Ice-off Dates Research Articles

Evaluating the potential importance of individual identity, maternal traits, and environment as predictors of egg characteristics in walleye Sander vitreus

Individual and environmental factors may influence gamete characteristics and contributions to recruitment in fishes. We tested for the influence of maternal, abiotic, and biotic factors on egg diameter and quality (i.e., oil droplet diameter) for walleye Sander vitreus in Escanaba Lake, Wisconsin, during 2018–2023 (omitting 2020). Analyses were conducted on fish captured once and for the same individuals captured multiple times during our study period. In the single-capture analysis, increasing maternal length was weakly related to larger egg diameter and oil droplet size. Increased yellow perch abundance was somewhat related to increased intra-clutch variation, whereas a later ice-off date was related to reduced intra-clutch variation. Fish that spawned later had more variable egg and oil droplet diameters. Among fish that were sampled over multiple years, individual identity was a strong predictor of egg and oil diameter. Our results suggest that regulations that preserve among individual variation in egg traits could increase the chances that environmental conditions will be favorable for spawning and recruitment for at least some fish.

Temporal variation in river ice phenology of the Heilongjiang River in response to climate change

Study regionUpstream of the Heilongjiang River, located in Northeast Asia, is the transboundary river between China and Russia. Study focusUsing long-term hydrological records provided by the Mohe station in combination with multiple statistical approaches, we investigate how river ice phenology of the Heilongjiang River has varied during the period 1957–2016, and quantitatively assess the individual contribution of changes in different climatic factors to such variation in river ice phenology. New insights for the regionWe show the later occurrence for newly formed ice date, ice-on date, and freeze-up date and the earlier occurrence for beak-up date and ice-off date, ultimately leading to a decrease in persistence of river ice in the Heilongjiang River. River ice phenology exhibits a general lag response to climate change, with ranging from 1 to 5 months. Further attribution analysis that explicitly considers time-lag effect suggests that climate change plays a dominant role in regulating river ice phenology. More specifically, compared to other climatic factors, air pressure and maximum and minimum temperature changes have larger contributions to variation in river ice phenology, particularly for the delay of formation time. These findings provide technical basis and beneficial reference to the development of regional river management strategies involved in climate change adaptation framework.

Ice phenology interactions with water and air temperatures in high mountain lakes

Ice phenology is of great importance for the thermal structure of lakes and ponds and the biology of lake species. Under the current climate change conditions, ice-cover duration has been reduced by an advance in ice-off, and a delay in ice-on, and future projections foresee this trend as continuing. Here, we describe the current ice phenology of Pyrenean high mountain lakes and ponds, including ice-cover duration and ice-on and ice-off dates. We used mixed models to identify the variables that explained the observed patterns, extrapolated them across all water bodies in the mountain range, and related the seasonality of air and water temperatures with ice phenology using structural equation models. Ice phenology was obtained from the temperature series of 85 lakes and ponds for fourteen years, including 2001 to 2004 and 2009 to 2019. We discovered that high autumn precipitation was related to earlier ice-on dates, and that earlier ice-off dates were associated with higher following-summer water temperatures. We found a greater predictability of ice-off dates and ice-cover duration than ice-on dates. Altitude was the most important variable explaining the variation in ice phenology, followed by latitude, which was related to climatic differences among the northern and southern slopes of the mountain range. The lake area was significant for ice-on dates and ice-cover duration. The interannual variability in air temperature and radiation was remarkable for the ice-off date and ice-cover duration but not for the ice-on date. In contrast, wind speed was related to an earlier ice-off date and shorter ice-cover duration. All the measured lakes and ponds froze in winter during the studied period, a feature maintained in the extrapolation to the whole set of water bodies.

Water temperature, mixing, and ice phenology in the arctic–alpine Lake Darfáljávri (Lake Tarfala), northern Sweden

ABSTRACT In the rapidly warming circumpolar Arctic, recent research of lakes has focused on their climatology and ecology but is challenged by sparsity of wintertime data. At the c. 48-m-deep and c. 0.5-km2 large proglacial Darfáljávri (Lake Tarfala), located in an arctic–alpine environment in the Scandinavian Mountains, year-round water temperatures were previously reported for 2016 to 2019. Here, this record is continued for 2019–2020 and 2021–2022, complemented by time-lapse imagery records of the state of the lake surface, as well as degree-day modeling of ice phenology (timing of ice-on and ice-off). Darfáljávri is cryostratified during winter, with interannual variations in the thermocline’s thickness and temperature range. The ice season lasts from October to July. Modeled ice-on dates match observed ones reasonably well; however, observed ice-off dates occur much later than modeled ones, likely because of cold impact from Darfáljávri’s glacial environment as inferred from a comparison with a close tundra lake. Though new insights into the complex lake mixing and ice phenology are provided, it remains to attribute the characteristics of Darfáljávri’s winter stratification to additional potential drivers, such as lake ice thickness, atmospheric heat fluxes, and the water balance of the lake.

Does the 11-year solar cycle affect lake and river ice phenology?

Records of ice-on and ice-off dates are available for lakes and rivers across the Northern Hemisphere spanning decades and in some cases centuries. This data provides an opportunity to investigate the climatic processes that may control ice phenology. Previous studies have reported a trend toward shorter ice-covered seasons with global warming, as well as links between ice phenology and several modes of natural climate variability such as the North Atlantic Oscillation, the Pacific-North American Pattern, the El Niño-Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation. The 11-year sunspot cycle has also been proposed as a driver of ice phenology, which is somewhat surprising given that this cycle’s strongest impacts are in the stratosphere. In this study, we use a large data set of lakes and rivers across the Northern Hemisphere to test this potential link. We find little or no connection between the sunspot cycle and either ice-on or ice-off dates. We conclude that while many well-known climate cycles do impact ice phenology, we are able to rule out any strong impact of the solar cycle.

Learning a Joint Embedding of Multiple Satellite Sensors: A Case Study for Lake Ice Monitoring

Fusing satellite imagery acquired with different sensors has been a long-standing challenge of Earth observation, particularly across different modalities such as optical and Synthetic Aperture Radar (SAR) images. Here, we explore the joint analysis of imagery from different sensors in the light of representation learning: we propose to learn a joint embedding of multiple satellite sensors within a deep neural network. Our application problem is the monitoring of lake ice on Alpine lakes. To reach the temporal resolution requirement of the Swiss Global Climate Observing System (GCOS) office, we combine three image sources: Sentinel-1 SAR (S1-SAR), Terra MODIS, and Suomi-NPP VIIRS. The large gaps between the optical and SAR domains and between the sensor resolutions make this a challenging instance of the sensor fusion problem. Our approach can be classified as a late fusion that is learned in a data-driven manner. The proposed network architecture has separate encoding branches for each image sensor, which feed into a single latent embedding. I.e., a common feature representation shared by all inputs, such that subsequent processing steps deliver comparable output irrespective of which sort of input image was used. By fusing satellite data, we map lake ice at a temporal resolution of < 1.5 days. The network produces spatially explicit lake ice maps with pixel-wise accuracies > 91% (respectively, mIoU scores > 60%) and generalises well across different lakes and winters. Moreover, it sets a new state-of-the-art for determining the important ice-on and ice-off dates for the target lakes, in many cases meeting the GCOS requirement.

Dissolved Oxygen in a Shallow Ice-Covered Lake in Winter: Effect of Changes in Light, Thermal and Ice Regimes

Oxygen conditions in ice-covered lakes depend on many factors, which, in turn, are influenced by a changing climate, so detection of the oxygen trend becomes difficult. Our research was based on data of long-term measurements of dissolved oxygen (2007–2020), water temperature, under-ice solar radiation, and snow-ice thickness (1995–2020) in Lake Vendyurskoe (Northwestern Russia). Changes of air temperature and precipitation in the study region during 1994–2020 and ice phenology of Lake Vendyurskoe for the same period based on field data and FLake model calculations were analyzed. The interannual variability of ice-on and ice-off dates covered wide time intervals (5 and 3 weeks, respectively), but no significant trends were revealed. In years with early ice-on, oxygen content decreased by more than 50% by the end of winter. In years with late ice-on and intermediate ice-off, the oxygen decrease was less than 40%. A significant negative trend was revealed for snow-ice cover thickness in spring. A climatic decrease of snow-ice cover thickness contributes to the rise of under-ice irradiance and earlier onset of under-ice convection. In years with early and long convection, an increase in oxygen content by 10–15% was observed at the end of the ice-covered period, presumably due to photosynthesis of phytoplankton.

Arctic char enter the marine environment before annual ice breakup in the high Arctic

Mobile consumers often match their movements to short-term resource pulses. In the Arctic, seasonal ice breakup facilitates an ephemeral productivity pulse exploited by marine consumers. The migration of anadromous Arctic char (Salvelinus alpinus) to marine waters occurs around the beginning of ice breakup, but the precise timing of movement is equivocal and current evidence is conflicting. To investigate the migratory timing of Arctic char, 34 individuals were tagged with acoustic telemetry transmitters within Tremblay Sound, Nunavut, Canada in two successive years. All tagged fish entered the marine environment before the coastal ice-off date (mean ± SE: 7.56 ± 0.56 days). Further movement metrics revealed that char utilized much of the sound before the ice-off date, with only slightly higher mean home ranges (0.3 km2 larger) and residency indices (by ~ 0.05) during the period following the ice-off date than prior. Such entry and use of marine waters prior to ice breakup may impart energetic benefits to early migrants, maximizing exploitation of the short, anticipated pulse of productivity. The current study provides a unique example of resource tracking that could confer heightened fitness to a marine consumer in the rapidly warming high Arctic.

Late Ice-Off Negatively Influences Breeding in Common Loons (Gavia immer)

Productivity of Gavia immer (Common Loon) has declined in Ontario and across southern Canada. Variations in the timing of lake ice-off have the potential to negatively influence productivity of Common Loons, but there is conflicting evidence as to how ice-off dates affect this species' reproductive success. Our study investigated the association between annual ice-off timing in southern Ontario and the presence and reproductive success of Common Loons surveyed at 69 small lakes in 16 years over a 38-year span (1982–2019). We found negative relationships between residual ice-off date and the presence of Common Loon pairs, the proportion of Common Loon pairs attempting to breed, and the number of large young per pair per year, suggesting that there were fewer pairs, breeding attempts per pair, and large young per pair in years with later ice-off dates. Our results show that ice-off date is an important factor affecting reproduction in Common Loons, and that ice-off dates can be used to help predict annual variations in productivity of Common Loons.

The Influence of Snow and Ice Albedo towards Improved Lake Ice Simulations

Lake ice models are a vital tool for studying the response of ice-covered lakes to changing climates throughout the world. The Canadian Lake Ice Model (CLIMo) is a one-dimensional freshwater ice cover model that simulates Arctic and sub-Arctic lake ice cover well. Modelling ice cover in temperate regions has presented challenges due to the differences in ice composition between northern and temperate region lake ice. This study presents a comparison of measured and modelled ice regimes, with a focus on refining CLIMo for temperate regions. The study sites include two temperate region lakes (MacDonald Lake and Clear Lake, Central Ontario) and two High Arctic lakes (Resolute Lake and Small Lake, Nunavut) where climate and ice cover information have been recorded over three seasons. The ice cover simulations were validated with a combination of time lapse imagery, field measurements of snow depth, snow density, ice thickness and albedo data, and historical ice records from the Canadian Ice Database (for Resolute Lake). Simulations of High Arctic lake ice cover show good agreement with previous studies for ice-on and ice-off dates (MAE 6 to 8 days). Unadjusted simulations for the temperate region lakes show good ice-on timing, but an under-representation of ice thickness, and earlier complete ice-off timing (~3 to 5 weeks). Field measurements were used to adjust the albedo values used in CLIMo, which resulted in improvements to both simulated ice thickness (~3 cm MAE compared to manual measurements), and ice-off timing, within 0 to 7 days (2 days MAE) of observations. These findings suggest regionally specific measurements of albedo can improve the accuracy of lake ice simulations, which further our knowledge of the response of temperate and High Arctic lake ice regimes to climate conditions.

Arctic char Salvelinus alpinus movement dynamics relative to ice breakup in a high Arctic embayment

Arctic waters are warming rapidly due to climate change, which is altering the timing of seasonal sea ice dynamics. Summer ice breakup provides a critical productivity bloom that consumers depend on. Arctic char Salvelinus alpinus undertake seasonal migrations to marine waters presumably to exploit this prey pulse. However, specific migratory timing and residency of char relative to breakup is largely unknown. To investigate char movement, individuals were tagged with acoustic transmitters in 2017 (n = 58) and 2018 (n = 52) within Tremblay Sound, Nunavut, Canada, resulting in 625482 detections. Generalized linear models were used to relate multiple movement metrics to ice conditions as well as biological and temporal factors. Char exhibited multiple migratory patterns (chronologies), by which fish either migrated to/from rivers within Tremblay Sound (n = 67), rivers in external systems (n = 35), or a combination of both (n = 8). Fish that migrated exclusively from external systems were longer (~14 cm) than fish exhibiting other chronologies. Migration timing was related to chronology and preempted the specific ice-off date. Fish migrating from rivers within Tremblay Sound entered the marine environment ~7.5 d before the start of ice-off, while external migrants entered ~21 d after ice-off start. Differing migratory chronologies highlight the complexity of char migrations and may indicate the presence of subpopulations or potential ontogenetic shifts in migration behavior. Our study underscores the importance of the brief ice-free season, with potential implications for climate change resilience and management of this important resource in a changing Arctic.

Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams Using Machine Learning

Continuous observation of climate indicators, such as trends in lake freezing, is important to understand the dynamics of the local and global climate system. Consequently, lake ice has been included among the Essential Climate Variables (ECVs) of the Global Climate Observing System (GCOS), and there is a need to set up operational monitoring capabilities. Multi-temporal satellite images and publicly available webcam streams are among the viable data sources capable of monitoring lake ice. In this work we investigate machine learning-based image analysis as a tool to determine the spatio-temporal extent of ice on Swiss Alpine lakes as well as the ice-on and ice-off dates, from both multispectral optical satellite images (VIIRS and MODIS) and RGB webcam images. We model lake ice monitoring as a pixel-wise semantic segmentation problem, i.e., each pixel on the lake surface is classified to obtain a spatially explicit map of ice cover. We show experimentally that the proposed system produces consistently good results when tested on data from multiple winters and lakes. Our satellite-based method obtains mean Intersection-over-Union (mIoU) scores &gt; 93%, for both sensors. It also generalises well across lakes and winters with mIoU scores &gt; 78% and &gt;80% respectively. On average, our webcam approach achieves mIoU values of ≈87% and generalisation scores of ≈71% and ≈69% across different cameras and winters respectively. Additionally, we generate and make available a new benchmark dataset of webcam images (Photi-LakeIce) which includes data from two winters and three cameras.

Beyond the trends: The need to understand multiannual dynamics in aquatic ecosystems

Beyond the trends: The need to understand multiannual dynamics in aquatic ecosystems

Water column changes under ice during different winters in a mid-latitude Mediterranean high mountain lake

Winter limnology has been developed mainly in northern-temperate or subarctic lakes, while mid-latitude Mediterranean high mountain lakes have been less studied during the ice-covered season. We present a five-year study in one of these lower latitude high mountain lakes, conducted with multiprobes located at two different depths recording high-frequency data. We have studied highly contrasted winters regarding temperature and snowfall. The results of a principal component analysis and a subsequent hierarchical clustering show that bottom oxygen depletion under ice is strongly influenced by winter cover thickness and transparency. A thick and opaque winter cover (dark mode) leads to an intense oxygen depletion until anoxia, while a thin and clear winter cover (clear mode) allows higher dissolved oxygen saturation due to oxygen production by photosynthesis. Under unusual conditions of cold and dry climate, only a weak decrease in bottom dissolved oxygen was observed. The extent of dissolved oxygen depletion and its relationship with meteorological parameters and climate patterns are further investigated with generalized additive models. Winter cover thickness and phenology are driven by the joint effect of the North Atlantic Oscillation and East Atlantic climatic patterns. Ice phenology could also influence the following ice-free period given the correlation of lake heat content with the ice-off date and the ice cover length. We propose some features jointly occurring in Lake Cimera as a model for mid-latitude Mediterranean high mountain lakes, including (yet not exclusive) the occurrence of very thick winter covers, the prevalence of dark mode, the relatively high and similar through the years oxygen depletion rates, and high water temperatures during the ice-free periods. It is unclear how the ongoing climate change will affect the prevalence of dark over clear modes due to the expected antagonistic effects of warmer temperatures and lower snowfalls.

MODELING THE THERMO-HYDRODYNAMICS OF A SHALLOW BOREAL LAKE: 3D MODEL VERIFICATION

3D modelled results were verified against observed data obtained along three transects in a shallow boreal lake Vendyurskoe several times during the ice season. It was revealed that 1) the model overestimates ice thickness; at the same time, modelled ice-on and iceoff dates are very close to those observed; 2) in general, the model underestimates the water temperature by 8–10 %; 3) comparison of modelled currents with observed data on mean currents revealed qualitative compliance of current direction (coincidence of quadrants) and modulus of velocity (coincidence of the order of magnitude and a slow decrease of velocity over time during the ice season 1994–1995). Underestimated water temperature may affect the quality of simulation of chemical-biological processes. For instance, one may expect overstated absolute values of dissolved oxygen content in the bulk of the water column. Overestimated modelled water temperature for layers near the bottom of local cavities may influence the rates of the chemical-biological processes occurring there. Despite the model errors found in the course of verification, the model quite realistically describes the hydrodynamic processes in a shallow ice-covered lake, and can therefore be regarded as a useful tool for further research after the diagnosed defects are removed from the computer code. As an option of the code improvement, the authors consider further elaboration of the module of heat/salt flux to/from bottom sediment, development of parameterisations facilitating heat transfer along the water column on sub-grid scale.

Explaining the Non-significant Changes in Ice-off Date over Six Decades at Lake of Bays and Lake Nipissing, South-Central Ontario

The phenomenon of non-significant trends in ice-off date under a warming climate was quantitatively explained by three efforts: exploring possible driving factors where possible and defining new factors to represent snow conditions, identifying the contributing factors through correlation and trend tests, and evaluating relative contributions through partial Mann-Kendall method. Why the ice-off became only slightly earlier over 62 years at Lake of Bays has been satisfactorily assessed: the increased winter temperature, increased total rain and decreased days of snow on ground acted as three promoting drivers to earlier ice-off date, but their promoting functions were effectively offset by adverse changes in four other factors (snowfall slope, precipitation slope, snowpack slope, and last day of snow). The ice-off date at Lake Nipissing did not have a significant trend over 58 years, although there were five factors contributing to the ice-off decline without sufficient offsetting, suggesting that the ice-off of this lake may not be sensitive, or basically elastic, to the climatic variation stressor. Relative contributions of drivers as calculated helped explain how much they contributed to ice-off trends or how much they offset the influences.

High-frequency climate oscillations drive ice-off variability for Northern Hemisphere lakes and rivers

This study examines the climatic drivers of ice-off dates for lakes and rivers across the Northern Hemisphere. Most lakes and rivers have trended toward earlier ice-off dates over the last century, as would be expected from long-term climate change. However, we also identify modes of climate variability that significantly impact the short-term behavior of ice-off time series. In particular, the North Atlantic Oscillation (NAO), Pacific-North American Pattern (PNA), and to a lesser degree the El Nino-Southern Oscillation (ENSO) explain a substantial fraction of the interannual variance in melt dates, while the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) generally do not. Furthermore, the spatial pattern of the early or late ice-off dates associated with the NAO, PNA, and ENSO matches a priori expectations due to the known surface temperature patterns associated with these oscillations. In all regions, the strongest correlation to ice-off is with one of the high-frequency modes—the NAO or PNA, suggesting that short-term weather variations play a stronger role than lower-frequency climate variability (ENSO, PDO, AMO) in driving ice-off.

Trends and abrupt changes in 104 years of ice cover and water temperature in a dimictic lake in response to air temperature, wind speed, and water clarity drivers

Abstract. The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.

The interplay of local and regional factors in generating temporal changes in the ice phenology of Dickie Lake, south-central Ontario, Canada

Ice-on date occurred significantly later over 1975–2009 at Dickie Lake, Ontario, while ice-off date showed no significant trend, differing from many other records in North America. We examined the ice phenology using 3 modelling approaches: a lake-specific regression model to derive a suite of local predictors; a regionally derived regression model to test larger-scale predictors; and a physically based, one-dimensional thermodynamic model. All 3 models were also applied to generate future ice cover scenarios. The local regression revealed air temperature to be an important predictor of ice phenology in our area, as reported elsewhere; however, reductions in wind speed and increases in lake heat storage over the last 35 years also contributed significantly to a delayed ice-on date. Ice-off dates were strongly correlated with the effects of warmer air temperatures but also influenced by increased snowfall and reduced wind speed. Thus, although changes in ice phenology were related to continental-scale changes in air temperature, they were also influenced by more localized climatic variables, and a careful examination of local events was needed for a complete assessment of ice phenology. Predictabilities of the regional regression model, which primarily relied on air temperature to predict phenology, and the physically based model were lower than the lake-specific local regressions, reinforcing the need for inclusion of local variables when greater accuracy is important. Finally, the 3 methods generated similar estimates of reductions in ice cover over the next 90 years, predicting a 4050 day decrease in ice season length by 2100.

Homage to Hutchinson: does inter-annual climate variability affect zooplankton density and diversity?

G. Evelyn Hutchinson proposed that external control by climate limits the fundamental productivity and the possible diversity of ecological communities. These climatic drivers are currently changing as a result of human activity, which may herald a shift in the influence of climate on global ecosystems. Long-term records reveal a reduction in ice cover on northern lakes over the last several centuries. Hence, we explore whether inter-annual climatic variability, represented by ice cover, influences the productivity and diversity of zooplankton communities in long-term datasets for five lakes in Northern Wisconsin. We used a multilevel modeling approach to test three predictions: (1) density will increase, (2) diversity will increase, and (3) community composition will be altered. We found an inverse relationship between ice-off date and annual zooplankton density. Daphnia density, for example, was inversely related to ice-off date, with 10-fold variability across the gradient of ice-off dates in Northern Wisconsin. In contrast, we did not observe a consistent shift in diversity or community structure. Thus, from ice cover records of northern lakes we found support for Hutchinson’s idea that external climatic forces may regulate aquatic productivity; however, the response was numeric and we did not find evidence that lakes moved closer to maximum diversity on an inter-annual scale.