The mechanics of spatially replicated sampling programmes to detect environmental impacts in a variable world

Abstract Procedures used to detect environmental impacts that occur as a result of planned disturbances are often inadequate. Widely used designs for univariate measures, such as the abundance of a population, lack proper spatial replication and have unjustified patterns of temporal sampling. Asymmetrical analyses of variance derived from repeated measures models can be used to detect many types of impact that are not identifiable using widely recommended BACI (Before/After, Control/Impact) sampling. These asymmetrical, beyond BACI designs are also more logical because of spatial replication. The mechanics of these procedures are discussed, including worked examples of calculations, considerations of their power to detect impacts of a specified magnitude and the integration of various temporal and spatial scales into the design. Related issues are briefly discussed concerning optimization of sampling and how to proceed when no data are available before a disturbance.     

Detecting anthropogenic disturbance in an environment with multiple gradients of physical disturbance,Manukau Harbour,New Zealand

Demonstrating spatial or temporal gradients of effects on macrobenthic communities can be a useful way of providing strong empirical evidence of natural or anthropogenic disturbance. Gradient designs for environmental assessment are sensitive to change for point source data, enabling the scale of the effects of a disturbance to be readily identified. If the spatial scale that is sampled from the point source is adequate, problems of selecting control sites can be avoided. However, sources of spatial variation in macrobenthic communities, which are not related to the impact, can confound the use of gradient designs. This can occur if the natural spatial structure overlaps that of the gradient and cannot be identified either as a location or environmental covariable. The ability to detect point source impacts using a gradient design against natural spatial variability was tested using benthic macrofaunal data collected from Manukau Harbour, New Zealand. Treated sewage wastewater is discharged into the north-west area of the Manukau Harbour. Sandflats in the vicinity of the outfall are also subject to physical disturbance from wind-waves and strong tides. Ordination techniques and the testing of a priori predictions were used to try and separate the relative effects of organic and physical disturbance on the benthic communities. While the occurrence of other environmental disturbances along a gradient of anthropogenic disturbance makes interpretation of community pattern more difficult, the use of a gradient sampling layout, ordination analysis and the testing of a priori predictions enabled impacts of the anthropogenic and natural environmental disturbances to be interpreted. Gradient designs, therefore, provide a method of assessing complex impacts that operate over broad spatial and temporal scales.     

What Users Want and May Need

An increasing number of software tools support designers and other decision makers in making design, production, and purchasing decisions. Some of these tools provide quantitative information on environmental impacts such as climate change, human toxicity, or resource use during the life cycle of these products. Very little is known, however, about how these tools are actually used, what kind of modeling and presentation approaches users really want, or whether the information provided is likely to be used the way the developers intended. A survey of users of one such software tool revealed that although users want more transparency, about half also want an easy-to-use tool and would accept built-in assumptions; that most users prefer modeling of environmental impacts beyond the stressor level, and the largest group of respondents wants results simultaneously on the stressor, impact potential, and damage level; and that although many users look for aggregated information on impacts and costs, a majority do not trust that such an aggregation is valid or believe that there are tradeoffs among impacts. Further, our results show that the temporal and spatial scales of single impact categories explain only about 6% of the variation in the weights between impact categories set by respondents if the weights are set first. If the weights are set after respondents specify temporal and spatial scales, however, these scales explain about 24% of the variation. These results not only help method and tool developers to reconsider some previous assumptions, but also suggest a number of research questions that may need to be addressed in a more focused investigation.     

Patterns of spatial and temporal variation of macrofauna under boulders in a sheltered boulder field

Abstract Spatial and temporal patterns of abundance of animals and plants must be quantified before models to explain distributions can be developed. These patterns also provide essential data for measuring potential effects of environmental disturbances. Studies in many different habitats have shown that most organisms, particularly invertebrates, have highly variable and interactive patterns of abundance, with much variability at the smallest temporal and spatial scales. Intertidal boulder fields in New South Wales, Australia, support a diverse fauna, many species of which are relatively rare. These habitats are commonly found near rock‐platforms and in sheltered estuaries and are subjected to many human disturbances. Although there have been a few studies on the fauna in boulder fields, none has documented variability of the assemblage using multivariate and univariate techniques and most studies have not incorporated different spatial and temporal scales. This study quantifies spatial variation at three scales (metres, tens of metres alongshore and tens of metres upshore) and temporal variation at two scales (3 months and 2 years) of the assemblage of molluscs and echinoderms in a sheltered boulder field subjected to little natural or human disturbance. Multivariate analyses revealed that each site contained a distinct assemblage, mainly due to the relative abundances of a few species. Most species, those generally only found under boulders and common, widespread species, had considerable spatial variability in abundances, with more than 90% measured at the smallest scale, that is metre to metre within a site. Changes in abundances over 3 months or 2 years varied among species and sites in unpredictable ways. These data show that sampling designs to measure impacts on these fauna will need to be complex and must incorporate a number of spatial and temporal scales if they are to be able to detect impact against such a variable background.     

Zooplankton sampling strategies for environmental studies

This study characterizes sources of variation in total zooplankton abundance estimates at seven stations within the 5–10 m depth contour of southeastern Lake Michigan which were sampled monthly, April through October, for the 1975 to 1979 period. Month, year, and station were statistically significant factors affecting abundance estimates as were all interactions. Month was the largest source of variance either as a main effect or interaction. Smallest coefficients of variation were associated with subsampling (mean 6.1%) and replicate sampling (mean 15.1%). The between-station coefficient of variation averaged 39.0% and tended to be highest during the summer. For a given station and month, the between-year coefficient of variation averaged 73.4% while the between-month coefficient of variation for a single station in a given year averaged 95.1%. A table shows the estimated number of replications necessary to detect a true difference in two population means as a function of coefficient of variation. Environmental studies designed to detect spatial alterations should conduct such analyses on a cruise-by-cruise basis. Cruises should consist of a large number of stations and be conducted at least once during each season. Studies designed to detect temporal alterations require more frequent sampling because of the greater variability associated with temporal data sets. Because spatial variability adds little to the overall variability of such data sets, only a few representative stations need be sampled during each cruise.     

Spatial analyses of intertidal assemblages on sheltered rocky shores

Abstract Understanding processes in complex assemblages depends on good understanding of spatial and temporal patterns of structure at various spatial scales. There has been little quantitative information about spatial patterns and natural temporal changes in intertidal assemblages on sheltered rocky shores in temperate Australia. Natural changes and responses to anthropogenic disturbances in these habitats cannot be accurately measured and assessed without quantitative data on patterns of natural variability in space and through time. This paper describes some suitable quantitative methods for examining spatial and temporal patterns of diversity and abundances of highshore, midshore and lowshore intertidal assemblages and the important component species for a number of shores in a bay that has not been severely altered by human disturbance. Despite a diverse flora and fauna on these shores, the midshore and lowshore assemblages on sheltered shores were characterized by a few species which were also the most important in discriminating among assemblages on a shore and, for each assemblage, among different shores. The same set of species was also important for measuring small-scale patchiness within each assemblage (i.e. between replicate sites on a shore). Therefore, these data provide a rationale for selecting species that are useful for measuring differences and changes in abundance among places and times at different scales and, hence, can be used in the more complex sampling designs necessary to detect environmental impacts. There was considerable spatial variability in all assemblages and all species (or taxa) examined at scales of metres, tens of metres and kilometres. There were no clear seasonal trends for most measures, with as much or more variability at intervals of 3 months as from year to year. Most interactions between spatial and temporal measures were at the smallest scale, with different sites on the same shore generally showing different changes from time to time. The cause(s) of this apparently idiosyncratic variability1 were not examined, but some potential causes are discussed. These data are appropriate for testing hypotheses about the applicability of these findings to other relatively undisturbed sheltered shores, about effects of different anthropogenic disturbances on sheltered intertidal assemblages and to test hypotheses about differences in intertidal assemblages on sheltered versus wave-exposed shores.     

Importance of experimental design in detecting and measuring stresses in marine populations

Environmental sampling to detect and measure the sizesof stresses is made extremely difficult by naturalspatial and temporal variations in most possibleecological measurements. Sound application ofprinciples of experimental design is therefore acrucial component of any study. Temporal replicationbefore and after a disturbance is necessary to ensurethat accurate estimates are made of averageconditions. Otherwise, sampling will only reveal whathappens at the particular time sampled. Spatialreplication of reference or control locations isessential to prevent confounding any interpretation ofa difference between a disturbed and a controllocation. Unless locations are replicated, anydifference may be a stress or may be caused by anyother processes causing a difference. If there is nodifference, this does not mean there is no stress. Environmental stresses are manifested as statisticalinteractions due to changes in time being different indisturbed as opposed to control locations (or,equally, spatial differences between the disturbed andcontrol locations being different before and after thedisturbance). Features of experimental design thatallow the most reliable interpretation of suchinteractions should be the focus of planning ofstudies. Here, an ideal design is considered, withdiscussion of what is lost when (as often happens),idealism cannot be maintained. The discussionidentifies that sound planning, good design andadherence to precautionary principles all require thatunambiguous hypotheses are identified in advance ofsampling. In contrast to other approaches to analysisof stress, this approach has an explicit logicalstructure, assists to prevent confounding ininterpretations, identifies the sizes of stress thatwould elicit different responses from decision-makersand allows advance calculation of power to detect theanticipated stress for any chosen size of sampling. As a result, it is clear that more emphasis is neededon advance categorization of the types, directionsand, above all, magnitudes of stress that might matterin any particular case. Explicit statements about thesize of a possible stress will allow better planning,clearer guidance for development of programmes ofsampling and their interpretation and would reduce theuncertainty that categorizes much of environmentalanalysis.     

Variability in patterns of growth and morphology of Posidonia oceanica exposed to urban and industrial wastes: contrasts with two reference locations

Urban and industrial wastes have been claimed to negatively affect Posidonia oceanica meadows, but few studies have addressed this issue by comparing disturbed locations with replicated reference locations. Here, we examined the general proposition that patterns of growth and morphology of P. oceanica exposed to urban and industrial effluents were different from those observed in reference meadows. Hypotheses were both on differences in mean values of response variables and on variation of these measures at a hierarchy of spatial scales (from centimetres to hundreds of metres). Results indicated a significant reduction in mean number of intermediate leaves at the outfall compared to reference locations, whereas the opposite pattern occurred for juvenile leaves. There were significant, though temporally variable differences in growth of rhizomes between disturbed and reference locations, with reduced growth at the outfall in 2 out of 3 years analysed. Measures of spatial variance in number of juvenile leaves and length of adult leaves at the scale of shoots were significantly larger at the outfall compared to reference locations. At the same scale, measures of spatial variance in length of juvenile and intermediate leaves were significantly lower at the putatively impacted location. Spatial variance in number of intermediate leaves was reduced at the outfall compared to reference locations at the scale of quadrats. Past values of spatial variance in number of leaves per shoot were lower at the outfall than at the two reference locations at the scale of shoots, whereas the opposite occurred at the scale of areas. None of the structural variables examined showed any difference between the putatively impacted location and the two reference locations, either in terms of mean response or as changes in spatial variance. These results indicated that integrating methods to examine present and past events of disturbance, including analyses to detect changes in spatial variance of response variables, may provide a powerful approach to the analysis of environmental impacts on P. oceanica.     

Coarse climate change projections for species living in a fine‐scaled world

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change.     

Effects of recent experience on foraging decisions by bumble bees

The temporal and spatial scales employed by foraging bees in sampling their environment and making foraging decisions should depend both on the limits of bumble bee memory and on the spatial and temporal pattern of rewards in the habitat. We analyzed data from previous experiments to determine how recent foraging experience by bumble bees affects their flight distances to subsequent flowers. A single visit to a flower as sufficient to affect the flight distance to the next flower. However, longer sequences of two or three visits had an additional effect on the subsequent flight distance of individual foragers. This suggests that bumble bees can integrate information from at least three flowers for making a subsequent foraging decision. The existence of memory for floral characteristics at least at this scale may have significance for floral selection in natural environments.     

Using Asymmetrical Designs for Environmental Impact Assessment of Unplanned Disturbances

Environmental impact assessment of unplanned disturbances is often difficult to accomplish due to the absence of ‘before’ data for the impacted sites. In an attempt to overcome this problem, a beyond BACI model is used in order to detect possible changes in the temporal patterns of variation when no previous data are available. The model attempted to detect changes in the abundance of macroinvertebrate species inhabiting the intertidal mussel matrix after an oil spill which occurred in northern Portugal. The detection of a significant impact failed, most probably due to low temporal replication. An extension of the analysis, including the hierarchical arrangement of temporal variability in periods, suggests that increasing the number of sampling times may result in a higher efficiency of the model.     

Positive interspecific relationship between temporal occurrence and abundance in insects

One of the most studied macroecological patterns is the interspecific abundance-occupancy relationship, which relates species distribution and abundance across space. Interspecific relationships between temporal distribution and abundance, however, remain largely unexplored. Using data for a natural assemblage of tabanid flies measured daily during spring and summer in Nova Scotia, we found that temporal occurrence (proportion of sampling dates in which a species occurred in an experimental trap) was positively related to temporal mean abundance (number of individuals collected for a species during the study period divided by the total number of sampling dates). Moreover, two models that often describe spatial abundance-occupancy relationships well, the He-Gaston and negative binomial models, explained a high amount of the variation in our temporal data. As for the spatial abundance-occupancy relationship, the (temporal) aggregation parameter, k, emerged as an important component of the hereby named interspecific temporal abundance-occurrence relationship. This may be another case in which a macroecological pattern shows similarities across space and time, and it deserves further research because it may improve our ability to forecast colonization dynamics and biological impacts.     

Overview: Spatial information and indicators for sustainable management of natural resources

Natural resource management (NRM) is becoming increasingly important at all scales, local, regional, national and global, because of an increasing human population and increasing per capita use of resources and space. Conflicts are intensifying between different interest groups. Production and conservation aspects are particularly debated because conservation often conflicts with economic and social sustainability. There is public demand for objective decision based NRM but limitations are all pervasive due to the spatial and temporal complexity and interdisciplinary nature.This special issue explores the use of spatial data and models to overcome some limitations of NRM decision making. The papers in this issue show modern approaches of natural resources management with a particular focus on spatial data collection, analysis and the development of spatial indicators. This issue presents a balanced mix of review and research papers that give examples of how to find or improve the spatial information base for evidence-based decision making.This overview makes the argument that understanding complex spatial pattern and processes, and the development of spatial indicators, is an essential aspect of evidence-based NRM. If spatial and temporal patterns are complex, ecological evidence from field data or experiments may have limited value for NRM and observational study designs become more appropriate for understanding complex spatial pattern and processes. Data quality should be documented as a combination of accuracy and spatio-temporal representativeness in order to be useful in the NRM decision process.     

A practical protocol to assess impacts of unplanned disturbance: a case study in Tuggerah Lakes Estuary,NSW

Summary Environmental managers are often confronted with unplanned or accidental disturbances that may lead to environmental impacts. Procedures for detecting or measuring the size of such impacts are complicated because of the lack of data available before the disturbance and because of the intrinsic variability of most natural measures. Here, a protocol for detecting impacts is illustrated for single‐measure variables (numbers of individual species) and multivariate measures (relative abundances of invertebrates in assemblages). The present paper describes a case concerning drainage of acidified water into an estuary due to construction of a drainage channel in an area of wetland for which there had been no prior investigations (i.e. no ‘before’ data). The spatial extent of any impact was also unknowable. Sampling was, therefore, designed to allow for impacts of only a few tens of metres (using control sites 50 m from the mouth of the channel) and impacts covering much larger areas (500 m and 1 km from the mouth of the channel). Invertebrates in the mud around the channel and in control sites were sampled in replicated cores and the amount of seagrass in each core was weighed. Average abundances of invertebrate animals and weights of seagrass were compared, as was variation among samples in potentially impacted and control sites (using univariate analyses of variance). Sets of species were compared using multivariate methods to test the hypothesis that there was an impact at one of the scales examined. In fact, there was no evidence for any sort of impact on the fauna or seagrasses; the disturbance was a short‐term pulse without any obvious or sustained ecological response. One consequence of the study was that the local council was able to demonstrate no impact requiring remediation and no penalties were imposed for the unapproved construction of the channel. The implications of this type of study after an environmental disturbance are discussed. The present study identifies the need for clear definition of relevant hypotheses, coupled with rigorous planning of sampling and analyses, so that reliable answers are available to regulators and managers.     

Demographic and genetic estimates of effective population size (Ne) reveals genetic compensation in steelhead trout

Estimates of effective population size (Ne) are required to predict the impacts of genetic drift and inbreeding on the evolutionary dynamics of populations. How the ratio of Ne to the number of sexually mature adults (N) varies in natural vertebrate populations has not been addressed. We examined the sensitivity of Ne/N to fluctuations of N and determined the major variables responsible for changing the ratio over a period of 17 years in a population of steelhead trout (Oncorhynchus mykiss) from Washington State. Demographic and genetic methods were used to estimate Ne. Genetic estimates of Ne were gained via temporal and linkage disequilibrium methods using data from eight microsatellite loci. DNA for genetic analysis was amplified from archived smolt scales. The Ne/N from 1977 to 1994, estimated using the temporal method, was 0.73 and the comprehensive demographic estimate of Ne/N over the same time period was 0.53. Demographic estimates of Ne indicated that variance in reproductive success had the most substantial impact on reducing Ne in this population, followed by fluctuations in population size. We found increased Ne/N ratios at low N, which we identified as genetic compensation. Combining the information from the demographic and genetic methods of estimating Ne allowed us to determine that a reduction in variance in reproductive success must be responsible for this compensation effect. Understanding genetic compensation in natural populations will be valuable for predicting the effects of changes in N (i.e. periods of high population density and bottlenecks) on the fitness and genetic variation of natural populations.     

Assessing the ecological health status using macrobenthic communities of tropical coastal water

The relative contributions of natural and anthropogenic fluctuations are different in shaping habitat health status and natural benthic communities in tropical coastal water. Understanding responses of coastal benthic communities to these fluctuations are still equivocal and thus available data are inadequate. Here, multiple analytical approaches were used to address the significant risk factors and their impacts on coastal benthic habitat health through space and time. A total abundance of 1436 ± 612 individuals of 33 benthic species were counted and identified from 22 sampling stations across eight sampling periods over the two years of study. Bioassay results showed that the benthic community is moderately exposed to anthropogenic pollutants in Klang Strait coastal water. The results showed that there were no significant temporal changes of habitat health status and macrobenthic community structure; however, spatial changes were significant and synchronized with anthropogenic and natural fluctuations. This study demonstrates that Cd and Hg levels and sediment characteristics played the primary role in shaping the habitat health and macrobenthic assemblages, whereas the influence of other factors were insignificant.     

Spatial and temporal homogenisation of freshwater macrofaunal communities in ditches

相似文献   

A Three-Tiered Approach to Long Term Monitoring Program Optimization

Long term monitoring optimization (LTMO) has proved a valuable method for reducing costs, assuring proper remedial decisions are made, and streamlining data collection and management requirements over the life of a monitoring program. A three-tiered approach for LTMO has been developed that combines a qualitative evaluation with an evaluation of temporal trends in contaminant concentrations, and a spatial statistical analysis. The results of the three evaluations are combined to determine the degree to which a monitoring program addresses the monitoring program objectives, and a decision algorithm is applied to assess the optimal frequency of monitoring and spatial distribution of the components of the monitoring network. Ultimately, application of the three-tiered method can be used to identify potential modifications in sampling locations and sampling frequency that will optimally meet monitoring objectives. To date, the three-tiered approach has been applied to monitoring programs at 18 sites and has been used to identify a potential average reduction of over one-third of well sampling events per year. This paper discusses the three-tiered approach methodology, including data compilation and site screening, qualitative evaluation decision logic, temporal trend evaluation, and spatial statistical analysis, illustrated using the results of a case study site. Additionally, results of multiple applications of the three-tiered LTMO approach are summarized, and future work is discussed.     

A Three-Tiered Approach to Long Term Monitoring Program Optimization

Long term monitoring optimization (LTMO) has proved a valuable method for reducing costs, assuring proper remedial decisions are made, and streamlining data collection and management requirements over the life of a monitoring program. A three-tiered approach for LTMO has been developed that combines a qualitative evaluation with an evaluation of temporal trends in contaminant concentrations, and a spatial statistical analysis. The results of the three evaluations are combined to determine the degree to which a monitoring program addresses the monitoring program objectives, and a decision algorithm is applied to assess the optimal frequency of monitoring and spatial distribution of the components of the monitoring network. Ultimately, application of the three-tiered method can be used to identify potential modifications in sampling locations and sampling frequency that will optimally meet monitoring objectives. To date, the three-tiered approach has been applied to monitoring programs at 18 sites and has been used to identify a potential average reduction of over one-third of well sampling events per year. This paper discusses the three-tiered approach methodology, including data compilation and site screening, qualitative evaluation decision logic, temporal trend evaluation, and spatial statistical analysis, illustrated using the results of a case study site. Additionally, results of multiple applications of the three-tiered LTMO approach are summarized, and future work is discussed.     

Inconsistency in short-term temporal variability of microgastropods within and between two different intertidal habitats

Small-scale temporal variation in abundances of fauna in marine soft sediments has long been recognised. Many studies on rocky intertidal shores have, however, focused on larger fauna in single habitats and have primarily examined relatively long time-scales. The implications of small-scale variability are frequently not adequately addressed in the studies of changes in fauna over longer time-scales. Without knowledge of the magnitude of variation at smaller scales, comparisons across longer time-scales may be confounded. In this study, the temporal variability of a number of co-existing species of microgastropods in patches of two different intertidal habitats (coralline turf and sediment) in Botany Bay, New South Wales, Australia, was measured using a nested, hierarchical sampling design incorporating temporal scales of weeks, 1 and 3 months. In addition to habitats, there were also spatial scales of metres between plots and 100s of metres between the locations. There was generally a lack of consistency in the trends of variance for the three temporal scales at the smallest spatial scale of plots. In addition, the different species, including those that were closely related, showed different patterns of variation, depending on the habitat and site. These data show the importance of incorporating adequate scales of sampling in different habitats when analysing the distribution and abundance of microbenthos in intertidal habitats.