Assessing alternative lake management actions for climate change adaptation.

Lake management actions are required to protect lake ecosystems that are being threatened by climate change. Freshwater lakes in semiarid regions are of upmost importance to their region. Simulations of the subtropical Lake Kinneret project that rising temperatures will cause change to phytoplankton species composition, including increased cyanobacteria blooms, endangering lake ecosystem services. Using lake ecosystem models, we examined several management actions under climate change, including two alternatives of desalinated water introduction into the lake, hypolimnetic water withdrawal, watershed management changes and low versus high lake water level. To account for prediction uncertainty, we utilized an ensemble of two 1D hydrodynamic-biogeochemical lake models along with 500 realizations of meteorological conditions. Results suggest that supplying desalinated water for local use, thus releasing more natural waters through the Jordan River, increasing nutrient flow, may reduce cyanobacteria blooms, mitigating climate change effects. However, these results are accompanied by considerable uncertainty.

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.

Early warning signals have limited applicability to empirical lake data.

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

Planktonic functional diversity changes in synchrony with lake ecosystem state.

Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional diversity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of biodiversity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait-based indicators. There is consequently a knowledge gap regarding when functioning changes relative to biodiversity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance-based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non-linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. Individual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of biodiversity when considered at the system level.

A novel approach for accurate quantification of lake residence time - Lake Kinneret as a case study.

Water residence time, which is affected by increasing water demands and climate change, plays a crucial role in lakes and reservoirs since it influences many natural physical and ecological processes that eventually impact the water quality of the waterbody. Thus, accurate quantification of the water residence time and its distribution is an important tool in lake management. In this study we present a novel approach for assessing the residence time in lakes and reservoirs. The approach is based on the Leslie matrix model that was originally developed for the analysis of age-structured biological population dynamics. In this approach the water in the lake is divided into different age classes each representing the time since the "parcel" of water entered the lake and provides an overall picture of the water age structure. The traditional approach for calculating residence times, which relies only on the lake volume and annual inflow or outflow volumes thereby disregarding any previous information, is very sensitive to large interannual variation. While the proposed approach produces the fraction and volume distribution curves of all age classes within the lake for each simulated timestep. Thus, in addition to mean residence time, the fraction of young water (FYW), quantifying the "young" fraction of water in the lake can be analyzed. The same is true for any other age class of water. The approach was applied to Lake Kinneret (Sea of Galilee) historical data collected over 32 years (1987-2018) and for prediction of long-term time series based on several future scenarios (inflows and outflows). It offers a more accurate quantification of the mean residence time of water in a lake and can easily be adapted to other waterbodies. Comparison of simulation results may serve as basis for determining the lake's management policy, by controlling the inflows and outflows, that will affect both the mean residence time and the fraction of "young/old" age classes of water.

Causal networks of phytoplankton diversity and biomass are modulated by environmental context.

Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24◦~N58◦) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management.

Costs and benefits of automated high-frequency environmental monitoring - The case of lake water management.

Freshwater lakes are dynamic ecosystems and provide multiple ecosystem services to humans. Sudden changes in lake environmental conditions such as cyanobacterial blooms can negatively impact lake usage. Automated high-frequency monitoring (AHFM) systems allow the detection of short-lived extreme and unpredictable events and enable lake managers to take mitigation actions earlier than if basing decisions on conventional monitoring programmes. In this study a cost-benefit approach was used to compare the costs of implementing and running an AHFM system with its potential benefits for three case study lakes. It was shown that AHFM can help avoid human health impacts, lost recreation opportunities, and revenue losses for livestock, aquaculture and agriculture as well as reputational damages for drinking water treatment. Our results showed that the largest benefits of AHFM can be expected in prevention of human health impacts and reputational damages. The potential benefits of AHFM, however, do not always outweigh installation and operation costs. While for Lake Kinneret (Israel) over a 10-year period, the depreciated total benefits are higher than the depreciated total costs, this is not the case for Lough Gara (Ireland). For Lake Mälaren in Sweden it would depend on the configuration of the AHFM system, as well as on how the benefits are calculated. In general, the higher the frequency and severity of changes in lake environmental conditions associated with detrimental consequences for humans and the higher the number of lake users, the more likely it is that the application of an AHFM system is financially viable.

Intraguild Predation Dynamics in a Lake Ecosystem Based on a Coupled Hydrodynamic-Ecological Model: The Example of Lake Kinneret (Israel).

The food web of Lake Kinneret contains intraguild predation (IGP). Predatory invertebrates and planktivorous fish both feed on herbivorous zooplankton, while the planktivorous fish also feed on the predatory invertebrates. In this study, a complex mechanistic hydrodynamic-ecological model, coupled to a bioenergetics-based fish population model (DYCD-FISH), was employed with the aim of revealing IGP dynamics. The results indicate that the predation pressure of predatory zooplankton on herbivorous zooplankton varies widely, depending on the season. At the time of its annual peak, it is 10-20 times higher than the fish predation pressure. When the number of fish was significantly higher, as occurs in the lake after atypical meteorological years, the effect was a shift from a bottom-up controlled ecosystem, to the top-down control of planktivorous fish and a significant reduction of predatory and herbivorous zooplankton biomass. Yet, seasonally, the decrease in predatory-zooplankton biomass was followed by a decrease in their predation pressure on herbivorous zooplankton, leading to an increase of herbivorous zooplankton biomass to an extent similar to the base level. The analysis demonstrates the emergence of non-equilibrium IGP dynamics due to intra-annual and inter-annual changes in the physico-chemical characteristics of the lake, and suggests that IGP dynamics should be considered in food web models in order to more accurately capture mass transfer and trophic interactions.

Assessment and implementation of a methodological framework for sustainable management: Lake Kinneret as a case study.

We outlined a methodological framework for sustainable water resource management comprising of ecological monitoring, quantified water quality and an ecosystem model. We tested the proposed framework on the subtropical Lake Kinneret (Israel), a major national water resource. Methodologically, this study linked the economic activities in Lake Kinneret and its watershed (i.e. nutrient loads and water supply regimes) with lake water quality, sustaining of which was considered as the management objective. Based on analysis of the monitoring data and model scenario simulations we established quantitative relationships between changes to lake water level and nutrient loading and water quality. We assessed a set of ranges of nutrient loads from the watershed and water levels that will allow conservation of the lake water quality within pre-defined limits thereby defining limits for a sustainable management policy for the lake water resources. The defined sustainable management policy is in good correspondence with the loads and water level permissible ranges estimated from the ecological monitoring of the lake.

Estimation of long-term bacterial respiration and growth efficiency in Lake Kinneret.

Semi-annual averaged values of photosynthetic carbon fixation (PCF), community respiration (CR), bacterial productivity (BP) and zooplankton carbon biomass, measured biweekly or monthly, were used to obtain long-term estimates of bacterial respiration (BR) and bacterial growth efficiency (BGE) in Lake Kinneret from 2001 through 2007. We posited that CR=BR+phytoplankton respiration (PR)+zooplankton respiration (ZR). Based on the results of independent experimental series, PR was estimated as 0.3 x gross primary production (GPP) and GPP as 1.5 x PCF. ZR was determined by multiplying zooplankton carbon biomass, measured biweekly, with published respiration rates for major zooplankton groups. From these data, we calculated BR and consequently BGE, determined as BP/(BR+BP). Over the entire study period, BR averaged 49 (+/-10)% of CR and was consistently higher during the first half of the year. Semi-annual averaged BGE ranged from 26% to 53%, mean 39 (+/-9)%. Similar values of BGE were obtained if we did not use the measured values for ZR, but estimated BR+ZR from CR-PR and then assumed that BR ranged from two to three times ZR. The approach outlined in this paper can be useful for determining BGE in aquatic systems where long-term data sets of PCF, CR and BP are available.