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Climate change will significantly impact the world’s ecosystems, in part by altering species interactions and ecological processes, such as herbivory and plant community dynamics, which may impact forage quality and ecosystem production. Yet relatively few field experimental manipulations assessing all of these parameters have been performed to date. To help fill this knowledge gap, we evaluated the effects of increased temperature (+3°C day and night, year-round) and precipitation (+30% of mean annual rainfall) on slug herbivory and abundance and plant community dynamics biweekly in a pasture located in central Kentucky, U.S.A. Warming increased slug abundance once during the winter, likely due to improving conditions for foraging, whereas warming reduced slug abundance at times in late spring, mid-summer, and early fall (from 62–95% reduction depending on month). We found that warming and increased precipitation did not significantly modify slug herbivory at our site, despite altering slug abundance and affecting plant community composition and forage quality. Climate change will alter seasonal patterns of slug abundance through both direct effects on slug biology and indirect effects mediated by changes in the plant community, suggesting that pasture management practices may have to adapt.

Recent increases in the burn area and severity of wildfires in the western US have raised concerns about the impact on stream water temperature–a key determinant of cold-water fish habitats. However, the effect on seasonal water temperatures of concern, including winter and summer, are not fully understood. In this study, we assessed the impact of wildfire burns at Boulder Creek (Oregon), Elk Creek (Oregon), and Gibbon River (Wyoming) watersheds on the downstream winter and summer water temperatures for the first three post-fire years. To obtain results independent of the choice of the analytical method, we evaluated the consequence of each burn using three different statistical approaches that utilize local water temperature data. Our results from the three approaches indicated that the response of water temperatures to wildfire burns varied across seasons and sites. Wildfire burns were associated with a median increase of up to 0.56°C (Standard Error; S.E. < 0.23°C) in the summer mean water temperatures (MWT) and 62 degree-day Celsius (DDC; S.E. < 20.7 DDC) in the summer accumulated degree days (ADD) for the three subsequent years across studied stream sites. Interestingly, these burns also corresponded to a median decrease of up to 0.49°C (S.E. < 0.45°C) in the winter MWT and 39 DDC (S.E. < 40.5 DDC) in the winter ADD for the same period across sites. Wildfire effects on the downstream water temperatures diminished with increasing site distance from the burn perimeter. Our analyses demonstrated that analytical methods that utilize local watershed data could be applied to evaluate fire effects on downstream water temperatures.

Recent studies evaluating multiple years of groundwater radioiodine (¹²⁹I) concentration in a riparian wetland located in South Carolina, USA identified strong seasonal concentration fluctuations, such that summer concentrations were much greater than winter concentrations. These fluctuations were observed only in the wetlands but not in the upland portion of the plume and only with ¹²⁹I, and not with other contaminants of anthropogenic origin: nitrate/nitrite, strontium-90, technecium-99, tritium, or uranium. This unexplained observation was hypothesized to be the result of strongly coupled processes involving hydrology, water temperature, microbiology, and chemistry. To test this hypothesis, an extensive historical groundwater database was evaluated, and additional measurements of total iodine and iodine speciation were made from recently collected samples. During the summer, the water table decreased by as much as 0.7 m, surface water temperature increased by as much as 15 °C, and total iodine concentrations were consistently greater (up to 680%) than the following winter months. Most of the additional iodine observed in the summer could be attributed to proportional gains in organo-iodine, and not iodide or iodate. Furthermore, ¹²⁹I concentrations were observed to be two-orders-of-magnitude greater at the bottom of the upland aquifer than at the top. A coupled hydrological and biogeochemical conceptual model is proposed to tie these observations together. First, as the surface water temperature increased during the summer, microbial activity was enhanced, which in turn stimulated the formation of mobile organo-I. Hydrological processes were also likely involved in the observed iodine seasonal changes: (1) as the water table decreased in summer, the remaining upland water entering the wetland was comprised of a greater proportion of water containing elevated iodine concentrations from the low depths, and (2) water flow paths in summer changed such that the wells intercepted more of the contaminant plume and less of the diluting rainwater (due to evapotranspiration) and streamwater (as the lower levels promote a predominantly recharging system). Furthermore, these results underscore the importance of coupled processes influencing contaminant concentrations, and the need to assess seasonal contaminant variations to optimize long-term monitoring programs of wetlands.

The objective of this study was to explore the effects of time, seasons, and total carbon (TC) on Copper (Cu) and Zinc (Zn) deposition in the surface sediments. This study was performed at the H-02 constructed wetland on the Savannah River Site (Aiken, SC, USA). Covering both warm (April-September) and cool (October-March) seasons, several sediment cores were collected twice a year from the H-02 constructed wetland cells from 2007 to 2013. Total concentrations of Cu and Zn were measured in the sediments. Concentrations of Cu and Zn (mean ± standard deviation) in the surface sediments over 7 years of operation increased from 6.0 ± 2.8 and 14.6 ± 4.5 mg kg^-1 to 139.6 ± 87.7 and 279.3 ± 202.9 mg kg^-1 dry weight, respectively. The linear regression model explained the behavior and the variability of Cu deposition in the sediments. On the other hand, using the generalized least squares extension with the linear regression model allowed for unequal variance and thus produced a model that explained the variance properly, and as a result, was more successful in explaining the pattern of Zn deposition. Total carbon significantly affected both Cu (p = 0.047) and Zn (p < 0.001). Time effect on Cu deposition was statistically significant (p = 0.013), whereas Zn was significantly affected by the season (p = 0.009).

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. In this study, we develop the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Several calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed. When accounting for recycling of N through plant litter turnover, rock weathering accounts for approximately 12% of the annual dissolved N sources to the watershed in the most probable calibration scenario (0–31% in other scenarios), and 21% (0–44% in other scenarios) when considering only “new” N sources (i.e. geogenic and atmospheric). On an annual scale, instream dissolved N elimination, plant turnover (including cattle grazing) and atmospheric deposition are the most important controls on N cycling.

Glacierized mountain environments can preserve and release mercury (Hg) and play an important role in regional Hg cycling. In the Tibetan Plateau (TP), most glaciers have been retreating at unprecedented rate in recent decades, acting as one of the most active factors in regional hydrological cycling. In this mini-review, we summarized recent studies on Hg distribution, transport, and accumulation in Tibetan glacierized environments. We highlight that melting glacier may represent a stimulator that exports Hg to glacier-fed ecosystems. We identified major knowledge gaps and proposed future research needs with several emphases, including quantifying Hg in glacier ablation zone, depicting Hg transport and transformation in glacial rivers during spring melt season, and better constraining glacier-export Hg and its environmental risks to the downstream. Besides, Hg isotopic technical, passive sampling and hydrological transport model should be utilized to improve the understanding of Hg cycling in high mountain regions in the TP.

Associative N fixation (ANF), the process by which dinitrogen gas is converted to ammonia by bacteria in casual association with plants, has not been well-studied in temperate ecosystems. We examined the ANF potential of switchgrass (Panicum virgatum L.), a North American prairie grass whose productivity is often unresponsive to N fertilizer addition, via separate short-term ¹⁵N₂ incubations of rhizosphere soils and excised roots four times during the growing season. Measurements occurred along N fertilization gradients at two sites with contrasting soil fertility (Wisconsin, USA Mollisols and Michigan, USA Alfisols). In general, we found that ANF potentials declined with long-term N addition, corresponding with increased soil N availability. Although we hypothesized that ANF potential would track plant N demand through the growing season, the highest root fixation rates occurred after plants senesced, suggesting that root diazotrophs exploit carbon (C) released during senescence, as C is translocated from aboveground tissues to roots for wintertime storage. Measured ANF potentials, coupled with mass balance calculations, suggest that ANF appears to be an important source of N to unfertilized switchgrass, and, by extension, to temperate grasslands in general.

Abstract This study explores water vapor turbulence in the convective boundary layer (CBL) using the Raman lidar observations from the Atmospheric Radiation Measurement site located at Darwin, Australia. An autocovariance technique was used to separate out the random instrument error from the atmospheric variability during time periods when the CBL is cloud‐free, quasi‐stationary, and well mixed. We identified 45 cases, comprising of 8 wet and 37 dry seasons events, over the 5‐year data record period. The dry season in Darwin is known by warm and dry sunny days, while the wet season is characterized by high humidity and monsoonal rains. The inherent variability of the latter resulted in a more limited number of cases during the wet season. Profiles of the integral scale, variance, coefficient of the structure function, and skewness were analyzed and compared with similar observations from the Raman lidar at the Atmospheric Radiation Measurement Southern Great Plains (SGP) site. The wet season shows larger median variance profiles than the dry season, while the median profile of the variance from the dry season and the SGP site are found to be more comparable particularly between 0.4 and 0.75 z _i . The variance and coefficient of the structure function show qualitatively the same vertical pattern. Furthermore, deeper CBL, larger gradient of water vapor mixing ratio at z _i , and the strong correlation with the water vapor variance at z _i are seen during the dry season. The median value in the skewness is mostly positive below 0.6 z _i unlike the SGP site.

Highlights: • Future Tmax increases will be greater in May to October period than other months. • Sub-basins temperature change order: Superior > Huron > Michigan > Erie and Ontario. • Future Tmax and Tmin changes will be different over land areas and the Great Lakes. • Project extreme warm (Tmax ≥ 29°C ~ 32°C) and cold (Tmax ≤ -5°C ~ 0°C) day changes. • Identify some fluctuations of latitudinal temperature gradients in this region. The Great Lakes Basin is an important agricultural region for both the United States and Canada. The regional crop growths are affected by inter-annual climatic conditions and intra-seasonal variability. Consequently, monthly climate change projection data can provide more useful information for crop management than seasonal climate projections. However, very few studies undertaken for the Great Lakes Basin have focused on monthly timescales. In this study, we investigate the projected mid-century (2030–2059) monthly mean maximum temperature (Tmax) and minimum temperature changes of this region, relative to the baseline period (1980–2009). Future Tmax increases in this region are likely to be greater during the May to October period (coinciding with the region's growing season) than in other months. The order of magnitude of future Tmax and Tmin changes of the five Great Lakes sub-basins are Superior > Huron > Michigan > Erie and Ontario. Most future Tmax changes over land areas are higher than those over the lakes, whereas Tmin changes are likely to be higher over lakes than over the adjacent land areas in this region. The future number of extreme warm days (Tmax ≥ 29–32 °C) in this region will increase by between about 5 days (in the north) to 40 days (in southern parts of the basin), while the number of winter cold days (Tmax ≤ −5 °C ~ 0 °C) may decrease by between 3 days (south) and 35 days (north). This study furthermore identifies some fluctuations of latitudinal temperature gradients in the Great Lakes Basin, these areas covering the north latitude 40.5–41.5°, 43.5–44.0°, 45.5–46.5°, and 47.5–49.5°.