Increased atmospheric CO 2 concentration and climate change may significantly impact the hydrological and meteorological processes of a watershed system. Quantifying and understanding hydrological responses to elevated ambient CO 2 and climate change is, therefore, critical for formulating adaptive strategies for an appropriate management of water resources. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to assess the effects of increased CO 2 concentration and climate change in the Upper Mississippi River Basin (UMRB). The standard SWAT model was modified to represent more mechanistic vegetation type specific responses of stomatal conductance reduction and leaf area increase to elevated CO 2 based on physiological studies. For estimating the historical impacts of increased CO 2 in the recent past decades, the incremental (i.e., dynamic) rises of CO 2 concentration at a monthly time-scale were also introduced into the model. Our study results indicated that about 1-4% of the streamflow in the UMRB during 1986 through 2008 could be attributed to the elevated CO 2 concentration. In addition to evaluating a range of future climate sensitivity scenarios, the climate projections by

A study of trends and variability of hydrological variables was conducted for natural streamflow gauging stations within two watersheds that are important sources of flow within the Mackenzie River Basin. A comparison was made between trend results for the Liard River Basin and for the Athabasca River Basin. These basins represent a north-south transect of high elevation headwater basins within the Mackenzie River system and are significant since they produce 34% of the annual flow, while occupying only 24% of the total drainage area. Trend analysis was conducted using the Mann-Kendall test with an approach that corrects for serial correlation. The global (or field) significance of the results for each watershed was evaluated using a bootstrap resampling approach. The relationships between trends in hydrological variables and trends in meteorological variables were investigated using partial correlation analysis. The results reveal more trends in some hydrological variables than are expected to occur by chance. In general, both basins exhibit an increase in winter flows and some increase in spring runoff. These increased flows are somewhat offset by decreases (not field significant) in summertime flow. Almost 50% of the stations used in the analysis show an increasing trend in annual minimum flows. Other differences in trend responses are noted for the two watersheds and possible explanations for the differences are hypothesized.Résumé : Une étude des tendances et de la variabilité de variables hydrologiques a été menée pour des stations de mesure de l'écoulement naturel à l'intérieur de deux bassins hydrographiques qui représentent d'importantes sources d'écoulement dans le bassin du fleuve Mackenzie. Une comparaison a été établie entre les tendances obtenues pour le bassin de la rivière Liard et pour le bassin de la rivière Athabasca. Ces bassins représentent un transect nord-sud des bassins de cours supérieur d'altitude élevée à l'intérieur du système fluvial du Mackenzie et revêtent de l'importance car ils produisent 34 % du débit annuel, alors qu'ils n'occupent que seulement 24 % de la zone de drainage totale. Les tendances ont été analysées à l'aide du test de Mann-Kendall, avec une correction des auto-corrélations. Le niveau de signification des résultats pour chaque bassin a été évalué grâce à la méthode de rééchantillonnage « Bootstrap ». Les relations entre les tendances propres aux variables hydrologiques et les tendances propres aux variables

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Coastal wetlands are major global carbon sinks; however, they are heterogeneous and dynamic ecosystems. To characterize spatial and temporal variability in a New England salt marsh, greenhouse gas (GHG) fluxes were compared among major plant‐defined zones during growing seasons. Carbon dioxide (CO2) and methane (CH4) fluxes were compared in two mensurative experiments during summer months (2012–2014) that included low marsh (Spartina alterniflora), high marsh (Distichlis spicata and Juncus gerardii‐dominated), invasive Phragmites australis zones, and unvegetated ponds. Day‐ and nighttime fluxes were also contrasted in the native marsh zones. N2O fluxes were measured in parallel with CO2 and CH4 fluxes, but were not found to be significant. To test the relationships of CO2 and CH4 fluxes with several native plant metrics, a multivariate nonlinear model was used. Invasive P. australis zones (−7 to −15 μmol CO2·m−2·s−1) and S. alterniflora low marsh zones (up to −14 μmol CO2·m−2·s−1) displayed highest average CO2 uptake rates, while those in the native high marsh zone (less than −2 μmol CO2·m−2·s−1) were much lower. Unvegetated ponds were typically small sources of CO2 to the atmosphere (<0.5 μmol CO2·m−2·s−1). Nighttime emissions of CO2 averaged only 35% of daytime uptake in the low marsh zone, but they exceeded daytime CO2 uptake by up to threefold in the native high marsh zone. Based on modeling, belowground biomass was the plant metric most strongly correlated with CO2 fluxes in native marsh zones, while none of the plant variables correlated significantly with CH4 fluxes. Methane fluxes did not vary between day and night and did not significantly offset CO2 uptake in any vegetated marsh zones based on sustained global warming potential calculations. These findings suggest that attention to spatial zonation as well as expanded measurements and modeling of GHG emissions across greater temporal scales will help to improve accuracy of carbon accounting in coastal marshes.

We developed spatially explicit representations for seasonal high-seas (open ocean) thermal habitats for six species of Pacific salmon (Oncorhynchus spp.) and evaluated the effects of natural climate variability and projected changes under three Intergovernmental Panel on Climate Change scenarios of future greenhouse gas emissions. Changes in high-seas habitat due to natural climatic variation in 20th century were small relative to that under anthropogenic climate change scenarios for the middle to late 21st century. Under a multimodel ensemble average of global climate model outputs using A1B (medium) emissions scenario for the entire study area (North Pacific and part of Arctic Ocean), projected winter habitats of sockeye (Oncorhynchus nerka) decreased by 38%, and summer habitat decreased by 86% for Chinook (Oncorhynchus tshawytscha), 45% for sockeye, 36% for steelhead (Oncorhynchus mykiss), 30% for coho (Oncorhynchus kisutch), 30% for pink (Oncorhynchus gorbuscha), and 29% for chum (Oncorhynchus keta) salmon by 2100. Reductions were 25% lower for B1 (lower) emissions and 7% higher for A2 (higher) emissions scenarios. Projected habitat losses were largest in the Gulf of Alaska and western and central subarctic North Pacific. Nearly complete losses of Gulf of Alaska habitat for sockeye in both seasons and Chinook in summer raise important policy issues for North American fishery managers and governments.Résumé : Nous mettons au point des représentations spatialement explicites des habitats thermiques saisonniers de hautemer (au large) de six espèces de saumons du Pacifique (Oncorhynchus spp.) et évaluons les effets de la variabilité climatique naturelle et des changements prévus dans trois scénarios d'émissions futures de gaz à effets de serre produits par le Panel intergouvernemental sur le changement climatique. Les changements dans l'habitat de haute-mer dus à la variation climatique naturelle au 20 ième siècle sont faibles par comparaison aux scénarios de changements climatiques anthropiques prédits pour le milieu et la fin du 21 e siècle. Dans la moyenne d'un ensemble multi-modèles de projections faites par des modèles de climat global, utilisant le scénario A1B (moyen) pour les émissions dans l'ensemble de la région (Pacifique Nord et partie de l'Océan Arctique), les habitats d'hiver prédits pour le saumon rouge (Oncorhynchus nerka) diminuent de 38 % et les habitats d'été sont réduits de 86 % pour le saumon chinook (Oncorhynchus tshawytscha), 45 % pour le saumon rouge, 36 % pour la truite arc-en-ciel anadrome (Oncorhynchus mykiss), 30 % pour le saumon coho (Oncorhynchus kisutch), 30 % pour le saumon rose (Oncorhynchus gorbuscha) et 29 % pour le saumon kéta (Oncorhynchus keta) vers l'année 2100. Les réduc-tions sont 25 % plus basses avec le scénario B1 (plus faible) d'émissions et 7 % plus fortes pour le scénario (plus élevé) A2. Les pertes prédites d'habitat sont les plus importantes dans le golfe de l'Alaska et les portions ouest et centrales du Pacifique Nord arctique. Les pertes presque complètes de l'h...

We used a simple, systematic data-analytics approach to determine the relative linkages of different climate and environmental variables with the canopy-level, half-hourly CO2 fluxes of US deciduous forests. Multivariate pattern recognition techniques of principal component and factor analyses were utilized to classify and group climatic, environmental, and ecological variables based on their similarity as drivers, examining their interrelation patterns at different sites. Explanatory partial least squares regression models were developed to estimate the relative linkages of CO2 fluxes with the climatic and environmental variables. Three biophysical process components adequately described the system-data variances. The 'radiation-energy' component had the strongest linkage with CO2 fluxes, whereas the 'aerodynamic' and 'temperature-hydrology' components were low to moderately linked with the carbon fluxes. On average, the 'radiation-energy' component showed 5 and 8 times stronger carbon flux linkages than that of the 'temperature-hydrology' and 'aerodynamic' components, respectively. The similarity of observed patterns among different study sites (representing gradients in climate, canopy heights and soil-formations) indicates that the findings are potentially transferable to other deciduous forests. The similarities also highlight the scope of developing parsimonious data-driven models to predict the potential sequestration of ecosystem carbon under a changing climate and environment. The presented data-analytics provides an objective, empirical foundation to obtain crucial mechanistic insights; complementing process-based model building with a warranted complexity. Model efficiency and accuracy (R(2) = 0.55-0.81; ratio of root-mean-square error to the observed standard deviations, RSR = 0.44-0.67) reiterate the usefulness of multivariate analytics models for gap-filling of instantaneous flux data.

Hydrological processes of the wetland complex in the Prairie Pothole Region (PPR) are difficult to model, partly due to a lack of wetland morphology data. We used Light Detection And Ranging (LiDAR) data sets to derive wetland features; we then modelled rainfall, snowfall, snowmelt, runoff, evaporation, the "fill-and-spill" mechanism, shallow groundwater loss, and the effect of wet and dry conditions. For large wetlands with a volume greater than thousands of cubic metres (e.g. about 3000 m 3 ), the modelled water volume agreed fairly well with observations; however, it did not succeed for small wetlands (e.g. volume less than 450 m 3 ). Despite the failure for small wetlands, the modelled water area of the wetland complex coincided well with interpretation of aerial photographs, showing a linear regression with R 2 of around 0.80 and a mean average error of around 0.55 km 2 . The next step is to improve the water budget modelling for small wetlands. Résumé Les processus hydrologiques du complexe de zones humides de la région des fondrières des prairies sont difficiles à modéliser, en partie à cause d'un manque de données de morphologie des zones humides. Nous avons utilisé des jeux de données LiDAR (Light Detection And Ranging) pour calculer les caractéristiques des zones humides. Nous avons ensuite modélisé les pluies, les précipitations neigeuses, la fonte des neiges, le ruissellement, l'évaporation, le mécanisme de débordement par saturation, les pertes des eaux souterraines peu profondes, et l'effet des conditions humides et sèches. Pour les zones humides étendues ayant un volume supérieur à quelques milliers de mètres cubes (par exemple, environ 3000 m 3 ), le volume d'eau modélisé s'accorde assez bien avec les observations, mais le modèle a été tenu en échec pour les zones humides de petite taille (par exemple, volume inférieur à 450 m 3 ). Malgré l'échec pour les petites zones humides, la zone d'eau modélisée du complexe de zones humides coïncidait bien avec l'interprétation des photographies aériennes, montrant une régression linéaire avec un R 2 de l'ordre de 0,80 et une erreur moyenne autour de 0,55 km 2 . La prochaine étape est d'améliorer la modélisation du bilan hydrique pour les zones humides de petite taille.

A systematic data analytics was employed to determine the relative linkages of stream water quality and environmental health with the land use and hydrologic drivers in the coastal‐urban watersheds of southeast Florida. Power law‐based partial least squares regression models were developed to reliably estimate the linkages by appropriately resolving multicollinearity (Nash‐Sutcliffe efficiency = 0.72–0.95). The analytics indicated Everglades as the external and the largest source of total nitrogen (TN) in the coastal‐urban streams for both wet (June–October) and dry (November–May) seasons. The “external driver” exhibited 1.5–2 times stronger control on stream TN than that of the watershed “land use,” “hydrology,” and the “upstream reach” contributions. In contrast, Everglades appeared to be a minor source of in‐stream total phosphorus (TP), which was predominantly controlled by the internal watershed processes. TP was most strongly linked with the upstream reach concentrations and watershed land uses in the wet and dry seasons, respectively. Despite the predominantly built‐up fraction (74%) of the study area, agricultural land was the most substantial watershed source of in‐stream nutrients. The linkages of algal biomass (Chl a) with the drivers indicated TP as the limiting nutrient. Stream dissolved oxygen was most strongly influenced by the adjacent groundwater depth and watershed land uses, respectively, in the wet and dry seasons. The estimated relative linkages and insights would be useful to identify the management targets and priorities to achieve healthy coastal‐urban stream ecosystems in southeast Florida and around the world.