Limnology and Oceanography Letters最新文献

Viruses infecting aquatic microbes vary immensely in size, but the ecological consequences of virus size are poorly understood. Here we used a unique suite of diverse phytoplankton strains and their viruses, all isolated from waters around Hawai'i, to assess whether virus size affects the suppression of host populations. We found that small viruses of diverse genome type (3–24 kb genome size, 23–70 nm capsid diameter) have very similar effects on host populations, suppressing hosts less strongly and for a shorter period of time compared to large double-stranded DNA viruses (214–1380 kb, 112–386 nm). Suppressive effects of larger viruses were more heterogeneous, but most isolates reduced host populations by many orders of magnitude, without recovery over the ~ 25-d experiments. Our results suggest that disparate lineages of viruses may have ecological consequences that are predictable in part based on size, and that ecosystem impacts of viral infection may vary with the size structure of the viral community.

Fish inhabiting similar environments face space and resource constraints, develop diverse feeding strategies, and adjust their trophic niches during ontogeny to reduce competition. To investigate this process, we reconstructed the trophic trajectory of five species of the family Sciaenidae by analyzing δ¹³C and δ¹⁵N values in otolith organic matter along the growth axis of the otolith. We developed and optimized the approach by aligning isotope values with an age range estimated using growth ring counts and three-dimensional scanning of otolith morphology during organic matter extraction. δ¹³C values indicated habitat shifts, and δ¹⁵N values provided insights into trophic level changes, showing that sciaenids use benthic resources throughout their lifespan and may move closer to estuarine environments at approximately an age range from 1.5 to 3 yr old. During the early life stages, their diet consists of herbivores. As they grow, competition among age groups and species appears to be minimized.

Land permafrost thaw transfers increasing amounts of organic matter and nutrients to the Arctic Ocean. These nutrients could stimulate primary production directly, or indirectly following remineralization in sediments. Projections of this effect are limited by scarce observations and poor understanding of the underlying controls. Here, we focus on the Kara, Laptev, and East Siberian Sea shelves that receive strong input from large rivers and coastal erosion, linking ship-board measurements of sediment–water nutrient fluxes to environmental parameters associated with land input. Ammonium and nitrite releases were positively related to high concentration and low decomposition state of terrigenous organic matter, based on biomarkers. Nitrate release was related to O₂ penetration depth. Phosphate and silicate release were highest at stations with strong marine influence. Our findings suggest that changes in environmental conditions, such as land input, might alter the nutrient balance in the Siberian Arctic Ocean, with implications for ecological and biogeochemical processes.

Quantifying and predicting precipitation and water flow and their influences is challenged by the dynamic relationships between and timing of precipitation and water fluxes. To help with these challenges, scientists use “water year” to examine and predict the impacts of precipitation and relevant extreme climatic and hydrological events on ecosystems. However, traditional water year definitions used in the US lack a consideration of areal variation in climate and hydrology, which is needed when studying ecosystems at regional or national scales. We developed local water year (LWY) values that consider spatial variation using existing definitions whereby the water year begins in the month with the lowest or highest average monthly streamflow. We employed spatial interpolation to assign LWY start and end months to 202 subregions across the conterminous United States that range from 4,384 to 134,755 km². This dataset can be linked with diverse climate, terrestrial, and aquatic data for broad-scale studies.

While climate change affects the phytoplankton biodiversity at both local and global scales, predicting phytoplankton community responses to warming is impaired by their polyphyletic complexity. High mountain lakes are highly vulnerable systems, partly due to their limited biodiversity, and forecasting their ecological trajectories is a key challenge for scientists and conservation managers. We evaluated the phytoplankton's sensitivity to temperature in 24 high-altitude lakes over a multi-year (average 7-year) study. We detected assemblage-specific responses to warming, with different trends in biovolume and diversity observed among the diatom-dominant, mixed-mixotrophs dominant, and colonial-green dominant assemblages. The environmental settings partly governed assemblage responses, highlighting the role of the landscape filters in determining the response to warming. The biological stability of lakes, that is, their ability to resist shifts in their phytoplankton assemblage, is therefore determined both by the lake characteristics and warming intensity.

The daily cycle of solar radiation has a profound influence in structuring the physiology of microbes in the euphotic zone and subsequently setting the degree of coupling across trophic levels within ocean ecosystems. There has been an upsurge of interest in the biological role of the diel cycle and the ability to probe it using molecular approaches (i.e., “omics”), which now allow us to pinpoint the level of detail of the diel cycle that is required to better understand microbes' roles across multiple biogeochemical cycles. Although sampling the diel cycle requires additional resources, the payback is large. A better understanding of the diel cycle provides a holistic framework with which to align patterns and causal sequences across multi-omic layers, yielding consequent connections with metabolic processes to develop more robust mechanistic models. Such models provide the stepping stones to better understand how resource allocation in cells is driven by environmental forcing.

Understanding the impacts of multiple environmental stressors on phytoplankton biomass is crucial for predicting marine ecosystem responses under global climate change. This study employed a sequential modeling framework integrating principal component analysis, generalized additive models, and artificial neural networks to improve predictions of phytoplankton chlorophyll a concentrations in the Taiwan Strait. Analyzing a decadal dataset, we found that a 2°C rise in sea surface temperature and a 0.2 pH decline will each lead to an 11.3% reduction in chlorophyll a biomass, whereas nitrogen enrichment is expected to increase it by only 2.8%. The combined effects of these stressors will result in an 18.3% reduction, with the most significant declines occurring in high-chlorophyll areas during algal blooms. Compared to simpler models, our approach improved accuracy by reducing overestimation biases, particularly under acidification scenarios, highlighting the need for advanced, multivariate models in forecasting phytoplankton dynamics under global changes.

Litter decomposition is usually modeled with the negative exponential model, which assumes constant proportional mass loss. We assessed this assumption and its interpretive consequences using 145 stream litter mass loss time series and process-based simulations. Relatively simple (two to three parameters) models allowing time-varying decay rates produced more accurate predictions and were generally more parsimonious. Decomposition trajectories strongly deviated from constant decay for at least 50% of the time series, with the shape influenced by the degree of decomposition covered by a time series. Finally, simulations and empirical evidence suggested that the degree of decomposition covered can interact with time-varying decay rates and leachability to bias estimates of breakdown rates (k) from negative exponential models, obfuscating comparisons within and across studies. Considering alternative models could accelerate understanding and prediction of litter decomposition dynamics by enabling investigation of time-explicit decomposition dynamics and more precise modeling when warranted.

Freshwater systems are important sources of atmospheric methane (CH₄). However, estimated emissions are associated with high uncertainties due to limited knowledge about the temporal variability in emissions and their associated controls, such as air–water gas transfer velocity. Here, we determined the gas transfer velocity of CH₄ based on a novel measurement setup that combines simultaneous eddy covariance flux measurements with continuously monitored CH₄ water- and air-side concentrations. Measurements were conducted during a 10-d campaign in a freshwater lake in mid-Sweden. The gas transfer velocity fell within the range of existing wind-speed-based parameterizations derived for carbon dioxide in other lakes. For wind speeds below 4 m s⁻¹, the gas transfer velocity for CH₄ followed parameterizations predicting faster gas exchange, while for wind speeds above 5 m s⁻¹, it aligned with those predicting relatively lower gas exchange. This pattern can be explained by ebullition. Extending the wind speed range for such combined eddy covariance measurements with continuously monitored CH₄ water- and air-side concentrations would improve model reliability.

Cold thermal refuges may mitigate detrimental effects of future climate warming; yet, pond ecosystems have been largely omitted from thermal refuge research despite being globally numerous and providing critical ecosystem services. We create a formal definition for pond thermal refuge quality, then operationalize this definition by measuring the thermal characteristics and environmental attributes of ponds near Mount St. Helens (Washington, USA) to determine the environmental features that promote or hinder pond thermal refuges. Our results reveal substantial variation in thermal refuge quality between ponds and indicate that within-pond thermal refuges are a distinct metric from pond surface temperature. Denser floating surface vegetation promoted thermal refuges during summer conditions, while floating surface vegetation, water clarity, and canopy cover were associated with reduced mean pond temperatures during summer and heatwave conditions. These findings help identify ponds with high conservation value and suggest actionable steps for heightening the quality of pond thermal refuges.