Search for: All records

Abstract Wildfires have increased in size, frequency, and intensity in arid regions of the western United States because of human activity, changing land use, and rising temperature. Fire can degrade water quality, reshape aquatic habitat, and increase the risk of high discharge and erosion. Drawing from patterns in montane dry forest, chaparral, and desert ecosystems, we developed a conceptual framework describing how interactions and feedbacks among material accumulation, combustion of fuels, and hydrologic transport influence the effects of fire on streams. Accumulation and flammability of fuels shift in opposition along gradients of aridity, influencing the materials available for transport. Hydrologic transport of combustion products and materials accumulated after fire can propagate the effects of fire to unburned stream–riparian corridors, and episodic precipitation characteristic of arid lands can cause lags, spatial heterogeneity, and feedbacks in response. Resolving uncertainty in fire effects on arid catchments will require monitoring across hydroclimatic gradients and episodic precipitation. 

Abstract Floodplain lakes are widespread and ecologically important throughout tropical river systems, however data are rare that describe how temporal variations in hydrological, meteorological and optical conditions moderate stratification and mixing in these shallow lakes. Using time series measurements of meteorology and water‐column temperatures from 17 several day campaigns spanning two hydrological years in a representative Amazon floodplain lake, we calculated surface energy fluxes and thermal stratification, and applied and evaluated a 3‐dimensional hydrodynamic model. The model successfully simulated diel cycles in thermal structure characterized by buoyancy frequency, depth of the actively mixing layer, and other terms associated with the surface energy budget. Diurnal heating with strong stratification and nocturnal mixing were common; despite considerable heat loss at night, the strong stratification during the day meant that mixing only infrequently extended to the bottom at night. Simulations indicated that the diurnal thermocline up and downwelled creating lake‐wide differences in near‐surface temperatures and mixing depths. Infrequent full mixing creates conditions conducive to anoxia in these shallow lakes given their warm temperatures. 

Abstract The CO₂flux () from lakes to the atmosphere is a large component of the global carbon cycle and depends on the air–water CO₂concentration gradient (ΔCO₂) and the gas transfer velocity (k). Both ΔCO₂andkcan vary on multiple timescales and understanding their contributions to is important for explaining variability in fluxes and developing optimal sampling designs. We measured and ΔCO₂and derivedkfor one full ice‐free period in 18 lakes using floating chambers and estimated the contributions of ΔCO₂andkto variability. Generally,kcontributed more than ΔCO₂to short‐term (1–9 d) variability. With increased temporal period, the contribution ofkto variability decreased, and in some lakes resulted in ΔCO₂contributing more thankto variability over the full ice‐free period. Increased contribution of ΔCO₂to variability over time occurred across all lakes but was most apparent in large‐volume southern‐boreal lakes and in deeper (> 2 m) parts of lakes, whereaskwas linked to variability in shallow waters. Accordingly, knowing the variability of bothkand ΔCO₂over time and space is needed for accurate modeling of from these variables. We conclude that priority in assessments should be given to direct measurements of at multiple sites when possible, or otherwise from spatially distributed measurements of ΔCO₂combined withk‐models that incorporate spatial variability of lake thermal structure and meteorology. 

Abstract Floodplains lakes are abundant in the Amazon basin and are important methane sources to the atmosphere. Existing biogeochemical models require modifications and inclusion of hydrodynamic processes operative in shallow, warm waters to be applied to these aquatic ecosystems. We modified a 1‐dimensional process‐based, lake biogeochemical model and combined a 3‐dimensional hydrodynamic model to suit Amazon floodplains. We evaluated the combined model's performance simulating methane concentrations and fluxes and several related processes in the open lake and an embayment of a well‐studied Amazon lake. Parameters for calibration were selected through sensitivity tests using a machine learning‐based algorithm, classification, and regression trees. Comparison between simulated and measured fluxes indicate generally good agreement in seasonal patterns and magnitudes. Comparisons of near‐surface concentrations varied with no clear patterns. Simulations of methane concentrations at near‐surface and near‐bottom, and diffusive emissions are most sensitive to carbon mineralization rate, Q₁₀factors for methanogenesis and oxidation, and methane oxidation potential. Modeled rates of planktonic photosynthesis were generally lower than measurements, though simulated planktonic respiration was often similar to measurements. Simulated rates of methane oxidation were considerably lower, with a few exceptions, than measurements of methane oxidation in oxic water of the lake. Improvements of results of the linked hydrodynamic‐biogeochemical model will result from inclusion of advective transport, use of parameter values appropriate for tropical waters, especially for methane oxidation and photosynthesis, and addition of changes in hydrostatic pressure to model of ebullition. 

Abstract Increased occurrence, size, and intensity of fire result in significant but variable changes to hydrology and material retention in watersheds with concomitant effects on stream biogeochemistry. In arid regions, seasonal and episodic precipitation results in intermittency in flows connecting watersheds to recipient streams that can delay the effects of fire on stream chemistry. We investigated how the spatial extent of fire within watersheds interacts with variability in amount and timing of precipitation to influence stream chemistry of three forested, montane watersheds in a monsoonal climate and four coastal, chaparral watersheds in a Mediterranean climate. We applied state-space models to estimate effects of precipitation, fire, and their interaction on stream chemistry up to five years following fire using 15 + years of monthly observations. Precipitation alone diluted specific conductance and flushed nitrate and phosphate to Mediterranean streams. Fire had positive and negative effects on specific conductance in both climates, whereas ammonium and nitrate concentrations increased following fire in Mediterranean streams. Fire and precipitation had positive interactive effects on specific conductance in monsoonal streams and on ammonium in Mediterranean streams. In most cases, the effects of fire and its interaction with precipitation persisted or were lagged 2–5 years. These results suggest that precipitation influences the timing and intensity of the effects of fire on stream solute dynamics in aridland watersheds, but these responses vary by climate, solute, and watershed characteristics. Time series models were applied to data from long-term monitoring that included observations before and after fire, yielding estimated effects of fire on aridland stream chemistry. This statistical approach captured effects of local-scale temporal variation, including delayed responses to fire, and may be used to reduce uncertainty in predicted responses of water quality under changing fire and precipitation regimes of arid lands. 

Severe deterioration of water quality in lakes, characterized by overabundance of algae and declining dissolved oxygen in the deep lake (DO B ), was one of the ecological crises of the 20th century. Even with large reductions in phosphorus loading, termed “reoligotrophication,” DO B and chlorophyll (CHL) have often not returned to their expected pre–20th-century levels. Concurrently, management of lake health has been confounded by possible consequences of climate change, particularly since the effects of climate are not neatly separable from the effects of eutrophication. Here, using Lake Geneva as an iconic example, we demonstrate a complementary alternative to parametric models for understanding and managing lake systems. This involves establishing an empirically-driven baseline that uses supervised machine learning to capture the changing interdependencies among biogeochemical variables and then combining the empirical model with a more conventional equation-based model of lake physics to predict DO B over decadal time-scales. The hybrid model not only leads to substantially better forecasts, but also to a more actionable description of the emergent rates and processes (biogeochemical, ecological, etc.) that drive water quality. Notably, the hybrid model suggests that the impact of a moderate 3°C air temperature increase on water quality would be on the same order as the eutrophication of the previous century. The study provides a template and a practical path forward to cope with shifts in ecology to manage environmental systems for non-analogue futures.