoring is essential to guide evidence-based decision making necessary for sustainable water resource management and governance. Limited hydrometric datasets and the pressure on long-term hydrological monitoring networks make it paramount to explore alternative methods for data collection. This is particularly the case for low-income countries, where data scarcity is more pronounced, and where conventional monitoring methods are expensive and logistically challenging. Citizen science in hydrological research has recently gained popularity and crowdsourced monitoring is a promising cost-effective approach for data collection. Citizen science also has the potential to enhance knowledge co-creation and science-based evidence that underpins the governance and management of water resources. This paper provides a comprehensive review on citizen science and crowdsourced data collection within the context of hydrology, based on a synthesis of 71 articles from 2001 to 2018. Application of citizen science in hydrology is increasing in number and breadth, generating a plethora of scientific data. Citizen science approaches differ in scale, scope and degree of citizen involvement. Most of the programs are found in North America and Europe. Participation mostly comprises a contributory citizen science model, which engages citizens in data collection. In order to leverage the full potential of citizen science in knowledge co-generation, future citizen science projects in hydrology could benefit from more co-created types of projects that establish strong ties between research and public engagement, thereby enhancing the long-term sustainability of monitoring networks.
... This lack of information probably occurs because of the high costs involved in traditional water quality monitoring schemes (Cunha et al. 2017a). Environmental data collected through citizen science initiatives therefore represent an interesting opportunity for monitoring under-studied systems (Newman et al. 2011, Thornhill et al. 2017b, and may allow the acquisition of high-resolution information and larger amounts of data (see Cunha et al. 2017b). Thus, data collected by citizen scientists could supplement existing regulatory monitoring by agencies (Hadj-Hammou et al. 2017). ...
Studies of the effects of landscape configuration on nutrient concentrations in aquatic systems, apart from land cover percentages, remain limited. Understanding these influences is important to guide land use planning and avoid the undesirable consequences of artificial eutrophication. We investigated how land use and natural landscape attributes such as edge density, mean shape index, cohesion, and contagion were related to nitrate (N-NO3) and phosphate (P-PO4) concentrations in Brazilian streams and Mexican lakes. Data on nutrient concentrations were collected by citizen science volunteers from 2013 to 2016, and we calculated land use classes and landscape metrics for each watershed. We developed models to predict nutrient concentrations based on landscape metrics, watershed slope, and season after excluding autocorrelated predictors. We used the Generalized Additive Model for Location, Shape and Scale framework and found the distribution (gamma or lognormal) that provided the best fit to the data based on the Akaike Information Criterion. The best predictors were selected following a stepwise strategy. We found relatively high N-NO3 (5–10 mg/L) and P-PO4 (0.5–1.0 mg/L) concentrations in the watersheds in both countries. Landscape composition (percentages of urban and agricultural areas) and configuration (mean shape indexes for urban and agricultural land use) metrics were the key predictors in the model for P-PO4 in Brazilian streams. In Mexican lakes, the predictors of nutrient concentrations were configuration metrics such as contagion and edge density of natural areas for P-PO4, and cohesion of urban areas for N-NO3. Our findings can be used as a starting point for land use planning, as well as for helping managers predict nutrient enrichment in watersheds within existing urban and agricultural areas. Our study highlights the importance of community-based monitoring that supplements regular monitoring initiatives because we were able to use data collected by citizen scientists to assess potential drivers of nutrient pollution and differences between countries.
... This dual track approach allows both data to be globally harmonisable as well as locally relevant and all projects feed into a single online platform. In this way, all core data are both high resolution and comparable across local projects, e.g., in the Americas ( Loiselle et al., 2016) or across regions in China ( Thornhill et al., 2017). ...
Global biodiversity monitoring is urgently needed across the world to assess the impacts of environmental change on biodiversity. One way to increase monitoring is through citizen science. ‘Citizen science’ is a term that we use in this chapter to describe the diverse approaches that involve people in monitoring in a voluntary capacity, thus including participatory monitoring in which people work collaboratively with scientists in developing monitoring. There is great unrealised potential for citizen science, especially in Asia and Africa. However, to fulfil this potential citizen science will need to meet local needs (for participants, communities and decision makers, including people's own use of the data and their motivations to participate) and support global needs for biodiversity monitoring (including the United Nations’ Sustainable Development Goals and the Aichi Biodiversity Targets). Activities should be feasible (for participants to provide scientifically rigorous data) and useful (for data users, from local to global scales). We use examples from across the world to demonstrate how monitoring can engage different types of participants, through different technologies, to record different variables according to different sampling approaches. Overall, these examples show how citizen science has the potential to provide a step change in our ability to monitor biodiversity—and hence respond to threats at all scales from local to global.
... China has been experiencing a rapid urbanization nationwide in the last few decades (Chen 2007;Jiang 2009) and many of its rivers have undergone urbanization-induced degradation of water quality (Chen 2007;Cheung et al. 2003;Thornhill et al. 2017;Wang et al. 2008). A qualitative understanding of the relationship between land use and landscape pattern and water quality is important but underutilized in urban planning and rural development. ...
Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R²) > 0.70 and percentage bias (PBIAS) between −7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main “sink” landscape while cultivated and urban lands remained the main “source” landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3–4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.
Monitoring the condition (water quality, biodiversity, hydromorphology) of small water bodies presents a challenge for the relevant authorities in terms of time and resources (labour and financial) due to the extensive length of the stream network or the sheer number of small standing water bodies. Citizen science can help address information gaps, but the effort required should not be underestimated if such projects are to generate reliable and sustained data collection. The overall aim of this paper is to propose a framework for operationalisation of citizen science targeting collection of data from small water bodies. We first consider the data gaps and the elements (water chemistry, ecology, hydromorphology) to be addressed, in order to define where citizen science could best make an impact. We review examples of tools and methods that are appropriate for small water bodies, based on experience from a selection of freshwater citizen science projects, and the support that is needed for effective and sustained small water body projects across Europe.
The rivers and their floodplains are integrated systems. The biodiversity of the Lower Danube River (LDR), in terms of species and habitats, is strongly linked with its hydro-geomorphic-diversity and the natural regions it passes. Human activities, directly and indirectly, are the primary cause which has induced changes in hydrologic regime, longitudinal and lateral connectivity, floodplain geomorphology and function, biodiversity of the river waters and riparian zone. During the twentieth century, particularly after World War II, the LDR has undergone alteration of physical habitat, significant landscape changes, and ecological loss as a result of hydropower damming works and their associated water reservoirs, floodplain embankment, wetlands drainage, chemical pollution, eutrophication, and invasion of exotic species. The extensive embankments and drainage work along LDR in Romania converted about 80% of the annual flooded zone of the floodplain area primarily into agricultural region, obviating its essential connection with the river. Few areas, including reed marshes, meadows, floodplain forests, large shallow lakes, fluvial islands, and the braided section of the river named “the Small Island of Brăila”, have been preserved in natural regime in order to preserve valuable samples of biodiversity, hydro-morpho dynamic processes, and particular fluvial landforms. Most of them are ecotonal areas that have an increased and extremely dynamic biodiversity. This increased turnover of species is exacerbated by anthropogenic factors, which sometimes they can negatively influence certain species of fauna, such as sturgeons, modifying their habitats for reproduction, feeding and resting. After the 1990s, due to the change of the political system in Romania and following integrated programs of the Danube Riparian States, some areas of the engineered floodplain are subject to ecological restoration and integrated management in order to provide convenient ways of reconciliation between nature and human society for a sustainable development. The currently Ramsar and Natura 2000 sites network designed along the LDR provides the national and international legal framework of protection and conservation of wildlife and its habitats. The objectives of this chapter are to present a review of: (1) human interventions from the last century that lead to alteration, degradation, and irreversible losses of habitats along the LDR valley, (2) restoration projects of former floodplain areas, and (3) biodiversity protection and conservation actions carried out over the area in the last decades.
Policies and management plans in the Danube River basin were first developed and applied at its entire scale in the second part of the twentieth century and were exclusively based on the principles of neoclassical economy. These principles were translated in a high number of economic and social objectives, some of which that have been identified as driving forces for the wetlands of the Lower Danube System behind structural and functional changes. The transformations to which the Lower Danube System has been subjected and the absence of multi-connectivity in planning were marked by an insufficiency of support tools at decision-making level. Wetlands play a dual role in terms of planning, acting both as risk-inhibitor and services enabler when inclusive multi-dimensional planning is performed. Given the relevant spatial and temporal scale of the current context, capitalizing on scientific knowledge, experiences and information of local communities in future policymaking is crucial. The productivity and stability of ecosystems depend directly on their ability to ensure energy transfer both intra-, but especially inter-system. The lateral and longitudinal analysis of ecosystems in the Lower Danube System, regarded as both dynamic and nonlinear systems, as well as production units, is based on a conceptual framework aimed at their multi-connectivity. This ensures long-term processes whose variability and diversity are essential for the stability and productivity of these units. The study includes social and economic implications, considering the relationship between the natural heritage resources of the geographical sub-units and the existence of the socio-economic system.
Natural hazards, including droughts, are processes and phenomena that can trigger a negative impact on the environment, society and various economic sectors. The present chapter aims to identify spatial peculiarities of drought characteristics (frequency, duration, affected area) and to analyse drought hazard, vulnerability and risk in the Lower Danube region. The study area includes administrative regions from Romania (counties) and Bulgaria (districts) located along the Danube River, which is the common administrative border between the two countries. The northward and southward Danube territories are part of the most important agricultural areas of both countries, where natural landscapes have been significantly transformed by anthropogenic activities which contributed to the removal of the natural vegetation and its replacement with cultivated plants and urban areas. Drought characteristics and associated hazards were analysed using the Standardized Precipitation-Evapotranspiration Index (SPEI-3, 6, 12) for the period 1981–2019. Population density and land cover/land use data were taken into account in the drought vulnerability assessment. Drought hazard and vulnerability were considered in the drought risk evaluation which allowed the identification of the regional drought “hotspots”. Results show a very high level of drought risk associated to short-term drought (SPEI-3) in the central and eastern parts of the study region. In the case of long-term drought (SPEI-12), a reduction in areas showing a very high drought risk level is observed. The administrative regions located in the western part of the study area have very low and low levels of drought risk.
To achieve Sustainable Development Goals (SDGs) 6, universal and equitable access to safe and affordable drinking-water quality and sanitation for all, and 10, to reduce inequality within and among countries, additional and urgent work is required. Efforts to achieve these Goals in the context of small drinking-water supplies, which are the furthest behind in regards to progress, are of particular need. Reasons for this disparity in progress include the remoteness of access to small drinking-water supplies and the lack of technical and financial capacity for monitoring supplies. The World Health Organization promote the use of Sanitary inspection (SI) as an on-site assessment of risk. Despite the potential to increase the body of knowledge and information on supplies in a region, there has been limited research into the role of citizen science and SIs. To meet SDG targets, we need to improve the reach of SIs. This study uses a mixed methods approach of quantitative on-site SI data collection and remote SI data collection via photographic images, together with qualitative data collection, collected by non-expert students, who are citizens of Malawi, as well as a panel of experts in the field of SI. Results indicate that, although further research into the topic is required prior to widescale implementation, the potential exists for citizens to conduct SI, with remote expert verification of the results using photographic images of supplies. Further documentation or guidance is required to support citizens in this process. The results highlight a critical gap in the availability of appropriate documentation for unprotected spring sources which is urgently required. The use of citizen science for SI data collection is in its infancy. However, this study indicates that there is potential to explore the use of citizen science in this area, which will contribute to achieving SDGs 6 and 10.
The threshold effect in the relationship between impervious surfaces and water quality has been a focus in past decades, but little attention has been paid to how the threshold effect changes during a rapid urbanization period. This study reveals the temporal variation of threshold effect in the relationship between the percentage of total impervious area (PTIA) and water quality indicators in a reticular river network area in Shanghai, China. The PTIA was surveyed and defined using the ISC method (impervious surface coefficients). A segmented regression model was used to disclose the non-linear relationship between PTIA and water quality. It is confirmed that the threshold effect was different in terms of water quality indicators, but the effect size became smaller as the threshold increased with urbanization level during the period of 1989–2010. Meteorological conditions make influence on the threshold effect, it can be found that the effect is more significant under higher air temperature conditions, while in the lower temperature situation, there is no significant threshold effect.
This research was carried out at the Science Volunteer Program 2018, which is run by Taiwan’s Ministry of Science and Technology. The purpose of the research was to understand the effects of self-efficacy, satisfaction, and science trust on science volunteers’ intention to continue volunteering. The research drew on the Social Cognitive Career Theory (SCCT) to test how social cognitive variables affect volunteers’ intention to continue engaging in events and with organizations. A total of 156 volunteers taking part in the program completed a questionnaire measuring Self-efficacy, Satisfaction, Trust, and Intention. A structural equation model (SEM) was developed, and the proposed effects on the variables were tested using SEM procedures. The results of the SEM analysis found that there were positive effects between (a) Self-efficacy and Satisfaction, (b) Self-efficacy and Intention, (c) Satisfaction and Intention, and (d) Trust and Intention. The discussion highlights implications for science volunteer managers who are not only in a position to increase volunteers’ behavioral intention to continue their engagement in volunteer work, but also to facilitate interventions to boost volunteering in Taiwan. Keywords: citizen science, science volunteers, social cognitive career theory, structural equation model
Attempts to monitor the quality of freshwater resources on a global scale unveil huge data lacks. Involving citizens in data collection has potential to resolve this lack of water quality data. However, it is widely unclear which factors drive the success of citizen science activities. Based on a systematic literature review of 56 peer-reviewed research articles, we identify three sets of factors for successful citizen science projects in water quality monitoring: (i) attributes of citizens (knowledge and experience in collecting data, awareness of environmental problems, motivation, and socio-economic background of citizens), (ii) attributes of institutions (motivation, type of organization, consistent and adequate funding), and (iii) the interactions between citizens and institutions (supporting structure, communication and feedback). These three sets of factors enable a systematic analysis and design of citizen science projects in the future.
The United Nations has called for increased public participation in scientific research, to benefit professionals, the public and the planet. Citizen science has been suggested as a cost-effective means by which this call can be met, and by which monitoring for the Sustainable Development Goals (SDGs) may be carried out. Indeed, citizen science has gained significant attention in recent years as the scale of environmental issues surpasses the monitoring resources that currently exist. However, many challenges continue to act as a barrier to the acceptance of citizen science as a reliable scientific approach. Here, the current state of knowledge on the use of citizen science in water quality monitoring is reviewed, and the potential for utilizing this approach to enhance monitoring for SDG Indicator 6.3.2 on the “proportion of bodies of water of good ambient water quality” is evaluated. The objective of this review is to identify key knowledge gaps and hurdles hindering the adoption of citizen science contributions to water quality monitoring under the SDGs, so that these gaps may be addressed in a timely manner for future monitoring programmes.
Over the past decade, several citizen science projects have been launched, with a smaller subset addressing citizen scientists' involvement in water quality monitoring. Most of these projects were conducted in developed countries and focused on qualitative assessment and measurements of a limited number of water quality parameters. Moreover, data generated by citizen scientists were mainly for monitoring purposes and rarely resulted in remedial measures. In this work, a collaborative citizen science approach involving local citizens and university researchers was applied to assess the groundwater quality in a Lebanese village. Using a mobile laboratory, winter and summer sampling campaigns were conducted and 12 physical, chemical and biological water quality parameters were tested. Results indicated that the data generated by the citizen scientists were comparable with those generated by university researchers for the majority of physical and chemical water quality parameters. However, the bacteriological test results showed a marked difference and may be attributed to the complexity of the testing procedure and quality of testing material. The collaborative and participatory approach resulted in building local capacity and knowledge and in the formation of a locally elected water committee which will be responsible for continuous monitoring of the groundwater resources.
Global metrics of land cover and land use provide a fundamental basis to examine the spatial
variability of human-induced impacts on freshwater ecosystems. However, microscale
processes and site specific conditions related to bank vegetation, pollution sources, adjacent
land use and water uses can have important influences on ecosystem conditions, in
particular in smaller tributary rivers. Compared to larger order rivers, these low-order
streams and rivers are more numerous, yet often under-monitored. The present study
explored the relationship of nutrient concentrations in 150 streams in 57 hydrological basins
in South, Central and North America (Buenos Aires, Curitiba, São Paulo, Rio de Janeiro,
Mexico City and Vancouver) with macroscale information available from global datasets
and microscale data acquired by trained citizen scientists. Average sub-basin phosphate
(P-PO4) concentrations were found to be well correlated with sub-basin attributes on both
macro and microscales, while the relationships between sub-basin attributes and nitrate
(N-NO3) concentrations were limited. A phosphate threshold for eutrophic conditions (>0.1
mg L-1 P-PO4) was exceeded in basins where microscale point source discharge points
(eg. residential, industrial, urban/road) were identified in more than 86% of stream reaches
monitored by citizen scientists. The presence of bankside vegetation covaried (rho = –0.53)
with lower phosphate concentrations in the ecosystems studied. Macroscale information on
nutrient loading allowed for a strong separation between basins with and without eutrophic
conditions. Most importantly, the combination of macroscale and microscale information
acquired increased our ability to explain sub-basin variability of P-PO4 concentrations. The
identification of microscale point sources and bank vegetation conditions by citizen scientists
provided important information that local authorities could use to improve their management
of lower order river ecosystems.
Many citizen science projects are place-based - built on in-person participation and motivated by local conservation. When done thoughtfully, this approach to citizen science can transform humans and their environment. Despite such possibilities, many projects struggle to meet decision-maker needs, generate useful data to inform decisions, and improve social-ecological resilience. Here, we define leveraging the ‘power of place’ in citizen science, and posit that doing this improves conservation decision making, increases participation, and improves community resilience. First, we explore ‘place’ and identify five place dimensions: social-ecological, narrative and name-based, knowledge-based, emotional and affective, and performative. We then thematically analyze 134 case studies drawn from CitSci.org (n=39), The Stewardship Network New England (TSN-NE; n=39), and Earthwatch (n=56) regarding: (1) use of place dimensions in materials (as one indication of leveraging the power of place), (2) intent for use of data in decision-making, and (3) evidence of such use. We find that 89% of projects intend for data to be used, 46% demonstrate no evidence of use, and 54% provide some evidence of use. Moreover, projects used in decision making leverage more (t=−4.8, df=117; p<0.001) place dimensions (x̅=3.0; s=1.4) than those not used in decision making (x̅=1.8; s=1.2). Further, a Principal Components Analysis identifies three related components (aesthetic, narrative and name-based, and social-ecological). Given these findings, we present a framework for leveraging place in citizen science projects and platforms, and recommend approaches to better impart intended outcomes. We discuss place in citizen science related to relevance, participation, resilience, and scalability and conclude that effective decision making as a means towards more resilient and sustainable communities can be strengthened by leveraging the power of place in citizen science.
The world's population is concentrated in urban areas. This change in demography has brought landscape transformations that have a number of documented effects on stream ecosystems. The most consistent and pervasive effect is an increase in impervious surface cover within urban catchments, which alters the hydrology and geomorphology of streams. This results in predictable changes in stream habitat. In addition to imperviousness, runoff from urbanized surfaces as well as municipal and industrial discharges result in increased loading of nutrients, metals, pesticides, and other contaminants to streams. These changes result in consistent declines in the richness of algal, invertebrate, and fish communities in urban streams. Although understudied in urban streams, ecosystem processes are also affected by urbanization. Urban streams represent opportunities for ecologists interested in studying disturbance and contributing to more effective landscape management.
The field of urban stream ecology has evolved rapidly in the last 3 decades, and it now includes natural scientists from numerous disciplines working with social scientists, landscape planners and designers, and land and water managers to address complex, socioecological problems that have manifested in urban landscapes. Over the last decade, stream ecologists have met 3 times at the Symposium on Urbanization and Stream Ecology (SUSE) to discuss current research, identify knowledge gaps, and promote future research collaborations. The papers in this special series on urbanization and stream ecology include both primary research studies and conceptual synthesis papers spurred from discussions at SUSE in May 2014. The themes of the meeting are reflected in the papers in this series emphasizing global differences in mechanisms and responses of stream ecosystems to urbanization and management solutions in diverse urban streams. Our hope is that this series will encourage continued interdisciplinary and collaborative research to increase the global understanding of urban stream ecology toward stream protection and restoration in urban landscapes.
Freshwater ecosystems are severely threatened by urban development and agricultural intensification. Increased occurrence of algal blooms is a main issue, and the identification of local dynamics and drivers is hampered by a lack of field data. In this study, data from 13 cities (250 water bodies) were used to examine the capacity of trained community members to assess elevated phytoplankton densities in urban and peri-urban freshwater ecosystems. Coincident nutrient concentrations and land use observations were used to examine possible drivers of algal blooms. Measurements made by participants showed a good relationship to standard laboratory measurements of phytoplankton density, in particular in pond and lake ecosystems. Links between high phytoplankton density and nutrients (mainly phosphate) were observed. Microscale observations of pollution sources and catchment scale estimates of land cover both influenced the occurrence of algal blooms. The acquisition of environmental data by committed and trained community members represents a major opportunity to support agency monitoring programmes and to complement field campaigns in the study of catchment dynamics.
Electronic supplementary material
The online version of this article (doi:10.1007/s10661-015-4912-9) contains supplementary material, which is available to authorized users.
Attributing changes in river water quality to specific factors is
challenging because multiple factors act at different temporal and spatial
scales, and it often requires examining long-term series of continuous data.
Data consistency is sometimes hindered by the lack of observations of
relevant water quality variables and the low and uneven sampling frequency
that characterizes many water quality monitoring schemes. Nitrate and
dissolved phosphate concentration time series (1980–2011) from 50 sampling
stations across a large Mediterranean river basin were analyzed to
disentangle the role of hydrology, land-use practices, and global climatic
phenomena on the observed nutrient patterns, with the final aim of
understanding how the different aspects of global change affected nutrient
dynamics in the basin. Dynamic factor analysis (DFA) provided the
methodological framework to extract underlying common patterns in nutrient
time series with missing observations. Using complementary methods such as
frequency and trend analyses, we sought to further characterize the common
patterns and identify the drivers behind their variability across time and
space. Seasonal and other cyclic patterns were identified as well as trends
of increase or decrease of nutrient concentration in particular areas of the
basin. Overall, the impact of global change, which includes both climate
change and anthropogenic impacts, on the dynamics of nitrate concentration
across the study basin was found to be a multifaceted process including
regional and global factors, such as climatic oscillations and agricultural
irrigation practices, whereas impacts on phosphate concentration seemed to
depend more on local impacts, such as urban and industrial activities, and
less on large-scale factors.
Water degradation is strongly related to agricultural activity. The aim of this study was to evaluate the influence of land use and some environmental components on surface water quality in the Campestre catchment, located in Colombo, state of Parana, Brazil. Physical and chemical attributes were analyzed (total nitrogen, ammonium, nitrate, total phosphorus, electrical conductivity, pH, temperature, turbidity, total solids, biological oxygen demand, chemical oxygen demand and dissolved oxygen). Monthly samples of the river water were taken over one year at eight monitoring sites, distributed over three sub-basins. Overall, water quality was worse in the sub-basin with a higher percentage of agriculture, and was also affected by a lower percentage of native forest and permanent preservation area, and a larger drainage area. Water quality was also negatively affected by the presence of agriculture in the riparian zone. In the summer season, probably due to higher rainfall and intensive soil use, a higher concentration of total nitrogen and particulate nitrogen was observed, as well as higher electrical conductivity, pH and turbidity. All attributes, except for total phosphorus, were in compliance with Brazilian Conama Resolution Nº 357/2005 for freshwater class 1. However, it should be noted that these results referred to the base flow and did not represent a discharge condition since most of the water samples were not collected at or near the rainfall event.
We tested the hypothesis that urbanization alters stream sediment regimes and homogenizes fish assemblages in 30 sub-basins of the Etowah River. Sediment variables included average particle size (mean phi) of the stream bed, percent fines (<2 mm) in riffles, and baseflow turbidity (NTU). Homogenization was quantified as ratios of endemic to cosmopolitan species richness (Er:Cr) and abundance (Ea:Ca). High NTU and fine stream beds were associated with homogenized assemblages (i.e., lower E:C ratios). Mean phi and NTU were significantly correlated with E:C ratios (r = −0.74 to −0.76) and, when combined using multiple regression, accounted for 73% of the variance in ratios. Stream slope strongly covaried with mean phi (r = −0.92) and percent fines in riffles (r = −0.79), but multiple regression models showed that urbanized sites had finer beds and riffles than predicted by slope alone. Urban land cover was the primary predictor of NTU (r
2
= 0.42) and, combined with slope in multiple regression, explained 51% of the variance in NTU. Our results indicate that stream slope is a background variable predicting particle size and E:C ratios in these streams. Urbanization disrupts these relationships by transforming clear streams with coarse beds into turbid streams with finer beds. These conditions favor cosmopolitan species, ultimately homogenizing fish assemblages. Bed texture was linked to urbanization; however, NTU was the best indicator of urban impacts because it was statistically independent from slope.
This literature review addresses how wide a streamside forest buffer needs to be to protect water quality, habitat, and biota for small streams (≤~100 km2 or ~5th order watershed) with a focus on eight functions: (1) subsurface nitrate removal varied inversely with subsurface water flux and for sites with water flux >50 l/m/day (~40% avg base flow to Chesapeake Bay) median removal efficiency was 55% (26-64%) for buffers <40 m wide and 89% (27-99%) for buffers >40 m wide; (2) sediment trapping was ~65 and ~85% for a 10- and 30-m buffer, respectively, based on streamside field or experimentally loaded sites; (3) stream channel width was significantly wider when bordered by ~25-m buffer (relative to no forest) with no additional widening for buffers ≥25 m; (4) channel meandering and bank erosion were lower in forest but more studies are needed to determine the effect of buffer width; (5) temperature remained within 2°C of levels in a fully forested watershed with a buffer ≥20 m but full protection against thermal change requires buffers ≥30 m; (6) large woody debris (LWD) has been poorly studied but we infer a buffer width equal to the height of mature streamside trees (~30 m) can provide natural input levels; (7, 8) macroinvertebrate and fish communities, and their instream habitat, remain near a natural or semi-natural state when buffered by ≥30 m of forest. Overall, buffers ≥30 m wide are needed to protect the physical, chemical, and biological integrity of small streams.
The primary advantage of the Geostationary Ocean Color Imager (GOCI),
the world's first geostationary ocean color observation satellite, over
other ocean color satellite imagers is that it can obtain data every
hour during the daytime, allowing ocean monitoring in near real time.
Here, we investigated temporal variation in turbidity along a coastal
region. To estimate suspended sediment concentrations (SSC), water
samples and radiometric data were collected from waters in the Mokpo
coastal area, located along the west coast of Korea. GOCI images
acquired on the same day as the samples were used to generate a map of
turbidity and to estimate the differences in SSC displayed in each
image. Hourly GOCI images successfully identified the temporal variation
in turbidity, which is mainly driven by the tidal cycle. A hydrodynamic
model also showed that the GOCI-derived turbidity variation was
reliable. This study shows that the GOCI can be effectively used to
monitor the temporal dynamics of the turbidity of coastal waters, i.e.,
sediment movements driven by the tidal cycle along the west coast of the
Korean Peninsula.
In this paper we present a general overview of several supervised machine learning (ML) algorithms and illustrate their use for the prediction of mass mortality events in the coastal rocky benthic communities of the NW Mediterranean Sea. In the first part of the paper we present, in a conceptual way, the general framework of ML and explain the basis of the underlying theory. In the second part we describe some outstanding ML techniques to treat ecological data. In the third part we present our ecological problem and we illustrate exposed ML techniques with our data. Finally, we briefly summarize some extensions of several methods for multi-class output prediction.
Citizen science is on the rise. Aided by the internet, the popularity and scope of citizen science appears almost limitless. For citizens the motivation is to contribute to ‘‘real’’ science, public information and conservation. For scientists, citizen science offers a way to collect information that would otherwise not be affordable. The longest running and largest of these citizen science programs are broad-scale bird monitoring projects. There are two basic types of protocols possible: (a) cross-sectional schemes such as Atlases – collections of surveys of many species contributed by volunteers over a set period of time, and (b) longitudinal schemes such as Breeding Bird Surveys (BBS) – on-going stratified monitoring of sites that require more coordination. We review recent applications of these citizen science programs to determine their influence in the scientific literature. We use return-on-investment thinking to identify the minimum investment needed for different citizen science programs, and the point at which investing more in citizen science programs has diminishing benefits. Atlas and BBS datasets are used to achieve different objectives, with more knowledge-focused applications for Atlases compared with more management applications for BBS. Estimates of volunteer investment in these datasets show that compared to cross-sectional schemes, longitudinal schemes are more cost-effective, with increased BBS investment correlated with more applications, which have higher impact in the scientific literature, as measured by citation rates. This is most likely because BBS focus on measuring change, allowing the impact of management and policy to be quantified. To ensure both types of data are used to their full potential we recommend the following: elements of BBS protocols (fixed sites, long-term monitoring) are incorporated into Atlases; regional coordinators are in place to maintain data quality; communication between researchers and the organisations coordinating volunteer monitoring is enhanced, with monitoring targeted to meet specific needs and objectives; application of data to under-explored objectives is encouraged, and data are made freely and easily accessible.
In some situations algal blooms can have detrimental consequences to aquaculture, fisheries and tourism, with major economic, environmental and human health problems. Some 300 of the 5000 known species of marine phytoplankton can at times occur in such high numbers that they discolour the sea (red tides) and 40 or so species can produce toxins that can find their way though fish and shellfish to humans. While blooms are natural phenomena, much recent human activity has heightened the intensity, frequency and distribution of such algal growths. Comments are made on diarrhetic shellfish poisoning and amnesic shellfish poisoning. The consequences of the increased use of coastal waters for mariculture are noted, and the increase of algal blooms by cultural eutrophication is stressed, with particular reference to ciguatera fish-food poisoning and coral reef distribution. Stimulation of algal blooms by unusual climatic conditions are noted, with reference to toxic Pyrodinium bahamense blooms in the tropical Indo-West Pacific and fossil blooms of Gymnodinium catenatum in the Kattegat-Skagerrak. Notes are also given on the transport of dinoflagellate cysts in ships' ballast water or associated with the transfer of shellfish stock. -P.J.Jarvis
A method is presented for calculating the effectiveness of trees in reducing the incidence of shallow landslides on hillslopes. Computer processing of digital imagery is applied to aerial photographs of hillslopes on which widely spaced trees and landslide scars are both visible. A graph of average fraction of ground eroded versus distance from tree is derived. From this graph, the average radius of influence of trees and the area of ground saved from sliding by the trees are deduced. To demonstrate the method, it is applied to a hillslope that had experienced landsliding during a severe storm. The storm caused 20.9% of the study area to become immediately unproductive for pasture growth, either through landsliding or deposition of debris. The method predicted that without the poplar trees this figure would have been 24.2%, thus the storm reduced damage by 13.8%. If the trees had been planted on a 10m grid, with a 100% establishment rate, storm damage would have been reduced at least 70%. -from Authors
Sedimentation and turbidity are significant contributors to declines in populations of North American aquatic organisms. Impacts to lotic fauna may be expressed through pervasive alterations in local food chains beginning at the primary trophic level. Decreases in primary production are associated with increases in sedimentation and turbidity and produce negative cascading effects through depleted food availability to zooplankton, insects, freshwater mollusks, and fish. Direct effects at each trophic level are mortality, reduced physiological function, and avoidance; however, decreases in available food at trophic levels also result in depressed rates of growth, reproduction, and recruitment. Impacts of turbidity to aquatic organisms often seem inconsistent among watersheds and experiments, but this apparent difference is actually due to the lack of correlation between suspended sediment concentrations (mg/L) and units of measure (Nephelometric Turbidity Units, NTU). The use of NTU as a surrogate measurement of suspended sediment to predict biotic effects within watersheds is dubious. Similar NTU measurements from different watersheds may be correlated with different concentrations of suspended sediment. For monitoring the effects of turbidity within local watersheds, we recommend that the correlation between suspended sediment and NTUs be examined over a range of discharge recordings, and that this be used as a baseline to examine local effects. We recommend that riparian buffer strips and livestock fencing be used to reduce sediment input to streams.
Urban streams have been the focus of much research in recent years, but many questions about the mechanisms driving the urban stream syndrome remain unanswered. Identification of key research questions is an important step toward effective, efficient management of urban streams to meet societal goals. We developed a list of priority research questions by: 1) soliciting input from interested scientists via a listserv and online survey, 2) holding an open discussion on the questions at the Second Symposium on Urbanization and Stream Ecology, and 3) reviewing the literature in the preparation of this paper. We present the resulting list of 26 questions in the context of a review and summary of the present understanding of urban effects on streams. The key questions address major gaps in our understanding of ecosystem structure and function responses (e.g., what are the sublethal impacts of urbanization on biota?), characteristics of urban stream stressors (e.g., can we identify clusters of covarying stressors?), and management strategies (e.g., what are appropriate indicators of ecosystem structure and function to use as management targets?). The identified research needs highlight our limited understanding of mechanisms driving the urban stream syndrome and the variability in characteristics of the effects of urbanization across different biogeoclimatic conditions, stages of development, government policies, and cultural norms. We discuss how to proceed with appropriate management activities given our current incomplete understanding of the urban stream syndrome.
Approaches to citizen science – an indispensable means of combining ecological research with environmental education and natural history observation – range from community-based monitoring to the use of the internet to “crowd-source” various scientific tasks, from data collection to discovery. With new tools and mechanisms for engaging learners, citizen science pushes the envelope of what ecologists can achieve, both in expanding the potential for spatial ecology research and in supplementing existing, but localized, research programs. The primary impacts of citizen science are seen in biological studies of global climate change, including analyses of phenology, landscape ecology, and macro-ecology, as well as in subdisciplines focused on species (rare and invasive),
disease, populations, communities, and ecosystems. Citizen science and the resulting ecological data can
be viewed as a public good that is generated through increasingly collaborative tools and resources, while supporting
public participation in science and Earth stewardship.
Estuaries throughout the world are experiencing water quality problems as the result of human population growth in coastal areas. By establishing the habitat requirements of critical submerged aquatic vegetation, water quality can be evaluated and restoration goals can be made. This study used submerged vegetation in Chesapeake Bay to examine the habitat and health of the Bay. Both natural distributions and transplant survival in different studies were analyzed. The five habitat requirements used were light attenuation, total suspended solids, chlorophyll, dissolved inorganic nitrogen, and dissolved inorganic phosphorus. Water-quality conditions supporting vegetation growth to one meter depth was used. This study represents the first attempt at linking habitat requirements of a living resource to water quality standards in an estuarine system. It allows for predictive capability without detailed knowledge of the precise nature of vegetation/water quality interactions.
The NCEP-DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the "50-year" (1948-present) NCEP-NCAR Reanalysis Project. NCEP-DOE AMIP-II reanalysis covers the "20-year" satellite period of 1979 to the present and uses an updated forecast model, updated data assimilation system, improved diagnostic outputs, and fixes for the known processing problems of the NCEP-NCAR reanalysis. Only minor differences are found in the primary analysis variables such as free atmospheric geopotential height and winds in the Northern Hemisphere extratropics, while significant improvements upon NCEP-NCAR reanalysis are made in land surface parameters and land-ocean fluxes. This analysis can be used as a supplement to the NCEP-NCAR reanalysis especially where the original analysis has problems. The differences between the two analyses also provide a measure of uncertainty in current analyses.
As an integral part of the comprehensive water quality investigation of the Chattooga River watershed, an ecological and sedimentological study was conducted on selected stream reaches within the study area. The objective of this study was to conduct a sediment yield study and determine if sediment was a primary cause of physical and biological impairment to streams within the watershed. As result of this study, accelerated sedimentation has been identified to be the leading determinant in loss of habitat and reduction in bedform diversity within the study area. Good correlation was observed between aquatic ecology and normalized total suspended solids (TSS) data. Based on overlaying the biological index on TSS normalized to discharge/mean discharge, TSS concentrations greater than 284 mg/l adversely affected aquatic macroinvertebrate community structure. However, based on historic regional suspended-sediment concentrations, a normalized TSS concentration of 58 mg/l or less during storm flow provides an adequate margin of safety and is protective of aquatic macroinvertebrates in the Blue Ridge physiography. Corresponding turbidity limits of 69 and 22 NTU established the threshold of biological impairment and margin of safety, respectively. Previously, a similar turbidity of 25 NTU has been recommended for stream restoration management plans. Relative to reference streams, impaired streams yielded higher bedload and suspended load. The results of this study showed that road density and associated sediment sources accounted for 51% of the total sediment loading.
The term ''urban stream syndrome'' describes the consistently observed ecological degra-dation of streams draining urban land. This paper reviews recent literature to describe symptoms of the syndrome, explores mechanisms driving the syndrome, and identifies appropriate goals and methods for ecological restoration of urban streams. Symptoms of the urban stream syndrome include a flashier hy-drograph, elevated concentrations of nutrients and contaminants, altered channel morphology, and reduced biotic richness, with increased dominance of tolerant species. More research is needed before generaliza-tions can be made about urban effects on stream ecosystem processes, but reduced nutrient uptake has been consistently reported. The mechanisms driving the syndrome are complex and interactive, but most impacts can be ascribed to a few major large-scale sources, primarily urban stormwater runoff delivered to streams by hydraulically efficient drainage systems. Other stressors, such as combined or sanitary sewer overflows, wastewater treatment plant effluents, and legacy pollutants (long-lived pollutants from earlier land uses) can obscure the effects of stormwater runoff. Most research on urban impacts to streams has concentrated on correlations between instream ecological metrics and total catchment imperviousness. Recent research shows that some of the variance in such relationships can be explained by the distance between the stream reach and urban land, or by the hydraulic efficiency of stormwater drainage. The mech-anisms behind such patterns require experimentation at the catchment scale to identify the best management approaches to conservation and restoration of streams in urban catchments. Remediation of stormwater impacts is most likely to be achieved through widespread application of innovative approaches to drainage design. Because humans dominate urban ecosystems, research on urban stream ecology will require a broadening of stream ecological research to integrate with social, behavioral, and economic research.
1. The effects of catchment urbanisation on water quality were examined for 30 streams (stratified into 15, 50 and 100 km² ± 25% catchments) in the Etowah River basin, Georgia, U.S.A. We examined relationships between land cover (implying cover and use) in these catchments (e.g. urban, forest and agriculture) and macroinvertebrate assemblage attributes using several previously published indices to summarise macroinvertebrate response. Based on a priori predictions as to mechanisms of biotic impairment under changing land cover, additional measurements were made to assess geomorphology, hydrology and chemistry in each stream.
Agricultural intensification was linked to streamwaterpollution in a case study watershed using GIS andnutrient budgeting techniques. The results showed thatsurplus nitrogen applications from fertilizers andmanure averaged 120 kg ha-1 yr-1. In some parts of the watershed surplus applications exceeded 300 kg ha-1 yr-1. A consistent increase in pig and chickennumbers (59 and 165% increase between 1986 and1996) is considered the main reason for the surplus.Water quality was impacted in two ways: nitratecontaminated groundwater contributed to high nitratesin a major tributary during the summer, while in thewet winter season ammonia, phosphate and coliformlevels were high throughout the drainage system.Significant negative relationships were found betweensurplus nitrogen applications and dissolved oxygenwhile ammonia and nitrate concentrations during thewet season were positively correlated to surplusapplications. Soil texture and drainage type were alsosignificantly correlated with the water qualityindicators suggesting that it is possible to use thebudget/GIS linked techniques for pollution riskassessment from agricultural non-point sources.
Three streams in the Piedmont ecoregion of North Carolina were studied to evaluate the effect of land use (forested, agricultural, urban) on water quality and aquatic biota. In comparison with the forested stream, there were few changes in water quality at the agricultural and urban streams. Suspended-sediment yield was greatest for the urban catchment and least at the forested catchment. Suspended-sediment concentrations during storm events followed this same pattern, but at low-moderate flows suspended-sediment concentrations were greatest at the agricultural site. Most nutrient concentrations were highest at the agricultural site, and the amount of ‘available’ dissolved nitrogen was elevated at both the urban and agricultural sites. High concentrations of metals (totals) in the water column were sometimes observed at all sites, but maximum average concentrations were recorded at the urban site (especially Cr, Cu, and Pb). Maximum sediment metal concentrations, however, were not found at the urban site, but were usually recorded at the forested site. Only minor differences were noted between fish communities of the forested and agricultural sites, although both abundance and average size of some species increased at the agricultural site. The fish community at the urban site was characterized by low species richness, low biomass, and the absence of intolerant species.
Invertebrate taxa richness, a biotic index, and the number of unique invertebrate species (found at only one site) indicated moderate stress (Fair water quality) at the agricultural site and severe stress (Poor water quality) at the urban site. At the agricultural site, declines in taxa richness within intolerant groups were partially offset by increases within tolerant groups. The agricultural stream had the highest abundance values, indicating enrichment. The urban site, however, was characterized by low species richness for most groups and very low abundance values. Analysis of seasonal patterns suggested detritus was the most important food source for invertebrates in the forested stream, while periphyton was of greater importance in the agricultural stream. Dominant macroinvertebrate groups shifted from Ephemeroptera at the forested site, to Chironomidae at the agricultural site, and Oligochaeta at the urban site. There was little between-site overlap in dominant species (8–7%), indicating that land use strongly influenced the invertebrate community. Chemical and physical parameters measured at the three sites did not seem sufficient to account for all of the observed differences in the invertebrate communities, suggesting some unmeasured toxicity. Biological measurements, especially macroinvertebrates community structure, consistently indicated strong between-site differences in water and habitat quality.
While the urban runoff are increasingly being studied as a source of fecal indicator bacteria (FIB), less is known about the occurrence of FIB in watershed with mixed land use and ongoing land use and land cover (LULC) change. In this study, Escherichia coli (EC) and fecal streptococcus (FS) were monitored from 2012 to 2013 in agricultural, mixed and urban LULC and analyzed according to the most probable number (MPN). Pearson correlation was used to determine the relationship between FIB and environmental parameters (physicochemical and hydrometeorological). Multiple linear regressions (MLR) were used to identify the significant parameters that affect the FIB concentrations and to predict the response of FIB in LULC change. Overall, the FIB concentrations were higher in urban LULC (EC=3.33-7.39; FS=3.30-7.36log10MPN/100mL) possibly because of runoff from commercial market and 100% impervious cover (IC). Also, during early-summer season; this reflects a greater persistence and growth rate of FIB in a warmer environment. During intra-event, however, the FIB concentrations varied according to site condition. Anthropogenic activities and IC influenced the correlation between the FIB concentrations and environmental parameters. Stormwater temperature (TEMP), turbidity, and TSS positively correlated with the FIB concentrations (p>0.01), since IC increased, implying an accumulation of bacterial sources in urban activities. TEMP, BOD5, turbidity, TSS, and antecedent dry days (ADD) were the most significant explanatory variables for FIB as determined in MLR, possibly because they promoted the FIB growth and survival. The model confirmed the FIB concentrations: EC (R(2)=0.71-0.85; NSE=0.72-0.86) and FS (R(2)=0.65-0.83; NSE=0.66-0.84) are predicted to increase due to urbanization. Therefore, these findings will help in stormwater monitoring strategies, designing the best management practice for FIB removal and as input data for stormwater models.
Function estimation/approximation is viewed from the perspective of numerical optimization iti function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest-descent minimization. A general gradient descent "boosting" paradigm is developed for additive expansions based on any fitting criterion. Specific algorithms are presented for least-squares, least absolute deviation, and Huber-M loss functions for regression, and multiclass logistic likelihood for classification. Special enhancements are derived for the particular case where the individual additive components are regression trees, and tools for interpreting such "TreeBoost" models are presented. Gradient boosting of regression trees produces competitives highly robust, interpretable procedures for both regression and classification, especially appropriate for mining less than clean data. Connections between this approach and the boosting methods of Freund and Shapire and Friedman, Hastie and Tibshirani are discussed.
Despite significant recent advancements, global hydrological models and their input databases still show limited capabilities in supporting many spatially detailed research questions and integrated assessments, such as required in freshwater ecology or applied water resources management. In order to address these challenges, the scientific community needs to create improved large-scale datasets and more flexible data structures that enable the integration of information across and within spatial scales; develop new and advanced models that support the assessment of longitudinal and lateral hydrological connectivity; and provide an accessible modeling environment for researchers, decision makers, and practitioners. As a contribution, we here present a new modeling framework that integrates hydrographic baseline data at a global scale (enhanced HydroSHEDS layers and coupled datasets) with new modeling tools, specifically a river network routing model (HydroROUT) that is currently under development. The resulting ‘hydro-spatial fabric’ is designed to provide an avenue for advanced hydro-ecological applications at large scales in a consistent and highly versatile way. Preliminary results from case studies to assess human impacts on water quality and the effects of dams on river fragmentation and downstream flow regulation illustrate the potential of this combined data-and-modeling framework to conduct novel research in the fields of aquatic ecology, biogeochemistry, geo-statistical modeling, or pollution and health risk assessments. The global scale outcomes are at a previously unachieved spatial resolution of 500 m and can thus support local planning and decision making in many of the world's large river basins. Copyright © 2013 John Wiley & Sons, Ltd.
Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, ***, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.
Socioeconomic development in China has resulted in rapid urbanization, which includes a large amount of people making the transition from rural areas to cities. Many have speculated that this mass migration may have worsened the water crisis in many parts of the country. However, this study shows that the water crisis would be more severe if the rural-to-urban migration did not occur.
The ever-increasing demand for water due to growth of population and socioeconomic development in the past several decades has posed a worldwide threat to water supply security and to the environmental health of rivers. This study aims to derive reservoir operating rules through establishing a multi-objective optimization model for the Xinfengjiang (XFJ) reservoir in the East River Basin in southern China to minimize water supply deficit and maximize hydropower generation. Additionally, to enhance the estimation of irrigation water demand from the downstream agricultural area of the XFJ reservoir, a conventional method for calculating crop water demand is improved using hydrological model simulation results. Although the optimal reservoir operating rules are derived for the XFJ reservoir with three priority scenarios (water supply only, hydropower generation only, and equal priority), the river environmental health is set as the basic demand no matter which scenario is adopted. The results show that the new rules derived under the three scenarios can improve the reservoir operation for both water supply and hydropower generation when comparing to the historical performance. Moreover, these alternative reservoir operating policies provide the flexibility for the reservoir authority to choose the most appropriate one. Although changing the current operating rules may influence its hydropower-oriented functions, the new rules can be significant to cope with the increasingly prominent water shortage and degradation in the aquatic environment. Overall, our results and methods (improved estimation of irrigation water demand and formulation of the reservoir optimization model) can be useful for local watershed managers and valuable for other researchers worldwide.
Reviews the literature on riparian vegetated buffer strips (VBS) for use in stream-water-quality restoration and limitations associated with their use. Results are also presented of investigations on the effectiveness of a forested and a grass vegetated buffer strip for reducing shallow subsurface inputs of nutrients from agriculture to a stream in central Illinois. Because riparian zones link the stream with its terrestrial catchment, they can modify, incorporate, dilute, or concentrate substances before they enter a lotic system. In small to mid-size streams forested riparian zones can moderate temperatures, reduce sediment inputs, provide important sources of organic matter, and stabilize stream banks. VBS are not as effective in agriculture areas with tile drained fields. Alternative restoration practices such as discharging drain tiles into wetlands constructed parallel to the stream channel may prove to be a more effective means of controlling non-point-source agricultural inputs of nutrients in such areas. -from Authors
While some of the world's most productive agriculture is on artificially drained soils, drainage is increasingly perceived as a major contributor to detrimental off‐site environmental impacts. However, the environmental impacts of artificial or improved agricultural drainage cannot be simply and clearly stated. The mechanisms governing the hydrology and loss of pollutants from artificially drained soils are complex and vary with conditions prior to drainage improvements and other factors: land use, management practices, soils, site conditions, and climate. The purpose of this paper is to present a review of research on the hydrologic and water quality effects of agricultural drainage and to discuss design and management strategies that reduce negative environmental impacts.Although research results are not totally consistent, a great majority of studies indicate that, compared to natural conditions, drainage improvements in combination with a change in land use to agriculture increase peak runoff rates, sediment losses, and nutrient losses. Nevertheless, sediment and nutrient losses from artificially drained croplands are usually small compared to cropland on naturally well‐drained uplands.Increasing drainage intensity on lands already in agricultural production may have positive, as well as negative, impacts on hydrology and water quality. For example, increasing the intensity of subsurface drainage generally reduces loss of phosphorus and organic nitrogen, whereas it increases loss of nitrate‐nitrogen and soluble salts. Conversely, increasing surface drainage intensity tends to increase phosphorus loss and reduce nitrate‐nitrogen outflows.Improved drainage is required on many irrigated, arid lands to prevent the rise of the water table, water logging, and salinity buildup in the soil. Although salt accumulation in receiving waters is the most prevalent problem affecting downstream users, the effect of irrigation and improved drainage on loss of trace elements to the environment has had the greatest impact in the U.S. These detrimental effects often can be avoided by identifying a reliable drainage outlet prior to construction of irrigation projects.Research has shown that management strategies can be used to minimize pollutant loads from drained lands. These strategies range from the water table management practices of controlled drainage and subirrigation, to cultural and structural measures. For example, controlled drainage has been found to reduce nitrate‐nitrogen and phosphorus losses by 45 and 35%, respectively, in North Carolina.It is becoming increasingly clear that drainage and related water management systems must be designed and managed to consider both agricultural and environmental objectives. While significant advances in our knowledge of environmental impacts and methods for managing these systems have improved in the last 20 years, there is much yet to be learned about the complex mechanisms governing losses of pollutants from drained soils.
Predicting plant community responses to changing environmental conditions is a key element of forecasting and mitigating the effects of global change. Disturbance can play an important role in these dynamics, by initiating cycles of secondary succession and generating opportunities for communities of long-lived organisms to reorganize in alternative configurations. This study used landscape-scale variations in environmental conditions, stand structure, and disturbance from an extreme fire year in Alaska to examine how these factors affected successional trajectories in boreal forests dominated by black spruce. Because fire intervals in interior Alaska are typically too short to allow relay succession, the initial cohorts of seedlings that recruit after fire largely determine future canopy composition. Consequently, in a dynamically stable landscape, postfire tree seedling composition should resemble that of the prefire forest stands, with little net change in tree composition after fire. Seedling recruitment data from 90 burned stands indicated that postfire establishment of black spruce was strongly linked to environmental conditions and was highest at sites that were moist and had high densities of prefire spruce. Although deciduous broadleaf trees were absent from most prefire stands, deciduous trees recruited from seed at many sites and were most abundant at sites where the fires burned severely, consuming much of the surface organic layer. Comparison of pre- and postfire tree composition in the burned stands indicated that the expected trajectory of black spruce self-replacement was typical only at moist sites that burned with low fire severity. At severely burned sites, deciduous trees dominated the postfire tree seedling community, suggesting these sites will follow alternative, deciduous-dominated trajectories of succession. Increases in the severity of boreal fires with climate warming may catalyze shifts to an increasingly deciduous-dominated landscape, substantially altering landscape dynamics and ecosystem services in this part of the boreal forest.
Submerged vegetation respond to increased nutrient loading through a shift from slow-growing seagrasses and large macroalgae to fast-growing macroalgae, and the ultimate dominance of phytoplankton at high nutrient loadings. This shift reflects a change from nutrient to light limitation along the eutrophication gradient. Slow-growing seagrasses and large macroalgae are good competitors when nutrients are limiting because they have relatively low nutrient requirements, are able of efficient internal nutrient recycling, and can access the elevated nutrient pools in the sediment. Fast-growing macroalgae and phytoplankton are superior competitors when light is limiting because they are positioned closer to the water surface, and capture and use light more efficiently. The important ecosystem consequences of altered nutrient regimes derive from the shift in dominant vegetation types. Slow-growing seagrasses and large macroalgae are longevous, decompose slowly, and experience only moderate grazing losses, whereas the production of fast growing macroalgae and phytoplankton is transferred faster to heterotrophs, through increased grazing and decomposition rates. Recovery of submerged vegetation following nutrient reduction plans is a very slow process, which involves the replacement of fast-growing for slow-growing plants. Simulation models predict recovery times to oscillate between a few years for macroalgae and fast-growing seagrasses to centuries for slow-growing seagrasses following nutrient reduction plans.
Planners concerned with water resource protection in urbanizing areas must deal with the adverse impacts of polluted runoff. Impervious surface coverage is a quantifiable land-use indicator that correlates closely with these impacts. Once the role and distribution of impervious coverage are understood, a wide range of strategies to reduce impervious surfaces and their impacts on water resources can be applied to community planning, site-level planning and design, and land use regulation. These strategies complement many current trends in planning, zoning, and landscape design that go beyond water pollution concerns to address the quality of life in a community.
Community-based ecosystem monitoring activities in Canada are increasing in response to a number of factors including: (i) the needs of decision-makers for timely information on local environmental changes; (ii) limited use of government monitoring data and information by decision makers: (iii) government cuts to monitoring programs; (iv) the increasingly recognized need to include stakeholders in planning and management processes; and (v) the desire of citizens to contribute to environmental protection. To date there has been no network coordination of community based monitoring in Canada. This paper reports on the establishment of the Canadian Community Monitoring Network by Environment Canada's Ecological Monitoring and Assessment Network Coordinating Office and the Canadian Nature Federation. Information on research prepared in support of network establishment is presented along with a discussion of the potential of the network.
1. Atmospheric conditions strongly influence ecological systems, and tools that simplify the access and processing of atmospheric data can greatly facilitate ecological research.
2. We have developed RNCEP, a package of functions in the open-source R language, to access, organise and visualise freely available atmospheric data from two long-term high-quality data sets with global coverage.
3. These functions retrieve data, via the Internet, for either a desired spatiotemporal extent or interpolated to a point in space and time. The package also contains functions to temporally aggregate data, producing user-defined variables, and to visualise these data on a map.
4. By making access to atmospheric data and integration with biological data easier and more flexible, we hope to facilitate and encourage the exploration of relationships between biological systems and atmospheric conditions.
Dosskey, Michael G., Philippe Vidon, Noel P. Gurwick, Craig J. Allan, Tim P. Duval, and Richard Lowrance, 2010. The Role of Riparian Vegetation in Protecting and Improving Chemical Water Quality in Streams. Journal of the American Water Resources Association (JAWRA) 46(2):261-277. DOI: 10.1111/j.1752-1688.2010.00419.x
Abstract: We review the research literature and summarize the major processes by which riparian vegetation influences chemical water quality in streams, as well as how these processes vary among vegetation types, and discuss how these processes respond to removal and restoration of riparian vegetation and thereby determine the timing and level of response in stream water quality. Our emphasis is on the role that riparian vegetation plays in protecting streams from nonpoint source pollutants and in improving the quality of degraded stream water. Riparian vegetation influences stream water chemistry through diverse processes including direct chemical uptake and indirect influences such as by supply of organic matter to soils and channels, modification of water movement, and stabilization of soil. Some processes are more strongly expressed under certain site conditions, such as denitrification where groundwater is shallow, and by certain kinds of vegetation, such as channel stabilization by large wood and nutrient uptake by faster-growing species. Whether stream chemistry can be managed effectively through deliberate selection and management of vegetation type, however, remains uncertain because few studies have been conducted on broad suites of processes that may include compensating or reinforcing interactions. Scant research has focused directly on the response of stream water chemistry to the loss of riparian vegetation or its restoration. Our analysis suggests that the level and time frame of a response to restoration depends strongly on the degree and time frame of vegetation loss. Legacy effects of past vegetation can continue to influence water quality for many years or decades and control the potential level and timing of water quality improvement after vegetation is restored. Through the collective action of many processes, vegetation exerts substantial influence over the well-documented effect that riparian zones have on stream water quality. However, the degree to which stream water quality can be managed through the management of riparian vegetation remains to be clarified. An understanding of the underlying processes is important for effectively using vegetation condition as an indicator of water quality protection and for accurately gauging prospects for water quality improvement through restoration of permanent vegetation.
Recently there have been major increases in water colour and dissolved organic carbon (DOC) in many forest lakes that serve as drinking water reservoirs in the southern part of Norway. We studied changes in the physical and chemical properties in (I) a selected group of lakes and (II) raw water from the municipal waterworks of Oslo since 1983 and 1976, respectively. The largest increase in DOC and water colour occurred between 1997 and 2001. Statistically significant correlations are seen between water colour and accumulated amounts of precipitation, while variation in temperature had no apparent effect. Despite significant reduction in sulphate concentrations in precipitation and lake waters since 1980, the lakes were more acidic in 2000 and 2001 than in previous years. Increases in colour and acidity, together with somewhat minor changes in DOC concentrations, indicate changes in the physical and chemical properties of the natural organic matter (NOM). Alteration in properties of NOM is most probably caused by increased precipitation that has changed the water pathways in the catchments and increased the leaching of organic components from the upper forest floor.