How complex do models need to be to predict dispersal of threatened species through matrix habitats?

Persistence of species in fragmented landscapes depends on dispersal among suitable breeding sites, and dispersal is often influenced by the "matrix" habitats that lie between breeding sites. However, measuring effects of different matrix habitats on movement and incorporating those differences into spatially explicit models to predict dispersal is costly in terms of time and financial resources. Hence a key question for conservation managers is: Do more costly, complex movement models yield more accurate dispersal predictions? We compared the abilities of a range of movement models, from simple to complex, to predict the dispersal of an endangered butterfly, the Saint Francis' satyr (Neonympha mitchellii francisci). The value of more complex models differed depending on how value was assessed. Although the most complex model, based on detailed movement behaviors, best predicted observed dispersal rates, it was only slightly better than the simplest model, which was based solely on distance between sites. Consequently, a parsimony approach using information criteria favors the simplest model we examined. However, when we applied the models to a larger landscape that included proposed habitat restoration sites, in which the composition of the matrix was different than the matrix surrounding extant breeding sites, the simplest model failed to identify a potentially important dispersal barrier, open habitat that butterflies rarely enter, which may completely isolate some of the proposed restoration sites from other breeding sites. Finally, we found that, although the gain in predicting dispersal with increasing model complexity was small, so was the increase in financial cost. Furthermore, a greater fit continued to accrue with greater financial cost, and more complex models made substantially different predictions than simple models when applied to a novel landscape in which butterflies are to be reintroduced to bolster their populations. This suggests that more complex models might be justifiable on financial grounds. Our results caution against a pure parsimony approach to deciding how complex movement models need to be to accurately predict dispersal through the matrix, especially if the models are to be applied to novel or modified landscapes.     

ERI evaluation of injectates used at a dry‐cleaning site

A former dry‐cleaning site in Jackson, Tennessee, has undergone remediation to treat dense nonaqueous‐phase liquid (trichloroethene [TCE] and tetrachloroethene [PCE]) contamination in the subsurface. The dry cleaning operation closed in 1977. In 2002, a series of injections were made at the site consisting of corn syrup, vegetable oils, and Simple Green®. In 2004, approximately 200 cubic yards of contaminated soil were excavated, and the bottom of the excavation was covered with sodium lactate. In 2009, the site was characterized using proprietary electrical resistivity imaging (ERI; commercially available as Aestus GeoTrax Surveys^TM). Follow‐up confirmation soil borings targeted anomalies detected via the geophysical work. The results indicate an extremely electrically conductive (less than 1 ohm‐m) vadose zone downgradient from the injection wells, and extremely electrically resistive areas (greater than 10,000 ohm‐m) in the phreatic zone near the injection area. The sample data indicate that the electrically resistive anomalous zones contain moderate to high concentrations of undegraded dry‐cleaning compounds. Electrically conductive anomalous zones are interpreted to be areas of biological activity generated by the amendments injected into the subsurface based on the extreme conductivity values detected, the chemical composition (i.e., PCE degradates are present), and the dominant vadose‐zone location of the conductive zones. © 2012 Wiley Periodicals, Inc.     

MBM fuel feeding system design and evaluation for FBG pilot plant

A biomass fuel feeding system has been designed, constructed and evaluated for a fluidized bed gasifier (FBG) pilot plant at the University of Saskatchewan (Saskatoon, SK, Canada). The system was designed for meat and bone meal (MBM) to be injected into the gasifier at a mass flow-rate range of 1-5 g/s. The designed system consists of two stages of screw conveyors, including a metering stage which controlled the flow-rate of fuel, a rotary airlock and an injection conveyor stage, which delivered that fuel at a consistent rate to the FBG. The rotary airlock which was placed between these conveyors, proved unable to maintain a pressure seal, thus the entire conveying system was sealed and pressurized. A pneumatic injection nozzle was also fabricated, tested and fitted to the end of the injection conveyor for direct injection and dispersal into the fluidized bed. The 150 mm metering screw conveyor was shown to effectively control the mass output rate of the system, across a fuel output range of 1-25 g/s, while the addition of the 50mm injection screw conveyor reduced the irregularity (error) of the system output rate from 47% to 15%. Although material plugging was found to be an issue in the inlet hopper to the injection conveyor, the addition of air sparging ports and a system to pulse air into those ports was found to successfully eliminate this issue. The addition of the pneumatic injection nozzle reduced the output irregularity further to 13%, with an air supply of 50 slpm as the minimum air supply to drive this injector. After commissioning of this final system to the FBG reactor, the injection nozzle was found to plug with char however, and was subsequently removed from the system. Final operation of the reactor continues satisfactorily with the two screw conveyors operating at matching pressure with the fluidized bed, with the output rate of the system estimated based on system characteristic equations, and confirmed by static weight measurements made before and after testing. The error rate by this method is reported to be approximately 10%, which is slightly better than the estimated error rate of 15% for the conveyor system. The reliability of this measurement prediction method relies upon the relative consistency of the physical properties of MBM with respect to its bulk density and feeding characteristics.     

Sex-specific patterns of lifetime reproductive success in single and repeat breeding steelhead trout (Oncorhynchus mykiss)

All other things being equal, the lifetime reproductive success (LRS) of iteroparous and semelparous individuals should scale with the number of breeding seasons. Deviations from this relationship may occur for many reasons, including age- or size-related fecundity or life history trade-offs, which may differ between sexes. We used 19 brood years of DNA parentage analysis in a small (N = 4–143 year⁻¹) wild, unexploited population of steelhead trout (Oncorhynchus mykiss) to compare the LRS of individuals that spawned only once [“one time spawners” (OTS), N = 355 male, 371 female] to those spawning twice [“repeat spawners” (RPS), N = 13 male, 49 female]. Female RPS had nearly twice the LRS of female OTS (1.17 offspring per female vs 0.91 offspring per female), whereas male RPS had nearly three times the LRS of male OTS (1.54 offspring per male vs 0.57 offspring per male). Female RPS produced slightly more adult offspring during their second breeding season than their first (0.78 vs 0.82 offspring per female); however, male RPS produced all of their adult offspring in their second breeding season (0 vs 1.54 offspring per male). The additional growth in body size of males between breeding seasons may give them an advantage in their second breeding season, but the lack of offspring produced in their first season suggests a trade-off between survival and future reproduction that was not expressed in females.     

Estimating landscape-scale species richness: reconciling frequency- and turnover-based approaches

One hypothesis for why estimators of species richness tend to underestimate total richness is that they do not explicitly account for increases in species richness due to spatial or environmental turnover in species composition (beta diversity). I analyze the similarity of a data set of native trees in Great Smoky Mountains National Park, USA, and assess the robustness of these estimators against recently developed ones that incorporate turnover explicitly: the total species accumulation method (T-S) and a method based on the distance decay of similarity. I show that the T-S estimator can give reliable estimates of species richness, given an appropriate grouping of sites. The estimator based on distance decay of similarity performed poorly. There are two main reasons for this: sample size effects and the assumption that distance decay of similarity exhibits a power law relationship. I show that estimators based on distance-decay relationships exhibit systematically lower rates of distance decay for samples with few individuals per site independent of environmental variation. Second, the data presented here and many other survey data sets exhibit exponential rather than power law distance-decay relationships. Richness estimators that explicitly incorporate beta diversity can be improved by beginning from an exponential distance-decay relationship and adjusting for the systematic errors introduced by small sample sizes.     

The development and application of a multilevel decision analysis model for the remediation of contaminated groundwater under uncertainty

A study was initiated which combined elements of stochastic hydrology, risk assessment, simulation modeling, cost analysis and decision making to define the optimum remediation choice(s) for a Superfund site in the southern United States. The effort focused upon the premise that groundwater remediation is inherently complex due to uncertainties in the geological matrix as well as in contaminant concentrations at points of compliance and/or exposure. The technical analyst should supply the decision maker with estimates of these uncertainties as well as the cost penalties required to reduce them to manageable levels. Monte Carlo transport modeling was employed to define the probability of contaminant excursions from the site, while geostatistical simulation identified a joint plume configuration and its attendant probability. Bayesian modeling was used to define the worth of additional data. These individual components were combined within a Decision Model to identify optimum remediation configurations for a given levels of risk tolerance which could be supplied by the decision maker or affected community. Sensitivity analyses were conducted to define ranges over which the decision would not be affected by variation in the respective decision parameter.     

Dynamic selective environments and evolutionary traps in human-dominated landscapes

Human activities can alter selective environments in ways that can reduce the usefulness of certain ornamental traits as honest signals of individual quality and, in some cases, may create evolutionary traps, where rapid changes in selective environments result in maladaptive behavioral decisions. Using the sexually dichromatic, socially monogamous Northern Cardinal (Cardinalis cardinalis) as a model, we hypothesized that urbanization would erode the relationship between plumage coloration and reproductive success. Because the exotic Amur honeysuckle (Lonicera maackii) provides carotenoids, is a preferred habitat attribute, and increases vulnerability to nest predation, we predicted the presence of an evolutionary trap, whereby the brightest males would achieve the lowest reproductive success. Working at 14 forests in Ohio, USA, 2006-2008, we measured plumage color, monitored reproduction, and quantified habitat within territories. In rural landscapes, the brightest males bred earliest in the season and secured more preferred territories; however, annual reproduction declined with plumage brightness. Coloration of urban males was not associated with territory attributes or reproduction. Female redness across all landscapes was negatively related to reproduction. Poor reproductive performance of otherwise higher-quality males probably resulted from preferences for honeysuckle, which reduces annual reproduction when used as a nesting substrate early in the season. In this way, exotic shrubs prompted an evolutionary trap that was avoided in urban forests where anthropogenic resources disassociated male color and reproductive phenology and success. Our study illustrates how modified selective environments in human-dominated landscapes might shape microevolutionary processes in wild bird populations.     

Land Use Planning and Social Equity in North Carolina’s Compensatory Wetland and Stream Mitigation Programs

The U.S. Clean Water Act requires compensatory mitigation for wetland and stream damage through restoration of damaged aquatic ecosystems. We evaluate the North Carolina’s Ecosystem Enhancement Program (EEP), a state agency responsible for compensatory mitigation. We compare communities gaining and losing aquatic resources during mitigation, finding new types of socioeconomic disparities that contradict previous studies of mitigation program behavior. We find average distances between impact and mitigation sites for streams (43.53 km) and wetlands (50.3 km) to be larger in North Carolina than in off-site mitigation programs in other regions previously studied. We also find that aquatic resources in the State are lost from urbanized areas that are more affluent, white, and highly educated, and mitigated at sites in rural areas that are less affluent, less well educated, and have a higher percentage of minorities. We also analyze the relationship between urban growth indicators and EEP accumulation of compensation sites. Growth indicators and long-term population projections are uncorrelated with both projected transportation impacts and advance mitigation acquired by the EEP, suggesting that growth considerations can be more effectively incorporated into the EEP’s planning process. We explore the possibility that spatial mismatches could develop between watersheds that are rapidly growing and those that are gaining mitigation. We make recommendations for ways that regulators incorporate growth indicators into the mitigation planning process.