Toward a predictive theory of risk effects: hypotheses for prey attributes and compensatory mortality

Risk effects, or the costs of antipredator behavior, can comprise a large proportion of the total effect of predators on their prey. While empirical studies are accumulating to demonstrate the importance of risk effects, there is no general theory that predicts the relative importance of risk effects and direct predation. Working toward this general theory, it has been shown that functional traits of predators (e.g., hunting modes) help to predict the importance of risk effects for ecosystem function. Here, I note that attributes of the predator, the prey, and the environment are all important in determining the strength of antipredator responses, and I develop hypotheses for the ways that prey functional traits might influence the magnitude of risk effects. In particular, I consider the following attributes of prey: group size and dilution of direct predation risk, the degree of foraging specialization, body mass, and the degree to which direct predation is additive vs. compensatory. Strong tests of these hypotheses will require continued development of methods to identify and quantify the fitness costs of antipredator responses in wild populations.     

Microsatellite data reveal fine genetic structure in male Guiana dolphins (<Emphasis Type="Italic">Sotalia guianesis)</Emphasis> in two geographically close embayments at south-eastern coast of Brazil

A large macrogeographic differentiation has been observed among Sotalia guianensis populations along the South American coast. However, no genetic structure has been detected so far in closely distributed populations of this species, even though it has been observed in other cetaceans. Here, we examined the fine scale population structure for the largest populations of S. guianensis inhabiting Sepetiba and Paraty embayments at the south-eastern coast of Rio de Janeiro, Brazil. Analysis of mitochondrial DNA (mtDNA) control region sequences failed to detect variability among sequences. Conversely, evidence of significant male population structure was found on the basis of ten nuclear microsatellite loci. Surprisingly, the microsatellite markers were able to distinguish between individuals from the two embayments located 60 km apart. The results suggest that differences in habitat type and behavioral specializations are likely to explain the patterns of genetic structure. These findings should provide baselines for the management of communities exposed to increasing human-driven habitat loss.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.     

Effect of diel period and season on seining effort required to detect changes in Lake Erie beach fish assemblages

Using beach seining data from Lake Erie beaches, we examined the effect of diel period and season on two common study objectives considered sensitive to sampling effort: (1) has fish assemblage composition changed between two sampling time periods?, and (2) how many samples are necessary to provide a representative sample of the fish assemblage? Across a range of effect sizes and power levels, sample sizes were estimated for species richness, total fish abundance, round goby (Neogobius melanostomus) abundance and emerald shiner (Notropis atherinoides) abundance. For most sampling periods and effect sizes, several hundred to several thousand seine hauls were estimated to be required for detecting large-scale (e.g. basin-wide) changes in round goby and emerald shiner abundance. Depending on the indicator of interest, night seining (either spring or fall) was interpreted as the most efficient approach. For both seasons, sampling effort beyond 40 to 50 night seine hauls results in few additional species being detected. Both species accumulation curves and estimated sample sizes indicate that less effort is required to detect species richness changes than fish abundance. For most effect sizes and power levels, estimates of the number of seine hauls required to detect changes in fish abundance are unrealistically large for most monitoring programs. More practical monitoring strategies could be achieved by adopting alternative indicators (e.g. guilds), a more liberal significance level (p=0.1), a paired-site sampling design, or including reference sites.     

Co-pyrolysis of swine manure with agricultural plastic waste: Laboratory-scale study

Manure-derived biochar is the solid product resulting from pyrolysis of animal manures. It has considerable potential both to improve soil quality with high levels of nutrients and to reduce contaminants in water and soil. However, the combustible gas produced from manure pyrolysis generally does not provide enough energy to sustain the pyrolysis process. Supplementing this process may be achieved with spent agricultural plastic films; these feedstocks have large amounts of available energy. Plastic films are often used in soil fumigation. They are usually disposed in landfills, which is wasteful, expensive, and environmentally unsustainable. The objective of this work was to investigate both the energetics of co-pyrolyzing swine solids with spent plastic mulch films (SPM) and the characteristics of its gas, liquid, and solid byproducts. The heating value of the product gas from co-pyrolysis was found to be much higher than that of natural gas; furthermore, the gas had no detectable toxic fumigants. Energetically, sustaining pyrolysis of the swine solids through the energy of the product gas could be achieved by co-pyrolyzing dewatered swine solids (25% m/m) with just 10% SPM. If more than 10% SPM is used, the co-pyrolysis would generate surplus energy which could be used for power generation. Biochars produced from co-pyrolyzing SPM and swine solid were similar to swine solid alone based on the surface area and the ¹H NMR spectra. The results of this study demonstrated the potential of using pyrolysis technology to manage two prominent agricultural waste streams (SPM and swine solids) while producing value-added biochar and a power source that could be used for local farm operations.     

Behaviour and physiology of sockeye salmon homing through coastal waters to a natal river

Adult sockeye salmon (Oncorhynchus nerka, N = 179) from six Fraser River populations (British Columbia) were intercepted in continental shelf waters ∼215 km from the Fraser River mouth, gastrically implanted with acoustic transmitters, non-lethally biopsied for blood biochemistry, gill Na⁺,K⁺-ATPase activity and somatic energy density and then released. Migration behaviour and travel times to the river mouth and into the river were monitored by underwater telemetry receivers positioned at the river mouth and in the river. Post-release survival of salmon was excellent, with 84% (N = 150) of fish reaching the furthest receiving station ∼85 km upriver. Fish from Late-summer run populations (Adams and Weaver Creek) averaged a migration rate of ∼20 km day⁻¹ through the marine area and held at the river mouth and adjacent areas for 7–9 days before entering the river. Summer-run populations (Birkenhead, Chilko, Horsefly and Stellako) had a migration rate ∼33 km day⁻¹ and held for only 1–3 days. Once in river, similar patterns were observed: Late-run populations migrated at ∼28 km day⁻¹ and Summer-run populations at ∼40 km day⁻¹. From point of release to the river mouth, males migrated faster than females, but once in river migration rates did not differ between sexes. Among all females, a correlation was discovered between levels of circulating testosterone and river entry timing. This correlation was not observed among males. Plasma K⁺, Cl⁻, glucose, lactate and osmolality were also correlated with entry timing in both sexes.     

Assessing Landscape Condition Relative to Water Resources in the Western United States: A Strategic Approach

The Environmental Monitoring and Assessment Program (EMAP) is proposing an ambitious agenda to assess the status of streams and estuaries in a 12-State area of the western United States by the end of 2003. Additionally, EMAP is proposing to access landscape conditions as they relate to stream and estuary conditions across the west. The goal of this landscape project is to develop a landscape model that can be used to identify the relative risks of streams and estuaries to potential declines due to watershed-scale, landscape conditions across the west. To do so, requires an understanding of quantitative relationships between landscape composition and pattern metrics and parameters of stream and estuary conditions. This paper describes a strategic approach for evaluating the degree to which landscape composition and pattern influence stream and estuary condition, and the development and implementation of a spatially-distributed, landscape analysis approach.     

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.     

Agricultural Chemicals in the Alluvial Aquifer of a Typical County of the Arkansas Delta

Statistical methods and a Geographic Information System (GIS) were used to investigate potential indicators of ground water vulnerability to agricultural chemical contamination in a representative area of the Mississippi River alluvial aquifer. A total of 47 wells were sampled for analysis of nitrate, phosphorus, potassium, and 13 pesticides commonly-used in the area. Ten soil and hydrogeologic variables and five ground water vulnerability indices were examined to explain the variations of chemical concentrations. The results showed that no individual soil or hydrogeologic variables or their linear combinations could explain more than 25% of the variation of the chemical concentrations. A quadratic response surface model with the values of confining unit thickness, slope, soil permeability, depth to ground water, and recharge rate accounted for 62% of the variation of nitrate, 43% of P, and 83% of K, suggesting that the interactions among soil and hydrogeologic variables were significant. Observed trends of decreasing nitrate and P concentrations with increasing well depth and/or depth to ground water seemed to correlate with carbonate equilibrium in the aquifer and more reduced environment with depth. In view of uncertainties involved, it was recognized that the limitations associated with input data resolution used in GIS and the formulation of leaching indices limited their use for predicting ground water vulnerability. Misuse of pesticides could be another factor that would complicate the relationships between pesticide concentrations and the vulnerability indices.     

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.