Wisconsin Department of Natural Resources

Abstract The accelerated eutrophication of most freshwaters is limited by P inputs. Nonpoint sources of P in agricultural runoff now contribute a greater portion of freshwater inputs, due to easier identification and recent control of point sources. Although P management is an integral part of profitable agrisystems, continued inputs of fertilizer and manure P in excess of crop requirements have led to a build‐up of soil P levels, which are of environmental rather than agronomic concern, particularly in areas of intensive crop and livestock production. Thus, the main issues facing the establishment of economically and environmentally sound P management systems are the identification of soil P levels that are of environmental concern; targeting specific controls for different water quality objectives within watersheds; and balancing economic with environmental values. In developing effective options, we have brought together agricultural and limnological expertise to prioritize watershed management practices and remedial strategies to mitigate nonpoint‐source impacts of agricultural P. Options include runoff and erosion control and P‐source management, based on eutrophic rather than agronomic considerations. Current soil test P methods may screen soils on which the aquatic bioavailability of P should be estimated. Landowner options to more efficiently utilize manure P include basing application rates on soil vulnerability to P loss in runoff, manure analysis, and programs encouraging manure movement to a greater hectareage. Targeting source areas may be achieved by use of indices to rank soil vulnerability to P loss in runoff and lake sensitivity to P inputs.

Abstract This is the third compilation of imperiled (i.e., endangered, threatened, vulnerable) plus extinct freshwater and diadromous fishes of North America prepared by the American Fisheries Society'S Endangered Species Committee. Since the last revision in 1989, imperilment of inland fishes has increased substantially. This list includes 700 extant taxa representing 133 genera and 36 families, a 92% increase over the 364 listed in 1989. The increase reflects the addition of distinct populations, previously non-imperiled fishes, and recently described or discovered taxa. Approximately 39% of described fish species of the continent are imperiled. There are 230 vulnerable, 190 thretened, and 280 endangered extant taxa, and 61 taxa presumed extinct or extirpated from nature. Of those that were imperiled in 1989, most (89%) are the same or worse in conservation status; only 6% have improved in status, and 5% were delisted for various reasons. Habitat degradation and nonindigenous species are the main threats to at-risk fishes, many of which are restricted to small ranges. Documenting the diversity and status of rare fishes is a critical step in identifying and implementing appropriate actions necessary for their protection and management.

We analyzed relationships between watershed land use and habitat quality, and between watershed land use and biotic integrity for 134 sites on 103 streams located throughout Wisconsin. Habitat quality and index of biotic integrity (IBI) scores were significantly positively correlated with the amount of forested land and negatively correlated with the amount of agricultural land in the entire watershed and in a 100-m-wide buffer along the stream. Correlations were generally stronger for the entire watershed than for the buffer. Relationships between forested land and habitat and biotic integrity were linear, although there were several outlying sites with lower-than-expected IBI scores. Relationships with agricultural land use were more complex, with an obvious decline in habitat quality and IBI scores apparent only when agricultural land use exceeded 50%. Even when agricultural land use exceeded 80%, some sites maintained relatively good habitat quality and biotic integrity. These “good” sites tended to have relatively high gradients and rocky substrates, and had not been channelized. High urban land use was strongly associated with poor biotic integrity and was weakly but significantly associated with poor habitat quality. There appeared to be a threshold value of urbanization between 10% and 20% beyond which IBI scores were consistently very low. Overall, watershed land uses had strong effects on habitat quality and biotic integrity in Wisconsin streams.

Over the past 15 years the endangered eastern timber wolf ( Canis lupus lycaon ) has been slowly recolonizing northern Wisconsin and, more recently, upper Michigan, largely by dispersing from Minnesota (where it is listed as threatened). We have used geographic information systems (GISs) and spatial radiocollar data on recolonizing wolves in northern Wisconsin to assess the importance of factors in defining favorable wolf habitat. We built a multiple logistic regression model applied to the northern Great Lakes states to estimate the amount and spatial distribution of favorable wolf habitat at the regional landscape scale. Our results suggest that areas with high probability of favorable habitat are more extensive than previously estimated in the northern Great Lake States. Several variables were significant in comparing new pack areas in Wisconsin to nonpack areas, including land ownership class, land cover type, road density, human population, and spatial landscape indices such as fractal dimension (land cover patch boundary complexity), land cover type contagion, landscape diversity, and landscape dominance. Road density and fractal dimension were the most important predictor variables in the logistic regression models. The results indicate that public forest land and private industrial forest land are both important in managing for a broad‐ranging animal such as the wolf. Our data portray favorable habitat that is highly fragmented along development corridors in northern Wisconsin, which may be responsible for the slow growth of the wolf population. Upper Michigan, which is just beginning to be colonized by wolves, has very large, contiguous areas of likely habitat approaching the importance of those in northeastern Minnesota. If continuing development or wolf control restrict dispersing wolves from moving from Minnesota to Wisconsin, and Wisconsin habitat becomes more marginal through further fragmentation, Michigan has the potential to maintain a significant wolf population independent of Minnesota and serve as a source population for Wisconsin. However, a simple island/corridor model of wolf habitat in Wisconsin does not seem to apply. Wolves apparently move throughout the landscape, across many unfavorable areas, but establishment success is restricted to higher quality habitat. Source‐sink dynamics may be operating here, and they suggest that reduction of the Minnesota population in the near term may affect recovery in Wisconsin and Michigan. Our analysis is an example of use of long‐term monitoring data and large‐scale cross‐boundary regional analysis that must be done to solve complex spatial questions in resource management and conservation.

Consistent, cross-mission retrievals of near-surface concentration of chlorophyll-a (Chla) in various aquatic ecosystems with broad ranges of trophic levels have long been a complex undertaking. Here, we introduce a machine-learning model, the Mixture Density Network (MDN), that largely outperforms existing algorithms when applied across different bio-optical regimes in inland and coastal waters. The model is trained and validated using a sizeable database of co-located Chla measurements (n = 2943) and in situ hyperspectral radiometric data resampled to simulate the Multispectral Instrument (MSI) and the Ocean and Land Color Imager (OLCI) onboard Sentinel-2A/B and Sentinel-3A/B, respectively. Our performance evaluations of the model, via two-thirds of the in situ dataset with Chla ranging from 0.2 to 1209 mg/m3 and a mean Chla of 21.7 mg/m3, suggest significant improvements in Chla retrievals. For both MSI and OLCI, the mean absolute logarithmic error (MAE) and logarithmic bias (Bias) across the entire range reduced by 40–60%, whereas the root mean squared logarithmic error (RMSLE) and the median absolute percentage error (MAPE) improved two-to-three times over those from the state-of-the-art algorithms. Using independent Chla matchups (n < 800) for Sentinel-2A/B and -3A, we show that the MDN model provides most accurate products from recorded images processed via three different atmospheric correction processors, namely the SeaWiFS Data Analysis System (SeaDAS), POLYMER, and ACOLITE, though the model is found to be sensitive to uncertainties in remote-sensing reflectance products. This manuscript serves as a preliminary study on a machine-learning algorithm with potential utility in seamless construction of Chla data records in inland and coastal waters, i.e., harmonized, comparable products via a single algorithm for MSI and OLCI data processing. The model performance is anticipated to enhance by improving the global representativeness of the training data as well as simultaneous retrievals of multiple optically active components of the water column.

The objectives of this study are to (1) characterize the carbon (C) content, leaf area index, and aboveground net primary production (ANPP) for mature aspen, black spruce, and young and mature jack pine stands at the southern and northern Boreal Ecosystem‐Atmosphere Study (BOREAS) areas and (2) compare net primary production and carbon allocation coefficients for the major boreal forest types of the world. Direct estimates of leaf area index, defined as one half of the total leaf surface area, range from a minimum of 1.8 for jack pine forests to a maximum of 5.6 for black spruce forests; stems comprise 5 to 15% of the total overstory plant area. In the BOREAS study, total ecosystem (vegetation plus detritus plus soil) carbon content is greatest in the black spruce forests (445,760–479,380 kg C ha −1 ), with 87 to 88% of the C in the soil, and is lowest in the jack pine stands (68,370–68,980 kg C ha −1 ) with a similar distribution of carbon in the vegetation and soil. Forest floor carbon content and mean residence time (MRT) also vary more among forest types in a study area than between study areas for a forest type; forest floor MRT range from 16 to 19 years for aspen stands to 28 to 39 years for jack pine stands. ANPP differs significantly among the mature forests at each of the BOREAS study areas, ranging from a maximum of 3490 to 3520 kg C ha −1 yr −1 for aspen stands to 1170 to 1220 kg C ha −1 yr −1 for jack pine stands. Both net primary production (NPP) and carbon allocation differ between boreal evergreen and deciduous forests in the world, suggesting global primary production models should distinguish between these two forest types. On average, 56% of NPP for boreal forests occurs as detritus and illustrates the need to better understand factors controlling aboveground and below‐ground detritus production in boreal forests.

The region studied includes the Laurentian Great Lakes and a diversity of smaller glacial lakes, streams and wetlands south of permanent permafrost and towards the southern extent of Wisconsin glaciation. We emphasize lakes and quantitative implications. The region is warmer and wetter than it has been over most of the last 12000 years. Since 1911 observed air temperatures have increased by about 0·11°C per decade in spring and 0·06°C in winter; annual precipitation has increased by about 2·1% per decade. Ice thaw phenologies since the 1850s indicate a late winter warming of about 2·5°C. In future scenarios for a doubled CO2 climate, air temperature increases in summer and winter and precipitation decreases (summer) in western Ontario but increases (winter) in western Ontario, northern Minnesota, Wisconsin and Michigan. Such changes in climate have altered and would further alter hydrological and other physical features of lakes. Warmer climates, i.e. 2 × CO2 climates, would lower net basin water supplies, stream flows and water levels owing to increased evaporation in excess of precipitation. Water levels have been responsive to drought and future scenarios for the Great Lakes simulate levels 0·2 to 2·5 m lower. Human adaptation to such changes is expensive. Warmer climates would decrease the spatial extent of ice cover on the Great Lakes; small lakes, especially to the south, would no longer freeze over every year. Temperature simulations for stratified lakes are 1–7°C warmer for surface waters, and 6°C cooler to 8°C warmer for deep waters. Thermocline depth would change (4 m shallower to 3·5 m deeper) with warmer climates alone; deepening owing to increases in light penetration would occur with reduced input of dissolved organic carbon (DOC) from dryer catchments. Dissolved oxygen would decrease below the thermocline. These physical changes would in turn affect the phytoplankton, zooplankton, benthos and fishes. Annual phytoplankton production may increase but many complex reactions of the phytoplankton community to altered temperatures, thermocline depths, light penetrations and nutrient inputs would be expected. Zooplankton biomass would increase, but, again, many complex interactions are expected. Generally, the thermal habitat for warm-, cool- and even cold-water fishes would increase in size in deep stratified lakes, but would decrease in shallow unstratified lakes and in streams. Less dissolved oxygen below the thermocline of lakes would further degrade stratified lakes for cold water fishes. Growth and production would increase for fishes that are now in thermal environments cooler than their optimum but decrease for those that are at or above their optimum, provided they cannot move to a deeper or headwater thermal refuge. The zoogeographical boundary for fish species could move north by 500–600 km; invasions of warmer water fishes and extirpations of colder water fishes should increase. Aquatic ecosystems across the region do not necessarily exhibit coherent responses to climate changes and variability, even if they are in close proximity. Lakes, wetlands and streams respond differently, as do lakes of different depth or productivity. Differences in hydrology and the position in the hydrological flow system, in terrestrial vegetation and land use, in base climates and in the aquatic biota can all cause different responses. Climate change effects interact strongly with effects of other human-caused stresses such as eutrophication, acid precipitation, toxic chemicals and the spread of exotic organisms. Aquatic ecological systems in the region are sensitive to climate change and variation. Assessments of these potential effects are in an early stage and contain many uncertainties in the models and properties of aquatic ecological systems and of the climate system. © 1997 John Wiley & Sons, Ltd.

MOTIVATION: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. MAIN TYPES OF VARIABLES INCLUDED: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. SPATIAL LOCATION AND GRAIN: ). TIME PERIOD AND GRAIN: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. MAJOR TAXA AND LEVEL OF MEASUREMENT: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. SOFTWARE FORMAT: .csv and .SQL.

Abstract Ecologists often study wildlife populations by deploying camera traps. Large datasets are generated using this approach which can be difficult for research teams to manually evaluate. Researchers increasingly enlist volunteers from the general public as citizen scientists to help classify images. The growing number of camera trap studies, however, makes it ever more challenging to find enough volunteers to process all projects in a timely manner. Advances in machine learning, especially deep learning, allow for accurate automatic image classification. By training models using existing datasets of images classified by citizen scientists and subsequent application of such models on new studies, human effort may be reduced substantially. The goals of this study were to (a) assess the accuracy of deep learning in classifying camera trap data, (b) investigate how to process datasets with only a few classified images that are generally difficult to model, and (c) apply a trained model on a live online citizen science project. Convolutional neural networks ( CNN s) were used to differentiate among images of different animal species, images of humans or vehicles, and empty images (no animals, vehicles, or humans). We used four different camera trap datasets featuring a wide variety of species, different habitats, and a varying number of images. All datasets were labelled by citizen scientists on Zooniverse. Accuracies for identifying empty images across projects ranged between 91.2% and 98.0%, whereas accuracies for identifying specific species were between 88.7% and 92.7%. Transferring information from CNN s trained on large datasets (“transfer‐learning”) was increasingly beneficial as the size of the training dataset decreased and raised accuracy by up to 10.3%. Removing low‐confidence predictions increased model accuracies to the level of citizen scientists. By combining a trained model with classifications from citizen scientists, human effort was reduced by 43% while maintaining overall accuracy for a live experiment running on Zooniverse. Ecology researchers can significantly reduce image classification time and manual effort by combining citizen scientists and CNN s, enabling faster processing of data from large camera trap studies.

The morphological and biochemical properties of plant canopies are strong predictors of photosynthetic capacity and nutrient cycling. Remote sensing research at the leaf and canopy scales has demonstrated the ability to characterize the biochemical status of vegetation canopies using reflectance spectroscopy, including at the leaf level and canopy level from air- and spaceborne imaging spectrometers. We developed a set of accurate and precise spectroscopic calibrations for the determination of leaf chemistry (contents of nitrogen, carbon, and fiber constituents), morphology (leaf mass per area, Marea), and isotopic composition (δ15N) of temperate and boreal tree species using spectra of dried and ground leaf material. The data set consisted of leaves from both broadleaf and needle-leaf conifer species and displayed a wide range in values, determined with standard analytical approaches: 0.7–4.4% for nitrogen (Nmass), 42–54% for carbon (Cmass), 17–58% for fiber (acid-digestible fiber, ADF), 7–44% for lignin (acid-digestible lignin, ADL), 3–31% for cellulose, 17–265 g/m2 for Marea, and −9.4‰ to 0.8‰ for δ15N. The calibrations were developed using a partial least-squares regression (PLSR) modeling approach combined with a novel uncertainty analysis. Our PLSR models yielded model calibration (independent validation shown in parentheses) R2 and the root mean square error (RMSE) values, respectively, of 0.98 (0.97) and 0.10% (0.13%) for Nmass, R2 = 0.77 (0.73) and RMSE = 0.88% (0.95%) for Cmass, R2 = 0.89 (0.84) and RMSE = 2.8% (3.4%) for ADF, R2 = 0.77 (0.69) and RMSE = 2.4% (3.9%) for ADL, R2 = 0.77 (0.72) and RMSE = 1.4% (1.9%) for leaf cellulose, R2 = 0.62 (0.60) and RMSE = 0.91‰ (1.5‰) for δ15N, and R2 = 0.88 (0.87) with RMSE = 17.2 g/m2 (22.8 g/m2) for Marea. This study demonstrates the potential for rapid and accurate estimation of key foliar traits of forest canopies that are important for ecological research and modeling activities, with a single calibration equation valid over a wide range of northern temperate and boreal species and leaf physiognomies. The results provide the basis to characterize important variability between and within species, and across ecological gradients using a rapid, cost-effective, easily replicated method.

Rainfall runoff samples were collected from streets, parking lots, roofs, driveways, and lawns. These five source areas are located in residential, commercial, and industrial land uses in Madison, Wisconsin. Solids, phosphorus, and heavy metals loads were determined for all the source areas using measured concentrations and runoff volumes estimated by the Source Load and Management Model. Source areas with relatively large contaminant loads were identified as critical source areas for each land use. Streets are critical source areas for most contaminants in all the land uses. Parking lots are critical in the commercial and industrial land uses. Lawns and driveways contribute large phosphorus loads in the residential land use. Roofs produce significant zinc loads in the commercial and industrial land uses. Identification of critical source areas could reduce the amount of area needing best-management practices in two areas of Madison, Wisconsin. Targeting best-management practices to 14% of the residential area and 40% of the industrial area could significantly reduce contaminant loads by up to 75%.

Using trace-metal-clean sampling and handling techniques along with ultrasensitive analytical procedures, it is possible to measure both total Hg and monomethylmercury (methyl-Hg) in natural planktonic communities with the same level of taxonomic, ontogenic, and trophic resolution that is currently possible in fish communities. In an experimentally manipulated lake, both acidification and trophic position enhanced the bioaccumulation of methyl-Hg in the plankton. A consistant pattern of methyl-Hg enrichment (2−4 ×) in water, bulk phytoplankton, and individual zooplankton was associated with a 1.5 unit pH decrease in Little Rock Lake. Regardless of pH, bioconcentration factors [Bf = log(Cb/Cw), where Cb and Cw are Hg concentrations in biota and water] were substantially higher for methyl-Hg than those for total Hg or nonmethyl-Hg at three pelagic trophic levels (~10−100×). Between each trophic level, the Bf(methyl-Hg) increased by ~0.5 log units, clearly indicating biomagnification. Although somewhat higher in the acidified basin, Bf(methyl-Hg) was more strongly influenced by trophic position than by pH. This suggests that methyl-Hg was bioaccumulated largely in proportion to supply and that acidification may have directly increased supply to the base of the food chain.

Abstract: A stochastic computer model was used to examine the effects of varying degrees of habitat fragmentation on the dynamics of a hypothetical population of forest‐interior bid. The primary demographic parameter that influenced the population's dynamics was fecundity, which varied as a function of how far a birds territory was from an ecological edge. As our model landscape became more fragmented the proportion of forest habitat that was near edges increased geometrically, and the population's overall fecundity dropped as a result. The model demonstrates that impaired reproduction in a fragmented landscape is, by itself a sufficient disruption of the population's dynamics to generate population declines and shifts in distribution similar to those observed in the fragmented forests of southern Wisconsin. Without immigration of recruits from other regions where reproduction is better, habitat‐interior populations in a severely fragmented landscape can become locally extinct.

Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (ρ̂w). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ρ̂w560 and ρ̂w664 were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ρ̂w490≤λ≤743nm yielded 25–70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.

Abstract: Management of amphibian populations to reverse recent declines will require defining high‐quality habitat for individual species or groups of species, followed by efforts to retain or restore these habitats on the landscape. We examined landscape‐level habitat relationships for frogs and toads by measuring associations between relative abundance and species richness based on survey data derived from anuran calls and features of land‐cover maps for Iowa and Wisconsin. The most consistent result across all anuran guilds was a negative association with the presence of urban land. Upland and wetland forests and emergent wetlands tended to be positively associated with anurans. Landscape metrics that represent edges and patch diversity also had generally positive associations, indicating that anurans benefit from a complex of habitats that include wetlands. In Iowa the most significant associations with relative abundance were the length of the edge between wetland and forest ( positive) and the presence of urban land (negative). In Wisconsin the two most significant associations with relative abundance were forest area and agricultural area ( both positive). Anurans had positive associations with agriculture in Wisconsin but not in Iowa. Remnant forest patches in agricultural landscapes may be providing refuges for some anuran species. Differences in anuran associations with deep water and permanent wetlands between the two states suggest opportunities for management action. Large‐scale maps can contribute to predictive models of amphibian habitat use, but water quality and vegetation information collected from individual wetlands will likely be needed to strengthen those predictions. Landscape habitat analyses provide a framework for future experimental and intensive research on specific factors affecting the health of anurans.

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 247:59-73 (2003) - doi:10.3354/meps247059 Eelgrass Zostera marina loss in temperate estuaries: relationship to land-derived nitrogen loads and effect of light limitation imposed by algae Jennifer Hauxwell1,2,4,*, Just Cebrián1,3,5, Ivan Valiela1 1Boston University Marine Program, Marine Biological Laboratory, Woods Hole, Massachusetts 02543, USA 2Wisconsin Department of Natural Resources, DNR Research Center, 1350 Femrite Drive, Monona, Wisconsin 53716, USA 3Dauphin Island Sea Lab, 101 Bienville Boulevard, PO Box 369-370, Dauphin Island, Alabama 36528, USA 4Present address: Wisconsin Department of Natural Resources, DNR Research Center, 1350 Femrite Drive, Monona, Wisconsin 53716, USA 5Present address: Dauphin Island Sea Lab, 101 Bienville Boulevard, PO Box 369-370, Dauphin Island, Alabama 36528, USA *Email: jennifer.hauxwell@dnr.state.wi.us ABSTRACT: In this paper, we explicitly link changes in community structure of estuarine primary producers to measured nitrogen loading rates from watersheds to estuaries, and quantify the relationship between nitrogen load, annual dynamics of algal growth and Zostera marina L. productivity, and overall eelgrass decline at the watershed-estuarine scale in estuaries of Waquoit Bay, Massachusetts, USA. Substantial eelgrass loss (80 to 96% of bed area lost in the last decade) was found at loads of ~30 kgN ha-1 yr-1, and total disappearance at loads ≥60 kg N ha-1 yr-1. Rather than decreased eelgrass growth rates, we observed an exponential decrease in shoot densities and bed area (and subsequently areal production) as nitrogen loads increased, suggesting that eelgrass decline in higher-nitrogen estuaries of the Waquoit system occurred largely via lack of recruitment or enhanced mortality of established shoots. Similar to the patterns observed in many other systems and the experimental results obtained in laboratories or mesocosms, the relationship we observed between nitrogen loads and eelgrass health within the Waquoit system was indirect: increased nitrogen stimulated growth and standing stocks of algal producers, that may have caused severe light limitation of eelgrass. From light budgets that considered water column, epiphyte, and macroalgal shading, we estimated chronic, severe light limitation to newly recruiting shoots in higher-nitrogen estuaries, due mainly to shading by a coexisting ≤15 cm macroalgal canopy. Two management recommendations aimed at eelgrass preservation emerge from this work. First, development and management of watersheds must be conducted such that land-derived nitrogen loading to estuaries is restricted. In the Waquoit Bay estuaries, for example, eelgrass is absent or rapidly disappearing from all but those receiving the lowest (≤15th percentile) loads. Second, shoot density and meadow area, rather than g rates per shoot, seem to be adequate variables for routine monitoring of eelgrass health. We also show that the shift from eelgrass- to algae-dominated communities has important consequences for total system primary production and carbon and nitrogen cycling. Estimated total primary production by coastal assemblages in the Waquoit Bay system was 135% higher in estuaries receiving relatively high versus low loads of land-derived nitrogen, suggesting important trophic and biogeochemical alterations to temperate estuarine ecosystems as a result of eutrophication. KEY WORDS: Seagrass · Macroalgae · Epiphytes · Phytoplankton · Irradiance · Waquoit Bay · Eutrophication · Estuary Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 247. Online publication date: February 04, 2003 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2003 Inter-Research.

Modeling nonpoint‐source phosphorus (P) loading from land to surface waters can be both complex and data intensive. Our goal was to develop a simple model that would account for spatial pattern in topography and land use using geographic information system (GIS) databases. We estimated areas of the watershed that strongly contributed to P loading by approximating overland flow, and modeled annual P loading by fitting three parameters to data obtained by stream monitoring. We calibrated the model using P loading data from two years of contrasting annual precipitation for Lake Mendota, a Wisconsin eutrophic lake in a watershed dominated by agriculture and urban lands. Land‐use scenarios were developed to estimate annual P loading from pre‐settlement and future land uses. As much as half of the Lake Mendota watershed did not contribute significantly to annual P loading. The greatest contribution to loading came from a heterogeneous riparian corridor that varied in width from 0.1 km to ≈ 6 km depending on topography and runoff conditions. We estimate that loading from pre‐settlement land use was one‐sixth of the loading from present land use. A future scenario, representing an 80% increase in existing urban land (from 9 to 16% of total watershed area, which would be reached in 30 yr with current land‐use trends), showed only modest increases in annual P loading but possible significant effects on water quality. If the watershed were to become entirely urbanized, P loading to the lake would double and potential effects on water quality would be severe. Changes in P loading were strongest with conversions of undisturbed vegetated lands, especially riparian areas, to either urban or agricultural uses. Variability in total annual rainfall leads to variability in the riparian area that affects P loading, with implications for policies intended to control nonpoint nutrient inputs.

Abstract Climate is a critical driver of many fish populations, assemblages, and aquatic communities. However, direct observational studies of climate change impacts on North American inland fishes are rare. In this synthesis, we (1) summarize climate trends that may influence North American inland fish populations and assemblages, (2) compile 31 peer-reviewed studies of documented climate change effects on North American inland fish populations and assemblages, and (3) highlight four case studies representing a variety of observed responses ranging from warmwater systems in the southwestern and southeastern United States to coldwater systems along the Pacific Coast and Canadian Shield. We conclude by identifying key data gaps and research needs to inform adaptive, ecosystem-based approaches to managing North American inland fishes and fisheries in a changing climate. El clima es un factor forzante clave para muchas poblaciones y ensambles de peces y de comunidades acuáticas. Sin embargo, son pocos los estudios observacionales acerca de los impactos del cambio climático en los peces de aguas continentales en Norte América. En esta síntesis (1) se resumen las tendencias climáticas que pueden influir en las poblaciones y ensambles de peces de aguas continentales en Norte América, (2) se compilan 31 trabajos arbitrados que documentan los efectos del cambio climático sobre las poblaciones y ensambles de peces de aguas continentales en Norte América y (3) se comentan cuatro casos de estudio que representan una variedad de respuestas observadas que van desde los sistemas de aguas cálidas en el suroeste y sureste de Los EE.UU., hasta los sistemas de aguas frías a lo largo de la costa del Pacífico y del escudo canadiense. Finalmente, se identifican huecos de información clave y necesidades de investigación tendientes a proporcionar información para diseñar enfoques ecosistémicos con el fin de manejar a los peces y a las pesquerías de aguas continentales en Norte América de cara a un clima cambiante. Le climat est un facteur critique pour de nombreuses populations de poissons, bancs et communautés aquatiques. Cependant, les études d'observation directe des impacts des changements climatiques sur les poissons continentaux d'Amérique du Nord sont rares. Dans cette synthèse, nous (1) résumons les tendances climatiques qui peuvent influencer les populations et communautés de poissons continentaux d'Amérique du Nord, (2) compilons 31 études examinées par des pairs sur les effets documentés du changement climatique sur les populations et communautés de poissons continentaux dl'Amérique du Nord, et (3) mettons l'accent sur quatre études de cas représentant une variété de réponses observées allant des systèmes d'eaux chaudes dans le sud-ouest et sud-est des États-Unis aux systèmes d'eau froide le long de la côte du Pacifique et du Bouclier canadien. Nous concluons en identifiant les lacunes en matière de données clés et les besoins de recherche pour informer sur les approches fondées sur les écosystèmes adaptatifs à la gestion des pêches et des poissons continentaux d'Amérique du Nord face au changement climatique.

1. Using data from the North Temperate Lakes Long‐Term Ecological Research site in northern Wisconsin, we present a series of examples illustrating how landscape setting can influence the static and dynamic aspects of many physical, chemical and biological properties of lakes. 2. One important landscape attribute is the hydrologic position of a lake within the regional flow regime. Lake position determines the relative importance of groundwater and precipitation input to a lake, with lakes high in the landscape receiving a greater proportion of their input waters from precipitation than lakes lower in the landscape. Landscape position is strongly correlated with the concentration of base cations such as calcium and magnesium. 3. Landscape position also influences how lakes respond to drought conditions. Lakes high in the landscape responded to a 4‐year drought with decreases in calcium mass, whereas lakes low in the landscape increased in mass of calcium. During extended dry conditions, these differential responses of lakes suggest that lakes already low in calcium (i.e. in a high position in the flow system) will have further reductions in calcium concentrations. These reductions could decrease the number of lakes offering suitable habitat for organisms such as crayfish and snails whose distributions are limited by calcium. 4. Landscape position also affects silica concentrations in lakes, with lakes low in the landscape having silica concentrations up to three orders of magnitude greater than lakes high in the landscape. Differences in silica concentration affect robustness of freshwater sponge spicules which can potentially alter some aspects of the dynamics of littoral zone food webs. 5. Landscape position can influence the vertical distribution of primary production. Concentrations of dissolved organic carbon are affected by landscape setting and can influence vertical light penetration, thus affecting the depth at which primary production can occur. 6. Lake area and fish species richness are correlated with landscape position: larger, species‐rich lakes are low in the landscape, whereas smaller lakes with fewer species tend to be high in the landscape. 7. By taking a landscape‐scale view, in addition to the more usual lake‐specific view, it is possible to reach a more robust understanding of lake dynamics and avoid some of the problems associated with extrapolating from single lake results.

The rapid improvement of camera traps in recent decades has revolutionized biodiversity monitoring. Despite clear applications in conservation science, camera traps have seldom been used to model the abundance of unmarked animal populations. We sought to summarize the challenges facing abundance estimation of unmarked animals, compile an overview of existing analytical frameworks, and provide guidance for practitioners seeking a suitable method. When a camera records multiple detections of an unmarked animal, one cannot determine whether the images represent multiple mobile individuals or a single individual repeatedly entering the camera viewshed. Furthermore, animal movement obfuscates a clear definition of the sampling area and, as a result, the area to which an abundance estimate corresponds. Recognizing these challenges, we identified 6 analytical approaches and reviewed 927 camera-trap studies published from 2014 to 2019 to assess the use and prevalence of each method. Only about 5% of the studies used any of the abundance-estimation methods we identified. Most of these studies estimated local abundance or covariate relationships rather than predicting abundance or density over broader areas. Next, for each analytical approach, we compiled the data requirements, assumptions, advantages, and disadvantages to help practitioners navigate the landscape of abundance estimation methods. When seeking an appropriate method, practitioners should evaluate the life history of the focal taxa, carefully define the area of the sampling frame, and consider what types of data collection are possible. The challenge of estimating abundance of unmarked animal populations persists; although multiple methods exist, no one method is optimal for camera-trap data under all circumstances. As analytical frameworks continue to evolve and abundance estimation of unmarked animals becomes increasingly common, camera traps will become even more important for informing conservation decision-making.