Quantifying sample biases of inland lake sampling programs in relation to lake surface area and land use/cover

We quantified potential biases associated with lakes monitored using non-probability based sampling by six state agencies in the USA (Michigan, Wisconsin, Iowa, Ohio, Maine, and New Hampshire). To identify biases, we compared state-monitored lakes to a census population of lakes derived from the National Hydrography Dataset. We then estimated the probability of lakes being sampled using generalized linear mixed models. Our two research questions were: (1) are there systematic differences in lake area and land use/land cover (LULC) surrounding lakes monitored by state agencies when compared to the entire population of lakes? and (2) after controlling for the effects of lake size, does the probability of sampling vary depending on the surrounding LULC features? We examined the biases associated with surrounding LULC because of the established links between LULC and lake water quality. For all states, we found that larger lakes had a higher probability of being sampled compared to smaller lakes. Significant interactions between lake size and LULC prohibit us from drawing conclusions about the main effects of LULC; however, in general lakes that are most likely to be sampled have either high urban use, high agricultural use, high forest cover, or low wetland cover. Our analyses support the assertion that data derived from non-probability-based surveys must be used with caution when attempting to make generalizations to the entire population of interest, and that probability-based surveys are needed to ensure unbiased, accurate estimates of lake status and trends at regional to national scales.     

On the estimation of phosphorus from the Niagara River to Lake Ontario

A predictive or model based approach to making inferences about the loading of a contaminant from a point source is presented and illustrated by estimating the total phosphorus, TP, loading from the Niagara River to Lake Ontario for the years 1967 to 1982. Information about explanatory variables and/or autodependence among successive observations can be easily included in the model and this allows more accurate inferences to be made. The results of the application to the Niagara River show a major decrease in TP loadings has occurred during the study period.     

Use of Scale Invariance in Evaluating Judgement Indicators

Indicators are used to draw conclusions about ecological endpoints when these endpoints cannot be measured directly. In many cases, inferences about an endpoint are only possible because assumptions have been made about the relationship between indicator and endpoint; we refer to such indicators as judgement indicators. The validity of inferences made using a judgement indicator can be gauged by examining the known or assumed form of the general relationship between indicator and endpoint. The rules for this kind of inference are a consequence of scale invariance, which originates from measurement theory. For simple indicators comprised of a single indicator measurement, the inferences allowed – equivalence, rank, equality of intervals, and equality of ratios – depend on whether the data are nominal, ordinal, interval, or ratio scaled. For composite indicators containing two or more simple indicators, inferences are also affected by the mathematical form of combination; e.g., whether the terms are summed or multiplied. Standardizing simple or composite indicators can allow inferences about the relative importance of observations, based on the natural range of occurrence. Scale invariance is a particularly important consideration in landscape assessments, since these often make use of judgement indicators.     

基于O/E模型的浅水湖泊生态系统健康评价

以长江中下游阻隔型浅水湖泊为研究对象,分析了1998—2018年116湖次底栖动物野外调查数据,构建了基于预测模型的观测物种组成/期望物种组成(O/E)指数健康评价指标体系,评价了长江中下游浅水湖泊的底栖动物物种组成完整性.O/E指数模型评价结果显示,在物种采集概率(Pc)>0阈值条件下的O/E0模型预测得到的监测湖泊...     

Monitoring compared with paleolimnology: implications for the definition of reference condition in limed lakes in Sweden

Surface water acidification was identified as a major environmental problem in the 1960s. Consequently, a liming program was launched in Sweden in the 1970s. The primary purpose of liming is to restore conditions that existed prior to acidification. To reach this goal, as well as achieve 'good status' (i.e. low levels of distortion resulting from human activity) in European freshwaters until 2016 under the European Union Water Framework Directive, lake data are required to define reference conditions. Here, we compare data from chemical/biological monitoring of 12 limed lakes with results of paleolimnological investigations, to address questions of reference conditions, acidification, and restoration by liming. Using diatom-based lake-water pH inferences, we found clear evidence of acidification in only five of the 12 lakes, which had all originally been classified as acidified according to monitoring data. After liming, measured and diatom-inferred pH agree well in seven lakes. The sediment record of three of the five remaining lakes gave ambiguous results, presumably due to sediment mixing or low sediment accumulation rates. It is difficult to determine whether liming restored the lakes to a good status, especially as some of the lakes were not acidified during the twentieth century. In addition to acid deposition, other factors, such as natural lake and catchment ontogeny or human impact through agricultural activity, influence lake acidity. This study shows that monitoring series are usually too short to define reference conditions for lakes, and that paleolimnological studies are useful to set appropriate goals for restoration and for evaluation of counter measures.     

Identification of degradation characteristics – exemplified by Gd–DTPA in a large experimental column

Surface water from rivers or lakes, infiltrating through porous media, is increasingly used as a source of public water supply. During bank filtration the water chemistry is substantially changed by various processes such as biodegradation, sorption and mixing with ambient groundwater, but the details of this natural attenuation are not yet entirely understood. In order to gain a better understanding, the degradation of an organic substance (DTPA) is examined here using various model approaches for steady state conditions. Models are fitted on data from an experimental study under near-field conditions. The results show advantages and disadvantages of the different model approaches and provide a guideline for the modelling of other organic substances under different but similar conditions.     

Joint application of an empirical and mechanistic model for regional lake acidification

The empirical direct distribution model for lake acidification is calibrated for use in an integrated assessment model which predicts the regional impact of an acid deposition control strategy. The calibration is based on the mechanistic Model of Acidification of Groundwater in Catchments (MAGIC). The models are applied jointly to a set of 33 statistically-selected lakes in the Adirondack region of New York. Calibration of the direct distribution model is based on a step-function application of acid deposition to MAGIC. Comparative evaluations of the resulting model predictions are made using historic deposition estimates and two alternative future deposition scenarios. The predictions of the direct distribution model match well the shapes and patterns of change of the regional distributions of ANC and pH predicted by MAGIC, the short- and medium-term dynamics of these changes, and the effect of including organic acids. However, small, long-term decreases in the fraction of incoming acid deposition neutralized by lakes and their watersheds predicted by MAGIC are not reproduced.     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取;提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列;发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性;构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测;在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

Modeling the Effect of Liming on Calcium Concentration in Swedish Lakes

To abate the severe acidification of Swedish lakes are about 7% directly limed (AL-lakes). These are important to include when assessing acidification. Consequently, we need to estimate their chemical status as if they were not lime-affected. We hypothesize that there is a spatial dependence for calcium (Ca) and magnesium (Mg) concentrations. Spatial variation is determined using variograms. We study lakes within two 150 ∗ 150 km quadrates (EMEP150-grid) in the middle and southern parts of Sweden. We model Ca in AL-lakes using the Ca and Mg concentrations in nearby, unaffected lakes (UL-lakes). The mean Ca/Mg for the three or seven closest UL-lakes is used. We assume that Ca/Mg is constant for UL-lakes and that Mg unaltered by liming. For UL-lakes, Ca and Mg are spatially dependent. For AL-lakes, there is a spatial dependence for Mg, but, as anticipated, not for Ca. The modeled Ca for UL-lakes show a good correspondence with measured Ca; r ² > 0.6; slopes close to 1 and intercepts almost 0. Using three or seven nearby lakes when modeling Ca give similar results. Modeled Ca was higher than measured Ca for 36% (three closest lakes) and 38% (seven closest) of the modeled AL-lakes in the middle part of Sweden. The corresponding results for the southern part were 10% and 9%, respectively. This model is an acceptable estimator of Ca in limed lakes and for estimating critical loads and acidification status on an EMEP-scale.     

A national probabilistic study of polybrominated diphenyl ethers in fish from US lakes and reservoirs

Polybrominated diphenyl ethers (PBDEs) are persistent, bioaccumulative, and toxic chemicals that are present in air, water, soil, sediment, and biota (including fish). Most previous studies of PBDEs in fish were spatially focused on targeted waterbodies. National estimates were developed for PBDEs in fish from lakes and reservoirs of the conterminous US (excluding the Laurentian Great Lakes) using an unequal probability design. Predator (fillet) and bottom-dweller (whole-body) composites were collected during 2003 from 166 lakes selected randomly from the target population of 147,343 lakes. Both composite types comprised nationally representative samples that were extrapolated to the sampled population of 76,559 and 46,190 lakes for predators and bottom dwellers, respectively. Fish were analyzed for 34 individual PBDE congeners and six co-eluting congener pairs representing a total of 46 PBDEs. All samples contained detectable levels of PBDEs, and BDE-47 predominated. The maximum aggregated sums of congeners ranged from 38.3 ng/g (predators) to 125 ng/g (bottom dwellers). Maximum concentrations in fish from this national probabilistic study exceeded those reported from recent targeted studies of US inland lakes, but were lower than those from Great Lakes studies. The probabilistic design allowed the development of cumulative distribution functions to quantify PBDE concentrations versus the cumulative number of US lakes from the sampled population.     

Contaminants in fish tissue from US lakes and reservoirs: a national probabilistic study

An unequal probability design was used to develop national estimates for 268 persistent, bioaccumulative, and toxic chemicals in fish tissue from lakes and reservoirs of the conterminous United States (excluding the Laurentian Great Lakes and Great Salt Lake). Predator (fillet) and bottom-dweller (whole body) composites were collected from 500 lakes selected randomly from the target population of 147,343 lakes in the lower 48 states. Each of these composite types comprised nationally representative samples whose results were extrapolated to the sampled population of an estimated 76,559 lakes for predators and 46,190 lakes for bottom dwellers. Mercury and PCBs were detected in all fish samples. Dioxins and furans were detected in 81% and 99% of predator and bottom-dweller samples, respectively. Cumulative frequency distributions showed that mercury concentrations exceeded the EPA 300 ppb mercury fish tissue criterion at nearly half of the lakes in the sampled population. Total PCB concentrations exceeded a 12 ppb human health risk-based consumption limit at nearly 17% of lakes, and dioxins and furans exceeded a 0.15 ppt (toxic equivalent or TEQ) risk-based threshold at nearly 8% of lakes in the sampled population. In contrast, 43 target chemicals were not detected in any samples. No detections were reported for nine organophosphate pesticides, one PCB congener, 16 polycyclic aromatic hydrocarbons, or 17 other semivolatile organic chemicals.     

Addressing statistical and operational challenges in designing large-scale stream condition surveys

Implementing a statistically valid and practical monitoring design for large-scale stream condition monitoring and assessment programs can be difficult due to factors including the likely existence of a diversity of ecosystem types such as ephemeral streams over the sampling domain; limited resources to undertake detailed monitoring surveys and address knowledge gaps; and operational constraints on effective sampling at monitoring sites. In statistical speak, these issues translate to defining appropriate target populations and sampling units; designing appropriate spatial and temporal sample site selection methods; selection and use of appropriate indicators; and setting effect sizes with limited ecological and statistical information about the indicators of interest. We identify the statistical and operational challenges in designing large-scale stream condition surveys and discuss general approaches for addressing them. The ultimate aim in drawing attention to these challenges is to ensure operational practicality in carrying out future monitoring programs and that the resulting inferences about stream condition are statistically valid and relevant.     

The role of sample surveys for monitoring the condition of the nation's lakes

In order to meet a growing need to determine the condition of the nation's ecosystems and how their condition is changing, the U.S. Environmental Protection Agency (EPA) developed EMAP, the Environmental Monitoring and Assessment Program. A common survey design serves as the foundation on which to base monitoring of status and trends among diverse ecosystem types. In this paper, we describe the need for a statistically based survey design, briefly summarize the basic EMAP design, describe how that design is tailored for the selection of a probability sample of lakes on which to make measurements of lake condition, and illustrate the process for selecting a sample of lakes in the northeastern United States. Finally, we illustrate how measurements taken on the sample of lakes can be summarized, with known uncertainty, to describe the condition of a population of lakes.The U.S. Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

Survey design for lakes and reservoirs in the United States to assess contaminants in fish tissue

The National Lake Fish Tissue Study (NLFTS) was the first survey of fish contamination in lakes and reservoirs in the 48 conterminous states based on a probability survey design. This study included the largest set (268) of persistent, bioaccumulative, and toxic (PBT) chemicals ever studied in predator and bottom-dwelling fish species. The U.S. Environmental Protection Agency (USEPA) implemented the study in cooperation with states, tribal nations, and other federal agencies, with field collection occurring at 500 lakes and reservoirs over a four-year period (2000–2003). The sampled lakes and reservoirs were selected using a spatially balanced unequal probability survey design from 270,761 lake objects in USEPA’s River Reach File Version 3 (RF3). The survey design selected 900 lake objects, with a reserve sample of 900, equally distributed across six lake area categories. A total of 1,001 lake objects were evaluated to identify 500 lake objects that met the study’s definition of a lake and could be accessed for sampling. Based on the 1,001 evaluated lakes, it was estimated that a target population of 147,343 (±7% with 95% confidence) lakes and reservoirs met the NLFTS definition of a lake. Of the estimated 147,343 target lakes, 47% were estimated not to be sampleable either due to landowner access denial (35%) or due to physical barriers (12%). It was estimated that a sampled population of 78,664 (±12% with 95% confidence) lakes met the NLFTS lake definition, had either predator or bottom-dwelling fish present, and could be sampled.     

Agricultural Lakes in Finland: Current Water Quality and Trends

Agriculture is the largest source of nutrients into surface waters in Finland, and yet relatively little is known about the actual impact of the agricultural load on the state of lakes. We analysed the water quality data of 20 Finnish agricultural lakes and found that they had higher levels of nutrients, chlorophyll a and turbidity than did the other types of lakes (e.g. those receiving point-source load) in the national monitoring network (the Finnish Eurowaternet). Currently, six of the agricultural lakes can be classified as eutrophic and 14 as hypertrophic. Trend analysis (based on Kendall's tau-b) indicated that during 1976–2002 the water quality of the lakes either remained constant or showed signs of increasing eutrophication and elevated turbidity. Decreasing nutrient concentrations were found only in one intensively restored lake. In none of the lakes had the chlorophyll a concentration decreased. The results of the trend analysis are compatible with the recent finding that, despite vigorous efforts, the nutrient load from agriculture has not declined in Finland. Recovery of the most eutrophied agricultural lakes would call for a drastic reduction in the external nutrient load, possibly supplemented with in-lake restoration.     

Estimating Trophic State Proportions of a Regional Lake Population: Are Larger Samples Always Better?

During the summers of 1991–1994, the Environmental Monitoringand Assessment Program (EMAP) sampled 344 lakes throughout thenortheastern United States using a proportional stratified sampling design based on lake size. Approximately one-quarter ofthe 344 lakes were sampled each year (4 years) for totalphosphorus to determine the proportion (and associated95% confidence intervals) of the northeast lake population 1ha (11,076 ± 1,699 lakes) that was in oligotrophic,mesotrophic, eutrophic, or heupereutropic (4 classes) conditionaccording to the total phosphorus criteria of the North AmericaLake Manegement Society. Estimates for the second, third, andfourth yr were developed as cumulative of the previous yrsamples and the current yr samples for the northeast as a wholeand for each of its three ecoregions (4 regions). New confidence intervals were computed for each cumulative yrcondition estimate. This produced a total (4 years × 4classes × 4 regions) of 64 cumulative yr tropic conditionestimates. Confidence intervals for 21% of these estimates didnot shorten with increased sample size. This phenomena raisedquestions about the accuracy of estimates based on cumulativesampling procedures. We explain why and how the phenomenon comesabout with both straight random and proportional randomsampling. Further, we present an example of the effects thisphenomenon has on lake tropic state condition estimates in thenortheastern United States.     

Zooplankton and its grazing as indicators of trophic status in Dutch lakes

The existing data on the species composition of zooplankton and grazing intensities of crustacean plankton are discussed in the light of trophic status, particularly in the Dutch lakes of varying trophy. Several species of rotifers in northern Europe and North America are considered to indicate eutrophic environments. However, unanimity is less regarding crustacean zooplankton, since several species are encountered in lakes varying widely in trophic degree. The zooplankton to seston (33 μm) biomass ratio may provide information about the ecological transfer efficiency and trophic status. In the Dutch lakes the ratio decreases sharply with increase in food concentration during eutrophication, namely from ca 0.4 in oligotrophic lakes to about 0.05 in the hypertrophic ones. The zooplankton community grazing is high and variable in lakes of low trophy but low and relatively constant in lakes of high trophy. The fluctuations in the filtering rates of Daphnia sp. (e.g. D. magna) may provide information both on trophic degree as well as dissolved substances in lake waters. The dominance of small cladocerans in lakes may be due to quality of food and trophic level, besides fish predation. The recurrent clear-water phase in lakes would indicate oligo-mesotrophic situations in which the zooplankton plays an important role in the phytoplankton wax and wane.     

Eutrophication Prediction Using a Markov Chain Model: Application to Lakes in the Yangtze River Basin,China

Lake eutrophication is harmful and difficult to predict due to its complex evolution. As an alternative to existing mechanistic models, a Markov chain model was developed to predict the development of lake eutrophication based on an 11-year dataset in 41 lakes of the Yangtze River Basin. This model was validated using a real-time update strategy and was demonstrated to be reliable. Based on the dataset, the lake eutrophication dynamics from 2000 to 2010 were analyzed. Lakes with different trophic states from 2011 to 2050 and their responses to different water management practices were simulated based on the developed model. The simulation results show that lake eutrophication would worsen from 2011 to 2040; however, eutrophication could be significantly alleviated by changing 100 km² of hypereutrophic lakes into eutrophic lakes per year from 2010 to 2020. The nutrient conditions in most of the lakes in the Yangtze River Basin show that phosphorus control would be more efficient than nitrogen control in eutrophication management practices. This case study demonstrates the utility of Markov chain models in using prior information to predict the long-term evolution of lake eutrophication at large spatial scales. The Markov chain technique can be easily adapted to predict evolutionary processes in other disciplines.     

New insight into defining the lakes of the southern Baltic coastal zone

There exist many classification systems of hydrographic entities such as lakes found along the coastlines of seas and oceans. Each system has its advantages and can be used with some success in the area of protection and management. This paper aims to evaluate whether the studied lakes are only coastal lakes or rather bodies of water of a completely different hydrological and hydrochemical nature. The attempt to create a new classification system of Polish coastal lakes is related to the incompleteness of lake information in existing classifications. Thus far, the most frequently used are classifications based solely on lake basin morphogenesis or hydrochemical properties. The classifications in this paper are based not only on the magnitude of lake water salinity or hydrochemical analysis but also on isolation from the Baltic Sea and other sources of water. The key element of the new classification system for coastal bodies of water is a departure from the existing system used to classify lakes in Poland and the introduction of ion-“tracking” methods designed to identify anion and cation distributions in each body of water of interest. As a result of the work, a new classification of lakes of the southern Baltic Sea coastal zone was created. Featured objects such as permanently brackish lakes, brackish lakes that may turn into freshwater lakes from time to time, freshwater lakes that may turn into brackish lakes from time to time, freshwater lakes that experience low levels of salinity due to specific incidents, and permanently freshwater lakes. The authors have adopted 200 mg Cl^? dm^?3 as a maximum value of lake water salinity. There are many conditions that determine the membership of a lake to a particular group, but the most important is the isolation lakes from the Baltic Sea. Changing a condition may change the classification of a lake.     

Losses of biota from American aquatic communities due to acid rain

Models based on chemical survey data and geochemical assumptions were calibrated for areas where rates of acidification are known, then used to predict the declines in alkalinity and pH of lakes in the eastern and midwestern U.S.A. These results were combined with known acid tolerances of different taxonomic groups to estimate the extent of damage caused by acid rain to biological assemblages.An average of over 50% of the species in some taxonomic groups have probably been eliminated from lakes in the Adirondacks, Poconos-Catskills and southern New England. Moderate damage to biotic communities was predicted for lakes in central New England, and north-central Wisconsin. Damage predicted in Maine, upper Michigan, northeastern Minnesota and the remainder of the upper Great Lakes region was slight. Crustaceans, molluscs, leeches and insects were among the most severely affected groups. Among fishes, species of minnows (Cyprindae) were depleted in the most heavily acidified regions, with some declines in salmonid and centrarchid species.Predicted damage to individual lakes in all areas was highly variable. In areas receiving highly acidic deposition, 100% of the species in acid-sensitive taxonomic groups were eliminated in some lakes, while damage to other lakes was predicted to be slight.Estimated damage varied from lake to lake within each subregion, based on chemical characteristics. The most heavily damaged lakes in the Adirondacks and Pocono-Catskills have probably lost all species of molluscs, leeches and crustaceans. On the other hand, lakes of the Midwest showed either slight increases or decreases in the richness of predicted biotic communities.The possible ranges of original sulfate concentrations in lakes and the proportion of sulfuric acid in precipitation that liberated base cations from catchments were confined to relatively narrow limits by the model.Contribution from Fourth World Wilderness Congress-Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.