Global lake thermal regions shift under climate change

Temperatures and hypolimnetic oxygen in German lakes: Observations, future trends and adaptation potential

We investigated trends in temperature, stratification, and hypolimnetic oxygen concentration of German lakes under climate change using observational data and hydrodynamic modelling. Observations from 46 lakes revealed that annually averaged surface temperatures increased by + 0.5 °C between 1990 and 2020 while bottom temperatures remained almost constant. Modelling of 12 lakes predicted further increases in surface temperatures by 0.3 °C/decade until the year 2099 in the most pessimistic emission scenario RCP 8.5 (RCP 4.5: + 0.18 °C/decade; RCP 2.6: + 0.04 °C/decade). Again, bottom temperatures increased much less while summer stratification extended by up to 38 days. Using a simplified oxygen model, we showed that hypolimnetic oxygen concentrations decreased by 0.7-1.9 mg L-1 in response to the extended stratification period. However, model runs assuming lower productivity (e. g. through nutrient reduction) resulted in increased oxygen concentrations even in the most pessimistic emission scenario. Our results suggest that the negative effects of climate change on the oxygen budget of lakes can be efficiently mitigated by nutrient control.

Population origin and heritable effects mediate road salt toxicity and thermal stress in an amphibian

Human impacts on wild populations are numerous and extensive, degrading habitats and causing population declines across taxa. Though these impacts are often studied individually, wild populations typically face suites of stressors acting concomitantly, compromising the fitness of individuals and populations in ways poorly understood and not easily predicted by the effects of any single stressor. Developing understanding of the effects of multiple stressors and their potential interactions remains a critical challenge in environmental biology. Here, we focus on assessing the impacts of two prominent stressors associated with anthropogenic activities that affect many organisms across the planet - elevated salinity (e.g., from road de-icing salt) and temperature (e.g. from climate change). We examined a suite of physiological traits and components of fitness across populations of wood frogs originating from ponds that differ in their proximity to roads and thus their legacy of exposure to pollution from road salt. When experimentally exposed to road salt, wood frogs showed reduced survival (especially those from ponds adjacent to roads), divergent developmental rates, and reduced longevity. Family-level effects mediated these outcomes, but high salinity generally eroded family-level variance. When combined, exposure to both temperature and salt resulted in very low survival, and this effect was strongest in roadside populations. Taken together, these results suggest that temperature is an important stressor capable of exacerbating impacts from a prominent contaminant confronting many freshwater organisms in salinized habitats. More broadly, it appears likely that toxicity might often be underestimated in the absence of multi-stressor approaches.

Multivariate extremes in lakes

Extreme within-lake conditions have the potential to exert detrimental effects on lakes. Here we use satellite observations to investigate how the occurrence of multiple types of extremes, notably algal blooms, lake heatwaves, and low lake levels, have varied in 2724 lakes since the 1980s. Our study, which focuses on bloom-affected lakes, suggests that 75% of studied lakes have experienced a concurrent increase in at least two of the extremes considered (27% defined as having a notable increase), with 25% experiencing an increase in frequency of all three extremes (5% had a notable increase). The greatest increases in the frequency of these extremes were found in regions that have experienced increases in agricultural fertilizer use, lake warming, and a decline in water availability. As extremes in lakes become more common, understanding their impacts must be a primary focus of future studies and they must be carefully considered in future risk assessments.

Historical and projected response of Southeast Asian lakes surface water temperature to warming climate

The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts. Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986-2020) and future (2020-2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT. Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade: +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are: +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century. This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.

Climate change impact on sub-tropical lakes - Lake Kinneret as a case study

Climate change is anticipated to alter lake ecosystems by affecting water quality, potentially resulting in loss of ecosystem services. Subtropical lakes have high temperatures to begin with and are expected to exhibit higher temperatures all year round which might affect the thermal structure and ecological processes in a different manner than lakes in temperate zones. In this study the ecosystem response of the sub-tropical Lake Kinneret to climate change was explored using lake ecosystem models. Projection reliability was increased by using a weather generator and ensemble modelling, confronting uncertainty of both climate projections and lake models. The study included running two 1D hydrodynamic-biogeochemical models over one thousand realizations of two gradual temperature increase scenarios that span over 49 years. Our predictions show that an increase in air temperature would have subtle effects on stratification properties but may result in considerable changes to biogeochemical processes. Water temperature rise would cause a reduction in dissolved oxygen. Both of these changes would produce elevated phosphate and lowered ammonium concentrations. In turn, these changes are predicted to modify the phytoplankton community, expressed chiefly in increased cyanobacteria blooms at the expense of green phytoplankton and dinoflagellates; these changes may culminate in overall reduction of primary production. Identification of these trends would not be possible without the use of many realizations of climate scenarios. The use of ensemble modelling increased prediction reliability and highlighted elements of uncertainty. Though we use Lake Kinneret, the patterns identified most likely indicate processes that are expected in sub-tropical lakes in general.

Fish reproduction in a warming world: vulnerable points in hormone regulation from sex determination to spawning

Reproduction in fishes is sensitive to temperature. Elevated temperatures and anomalous 'heat waves' associated with climate change have the potential to impact fish reproductive performance and, in some cases, even induce sex reversals. Here we examine how thermal sensitivity in the hormone pathways regulating reproduction provides a framework for understanding impacts of warmer conditions on fish reproduction. Such effects will differ depending on evolved variation in temperature sensitivity of endocrine pathways regulating reproductive processes of sex determination/differentiation, gametogenesis and spawning, as well as how developmental timing of those processes varies with reproductive ecology. For fish populations unable to shift geographical range, persistence under future climates may require changes in temperature responsiveness of the hormone pathways regulating reproductive processes. How thermal sensitivity in those hormone pathways varies among populations and species, how those pathways generate temperature maxima for reproduction, and how rapidly reproductive thermal tolerances can change via adaptation or transgenerational plasticity will shape which fishes are most at risk for impaired reproduction under rising temperatures. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.

Tipping points of nitrogen use efficiency in freshwater phytoplankton along trophic state gradient

Eutrophication and harmful algal blooms have severe effects on water quality and biodiversity in lakes and reservoirs. Ecological regime shifts of phytoplankton blooms are generally thought to be driven by the rapidly rising nutrient use efficiency of bloom-forming species over short periods, and often exhibit nonlinear dynamics. Regime shifts of trophic state, eutrophication, stratification, and clear or turbid waters are well-studied topics in aquatic ecology. However, information on the prevalence of regime shifts in relationships between trophic states and phytoplankton resource transfer efficiencies in ecosystems is still lacking. Here, we provided a first insight into regime shifts in nitrogen use efficiency of phytoplankton along the trophic state gradient. We explored the regime shifts of phytoplankton resource use efficiency and detected the tipping points by combining four temporal or spatial datasets from tropical to temperate zones in Asia and Europe. We first observed significant abrupt transitions (abruptness > 1) in phytoplankton nitrogen use efficiency along the trophic state gradient. The tipping point values were lower in subtropical/tropical waterbodies (mesotrophic states; TSIc: around 50) than those in temperate zones (eutrophic states; TSIc: 60-70). The regime shifts significantly reduced the primary production transfer efficiency via zooplankton (from 0.15 ± 0.03 to 0.03 ± 0.01; mean ± standard error) in the aquatic food web. Nitrogen-fixing filamentous cyanobacteria can drive eutrophication under mesotrophic state. Our findings imply that the time-window of opportunity for harmful algae prevention and control in lakes and reservoirs is earlier in subtropical/tropical regions.

Climate change drives rapid warming and increasing heatwaves of lakes

Climate change could seriously threaten global lake ecosystems by warming lake surface water and increasing the occurrence of lake heatwaves. Yet, there are great uncertainties in quantifying lake temperature changes globally due to a lack of accurate large-scale model simulations. Here, we integrated satellite observations and a numerical model to improve lake temperature modeling and explore the multifaceted characteristics of trends in surface temperatures and lake heatwave occurrence in Chinese lakes from 1980 to 2100. Our model-data integration approach revealed that the lake surface waters have warmed at a rate of 0.11 °C 10a-1 during the period 1980-2021, being only half of the pure model-based estimate. Moreover, our analysis suggested that an asymmetric seasonal warming rate has led to a reduced temperature seasonality in eastern plain lakes but an amplified one in alpine lakes. The durations of lake heatwaves have also increased at a rate of 7.7 d 10a-1. Under the high-greenhouse-gas-emission scenario, lake surface temperature and lake heatwave duration were projected to increase by 2.2 °C and 197 d at the end of the 21st century, respectively. Such drastic changes would worsen the environmental conditions of lakes subjected to high and increasing anthropogenic pressures, posing great threats to aquatic biodiversity and human health.

Assessment of lake area in response to climate change at varying elevations: A case study of Mt. Tianshan, Central Asia

Changes in lake area (water surface area) are often considered accurate and sensitive representations of climate change. However, the role that elevation plays in this dynamic is somewhat unclear; studies remain inconclusive as to whether lake responses are consistent across elevation gradients. Here, we used Landsat and keyhole satellite images to quantify lake area changes from the 1960s to 2020 at different elevations in Central Asia's Tianshan Mountains and relate them to both climatic and anthropogenic factors. The results revealed that all low-elevation lakes showed a decreasing trend, and the total area of all monitored low-elevation lakes was reduced by 18.50 %. The total area of the mid-elevation lakes decreased by 0.16 %, while the total area of the high-elevation glacial lakes increased by 4.35 %. Lakes are recharged by a variety of influxes including glacial meltwater and precipitation. Notably, human activities (urban and agricultural water consumption) were the dominant factors in the shrinkage of low-elevation lakes. Climatic factors were the main driving factors of mid-elevation lake changes, and these lakes appeared to be more sensitive to temperature changes than lakes at other elevations. In addition, significant warming dominated area changes in high-elevation proglacial and unconnected glacial lakes. Overall, those results emphasized that when using lakes to reconstruct paleoclimates or predict lake evolution, it is necessary to consider how elevation gradients and recharge types may affect lake sensitivity to variations in climatic and anthropogenic activity.

The pace of shifting seasons in lakes

Lake ecosystems are vulnerable to seasonal thermal cues, with subtle alterations in the timing of seasonal temperatures having a dramatic influence on aquatic species. Here, a measure of seasonal change in temperature is used to describe the pace of shifting seasons in lakes. Since 1980 spring and summer temperatures in Northern Hemisphere lakes have arrived earlier (2.0- and 4.3-days decade^-1, respectively), whilst the arrival of autumn has been delayed (1.5-days decade^-1) and the summer season lengthened (5.6-days decade^-1). This century, under a high-greenhouse-gas-emission scenario, current spring and summer temperatures will arrive even earlier (3.3- and 8.3-days decade^-1, respectively), autumn temperatures will arrive later (3.1-days decade^-1), and the summer season will lengthen further (12.1-days decade^-1). These seasonal alterations will be much slower under a low-greenhouse-gas-emission scenario. Changes in seasonal temperatures will benefit some species, by prolonging the growing season, but negatively impact others, by leading to phenological mismatches in critical activities.

Warming of surface water in the large and shallow lakes across the Yangtze River Basin, China, and its driver analysis

A variety of physical, chemical, and biological processes within the lakes relies on the surface water temperature while the spatial pattern of large lakes of different warming trends and their connections with climate change remain unclear. Using correlation analysis, regression tree analysis (RTA), and general linear models (GLMs), we have estimated the warming trends of 192 lakes since 2000 in the populated Yangtze River Basin, China, to identify dominant climate drivers and quantify their contributions. The results show that surface water temperature has increased substantially in the majority of the investigated lakes (179 from a total of 192 lakes) at a rate of 0.29 (- 0.12 to 0.62) °C/decade (median and 95% confidence interval). The shallower lakes (< 13.1 m in depth) usually have the faster median warming rates than the deeper lakes (i.e., 0.37 °C/decade versus 0.16 °C/decade). We find that in the shallow lakes, rising air temperatures and declining wind speeds can explain the majority of variation in surface water temperature (i.e., 31.4‒80.3% and 13.0‒21.0%, respectively). In contrast, in deeper lakes, change of air temperatures plays a dominant role in water warming (75.4‒91.2%). This study has emphasized the importance of declining wind speed in water warming in large and shallow lakes and illustrated a difference of dominant climatic drivers in water warming between the shallow and deep lakes.

Heavy Metals Exacerbate the Effect of Temperature on the Growth of Chlorella sp.: Implications on Algal Blooms and Management

With the accelerated urbanization and rapid development of the industrial and agricultural sectors, concern about the pollution of water environments is becoming more widespread. Algal blooms of varying sizes are becoming increasingly frequent in lakes and reservoirs; temperatures, nutrients, heavy metals, and dissolved oxygen are the factors that influence algal bloom occurrence. However, knowledge of the combined effect of heavy metals and temperature on algal growth remains limited. Thus, this study investigated how specific concentrations of heavy metals affect algal growth at different temperatures; to this end, two heavy metals were used (0.01 mg/L Pb2+ and 0.05 mg/L Cr6+) at three incubation temperatures (15, 25, and 30 °C) with the alga Chlorella sp. A higher incubation temperature contributed to a rise in soluble proteins, which promoted algal growth. The density of algal cells increased with temperature, and catalase (CAT) decreased with increasing temperature. Chlorella sp. growth and catalase activity were optimal at 30 °C (algal cell density: 1.46 × 107 cell/L; CAT activity: 29.98 gprot/L). Pb2+ and Cr6+ significantly promoted Chlorella sp. growth during incubation at 25 and 30 °C, respectively. At specific temperatures, 0.01 mg/L Pb2+ and 0.05 mg/L Cr6+ promoted the production of soluble proteins and, hence, the growth of Chlorella sp. The results provide a useful background for the mitigation and prevention of algal blooms.

Seasonal Patterns of Phytoplankton Taxon Richness in Lakes: Effects of Temperature, Turnover and Abundance

Species richness is a key ecological characteristic that influences numerous ecosystem functions. Here we analyse the patterns and possible causes of phytoplankton taxon richness in seasonal datasets from twenty contrasting lakes in the English Lake District over six years and near-weekly datasets over 33 years from Windermere. Taxon richness was lowest in winter and highest in summer or autumn in all of the lakes. Observed richness was very similar to richness estimated from coverage and sampling effort, implying that it closely reflected true seasonal patterns. Summer populations were dominated by Chlorophyta and functional groups X1, F, N and P (sensu Reynolds). In Windermere, weekly taxon richness was strongly positively correlated with surface water temperature, as was the number of functional groups and the number of taxa per functional group. Turnover in richness of taxa and functional groups were positively correlated and both were related to surface temperature. This suggests that high taxon richness in summer is linked to higher water temperature, promoting a turnover in richness of taxa and functional groups in these lakes. However, since the number of taxa per unit concentration of chlorophyll a decreased with increasing concentration of chlorophyll a, competition might occur when abundance is high.

Elevated CO2 significantly increases N2 fixation, growth rates, and alters microcystin, anatoxin, and saxitoxin cell quotas in strains of the bloom-forming cyanobacteria, Dolichospermum

The effect of rising CO₂ levels on cyanobacterial harmful algal blooms (CHABs) is an emerging concern, particularly within eutrophic ecosystems. While elevated pCO₂ has been associated with enhanced growth rates of some cyanobacteria, few studies have explored the effect of CO₂ and nitrogen availability on diazotrophic (N₂-fixing) cyanobacteria that produce cyanotoxins. Here, the effects of elevated CO₂ and fixed nitrogen (NO₃^-) availability on the growth rates, toxin production, and N₂ fixation of microcystin, saxitoxin, and anatoxin-a - producing strains of the genus Dolichospermum were quantified. Growth rates of all Dolichospermum spp. were significantly increased by CO₂ or both CO₂ and NO₃^- with rates being highest in treatments with the highest levels of CO₂ and NO₃^-for all strains. While NO₃^- suppressed N₂ fixation, diazotrophy significantly increased when NO₃^--enriched Dolichospermum spp. were supplied with higher CO₂ compared to cultures grown under lower CO₂ levels. This suggests that diazotrophy will play an increasingly important role in N cycling in CO₂-enriched, eutrophic lentic systems. NO₃^- significantly increased quotas of the N-rich cyanotoxins, microcystin and saxitoxin, at ambient and enriched CO₂ levels, respectively. In contrast, elevated CO₂ significantly decreased cell quotas of microcystin and saxitoxin, but significantly increased cell quotas of the N-poor cyanotoxin, anatoxin. N₂ fixation was significantly negatively and positively correlated with quotas of N-rich and N-poor cyanotoxins, respectively. Findings suggest cellular quotas of N-rich toxins (microcystin and saxitoxin) may be significantly reduced, or cellular quotas of N-poor toxins (anatoxin) may be significantly enhanced, under elevated CO₂ conditions during diazotrophic cyanobacterial blooms. Finally, in the future, ecosystems that experience combinations of excessive N loading and CO₂ enrichment may become more prone to toxic blooms of Dolichospermum.

Assessment of physico-chemical parameters of surface waters of a tropical brackish water lake in South Asia

Brackish lake systems and estuaries are unique aquatic systems that support diversified life forms and strongly influence a region's economy. Major chemical water quality parameters of India's second-largest brackish water lake, Pulicat were assessed. Physico-chemical parameters like pH, temperature, suspended solid concentrates, total dissolved solids, salinity, nitrogenous nutrients, phosphate, silicate, and chlorophyll a were analysed. The results obtained for different parameters were compared and interpreted with statistical software SPSS version 20 and images were plotted using the Arc GIS spatial analyst tool. During the summer months, the nitrogen to phosphorus ratio ranges from a minimum of 1.96 to a maximum of 16.64 (9.55 ± 4.01) while it ranges from a minimum of 7.98 to a maximum of 15.52 (12.47 ± 2) during the pre-monsoon. In the monsoon season, the nitrogen to phosphorus ratio of surface water suggests a range from a minimum of 8.64 to a maximum of 17.58 (13.87 ± 2.14). During the post-monsoon season, the nitrogen to phosphorus ratio ranges from 4.98 to 17.34 (11.77 ± 3.68). The average nitrogen to phosphorus ratios were 9.6, 12.5, 13.9 and 11.8 in summer, pre-monsoon, monsoon, and post-monsoon respectively. The nitrogen to phosphorus ratio was lower than the Redfield ratio for all the seasons. The average concentration of chlorophyll a was 14.9, 13.4, 12.8 and 11.8 in summer, pre-monsoon, monsoon, and post-monsoon respectively. As per the Pearson Correlation Coefficient, there was no significant correlation among nitrogen, phosphorus, and chlorophyll a. This suggests the influence of suspended solid concentrates, and nitrogen and phosphorus flux in the sediment-water interface might be interfering with the nutrient cycles and primary productivity.

Earlier ice loss accelerates lake warming in the Northern Hemisphere

How lake temperatures across large geographic regions are responding to widespread alterations in ice phenology (i.e., the timing of seasonal ice formation and loss) remains unclear. Here, we analyse satellite data and global-scale simulations to investigate the contribution of long-term variations in the seasonality of lake ice to surface water temperature trends across the Northern Hemisphere. Our analysis suggests a widespread excess lake surface warming during the months of ice-off which is, on average, 1.4 times that calculated during the open-water season. This excess warming is influenced predominantly by an 8-day advancement in the average timing of ice break-up from 1979 to 2020. Until the permanent loss of lake ice in the future, excess lake warming may be further amplified due to projected future alterations in lake ice phenology. Excess lake warming will likely alter within-lake physical and biogeochemical processes with numerous implications for lake ecosystems.

Trends of lake temperature, mixing depth and ice cover thickness of European lakes during the last four decades

Lakes are particularly vulnerable ecosystems to global warming. Surface temperature of most lakes in the world has significantly increased. Here, we analysed time-series of water temperature, mixing-depth, and ice depth of 51 European lakes over the last four decades. We used data of surface temperature, total layer water temperature, mix-layer temperature, mix-layer depth, and ice cover depth obtained from the ERA5-Land reanalysis dataset. Our main objectives were a) to identify significant changes of the examined variables that have occurred from 1981 to 2019 and b) to assess the variability of changes in relation with geographical and lake morphological gradients. To this end, time series analysis was conducted using generalized additive models (GAMs). In addition, we quantified the magnitude of change by estimating the Sen's slopes for each variable and then we examined the variability of these slopes to geographical and lake morphological parameters using GAMs. Our results confirmed that water temperature parameters (surface, total-layer and mix-layer temperature) have significantly increased for all lakes during the last four decades. We also found significant changes of the mixing depth for 14 lakes. In addition, the lake ice depth has significantly decreased in all fifteen lakes of the subarctic climate region. Finally, we showed that the Sen's slopes depend on the geographic coordinates and the elevation of the lakes, whereas lake morphometry (e.g. depth) has a smaller effect on the magnitude of changes. These findings hint that lake ecosystems of Europe have substantially changed over the last forty years and urge the need to take precautionary measures to prevent future implications for the freshwater biota.

Possible consequences of climate change on global water resources stored in dam reservoirs

Construction of dams and transformation of rivers, not only affects river-related and adjacent habitats, but also establishes new threats to surface freshwater resources globally. Predicted climate changes and increase of mean annual temperature will affect thermal regimes of dam reservoir ecosystems, severely altering their functioning. Analyzing three projections of representative concentration pathway (RCP 4.5, 6.0 and 8.5) for period of 2061-2080, we found that mean annual temperature at dam reservoir locations will increase by 3.06 °C to 4.74 °C from present. The highest projected increase of temperature was identified for dam reservoirs located in high latitudes of Northern Hemisphere, and therefore dam reservoirs located there will be most significantly affected. Numerous consequences of temperature increase are already recorded. Further increase will amplify unfavorable effects on numerous ecosystems, including dam reservoirs which are built on the purpose of the human population development. Our study indicates a threat for artificially stored water globally, with special attention to high latitudes in northern hemisphere and latitudes close to 20⁰S meridian in southern hemisphere.

Evaporative water loss of 1.42 million global lakes

The evaporative loss from global lakes (natural and artificial) is a critical component of the terrestrial water and energy balance. However, the evaporation volume of these water bodies-from the spatial distribution to the long-term trend-is as of yet unknown. Here, using satellite observations and modeling tools, we quantified the evaporation volume from 1.42 million global lakes from 1985 to 2018. We find that the long-term average lake evaporation is 1500 ± 150 km³ year^-1 and it has increased at a rate of 3.12 km³ year^-1. The trend attributions include an increasing evaporation rate (58%), decreasing lake ice coverage (23%), and increasing lake surface area (19%). While only accounting for 5% of the global lake storage capacity, artificial lakes (i.e., reservoirs) contribute 16% to the evaporation volume. Our results underline the importance of using evaporation volume, rather than evaporation rate, as the primary index for assessing climatic impacts on lake systems.

Greenhouse gas emissions from African lakes are no longer a blind spot

Natural lakes are thought to be globally important sources of greenhouse gases (CO₂, CH₄, and N₂O) to the atmosphere although nearly no data have been previously reported from Africa. We collected CO₂, CH₄, and N₂O data in 24 African lakes that accounted for 49% of total lacustrine surface area of the African continent and covered a wide range of morphology and productivity. The surface water concentrations of dissolved CO₂ were much lower than values attributed in current literature to tropical lakes and lower than in boreal systems because of a higher productivity. In contrast, surface water-dissolved CH₄ concentrations were generally higher than in boreal systems. The lowest CO₂ and the highest CH₄ concentrations were observed in the more shallow and productive lakes. Emissions of CO₂ may likely have been substantially overestimated by a factor between 9 and 18 in African lakes and between 6 and 26 in pan-tropical lakes.

Seasonal Variation and Vertical Distribution of Inorganic Nutrients in a Small Artificial Lake, Lake Bulan, in Mongolia

This is the first seasonal observation study on nutrient dynamics undertaken in a small freshwater lake with eutrophication in Mongolia. The vertical profile and seasonal fluctuation of nutrients are crucial to understanding the biogeochemical cycles in aquatic systems. In this study, field research was carried out at a small and shallow lake, Lake Bulan, in the lower Kharaa River basin. The area has been receiving increased nutrient loads from the water catchment area for the last 20 years. Water samples were collected seasonally from the lake from 2019–2022 and analyzed for nutrients, major cations, trace metals, and dissolved organic carbon. The average concentration of dissolved inorganic nitrogen (DIN) in the surface lake water had a wide seasonal variation from 0.26 ± 0.11 mg N/L in August to 1.44 ± 0.08 mg N/L in January. Seasonal differences were also observed in the vertical profiles. Concentrations were relatively similar at the various water depths in April and September at turnover time. Thermal stratification was observed when the lake was covered in ice, with the maximum concentrations being observed in the bottom layer in the months of January and August. The phosphate concentration showed a similar variation trend. These results indicate that both the summer and winter stratifications are important for regeneration of nutrients in the bottom layer, biochemical cycling, and mitigating impacts of global warming on small and shallow lakes in Mongolia.

Monitoring the Water Mass Balance Variability of Small Shallow Lakes by an ERA5-Land Reanalysis and Water Level Measurement-Based Model. An Application to the Trasimeno Lake, Italy

Climate change has a strong impact on inland water bodies such as lakes. This means that the increase in lake temperature recorded in recent decades-in Europe as well-can change the evaporation regime of the lakes. This, together with the variation of the water cycle, in particular precipitation, implies that the water mass balance of lakes may vary due to climate change. Water mass balance modeling is therefore of paramount importance to monitor lakes in the context of global warming. Although many studies have focused on such a modeling, there is no shared approach that can be used for any lake across the globe, irrespective of the size. This becomes even more problematic for shallow and small lakes, for which few studies exist. For this reason, in this paper the use of reanalysis data, in particular ERA5-Land provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), is proposed for the mass balance modeling. In fact, ERA5-Land has a global coverage and it is the only data source comprising a specific model for lakes, the Fresh-water Lake model (FLake). The chosen case study is the Trasimeno lake, a small and shallow lake located in Central Italy. The use of the reanalysis was preceded by data validation by considering both ground-based and satellite observations. The results show that there is a good agreement between the observed monthly variation of the lake level, ΔH, and the corresponding values of the water storage, δ, computed by means of the ERA5-Land data (Pearson coefficient larger than 70%). Discrepancies between observations and the ERA5-Land data happen in periods characterized in Europe by an extreme climate anomaly. This promising result encourages the use of ERA5-Land for other lakes.

A Satellite-Based Tool for Mapping Evaporation in Inland Water Bodies: Formulation, Application, and Operational Aspects

With the increase of evaporation projected for water bodies worldwide, there is a growing need for flexible and low data-demanding tools enabling the monitoring and management of water resources. This study presents a simple satellite-based tool named LakeVap specifically designed for mapping evaporation from lakes and reservoirs. LakeVap requires a small amount of potentially available data with a global coverage. The tool follows a Dalton-type approach and produces instantaneous (i.e., hourly) and daily evaporation maps from satellite-derived Lake Surface Water Temperature (LSWT) maps and single-point/gridded meteorological data. The model is tested on Lake Garda, Italy, by using a long time series of LSWT (ESA CCI-Lakes) and different sources of meteorological forcing. The accuracy of LakeVap evaporation outputs is checked by comparison with those from a hydro-thermodynamic model (Delft3D) specifically set up and validated for the case study. Results are consistent and sensitive to the representativeness of the meteorological forcing. In the test site, wind speed is found to be the most spatially variable parameter, and it is significantly underestimated by the ERA5 meteorological dataset (up to 100%). The potential application of LakeVap to other case studies and in operational contexts is discussed.

Water clarity mapping of global lakes using a novel hybrid deep-learning-based recurrent model with Landsat OLI images

Information regarding water clarity at large spatiotemporal scales is critical for understanding comprehensive changes in the water quality and status of ecosystems. Previous studies have suggested that satellite observation is an effective means of obtaining such information. However, a reliable model for accurately mapping the water clarity of global lakes (reservoirs) is still lacking due to the high optical complexity of lake waters. In this study, by using gated recurrent units (GRU) layers instead of full-connected layers from Artificial Neural Networks (ANNs) to capture the efficient sequence information of in-situ datasets, we propose a novel and transferrable hybrid deep-learning-based recurrent model (DGRN) to map the water clarity of global lakes with Landsat 8 Operational Land Imager (OLI) images. We trained and further validated the model using 1260 pairs of in-situ measured water clarity and surface reflectance of Landsat 8 OLI images with Google Earth Engine. The model was subsequently utilized to construct the global pattern of temporal and spatial changes in water clarity (lake area>10 km²) from 2014 to 2020. The results show that the model can estimate water clarity with good performance (R² = 0.84, MAE = 0.55, RMSE = 0.83, MAPE = 45.13%). The multi-year average of water clarity for global lakes (16,475 lakes) ranged from 0.0004 to 9.51 m, with an average value of 1.88 ± 1.24 m. Compared to the lake area, elevation, discharge, residence time, and the ratio of area to depth, water depth was the most important factor that determined the global spatial distribution pattern of water clarity. Water clarity of 15,840 global lakes between 2014 and 2020 remained stable (P ≥ 0.05); while there was a significant increase in 243 lakes (P < 0.05) and a decrease in 392 lakes (P < 0.05). However, water clarity in 2020 (COVID-19 period) showed a significant increase in most global lakes, especially in China and Canada, suggesting that the worldwide lockdown strategy due to COVID-19 might have improved water quality, espically water clarity, dueto the apparent reduction of anthropogenic activities.

Direct and indirect effects of climate change on distribution and community composition of macrophytes in lentic systems

Macrophytes are an important part of freshwater ecosystems and they have direct and indirect roles in keeping the water clear and providing structure and habitats for other aquatic organisms. Currently, climate change is posing a major threat to macrophyte communities by altering the many drivers that determine macrophyte abundance and composition. We synthesise current literature to examine the direct effects of climate change (i.e. changes in CO₂, temperature, and precipitation patterns) on aquatic macrophytes in lakes as well as indirect effects via invasive species and nutrient dynamics. The combined effects of climate change are likely to lead to an increased abundance and distribution of emergent and floating species, and a decreased abundance and distribution of submerged macrophytes. In small shallow lakes, these processes are likely to be faster than in deep temperate lakes; with lower light levels, water level fluctuations and increases in temperature, the systems will become dominated by algae. In general, specialized macrophyte species in high‐latitude and high‐altitude areas will decrease in number while more competitive invasive species are likely to outcompete native species. Given that the majority of endemic species reside in tropical lakes, climate change, together with other anthropogenic pressures, might cause the extinction of a large number of endemic species. Lakes at higher altitudes in tropical areas could therefore potentially be a hotspot for future conservation efforts for protecting endemic macrophyte species. In response to a combination of climate‐change induced threats, the macrophyte community might collapse, which will change the status of lakes and may initiate a negative feedback loop that will affect entire lake ecosystems.

The state and fate of lake ice thickness in the Northern Hemisphere

Lake ice thickness (LIT) is important for regional hydroclimate systems, lake ecosystems, and human activities on the ice, and is thought to be highly susceptible to global warming. However, the spatiotemporal variability in LIT is largely unknown due to the difficulty in deriving in situ measurements and the lack of an effective remote sensing platform. Despite intensive development and applications of lake ice models driven by general circulation model output, evaluation of the global LIT is mostly based on assumed "ideal" lakes in each grid cell of the climate forcing data. A method for calculating the actual global LIT is therefore urgently needed. Here we use satellite altimetry to retrieve ice thickness for 16 large lakes in the Northern Hemisphere (Lake Baikal, Great Slave Lake, and others) with an accuracy of ∼0.2 m for almost three decades. We then develop a 1-D lake ice model driven primarily by remotely sensed data and cross-validated with the altimetric LIT to provide a robust means of estimating LIT for lakes larger than 50 km² across the Northern Hemisphere. Mean LIT (annual maximum ice thickness) for 1313 simulated lakes and reservoirs covering ∼840,000 km² for 2003-2018 is 0.63 ± 0.02 m, corresponding to ∼485 Gt of water. LIT changes are projected for 2071-2099 under RCPs 2.6, 6.0, and 8.5, showing that the mean LIT could decrease by ∼0.35 m under the worst concentration pathway and the associated lower ice road availability could have a significant impact on socio-economic activities.

Estimation of total flux of polycyclic aromatic hydrocarbons facilitated by methane ebullition into water column from global lake sediments

Methane ebullition and contamination are two typical characteristics from lakes, however, these two are generally studied independently. In fact, the exchange of matter and energy between methane bubbles and their surrounding environment can be very active to enhance the contaminant transport. There is limited research on understanding the characteristics and trends of gas ebullition facilitated contaminant emissions in large areas considering water and air as receptors. We herein estimate the transport capacity of methane ebullition for polycyclic aromatic hydrocarbons (PAHs) out of the sediment from global lakes, which may reach an average of 71 (up to 159) t yr^-1. Methane bubbles could transfer one third of the total PAH flux from sediments, or equivalent of 1.3-3.0 ng L^-1 of additional PAHs, into the water column with the rest going into air, offsetting from 52 to 118% of dry PAH deposition flux into global lakes sediment per year. Given the PAH concentration in lake water is often in the range of 0.1-100 ng L^-1, ebullition facilitated PAH flux may increase PAH concentration by a factor of 1.4 to 2.4 until 2,100, being a significant contributor for the PAH increment in lake waters.

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-a in north temperate lakes

Winter conditions, such as ice cover and snow accumulation, are changing rapidly at northern latitudes and can have important implications for lake processes. For example, snowmelt in the watershed-a defining feature of lake hydrology because it delivers a large portion of annual nutrient inputs-is becoming earlier. Consequently, earlier and a shorter duration of snowmelt are expected to affect annual phytoplankton biomass. To test this hypothesis, we developed an index of runoff timing based on the date when 50% of cumulative runoff between January 1 and May 31 had occurred. The runoff index was computed using stream discharge for inflows, outflows, or for flows from nearby streams for 41 lakes in Europe and North America. The runoff index was then compared with summer chlorophyll-a (Chl-a) concentration (a proxy for phytoplankton biomass) across 5-53 years for each lake. Earlier runoff generally corresponded to lower summer Chl-a. Furthermore, years with earlier runoff also had lower winter/spring runoff magnitude, more protracted runoff, and earlier ice-out. We examined several lake characteristics that may regulate the strength of the relationship between runoff timing and summer Chl-a concentrations; however, our tested covariates had little effect on the relationship. Date of ice-out was not clearly related to summer Chl-a concentrations. Our results indicate that ongoing changes in winter conditions may have important consequences for summer phytoplankton biomass and production.

Factors of surface thermal variation in high-mountain lakes of the Pyrenees

Thermal variables are crucial drivers of biological processes in lakes and ponds. In the current context of climate change, determining which factors better constrain their variation within lake districts become of paramount importance for understanding species distribution and their conservation. In this study, we describe the regional and short-term interannual variability in surface water temperature of high mountain lakes and ponds of the Pyrenees. And, we use mixed regression models to identify key environmental factors and to infer mean and maximum summer temperature, accumulated degree-days, diel temperature ranges and three-days’ oscillation. The study is based on 59 lake-temperature series measured from 2001 to 2014. We found that altitude was the primary explicative factor for accumulated degree-days and mean and maximum temperature. In contrast, lake area showed the most relevant effect on the diel temperature range and temperature oscillations, although diel temperature range was also found to decline with altitude. Furthermore, the morphology of the catchment significantly affected accumulated degree-days and maximum and mean water temperatures. The statistical models developed here were applied to upscale spatially the current thermic conditions across the whole set of lakes and ponds of the Pyrenees.

Shifting Patterns of Summer Lake Color Phenology in Over 26,000 US Lakes

Lakes are often defined by seasonal cycles. The seasonal timing, or phenology, of many lake processes are changing in response to human activities. However, long-term records exist for few lakes, and extrapolating patterns observed in these lakes to entire landscapes is exceedingly difficult using the limited number of available in situ observations. Limited landscape-level observations mean we do not know how common shifts in lake phenology are at macroscales. Here, we use a new remote sensing data set, LimnoSat-US, to analyze U.S. summer lake color phenology between 1984 and 2020 across more than 26,000 lakes. Our results show that summer lake color seasonality can be generalized into five distinct phenology groups that follow well-known patterns of phytoplankton succession. The frequency with which lakes transition from one phenology group to another is tied to lake and landscape level characteristics. Lakes with high inflows and low variation in their seasonal surface area are generally more stable, while lakes in areas with high interannual variations in climate and catchment population density show less stability. Our results reveal previously unexamined spatiotemporal patterns in lake seasonality and demonstrate the utility of LimnoSat-US, which, with over 22 million remote sensing observations of lakes, creates novel opportunities to examine changing lake ecosystems at a national scale.

Phenological shifts in lake stratification under climate change

One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 ± 7.0 days earlier and end 11.3 ± 4.7 days later by the end of this century. It is very likely that this 33.3 ± 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely.

Stratification has a considerable influence on lake ecology, but there is little understanding of past or future changes in its seasonality. Here, the authors use modelling and empirical data to determine that between 1901–2099, climate change causes stratification to start earlier and end later.

Physics-informed machine learning: case studies for weather and climate modelling

Machine learning (ML) provides novel and powerful ways of accurately and efficiently recognizing complex patterns, emulating nonlinear dynamics, and predicting the spatio-temporal evolution of weather and climate processes. Off-the-shelf ML models, however, do not necessarily obey the fundamental governing laws of physical systems, nor do they generalize well to scenarios on which they have not been trained. We survey systematic approaches to incorporating physics and domain knowledge into ML models and distill these approaches into broad categories. Through 10 case studies, we show how these approaches have been used successfully for emulating, downscaling, and forecasting weather and climate processes. The accomplishments of these studies include greater physical consistency, reduced training time, improved data efficiency, and better generalization. Finally, we synthesize the lessons learned and identify scientific, diagnostic, computational, and resource challenges for developing truly robust and reliable physics-informed ML models for weather and climate processes. This article is part of the theme issue 'Machine learning for weather and climate modelling'.

Lake heatwaves under climate change

Lake ecosystems, and the organisms that live within them, are vulnerable to temperature change^1-5, including the increased occurrence of thermal extremes⁶. However, very little is known about lake heatwaves-periods of extreme warm lake surface water temperature-and how they may change under global warming. Here we use satellite observations and a numerical model to investigate changes in lake heatwaves for hundreds of lakes worldwide from 1901 to 2099. We show that lake heatwaves will become hotter and longer by the end of the twenty-first century. For the high-greenhouse-gas-emission scenario (Representative Concentration Pathway (RCP) 8.5), the average intensity of lake heatwaves, defined relative to the historical period (1970 to 1999), will increase from 3.7 ± 0.1 to 5.4 ± 0.8 degrees Celsius and their average duration will increase dramatically from 7.7 ± 0.4 to 95.5 ± 35.3 days. In the low-greenhouse-gas-emission RCP 2.6 scenario, heatwave intensity and duration will increase to 4.0 ± 0.2 degrees Celsius and 27.0 ± 7.6 days, respectively. Surface heatwaves are longer-lasting but less intense in deeper lakes (up to 60 metres deep) than in shallower lakes during both historic and future periods. As lakes warm during the twenty-first century^7,8, their heatwaves will begin to extend across multiple seasons, with some lakes reaching a permanent heatwave state. Lake heatwaves are likely to exacerbate the adverse effects of long-term warming in lakes and exert widespread influence on their physical structure and chemical properties. Lake heatwaves could alter species composition by pushing aquatic species and ecosystems to the limits of their resilience. This in turn could threaten lake biodiversity⁹ and the key ecological and economic benefits that lakes provide to society.

Variability of chlorophyll and the influence factors during winter in seasonally ice-covered lakes

Lake ice is an essential and integral part of the cryosphere and freshwater systems. The formation of lake ice affects the physical, hydrological, and biological conditions of ecological systems. Global warming may contribute to even shorter periods of ice cover in the lakes of the Frigid Zone, which adversely affects the growth of phytoplankton and primary productivity. This study was conducted for the purpose of evaluating the growth of phytoplankton and factors involved, in 28 ice-covered lakes across the Songnen Plain, in the Northeast of China, to understand how they take part in the whole-ecosystem functioning. A total of 1026 water samples were collected in April, September, and January during the period 2014-2018. In the frozen period, the concentration levels of dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) were all comparable with the spring and autumn. Despite the limited light availability and low temperature, the phytoplankton survived in sub-ice waters during winter with a low concentration of chlorophyll a (Chla). Its average concentration was positively correlated with the concentration observed in the previous autumn (r_p = 0.563, p < 0.01). According to the regression tree analysis, during the winter period, Chla was mainly related to the concentration of TN in sub-ice water (TN_water) and with the difference of concentration of TP between water and ice (TP_cd). Furthermore, either in ice or in sub-ice water, the concentration of Chla was also significantly affected by total suspended matter (TSM) (p < 0.05). The levels of TN_water, TP_cd, and TSM could explain the 77.8% of the variance in the concentration of Chla during winter with contributions in the ranges of 25.5%-35.0%, 9.2%-11.3%, and 21.5%-34.0%, respectively (p < 0.05). This research substantially contributes to comprehending how the existing conditions under-ice affect the whole ecosystem when the ice cover is reduced lakes or rivers.

Estimation of the Dependence of Ice Phenomena Trends on Air and Water Temperature in River

The identification of changes in the ice phenomena (IP) in rivers is a significant element of analyses of hydrological regime features, of the risk of occurrence of ice jam floods, and of the ecological effects of river icing (RI). The research here conducted aimed to estimate the temporal and spatial changes in the IP in a lowland river in the temperate climate (the Noteć River, Poland, Central Europe), depending on air temperature (TA) and water temperature (TW) during the multi-annual period of 1987–2013. Analyses were performed of IP change trends in three RI phases: freezing, when there appears stranded ice (SI), frazil ice (FI), or stranded ice with frazil ice (SI–FI); the phase of stable ice cover (IC) and floating ice (FoI); and the phase of stranded ice with floating ice (SI–FoI), frazil ice with floating ice (FI–FoI), and ice jams (IJs). Estimation of changes in IP in connection with TA and TW made use of the regression model for count data with a negative binomial distribution and of the zero-inflated negative binomial model. The analysis of the multi-annual change tendency of TA and TW utilized a non-parametric Mann–Kendall test for detecting monotonic trends with Yue–Pilon correction (MK–YP). Between two and seven types of IP were registered at individual water gauges, while differences were simultaneously demonstrated in their change trends over the researched period. The use of the Vuong test confirmed the greater effectiveness of estimates for the zero-inflated model than for the temporal trend model, thanks to which an increase in the probability of occurrence of the SI phenomenon in the immediate future was determined; this, together with FI, was found to be the most frequently occurring IP in rivers in the temperate climate. The models confirmed that TA is the best estimator for the evaluation of trends of the occurrence of IC. It was shown that the predictive strength of models increases when thermal conditions are taken into consideration, but it is not always statistically significant. In all probability, this points to the impact of local factors (changes in bed and valley morphology and anthropogenic pressure) that are active regardless of thermal conditions and modify the features of the thermal-ice regime of rivers at specific spatial locations. The results of research confirm the effectiveness of compilating a few models for the estimation of the dependence of IP trends on air and water temperature in a river.

Deeper waters are changing less consistently than surface waters in a global analysis of 102 lakes

Globally, lake surface water temperatures have warmed rapidly relative to air temperatures, but changes in deepwater temperatures and vertical thermal structure are still largely unknown. We have compiled the most comprehensive data set to date of long-term (1970–2009) summertime vertical temperature profiles in lakes across the world to examine trends and drivers of whole-lake vertical thermal structure. We found significant increases in surface water temperatures across lakes at an average rate of + 0.37 °C decade⁻¹, comparable to changes reported previously for other lakes, and similarly consistent trends of increasing water column stability (+ 0.08 kg m⁻³ decade⁻¹). In contrast, however, deepwater temperature trends showed little change on average (+ 0.06 °C decade⁻¹), but had high variability across lakes, with trends in individual lakes ranging from − 0.68 °C decade⁻¹ to + 0.65 °C decade⁻¹. The variability in deepwater temperature trends was not explained by trends in either surface water temperatures or thermal stability within lakes, and only 8.4% was explained by lake thermal region or local lake characteristics in a random forest analysis. These findings suggest that external drivers beyond our tested lake characteristics are important in explaining long-term trends in thermal structure, such as local to regional climate patterns or additional external anthropogenic influences.

Rethinking discretization to advance limnology amid the ongoing information explosion

Limnologists often adhere to a discretized view of waterbodies-they classify them, divide them into zones, promote discrete management targets, and use research tools, experimental designs, and statistical analyses focused on discretization. By offering useful shortcuts, this approach to limnology has profoundly benefited the way we understand, manage, and communicate about waterbodies. But the research questions and the research tools in limnology are changing rapidly in the era of big data, with consequences for the relevance of our current discretization schemes. Here, I examine how and why we discretize and argue that selectively rethinking the extent to which we must discretize gives us an exceptional chance to advance limnology in new ways. To help us decide when to discretize, I offer a framework (discretization evaluation framework) that can be used to compare the usefulness of various discretization approaches to an alternative which relies less on discretization. This framework, together with a keen awareness of discretization's advantages and disadvantages, may help limnologists benefit from the ongoing information explosion.