The forest, the cicadas and the holey fluxes: Periodical cicada impacts on soil respiration depends on tree mycorrhizal type

The emergence of billions of periodical cicadas affects plant and animal communities profoundly, yet little is known about cicada impacts on soil carbon fluxes. We investigated the effects of Brood X cicadas (Magicicada septendecim, M. cassinii and M. septendeculain) on soil CO2 fluxes (RS ) in three Indiana forests. We hypothesized RS would be sensitive to emergence hole density, with the greatest effects occurring in soils with the lowest ambient fluxes. In support of our hypothesis, RS increased with increasing hole density and greater effects were observed near AM-associating trees (which expressed lower ambient fluxes) than near EcM-associating trees. Additionally, RS from emergence holes increased the temperature sensitivity (Q10 ) of RS by 13%, elevating the Q10 of ecosystem respiration. Brood X cicadas increased annual RS by ca. 2.5%, translating to an additional 717 Gg of CO2 across forested areas. As such, periodical cicadas can have substantial effects on soil processes and biogeochemistry.

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots, and microbes, and gradients in water potential drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in-situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely-sensed proxies. Together, these considerations offer a roadmap for clearer links between ecohydrological processes and the water potential gradients that have the 'potential' to substantially reduce conceptual and modeling uncertainties.

Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: successes and challenges

Decision-support tools (DSTs) are often produced from collaborations between technical experts and stakeholders to address environmental problems and inform decision making. Studies in the past two decades have provided key insights on the use of DSTs and the importance of bidirectional information flows among technical experts and stakeholders - a process that is variously referred to as co-production, participatory modeling, structured decision making, or simply stakeholder participation. Many of these studies have elicited foundational insights for the broad field of water resources management; however, questions remain on approaches for balancing co-production with uncertainty specifically for watershed modeling decision support tools. In this paper, we outline a simple conceptual model that focuses on the DST development process. Then, using watershed modeling case studies found in the literature, we discuss successful outcomes and challenges associated with embedding various forms of co-production into each stage of the conceptual model. We also emphasize the "3 Cs" (i.e., characterization, calculation, communication) of uncertainty and provide evidence-based suggestions for their incorporation in the watershed modeling DST development process. We conclude by presenting a list of best practices derived from current literature for achieving effective and robust watershed modeling decision-support tools.

The Potential Impacts of Climate Change on Biodiversity in Flowing Freshwater Systems

Ongoing increases in air temperature and changing precipitation patterns are altering water temperatures and flow regimes in lotic freshwater systems, and these changes are expected to continue in the coming century. Freshwater taxa are responding to these changes at all levels of biological organization. The generation of appropriate hydrologic and water temperature projections is critical to accurately predict the impacts of climate change on freshwater systems in the coming decade. The goal of this review is to provide an overview of how changes in climate affect hydrologic processes and how climate-induced changes in freshwater habitat can impact the life histories and traits of individuals, and the distributions of freshwater populations and biodiversity. Projections of biological responses during the coming century will depend on accurately representing the spatially varying sensitivity of physical systems to changes in climate, as well as acknowledging the spatially varying sensitivity of freshwater taxa to changes in environmental conditions.

MOESHA: A Genetic Algorithm for Automatic Calibration and Estimation of Parameter Uncertainty and Sensitivity of Hydrologic Models

Characterization of the uncertainty and sensitivity of model parameters is an essential facet of hydrologic modeling. This article introduces the multi-objective evolutionary sensitivity handling algorithm (MOESHA) that combines input parameter uncertainty and sensitivity analyses with a genetic algorithm calibration routine to dynamically sample the parameter space. This novel algorithm serves as an alternative to traditional static space-sampling methods, such as stratified sampling or Latin hypercube sampling. In addition to calibrating model parameters to a hydrologic model, MOESHA determines the optimal distribution of model parameters that maximizes model robustness and minimizes error, and the results provide an estimate for model uncertainty due to the uncertainty in model parameters. Subsequently, we compare the model parameter distributions to the distribution of a dummy variable (i.e., a variable that does not affect model output) to differentiate between impactful (i.e., sensitive) and non-impactful parameters. In this way, an optimally calibrated model is produced, and estimations of model uncertainty as well as the relative impact of model parameters on model output (i.e., sensitivity) are determined. A case study using a single-cell hydrologic model (EXP-HYDRO) is used to test the method using river discharge data from the Dee River catchment in Wales. We compare the results of MOESHA with Sobol's global sensitivity analysis method and demonstrate that the algorithm is able to pinpoint non-impactful parameters, demonstrate the uncertainty of model results with respect to uncertainties in model parameters, and achieve excellent calibration results. A major drawback of the algorithm is that it is computationally expensive; therefore, parallelized methods should be used to reduce the computational burden.

Climate change impacts on streamflow and subbasin-scale hydrology in the Upper Colorado River Basin

In the Upper Colorado River Basin (UCRB), the principal source of water in the southwestern U.S., demand exceeds supply in most years, and will likely continue to rise. While General Circulation Models (GCMs) project surface temperature warming by 3.5 to 5.6°C for the area, precipitation projections are variable, with no wetter or drier consensus. We assess the impacts of projected 21^st century climatic changes on subbasins in the UCRB using the Soil and Water Assessment Tool, for all hydrologic components (snowmelt, evapotranspiration, surface runoff, subsurface runoff, and streamflow), and for 16 GCMs under the A2 emission scenario. Over the GCM ensemble, our simulations project median Spring streamflow declines of 36% by the end of the 21^st century, with increases more likely at higher elevations, and an overall range of −100 to +68%. Additionally, our results indicated Summer streamflow declines with median decreases of 46%, and an overall range of −100 to +22%. Analysis of hydrologic components indicates large spatial and temporal changes throughout the UCRB, with large snowmelt declines and temporal shifts in most hydrologic components. Warmer temperatures increase average annual evapotranspiration by ∼23%, with shifting seasonal soil moisture availability driving these increases in late Winter and early Spring. For the high-elevation water-generating regions, modest precipitation decreases result in an even greater water yield decrease with less available snowmelt. Precipitation increases with modest warming do not translate into the same magnitude of water-yield increases due to slight decreases in snowmelt and increases in evapotranspiration. For these basins, whether modest warming is associated with precipitation decreases or increases, continued rising temperatures may make drier futures. Subsequently, many subbasins are projected to turn from semi-arid to arid conditions by the 2080 s. In conclusion, water availability in the UCRB could significantly decline with adverse consequences for water supplies, agriculture, and ecosystem health.

Assessment of climate change impacts on hydrology and water quality with a watershed modeling approach

The assessment of hydrologic responses to climate change is required in watershed management and planning to protect water resources and environmental quality. This study is designed to evaluate and enhance watershed modeling approach in characterizing climate change impacts on water supply and ecosystem stressors. Soil and Water Assessment Tool (SWAT) was selected as a base model, and improved for the CO2 dependence of potential evapotranspiration and stream temperature prediction. The updated model was applied to quantify the impacts of projected 21st century climate change in the northern Coastal Ranges and western Sierra Nevada, which are important water source areas and aquatic habitats of California. Evapotranspiration response to CO2 concentration varied with vegetation type. For the forest-dominated watersheds in this study, only moderate (1-3%) reductions on evapotranspiration were predicted by solely elevating CO2 concentration under emission scenarios A2 and B1. Modeling results suggested increases in annual average stream temperature proportional to the projected increases in air temperature. Although no temporal trend was confirmed for annual precipitation in California, increases of precipitation and streamflow during winter months and decreases in summers were predicted. Decreased streamflow during summertime, together with the higher projected air temperature in summer than in winter, would increase stream temperature during those months and result in unfavorable conditions for cold-water species. Compared to the present-day conditions, 30-60 more days per year were predicted with average stream temperature >20°C during 2090s. Overall, the hydrologic cycle and water quality of headwater drainage basins of California, especially their seasonality, are very sensitive to projected climate change.

Sensitivity of agricultural runoff loads to rising levels of CO2 and climate change in the San Joaquin Valley watershed of California

The Soil and Water Assessment Tool (SWAT) was used to assess the impact of climate change on sediment, nitrate, phosphorus and pesticide (diazinon and chlorpyrifos) runoff in the San Joaquin watershed in California. This study used modeling techniques that include variations of CO(2), temperature, and precipitation to quantify these responses. Precipitation had a greater impact on agricultural runoff compared to changes in either CO(2) concentration or temperature. Increase of precipitation by +/-10% and +/-20% generally changed agricultural runoff proportionally. Solely increasing CO(2) concentration resulted in an increase in nitrate, phosphorus, and chlorpyrifos yield by 4.2, 7.8, and 6.4%, respectively, and a decrease in sediment and diazinon yield by 6.3 and 5.3%, respectively, in comparison to the present-day reference scenario. Only increasing temperature reduced yields of all agricultural runoff components. The results suggest that agricultural runoff in the San Joaquin watershed is sensitive to precipitation, temperature, and CO(2) concentration changes.