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We describe development anthropogenic stress indices for coastal margins of the Laurentian Great Lakes basin. Indices were derived based on the response of species assemblages to watershed-scale stress from agriculture and urbanization. Metrics were calculated for five groups of wetland biota: diatoms, wetland vegetation, aquatic invertebrates, fishes, and birds. Previously published community change points of these assemblages were used to classify each watershed as ‘least-disturbed’, ‘at-risk’, or ‘degraded’ based on community response to these stressors. The end products of this work are an on-line map utility and downloadable data that characterize the degree of agricultural land use and development in all watersheds of the US and Canadian Great Lakes basin. Discrepancies between the observed biological condition and putative anthropogenic stress can be used to determine if a site is more degraded than predicted based on watershed characteristics, or if remediation efforts are having beneficial impacts on site condition. This study provides a landscape-scale evaluation of wetland condition that is a critical first step for multi-scale assessments to help prioritize conservation or restoration efforts.

The St. Louis River drains an area of 9412 km 2 into the western arm of Lake Superior. The river's lower section, including a 48.5 km 2 estuary, was designated as a Great Lakes Area of Concern due to degradation from industrial activities. Part of the estuary is occupied by the largest port in the Great Lakes. A GIS-based stressor index was previously developed to characterize anthropogenic stress within the watershed. The components of the stressor index were road density, point-source pollution permit density, population density, and percent agricultural and developed land. Water quality sampling was conducted at 27 sites in the estuary in tributaries and associated nearshore areas during multiple flow regimes in 2010–2011. Additional data were analyzed from 34 upper watershed sites sampled in 2009–2010. Stressor scores were significantly (p 2 − /NO 3 − -N, dissolved oxygen saturation, pH, specific electrical conductivity, chloride, sulfate, and E. coli in the upper watershed. In the estuary, the index was significantly and positively correlated with NO 2 − /NO 3 − -N, NH 4 + -N, and chloride at multiple flow regime and location combinations. Soil K factor (an erosivity index from recent NRCS SSURGO soil surveys) was found to have stronger relationships with sediment related parameters than the stressor gradient. Although originally designed to help stratify sampling across a gradient of landscape stress and identify reference areas for restoration projects, the stressor index was shown to have substantial predictive power for multiple water quality parameters.

We developed ecological indicators of stream macroinvertebrates in two regions of the Midwestern USA dominated by row-crop agriculture. Indicators were identified in a hierarchical fashion. Reach-scale variables related to macroinvertebrate attributes were first identified, and then catchment-scale variables related to those reach-scale variables were identified. Reach-scale indicators common to both regions were % fine sediments, number of habitats, and width:depth ratio. SD of elevation and % commercial land use were selected as catchment-scale indicators in both regions. Our analyses revealed a multi-scale mechanistic relationship between macroinvertebrate attributes associated with degraded conditions (i.e., fewer taxa of Plecoptera and Trichoptera, and a higher proportion of chironomids, burrowers, and depositional taxa) and % fine sediments in stream reaches, which, in turn, was negatively related to catchment characteristics (i.e., SD of elevation) in one region. Understanding how natural variables such as topography influence channel shape and within-channel structure can help guide management options and expectations for different regions. We suggest that developing multi-scale indicators in a mechanistic fashion will be more effective than developing indicators at only one spatial scale for protecting and restoring stream structure and function.

Developing indicators of ecosystem condition is a priority in the Great Lakes, but little is known about appropriate spatial scales to characterize disturbance or response for most indicators. We surveyed birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms at 276 coastal wetland locations throughout the U.S. Great Lakes coastal region during 2002-2004. We assessed the responsiveness of 66 candidate indicators to human disturbance (agriculture, urban devel- opment, and point source contaminants) characterized at multiple spatial scales (100, 500, 1,000, and 5,000 m buffers and whole watersheds) using classification and regression tree analysis (CART). Non- stressor covariables (lake, ecosection, watershed, and wetland area) accounted for a greater proportion of variance than disturbance variables. Row-crop agriculture and urban development, especially at

ECOPHYS, an individual-based process model for poplar, requires a three-dimensional soil water redistribution model to simulate soil water dynamics, plant uptake, and root growth. SOILPSI is a potential-driven water redistribution model based on the RHIZOS rhizosphere simulator. It expands on RHIZOS by calculating water flux based on water potential, and has a macropore flow mode to allow rapid drainage of the soil. SOILPSI simulates water flux in three dimensions and accounts for slope. SOILPSI was evaluated by comparing model output to soil moisture data collected under bare soil conditions. AMMI analysis of a date × depth matrix of differences between simulated and observed soil moisture content showed that excluding the two shallowest soil layers resulted in a difference matrix that conformed to an additive model. The grand mean predicted values were within 2% of the observed values, and 50 of 56 predicted values were within 5% of the observed values. Better agreements between simulated and observed soil moisture content were observed deeper in the soil profile and later in the season. Agreement between SOILPSI and field conditions was consistently more accurate than RHIZOS. Improving simulation of evaporative flux at the soil surface would improve simulation accuracy in the upper horizons.  2002 Elsevier Science Ltd. All rights reserved.

Predicting ozone-induced reduction of carbon sequestration of forests under elevated tropospheric ozone concentrations requires robust mechanistic leaf-level models, scaled up to whole tree and stand level. As ozone effects depend on genotype, the ability to predict these effects on forest carbon cycling via competitive response between genotypes will also be required. This study tests a process-based model that predicts the relative effects of ozone on the photosynthetic rate and growth of an ozone-sensitive aspen clone, as a first step in simulating the competitive response of genotypes to atmospheric and climate change. The resulting composite model simulated the relative above ground growth response of ozone-sensitive aspen clone 259 exposed to square wave variation in ozone concentration. This included a greater effect on stem diameter than on stem height, earlier leaf abscission, and reduced stem and leaf dry matter production at the end of the growing season. Further development of the model to reduce predictive uncertainty is discussed.

A generic bioenergetics model for chinook salmon was modified to estimate solid wastes from a commercial net-pen aquaculture operation in a Minnesota mine-pit lake. The model was calibrated using data from the operation on growth, ration, and temperature. Multiple simulations were run to form three-dimensional response surfaces for consumption, egestion, excretion and respiration as a function of fish size and water temperature. These formed the basis for the Fish Simulation Culture (FIS-C) Model. Predictions for food consumption and solids load were compared with actual ration levels and sedimentation within the mine-pit lake from 1989 to 1992, and compared well with the general trends of the observed data. However, the actual predictive power of FIS-C was very sensitive to our initial model assumption that aquaculture operations are predicated on maximizing the growth of their stock. FIS-C currently does not account for management decisions electing sub-optimal stock growth, but under these conditions does estimate a worst case loading scenario for the system. The annual phosphorus load to the system predicted by FIS-C was not significantly different from that of the mean of 17 values of annual P-load estimated empirically from the literature. However, FIS-C's estimate of P-loading shows a pronounced seasonal pattern to the annual loading. FIS-C offers substantial benefits to users by estimating seasonal and shorter term food wastage and wasteloads to receiving waters under particular operating conditions. Then, other operational scenarios can be created to examine the effects of changing fish inventory, feeding schedule, food composition, etc., in order to examine the impacts on production, environmental and/or regulatory requirements, prior to costly implementation.

A strategy for process modelling of short-rotation Salix coppice plantations is presented. To integrate effectively both large- and small-scale processes, this model must simulate critical processes at scales ranging from the individual leaf to the plantation. This multiscale modelling strategy extrapolates the detail of mechanistic physiological models to the patch and plantation scales. To accomplish this scaling, regional climatic and soil databases are used to generate model inputs; i.e. site and climatic information is passed from the regional scale to drive models operating at the stand or tree level. Key input variables at the individual tree level include genetically determined factors such as leaf morphology and branch architecture, as well as phenological and physiological parameters. Outputs such as carbon fixation, leaf area index, biomass by component, and yields per hectare are then passed back up to address regional questions. This strategy requires a parallel programme of modelling and experimentation. While this strategy focuses on Salix , the approach should also be applicable to species with similar life history attributes, such as Betula and Populus .

In order to effectively deploy short-rotation woody crop plantations for energy and fiber production at regional scales, biologically sound-field-level models of plant growth are required. Individual tree growth process models have proven effective at predicting growth based on environmental driving variables, but in the past these models have been too complex to use at the plantation scale. In this paper we describe an object-oriented strategy for scaling ECOPHYS, an individual tree growth process model for hybrid poplar, to a plantation. Included in this strategy are methods of scaling from an individual shoot to a tree, from individual trees to a patch, and from patches to a plantation. In describing interactions among trees, both above- and below-ground processes are considered. Finally, we describe methods for integrating the plantation level ECOPHYS with EPIC, a field scale model of soil productivity and erosion used in regional assessment.

In this paper we present the proposed conceptual approach and essential subsystems of SYLVATICA, a landscape-based simulation model which will integrate several resource-management technologies in a visual interactive environment. We believe this approach incorporates several critical technologies which should be common to any integrated landscape-based simulation and visualization environment.

Multivariate classification and ordination methods were used to develop ecological species groups for upland forest ecosystems of northwestern Lower Michigan. Species groups were based on similarities in ground-flora composition and abundance patterns among 76 sample stands. Nine ecological species groups were identified using 48 herbaceous, woody and moss species. The divisive classification produced six classes of stands: two dominated by northern hardwoods and four dominated by oaks. The distribution patterns typified by Deschampsia flexuosa, Vaccinium angustifolium, Viburnum acerifolium, and Desmodium spp. were important in discriminating among oak stands, whereas patterns typical of Osmorhiza claytonii and Maianthemum canadense distinguished northern hardwood stands. The species groups exhibited a wide range of ecological amplitudes, from highly specific associations with individual ecosystems to broad distributions across a range of site conditions. Within the geographic limits imposed by macroclimate and regional physiography, ecological species groups act to integrate site attributes and can simplify the process of mapping ecological land units.

During the week of 24 October, 1994, an international group of scientists met in Uppsala, Sweden, to discuss the problems of understanding and modelling the growth of short rotation forests for energy purposes. Three working groups were formed to study specific aspects of the problem: ecophysiology, competition and modelling strategies. This special issue of Biomass and Bioenergy reports the findings of those groups and presents a series of papers related to the ecophysiology and process modelling of Salix .