Invasive Microstegium populations consistently outperform native range populations across diverse environments

Plant species introduced into novel ranges may become invasive due to evolutionary change, phenotypic plasticity, or other biotic or abiotic mechanisms. Evolution of introduced populations could be the result of founder effects, drift, hybridization, or adaptation to local conditions, which could enhance the invasiveness of introduced species. However, understanding whether the success of invading populations is due to genetic differences between native and introduced populations may be obscured by origin x environment interactions. That is, studies conducted under a limited set of environmental conditions may show inconsistent results if native or introduced populations are differentially adapted to specific conditions. We tested for genetic differences between native and introduced populations, and for origin x environment interactions, between native (China) and introduced (U.S.) populations of the invasive annual grass Microstegium vimineum (stiltgrass) across 22 common gardens spanning a wide range of habitats and environmental conditions. On average, introduced populations produced 46% greater biomass and had 7.4% greater survival, and outperformed native range populations in every common garden. However, we found no evidence that introduced Microstegium exhibited greater phenotypic plasticity than native populations. Biomass of Microstegium was positively correlated with light and resident community richness and biomass across the common gardens. However, these relationships were equivalent for native and introduced populations, suggesting that the greater mean performance of introduced populations is not due to unequal responses to specific environmental parameters. Our data on performance of invasive and native populations suggest that post-introduction evolutionary changes may have enhanced the invasive potential of this species. Further, the ability of Microstegium to survive and grow across the wide variety of environmental conditions demonstrates that few habitats are immune to invasion.     

Monitoring fluvial water chemistry for trend detection: hydrological variability masks trends in datasets covering fewer than 12 years

This paper sub-samples four 35 year water quality time series to consider the potential influence of short-term hydrological variability on process inference derived from short-term monitoring data. The data comprise two time series for nitrate (NO(3)-N) and two for DOC (using water colour as a surrogate). The four catchments were selected not only because of their long records, but also because the four catchments are very different: upland and lowland, agricultural and non-agricultural. Multiple linear regression is used to identify the trend and effects of rainfall and hydrological 'memory effects' over the full 35 years, and then a moving-window technique is used to subsample the series, using window widths of between 6 and 20 years. The results suggest that analyses of periods between six and eleven years are more influenced by local hydrological variability and therefore provide misleading results about long-term trends, whereas periods of longer than twelve years tend to be more representative of underlying system behaviour. This is significant: if such methods for analysing monitoring data were used to validate changes in catchment management, a monitoring period of less than 12 years might be insufficient to demonstrate change in the underlying system.     

RELATION OF NITRATE CONCENTRATIONS TO BASEFLOW IN THE RACCOON RIVER,IOWA1

ABSTRACT: Excessive nitrate‐nitrogen (nitrate) export from the Raccoon River in west central Iowa is an environmental concern to downstream receptors. The 1972 to 2000 record of daily streamflow and the results from 981 nitrate measurements were examined to describe the relation of nitrate to streamflow in the Raccoon River. No long term trends in streamflow and nitrate concentrations were noted in the 28‐year record. Strong seasonal patterns were evident in nitrate concentrations, with higher concentrations occurring in spring and fall. Nitrate concentrations were linearly related to streamflow at daily, monthly, seasonal, and annual time scales. At all time scales evaluated, the relation was improved when baseflow was used as the discharge variable instead of total streamflow. Nitrate concentrations were found to be highly stratified according to flow, but there was little relation of nitrate to streamflow within each flow range. Simple linear regression models developed to predict monthly mean nitrate concentrations explained as much as 76 percent of the variability in the monthly nitrate concentration data for 2001. Extrapolation of current nitrate baseflow relations to historical conditions in the Raccoon River revealed that increasing baseflow over the 20th century could account for a measurable increase in nitrate concentrations.     

Habitat-mediated foraging limitations drive survival bottlenecks for juvenile salmon

Realistic population models and effective conservation strategies require a thorough understanding of mechanisms driving stage-specific mortality. Mortality bottlenecks for many species occur in the juvenile stage and are thought to result from limitation on food or foraging habitat during a "critical period" for growth and survival. Without a way to account for maternal effects or to measure integrated consumption rates in the field, it has been virtually impossible to test these relationships directly. Hence uncertainties about mechanisms underlying such bottlenecks remain. In this study we randomize maternal effects across sites and apply a new method for measuring consumption integrated over weeks to months to test the hypothesis that food limitation drives early-season juvenile mortality bottlenecks in Atlantic salmon (Salmo salar). Using natural signatures of geologically derived cesium (133Cs), we estimated consumption rates of >400 fry stocked into six streams. Two to four weeks after stocking, consumption was extremely low across sites (0.005 g x g(-1) x d(-1)) and was predicted to be below maintenance rations (i.e., yielding negative energy balances) for the majority of individuals from five of six sites. However, consumption during this time was positively correlated with growth rates and survival (measured at the end of the growing season). In contrast, consumption rates increased in mid- (0.030 g x g(-1) x d(-1)) and late (0.035 g x g(-1) x d(-1)) seasons, but juvenile survival and consumption were not correlated, and correlations between growth and consumption were weak. These findings are consistent with predictions of a habitat-based bioenergetic model constructed using the actual stream positions of the individual fish in the present study, which indicates that habitat-based models capture important environmental determinants of juvenile growth and survival. Hence, by combining approaches, reducing maternal effects and controlling initial conditions, we offer a general framework for linking foraging with juvenile survival and present the first direct consumption-based evidence for the early season bottleneck hypothesis.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

LONG‐TERM CHANGES IN REGIONAL HYDROLOGIC REGIME FOLLOWING IMPOUNDMENT IN A HUMID‐CLIMATE WATERSHED1

ABSTRACT: We analyzed the type of hydrologic adjustments resulting from flow regulation across a range of dam types, distributed throughout the Connecticut River watershed, using two approaches: (1) the Index of Hydrologic Alteration (IHA) and (2) log‐Pearson Type III flood frequency analysis. We applied these analyses to seven rivers that have extensive pre‐and post‐disturbance flow records and to six rivers that have only long post‐regulation flow records. Lastly, we analyzed six unregulated streams to establish the regional natural flow regime and to test whether it has changed significantly over time in the context of an increase in forest cover from less than 20 percent historically to greater than 80 percent at present. We found significant hydrologic adjustments associated with both impoundments and land use change. On average, maximum peak flows decrease by 32 percent in impounded rivers, but the effect decreases with increasing flow duration. One‐day minimum low flows increase following regulation, except for the hydro‐electric facility on the mainstem. Hydrograph reversals occur more commonly now on the mainstem, but the tributary flood control structures experience diminished reversals. Major shifts in flood frequency occur with the largest effect occurring downstream of tributary flood control impoundments and less so downstream of the mainstem's hydroelectric facility. These overall results indicate that the hydrologic impacts of dams in humid environments can be as significant as those for large, multiple‐purpose reservoirs in more arid environments.     

AN EVALUATION OF THE 1997 EDWARDS AQUIFER IRRIGATION SUSPENSION1

ABSTRACT: In early 1997, the Texas Edwards Aquifer Authority implemented a pilot Irrigation Suspension Program with the objectives of increasing springflow and providing relief to municipalities during drought. Irrigators were paid an average of $234 per acre to suspend water use, a price higher than regional land rental rates. Auction theory and program implementation details suggest that the program implementation partially caused inflated bids. The Irrigation Suspension Program is also compared to two alternative programs: (1) subsidizing more efficient irrigation technology and (2) buying land. The irrigation suspension is found to be more cost‐effective relative to subsidizing improved irrigation efficiency because it can be put in place only when aquifer levels are low. Land purchase is a cheaper alternative if the bid levels remain at the levels observed.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Nutrient retention in tile-fed and non-tile reconstructed oxbows in north central Iowa

Nutrient export from the agricultural Midwest threatens the Gulf of Mexico and new conservation practices are needed to reduce the loss of nutrient from subsurface tile drainage systems. Oxbows are natural waterbodies formed when a river cuts off a meander loop and water quality benefits of reconstructed oxbows are being increasingly recognized. In this study, we monitored four reconstructed oxbow sites (two tile-fed, two non-tile) over a 2-year period in north-central Iowa and assessed their capacity for NO₃-N and dissolved reactive phosphorus (DRP) reductions. Water flow and quality monitoring of tiles, shallow groundwater, oxbow and receiving streams documented that the oxbows were dominated by tile drainage inputs. NO₃-N concentrations were highest in the drainage tiles flowing into the tile-fed oxbows (mean 8–10 mg/L) and much lower in floodplain groundwater (<1–2 mg/L). Annual NO₃-N loads into the tile-fed oxbows were substantially larger than input loads into the non-tiled oxbows. For the two tile-fed oxbows, the 2-year NO₃-N retention efficiencies were very similar (0.76–0.77) and on a monthly basis, greater retention efficiencies were measured in summer and fall. DRP concentrations and loads into the tile-fed oxbows were too low to allow for meaningful estimates of retention. Reconstructing oxbows to receive tile drainage water should be considered a sustainable conservation practice for tile drainage treatment in agricultural areas.     

Developing a decision support tool for life-cycle cost assessments

Recent years have seen advancements in the development and use of life-cycle assessment (LCA) analytic techniques. Although these techniques have highlighted the power of LCA to identify the environmental consequences of a product system through its entire life cycle, they have also highlighted a major shortcoming of LCA—the lack of cost information. Because companies make daily decisions that involve trade-offs between economics and the environment, including cost information in LCA is critical for advancing its use as an overall environmental decision-making tool. This article outlines the current state of LCA methodology development, defines key life-cycle cost assessment terms and concepts, and evaluates existing cost assessment techniques with the objective of building an integrated life-cycle cost assessment tool.