Levels Of Sampling Effort Research Articles

Hybrid experimental designs for joint estimation of absolute and relative retention curves for trawl gears

Abstract Methods for jointly estimating both the size-specific relative retention and absolute retention (retention probability) of two experimental trawl gears are considered. One approach would be to undertake comparative fishing of both gears, from which their comparative catchability can be estimated directly. If comparative catchability can be corrected for differing sampling effort and fishing efficiency of the two gears, then relative retention can be estimated. Furthermore, if a suitable functional form of the absolute retention curve is assumed, then estimates of absolute retention can potentially be obtained. However, these estimated retention curves are seen to have extremely large statistical variability and will not be useful in practice. On the other hand, if the gears are each fished with a non-selective control, then absolute retention can be directly estimated, from which estimates of relative retention can immediately be obtained. However, these estimates of relative retention have greater variability than would be obtained by comparative fishing with the same level of sampling effort. It is shown that a hybrid selectivity design that includes both comparative fishing of the experimental trawls and fishing with a non-selective control provides a more balanced approach. An extensive simulation study is conducted using scenarios based on recently published work on selectivity experiments targeting cod (Gadus Morhua) and hoki/blue grenadier (Macruronus novaezelandiae).

Multisite species‐level roadkill across years reveals challenges and opportunities for monitoring and mitigation

AbstractUnderstanding spatiotemporal patterns of roadkill is challenging but essential for mitigation. Spatiotemporal roadkill patterns are seldom studied for single species at broad scales. We evaluated the spatiotemporal variation of roadkill of the water snake Helicops infrataeniatus (Squamata, Dipsadidae) in three Brazilian roads stretching 540 km and spanning up to 6 years of monitoring. We modelled the effect of sampling effort, evaluation scale and sample size on hotspot location over the years and evaluated hotspot persistence between roads at different evaluation scales. We also assessed the annual variability of roadkill hot moments within roads and tested if fatality was synchronous between roads. We correlated hotspots obtained with different evaluation scales and levels of sampling effort with those in a reference dataset built with fatality events from all sampling years. Coarser evaluation scales had a positive effect on correlation values, but the interaction between evaluation scale and sampling effort and the main effect of the latter differed between roads. Hotspot persistence over the years differed with road identity and increased with evaluation scales. Hot moments changed annually within roads and were concentrated in the warmest seasons of the year. Despite the ephemerality of hotspots within roads, fatality was synchronous between roads. Spatiotemporal variation of roadkills may reflect environmental, behavioural or populational changes at multiple scales. We suggest that both permanent and temporal mitigation strategies may be used according to spatiotemporal characteristics of hotspots. Our study exemplifies how synchrony studies can provide clues to understand roadkill patterns and improve mitigation planning at regional scales.

Quantifying the Statistical Power of Monitoring Programs for Marine Protected Areas

Marine Protected Areas (MPAs) are increasingly established globally as a spatial management tool to aid in conservation and fisheries management objectives. Assessing whether MPAs are having the desired effects on populations requires effective monitoring programs. A cornerstone of an effective monitoring program is an assessment of the statistical power of sampling designs to detect changes when they occur. We present a novel approach to power assessment that combines spatial point process models, integral projection models (IPMs) and sampling simulations to assess the power of different sample designs across a network of MPAs. We focus on the use of remotely operated vehicle (ROV) video cameras as the sampling method, though the results could be extended to other sampling methods. We use empirical data from baseline surveys of an example indicator fish species across three MPAs in California, USA as a case study. Spatial models simulated time series of spatial distributions across sites that accounted for the effects of environmental covariates, while IPMs simulated expected trends over time in abundances and sizes of fish. We tested the power of different levels of sampling effort (i.e., the number of 500-m ROV transects) and temporal replication (every 1-3 yr) to detect expected post-MPA changes in fish abundance and biomass. We found that changes in biomass are detectable earlier than changes in abundance. We also found that detectability of MPA effects was higher in sites with higher initial densities. Increasing the sampling effort had a greater effect than increasing sampling frequency on the time taken to achieve high power. High power was best achieved by combining data from multiple sites. Our approach provides a powerful tool to explore the interaction between sampling effort, spatial distributions, population dynamics, and metrics for detecting change in previously fished populations.

Quantifying the statistical power of monitoring programs for marine protected areas

Marine Protected Areas (MPAs) are increasingly established globally as a spatial management tool to aid in conservation and fisheries management objectives. Assessing whether MPAs are having the desired effects on populations requires effective monitoring programs. A cornerstone of an effective monitoring program is an assessment of the statistical power of sampling designs to detect changes when they occur. We present a novel approach to power assessment that combines spatial point process models, integral projection models (IPMs) and sampling simulations to assess the power of different sample designs across a network of MPAs. We focus on the use of remotely operated vehicle (ROV) video cameras as the sampling method, though the results could be extended to other sampling methods. We use empirical data from baseline surveys of an example indicator fish species across three MPAs in California, USA as a case study. Spatial models simulated time series of spatial distributions across sites that accounted for the effects of environmental covariates, while IPMs simulated expected trends over time in abundances and sizes of fish. We tested the power of different levels of sampling effort (i.e., the number of 500-m ROV transects) and temporal replication (every 1-3yr) to detect expected post-MPA changes in fish abundance and biomass. We found that changes in biomass are detectable earlier than changes in abundance. We also found that detectability of MPA effects was higher in sites with higher initial densities. Increasing the sampling effort had a greater effect than increasing sampling frequency on the time taken to achieve high power. High power was best achieved by combining data from multiple sites. Our approach provides a powerful tool to explore the interaction between sampling effort, spatial distributions, population dynamics, and metrics for detecting change in previously fished populations.

Heterogeneity in macroinvertebrate sampling strategy introduces variability in community characterization and stream trait-based biomonitoring: Influence of sampling effort and habitat selection criteria

Benthic macroinvertebrate assemblages have been of major importance in the biomonitoring of rivers for many decades. To more closely fit with new regulatory purposes, standardized methods of macroinvertebrate field sampling have changed over time both in terms of sampling effort and criteria of habitat type sampling priority (e.g. according to a decreasing gradient of “bottom surface coverage” versus “substratum favorability”). Such methodological heterogeneity has rendered the exploitation of biomonitoring data far more complex because they are indeed not fully comparable over time and may induce bias in long term series studies. In this context, we assessed the influence of variation in field sampling strategy on (i) the taxonomical characterization of benthic macroinvertebrate assemblages (297 taxon abundances, taxonomic richness and diversity, EPT-related metrics), (ii) the response of sensitivity descriptors (ASPT, SPEAR), (iii) the bio-ecological trait description of assemblages and (iv) the resulting ecological diagnostic of river reaches, based on 10,074 sampling events across France. Six sampling strategies were compared, corresponding to three levels of sampling effort (4, 8 and 12 individual samples) and different criteria for substratum selection; e.g. marginal (=<5% coverage at reach scale) vs. dominant; hosting capacity (=substratum favorability) vs. bottom coverage. A strong influence of the sampling strategy was observed on the characterization of the macroinvertebrate assemblages. Marginal substrata revealed a unique picture of the community at the reach scale and presented a higher taxonomic diversity and richness than dominant ones, as well as a higher number of sensitive EPT and SPEAR taxa. Both strategies based on dominant substratum sampling provided similar pictures of the taxonomical and bio-ecological characteristics of macroinvertebrate assemblages. The high hosting capacity of the most frequent marginal substrata has been identified as an important driver of the observed responses. When using a tool calculating the probability that sampled macroinvertebrate assemblages were impaired by several pressures related to water quality degradation, hydromorphological alteration or land-use, differences in sampling strategy affected the probability estimation. As a main trend, the results were especially reliable when they were obtained from an 8-sample strategy, even more if they included the information provided by the marginal substrata. If sampling effort definitely matters for environmental diagnostic, substratum selection criteria play also a crucial role on (i) the description of local assemblages and (ii) the reliability of calculated impairment risks, due to the strong relationship between stenotopic taxa and specific habitat conditions.

Using Multistage Design‐Based Methods to Construct Abundance Indices and Uncertainty Measures for Delta Smelt

AbstractPopulation abundance indices and estimates of uncertainty are starting points for many scientific endeavors. However, if the indices are based on data collected by different monitoring programs with possibly different sampling procedures and efficiencies, applying consistent methodology for calculating them can be complicated. Ideally, the methodology will provide indices and associated measures of uncertainty that account for the sample design, the level of sampling effort (e.g., sample size), and the capture or detection probabilities. We develop and demonstrate consistent methodology for multiple monitoring programs that sample different life stages of Delta Smelt Hypomesus transpacificus, a critically endangered fish species endemic to the San Francisco Estuary, whose abundance indices have been at the center of much controversy given the regulatory consequences of their listed status. Current indices use different and incomparable methods, do not account for gear selectivity, and do not provide measures of uncertainty. Using recently available information on gear‐specific, length‐based conditional probabilities of capture given availability, we develop new abundance indices along with measures of uncertainty by means of a single methodological approach. These new indices are highly correlated with existing ones, but the approach taken here illuminates different sources of bias and quantifies between‐year variation using probabilistic statements where the previous indices cannot. Decomposition of uncertainty into its constituent sources reveals that early life stage uncertainty is dominated by gear inefficiency while later life stage uncertainty is dominated by sample size, thus providing guidance for improvements to existing surveys. An additional result of general methodological interest is a demonstration, via simulation intended to reflect realistic data properties, that a lognormal distribution is preferable to the normal distribution for making probabilistic statements about the indices. The work here facilitates the fitting of models attempting to identify factors associated with the dynamics and decline of the species.

Reducing effects of dispersal on the bias of 2-sample mark-recapture estimators of stream fish abundance.

The 2-sample mark-recapture method with Chapman’s estimator is often used by inland fishery managers to estimate the reach-scale abundance of stream fish. An important assumption of this method is that no dispersal into or out of the study reach occurs between the two samples. Violations of this assumption are probably common in practice, but their effect on bias (systematic error) of abundance estimates is poorly understood, especially in small populations. Estimation methods permitting dispersal exist but, for logistical reasons, often are infeasible for routine assessments in streams. The purpose of this paper is to extend available results regarding effects of dispersal on the bias of Chapman’s estimator as applied to reach-scale studies of stream fish abundance. We examine for the first time the joint effects of dispersal and sampling variation on the bias of this estimator. To reduce the bias effects of dispersal, we propose a modified sampling scheme in which the original study reach is expanded, a central subreach is sampled during the mark session (sample 1), and the entire reach is sampled during the recapture session (sample 2). This modified sampling scheme can substantially reduce bias effects of dispersal without requiring unique marking of individual fish or additional site visits. Analytical and simulation results show that sampling variation tends to create negative bias with respect to study-reach abundance, while dispersal tends to create positive bias; the net effect can be positive, negative, or zero, depending on the true abundance, capture probabilities, and amount and nature of dispersal. In most cases, simply expanding the study reach is an effective way to reduce dispersal-related bias of Chapman’s estimator, but expanding the study reach and employing the modified sampling scheme we propose is a better alternative for accurately estimating abundance with the same level of sampling effort.

Simulations inform design of regional occupancy-based monitoring for a sparsely distributed, territorial species.

Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy‐based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify minimum levels of sampling effort for a regional occupancy monitoring study design, using white‐headed woodpeckers (Picoides albolvartus), a sparsely distributed, territorial species threatened by habitat decline and degradation, as a case study. We compared the original design with commonly proposed alternatives with varying targets of inference (i.e., species range, space use, or abundance) and spatial extent of sampling. Sampling effort needed to achieve adequate power to observe a long‐term population trend (≥80% chance to observe a 2% yearly decline over 20 years) with the previously used study design consisted of annually monitoring ≥120 transects using a single‐survey approach or ≥90 transects surveyed twice per year using a repeat‐survey approach. Designs that shifted inference toward finer‐resolution trends in abundance and extended the spatial extent of sampling by shortening transects, employing a single‐survey approach to monitoring, and incorporating a panel design (33% of units surveyed per year) improved power and reduced error in estimating abundance trends. In contrast, efforts to monitor coarse‐scale trends in species range or space use with repeat surveys provided extremely limited statistical power. Synthesis and applications. Sampling resolutions that approximate home range size, spatially extensive sampling, and designs that target inference of abundance trends rather than range dynamics are probably best suited and most feasible for broad‐scale occupancy‐based monitoring of sparsely distributed territorial animal species.

Estimating Riverwide Abundance of Juvenile Fish Populations: How Much Sampling is Enough?

AbstractEstimating riverwide abundance of juvenile fish populations is challenging because detection probability is typically low and juveniles can be patchily distributed over large areas. We used a hierarchical Bayesian model to estimate the abundance of juvenile steelhead Oncorhynchus mykiss in two rivers in British Columbia over 3 years based on a multigear, two‐phase sampling design. These estimates were used to drive a simulation model to evaluate how the precision of abundance estimates varied with the number of single‐pass index and mark–recapture sites that were sampled, the proportion of shoreline sampled, and the mean and variation of detection probability and fish density across sites. The extent of variation in fish densities across index sites was the most important factor influencing the precision of river‐wide abundance estimates, and increasing the number of index sites was the best approach to reduce variability in abundance estimates. River size, which controls the proportion of habitat sampled for a given level of sampling effort, had a moderate effect on precision, but only when the extent of site‐to‐site variation in fish density was high. Factors affecting detection probability, such as the number of mark–recapture sites, the mean detection probability, or the extent of variation in detection probability across sites, had much less influence on precision of abundance estimates unless the proportion of river sampled was high. Hierarchical Bayesian models are no substitute for collecting informative data, but they improve our understanding of variance structure, which is critical for providing realistic estimates of uncertainty and designing informative and efficient sampling programs.Received July 16, 2015; accepted October 7, 2015 Published online March 8, 2016

Search effort and imperfect detection: Influence on timed-search mussel (Bivalvia: Unionidae) surveys in Canadian rivers

Inventories and population monitoring are essential activities supporting the conservation of freshwater mussel diversity in Canadian rivers. Despite widespread use of timed-search methods to survey river mussels, the relationship between species detection and search effort has received limited study. In this study, repeat-sampling data from 54 Ontario river sites were used to estimate: (1) species detection probabilities; (2) the number of sampling events required to confidently detect species; and, (3) the power of timed-search surveys to detect future distribution declines. Mussels were collected using visual and tactile methods, and collection data were recorded separately for each 1.5 h of search time (up to 4.5 h). Thirteen species were collected; including two endangered species (Rainbow Villosa iris and Eastern Pondmussel Ligumia nasuta ). In all cases, species detection was imperfect. However, detection probabilities (p ) for most species were high (>0.69). Two repeat 4.5 h surveys are required to confidently assess whether most (83%) species are present at a site. Search effort had a positive effect on estimates of species richness, detection probability and site occupancy, and the power to detect future distribution declines. At all levels of sampling effort, detection probability and site occupancy estimates were positively correlated to mussel abundance.

Feasibility and Evaluation of Probabilistic On‐site Surveys for Estimating Angler Use and Catch in High Mountain Lakes

AbstractEstimating angling effort and catch at high mountain lakes can be difficult due the abundance, remoteness, and diffuse nature of angling effort that typify high mountain lake fisheries. In this study, a simulation was used to evaluate the accuracy of catch and effort estimates derived using on‐site access–access and roving–access creel surveys at a complex of 35 high mountain lakes. Five levels of angling effort and catch at the 35 lakes were simulated, and effort varied from 3,278 to 68,741 h and catch varied from 1,737 to 50,525 fish over the duration of the season. Access–access creel surveys had an average of 32% relative error and roving–access surveys had an average of 17% relative error in estimates of aggregate (i.e., at all 35 lakes) angling effort and catch when one creel surveyor was used. Estimates were relatively robust to temporal and spatial changes in patterns of effort and catch rate over the duration of the season. Relative error was inversely related to the amount of angling effort, catch, and creel surveyors. Roving–access surveys outperformed access–access surveys at all levels of sampling effort. Bias and relative error of estimates of angling effort and catch were greater at the individual‐lake scale than when estimates were derived for all 35 lakes. Results of this study suggest that on‐site surveys can provide relatively accurate estimates of angling effort and catch at as many as 35 lakes with minimal sampling effort.Received March 16, 2015; accepted August 14, 2015

Sensitivity of secretive marsh birds to vegetation condition in natural and restored wetlands in Wisconsin

ABSTRACTWetland loss, biological invasions, and ecological restoration are major factors altering wetland resources in the Midwestern United States. Large‐scale plant‐community change associated with these factors is an under‐investigated, potentially strong driver of habitat suitability for wetland‐dependent wildlife, such as secretive marsh birds (SMBs), which are of widespread conservation concern. We employed multi‐year, hierarchical Bayesian occupancy modeling to investigate sensitivity of 3 SMB species (American bittern, sora, and Virginia rail) to habitat and vegetation characteristics in Wisconsin, USA. We contrasted habitat characteristics and SMB occupancy in natural wetlands with those restored under the federally funded Wetlands Reserve Program (WRP). We also examined the extent to which SMB occupancy was explained by 3 levels of habitat assessment that encompassed different spatial scales and levels of sampling effort (landscape, rapid, and intensive). All species were significantly associated with variables derived from intensive assessment, and showed high sensitivity to differences in plant‐community composition and vegetation quality. Both American bittern and Virginia rail were negatively associated with abundance of the invasive wetland grass, Phalaris arundinacea (reed canarygrass), and were positively associated with an indicator of plant‐community quality (mean coefficient of conservatism, or C‐value). Sora occupancy was positively associated with Typha (cattail) abundance. For all 3 species, occupancy was greater in natural sites than in restored sites, which were characterized by greater Phalaris abundance and lower mean C‐values. Our results show broad agreement between botanical and avian indicators of wetland quality, suggesting that enhancing the condition of wetland vegetation can yield ancillary benefits for SMBs. In this region, efforts to control Phalaris and restore diverse, native‐dominated plant communities are likely to increase wetlands’ capacity to support SMBs. © 2015 The Wildlife Society.

A Random Parameter Model with Onsite Sampling for Recreation Site Choice: An Application to Southern California Shoreline Sportfishing

Estimation of consistent parameter estimates for recreational demand models faces challenges arising from the choice-based nature of the data collected primarily for resource management purposes. As an alternative to randomized respondent-based sampling, choice-based onsite sampling can provide information on actual choices made by a subset of the population where participation has a low incidence. While the literature has shown that under specific restrictions the estimation of choice models from onsite sampling data yields unbiased fixed parameter estimates for the conditional logit model, this result does not carry over to estimation of the random parameter logit model. We propose an estimator for the unbiased estimation of the random parameter model using choice-based data; our estimator uses weights based on information about the level of sampling effort. An empirical application of the standard and weighted discrete choice RUM models to onsite sample data on recreational fishing illustrates the advantages of the proposed estimator. The estimation results indicate the compensating variation associated with an decrease, or increase, of 50 % in expected catch rates for a recreational shoreline sportfishing trip to a man-made structure in southern California is $$-{\$}2.80$$ or $${\$}3.54$$ per trip, respectively.

How a Statewide Stream Survey Can Aid in Understanding Freshwater Mussel (Bivalvia: Unionidae) Ecology: Examples of Utility and Limitations from Maryland

Gaps in our knowledge of freshwater mussel life history, distribution, and ecology remain even though their study has increased considerably over the past few decades. These studies have traditionally taken place within a population, river, or larger drainage unit, but rarely across a broad landscape, such as a state. Given the imperiled status of a majority of unionid species alternative opportunities to collect valuable data cannot be overlooked. We present results from a statewide biological monitoring program (Maryland Biological Stream Survey) that has incorporated a visual survey for mussels, several example analyses using mussel-bioassessment data, and discuss the utility and limitations of incorporating freshwater mussels into stream assessments. Since 2007, we encountered 11 of the 16 mussel species extant in Maryland during assessments of wadeable streams by using an informal visual survey and recording incidental observations. On several occasions, we have discovered new populations of imperiled mussels or extended a species distribution. The biological and physiochemical data collected at sites coincident with freshwater mussels have allowed us to hypothesize factors potentially limiting species distribution, such as fish-host dynamics, habitat quality, nutrient concentration, and catchment land use. We feel that the addition of a survey effort into a biological monitoring program, invaluable data can be collected that can assist resource managers, malacologists, and researchers answer a variety of questions. Further investigation into the cost-benefits of an appropriate level of sampling effort is needed as this could vary markedly among molluscan faunal regions and by objectives.

Assemblage level monitoring of stream fishes: The relative efficiency of single-pass vs. double-pass electrofishing

The relative efficiency of single-pass electrofishing of longer stream sections vs. double-pass electrofishing of shorter reaches was evaluated in small (<5 m wide) wadable lowland streams in the Lake Balaton basin, Hungary. Two hundred meters long stream sections at 8 sites were divided into ten 20 m long sampling units each. These units were used to estimate the representativeness of species richness, species composition and relative abundance data at each level of sampling effort (single vs. double-pass, and number of sampling units pooled) using rarefaction and similarity-based approaches. Assemblage variables showed strong response to the length of the stream sampled (number of sampling units pooled). However, no differences were found between the single- and double-pass methods at any level of sample size for any assemblage variable. Estimates of species richness and species occurrence distributions required more sampling effort than estimates of species relative abundances, using any evaluation method. If a proxy estimate of sample representativeness cannot be obtained in the field, a minimum sampling of single-pass electrofishing of 100 m long sections may be necessary even in small wadable streams with low level of habitat and assemblage diversity to get a relatively unbiased picture on assemblage characteristics.

The terrestrial vertebrate fauna of Litchfield National Park, Northern Territory: monitoring over a 6-year period and response to fire history

Forty-seven 50 m × 50 m quadrats were sampled systematically for vertebrates at Litchfield National Park, northern Australia, in both 1995–96 and 2001–02. A total of 184 vertebrate species was recorded from this sampling, of which 92 species were recorded from five or more quadrats. There was substantial change in the reported species composition of these quadrats between these two periods: the mean Bray–Curtis index for similarity in species composition from the baseline to subsequent sampling of a quadrat was only 22.1 (for an index that varies from 0 for complete turnover in species to 100 for unchanged composition). For individual species, correlations across quadrats in the abundance scores from baseline to resampling varied from –0.12 to 0.85. Matched-pairs testing showed that there was significant change in abundance for 18 species from the baseline to repeat sampling, and significant increase in total bird species richness and total native mammal abundance, but significant decrease in reptile species richness. Fire history was recorded biannually for 40 of the 47 quadrats. Fire was very frequent, with quadrats being burnt in an average of 3.65 years of the six years between fauna samples. Three aspects of this fire history (total number of years of fires, number of fires in the late dry season, and interval from the last fire to the date of resampling) were related to change in the fauna composition of quadrats. Neither the similarity in species composition, nor change in richness or total abundance of all vertebrates or of the four taxonomic classes considered (frogs, reptiles, birds and mammals) were significantly correlated with these components of the fire history of sampled quadrats. This lack of association was possibly because the monitoring period was too short to show pronounced directional change, because the system was responding to many factors other than fire, because the variations in abundance were too large and the number of samples too small to detect true associations, or because fire histories preceding baseline sampling were not considered. The apparent instability of fauna species and communities in this system provides a considerable challenge for broad-brush (that is, vertebrate community–wide) monitoring. Power analysis demonstrated that, for most species, more than 1000 sample sites are needed to be 90% certain of detecting a 20% change in abundance, and with a 10% chance of accepting a Type I error. This level of sampling effort is commensurate with the current level of vertebrate sampling in this region. Broad-brush monitoring approaches such as described here are valuable, but need also to be complemented by more targetted monitoring for individual threatened species or species of particular management interest.

Reserve Selection in Regions with Poor Biological Data

Abstract: New approaches to the identification of priority areas for conservation are gaining popularity for their efficiency in maximizing species representation. However, their dependence on detailed distributional data severely hinders their application to regions where such information is limited, although these are commonly also the regions where conservation planning and action are most urgently required. We used exemplar data on the distribution of southern African birds to assess how sampling effort affects the performance of reserve networks selected by methods based on complementarity. We derived four scenarios of data availability from the initial data, resulting from different levels of sampling effort: abundance data, presence/absence data, low sampling effort, and absence of data. Reserve selection based on data obtained with low sampling effort can be highly effective in the representation of species, with a good relative performance also in terms of representation of species in peaks of abundance. This is because although the data on low sampling effort represent far fewer records than the original data, the records retained are biased toward the selection of peaks of abundance, even for the restricted‐range species. Although the best results were naturally obtained from the most effort‐intensive data set (with abundance data), these results suggest that methods based on complementarity are potentially valuable tools for reserve selection in regions for which biological data are poor.

Sampling Design Methods for Water Distribution Model Calibration

Field sampling is sometimes performed to support modeling activities—specifically, to estimate the parameters of a mathematical model or, more accurately, to calibrate the model. In this case, a relevant question for field samplings design is “how to maximize the confidence in estimated parameter values, given a level of sampling effort?” We approach this question using established ideas in parameter estimation and sampling design theory and propose general sensitivity-based methods to rank the locations and types of measurements for estimating the parameters of a water distribution network model. The proposed methods are suboptimal, yet practical, and are applied to select good tracer and pressure measurement locations for estimating pipe roughness coefficients. These particular results suggest that, when compared to pressure measurements, tracer measurements can be informative for calibrating network hydraulic parameters but one must take more care in selecting their location. Using the proposed methods, a selection of both tracer and pressure measurements improves estimation confidence by a factor of 2, over that obtained using tracer or pressure measurements alone.

Perceptions of Species Abundance, Distribution, and Diversity:Lessons from Four Decades of Sampling on a Government-Managed Reserve

/ We examined data relative to species abundance, distribution, anddiversity patterns of reptiles and amphibians to determine how perceptionschange over time and with level of sampling effort. Location data werecompiled on more than one million individual captures or observations of 98species during a 44-year study period on the US Department of Energy's(DOE) Savannah River Site National Environmental Research Park (SRS-NERP) inSouth Carolina. We suggest that perceptions of herpetofaunal speciesdiversity are strongly dependent on level of effort and that land managementdecisions based on short-term data bases for some faunal groups could resultin serious errors in environmental management. We provide evidence thatacquiring information on biodiversity distribution patterns is compatiblewith multiyear spatially extensive research programs and also provide aperspective of what might be achieved if long-term, coordinated researchefforts were instituted nationwide.To conduct biotic surveys on government-managed lands, we recommend revisionsin the methods used by government agencies to acquire and report biodiversitydata. We suggest that government and industry employees engaged inbiodiversity survey efforts develop proficiency in field identification forone or more major taxonomic groups and be encouraged to measure the status ofpopulations quantitatively with consistent and reliable methodologies. Wealso suggest that widespread academic cooperation in the dissemination ofinformation on regional patterns of biodiversity could result byestablishment of a peer-reviewed, scientifically rigorous journal concernedwith status and trends of the biota of the United States. KEY WORDS: Abundance; Amphibian; Biodiversity; Distribution; Landmanagement; Reptile

The Trade-off between Species Capture and Quantitative Accuracy in Ecological Inventory of Lichens and Bryophytes in Forests in Montana

For a given level of sampling effort there is a trade-off between accuracy of cover estimates and the proportion of the species present that are recorded in the data (species capture). We evaluated this trade-offfor three strata of lichens and bryophytes in western Montana: branch epiphytes, trunk epiphytes, and ground layer. At one extreme, visually integrating a single large plot resulted in high species capture but low accuracy ofcover estimates. At the other extreme, subsampling with many small plots, species capture was low but accuracy of cover estimates was higher for common species. Belt transects were intermediate in both respects. In general, larger areas of visual integration are preferable when the vegetation is sparse. Differences in sampling times between methods were mostly minor, and these differences were inconsistent among strata. When density and diversity of vegetation in a stratum are relatively high, sampling times are somewhat longer. To represent effectively both species diversity and cover, we recommend subsampling with small quadrats when vegetation is relatively dense or belt transects with sparse vegetation. These techniques should be supplemented by a fixed-area reconnaissance for species not included in the quantitative sample.