With the accelerated development of urbanization, rivers in urban areas have become the most closely synergized water ecosystem between human activities and natural processes. To achieve the restoration goal of using hydrological regime change-ecological response relationship to advance the sustainable development of regulated river ecosystems, this study collected ecohydrological data at four tributaries of the Wei River system (Ba, Chan, Feng, and Hei Rivers) at a total of 24 stations in October 2020 and June 2021. Taking ecological flow as hydrological parameter and zooplankton as indicator organism, combined with habitat data scored on-site, the indicator system of zooplankton index of biological integrity and comprehensive habitat quality index was established to explore the hydrological-ecological response relationship in a multi-dimensional way. The results showed that during the ebb stage, the ecological health of the Feng River was better overall, with an average ecological flow value of 267.09 ± 348.62. The ecological health of the Hei River was the worst, with an average ecological flow value of 37.80 ± 38.80. During the abundant water period, the ecological health of the Chan River was optimal with an average ecological flow value of 189.25 ± 190.10, while the ecological health of the Hei River remained unimproved, but the average ecological flow value increased by 283.12 ± 197.76. There was a clear negative correlation relationship between the comprehensive habitat quality index and ecological flow. The correlation between zooplankton index of biological integrity and ecological flows is extremely strong and threshold values exist, but there is strong heterogeneity in the interaction of disturbance factors across water systems, which may not provide a predictable response to flow changes. This study aims to provide a case reference for flow management in watersheds that also lack long-time series hydrological data and to contribute new thinking to the wide application of the hydrological-ecological response relationship.

Climate change has advanced plant phenology globally 4-6 d °C-1 on average. Such shifts are some of the most reported and predictable biological impacts of rising temperatures. Yet as climate change has marched on, phenological shifts have appeared muted over recent decades - failing to match simple predictions of an advancing spring with continued warming. The main hypothesis for these changing trends is that interactions between spring phenological cues - long-documented in laboratory environments - are playing a greater role in natural environments due to climate change. Here, we argue that accurately linking shifts observed in long-term data to underlying phenological cues is slowed by biases in observational studies and limited integration of insights from laboratory studies. We synthesize seven decades of laboratory experiments to quantify how phenological cue-space has been studied and how treatments compare with shifts caused by climate change. Most studies focus on one cue, limiting our ability to make accurate predictions, but some well-studied forest species offer opportunities to advance forecasting. We outline how greater integration of controlled-environment studies with long-term data could drive a new generation of laboratory experiments, built on physiological insights, that would transform our fundamental understanding of phenology and improve predictions.

AbstractDirect species interactions are commonly included in individual fitness models used for coexistence and local diversity modeling. Though widely considered important for such models, direct interactions alone are often insufficient for accurately predicting fitness, coexistence, or diversity outcomes. Incorporating higher-order interactions (HOIs) can lead to more accurate individual fitness models but also adds many model terms, which can quickly result in model overfitting. We explore approaches for balancing the trade-off between tractability and model accuracy that occurs when HOIs are added to individual fitness models. To do this, we compare models parameterized with data from annual plant communities in Australia and Spain, varying in the extent of information included about the focal and neighbor species. The best-performing models for both data sets were those that grouped neighbors based on origin status and life form, a grouping approach that reduced the number of model parameters substantially while retaining important ecological information about direct interactions and HOIs. Results suggest that the specific identity of focal or neighbor species is not necessary for building well-performing fitness models that include HOIs. In fact, grouping neighbors by even basic functional information seems sufficient to maximize model accuracy, an important outcome for the practical use of HOI-inclusive fitness models.

Starving and nondividing yeast cells induce changes in the electron donor nicotinamide adenine dinucleotide (NADH) levels in a cyclic and wave-like manner for over 90min. Yeast suspensions were used to examine the toxic effects of contaminants on the cyclic behaviour of metabolite changes during anaerobic glycolysis. The cyclic behaviour NADH levels in yeast cell suspensions starved for 2 to 5h was studied after the addition of 10mM glucose for 5min followed by 10mM KCN to block aerobic glycolysis. The effects of three toxic elements (CuSO4, silver nanoparticles-nAg, and GdCl3), known for their potential to alter glycolsysis, on NADH levels over time were examined during the 3-h starvation step. The data were analyzed using spectral analysis (Fourier transformation) to characterize the cyclic behaviour of NADH levels during anaerobic glycolysis. Increasing the starvation time by 3h increased the amplitude of changes in NADH levels with characteristic periods of 3 to 8min. Longer starvation times decreased the amplitude of oscillations during these periods, with the appearance of NADH changes at higher frequencies. Moreover, the amplitude changes in NADH were proportional to the starvation time. Exposure to the above chemicals during the 3-h starvation time led to the formation of higher frequencies with concentration-dependent amplitude changes. In comparison with nAg and Gd3+, Cu2+ was the most toxic (decreased viability the most) and produce changes at higher frequencies as well. It is noteworthy that each element produced a characteristic change in the frequency profiles, which suggests different mechanisms of action in which the severity of toxicity shifted NADH changes at higher frequencies. In conclusion, the appearance of synchronized oscillations in dense yeast populations following synchronization stress could be induced by starvation and exposure to chemicals. However, synchronicity could be abolished when cells desynchronize as a result of loss of cell viability, which contributes to heterogeneity in yeast populations, translating into NADH changes at higher frequencies. This is the first report on the influence of environmental contaminants on the cyclic or wave-like behaviour of biochemical changes in cells.

Summer temperature on the Cape Churchill Peninsula (Manitoba, Canada) has increased rapidly over the past 75 years, and flowering phenology of the plant community is advanced in years with warmer temperatures (higher cumulative growing degree days). Despite this, there has been no overall shift in flowering phenology over this period. However, climate change has also resulted in increased interannual variation in temperature; if relationships between phenology and temperature are not linear, an increase in temperature variance may interact with an increase in the mean to alter how community phenology changes over time. In our system, the relationship between phenology and temperature was log-linear, resulting in a steeper slope at the cold end of the temperature spectrum than at the warm end. Because below-average temperatures had a greater impact on phenology than above-average temperatures, the long-term advance in phenology was reduced. In addition, flowering phenology in a given year was delayed if summer temperatures were high the previous year or 2 years earlier (lag effects), further reducing the expected advance over time. Phenology of early-flowering plants was negatively affected only by temperatures in the previous year, and that of late-flowering plants primarily by temperatures 2 years earlier. Subarctic plants develop leaf primordia one or more years prior to flowering (preformation); these results suggest that temperature affects the development of flower primordia during this preformation period. Together, increased variance in temperature and lag effects interacted with a changing mean to reduce the expected phenological advance by 94%, a magnitude large enough to account for our inability to detect a significant advance over time. We conclude that changes in temperature variability and lag effects can alter trends in plant responses to a warming climate and that predictions for changes in plant phenology under future warming scenarios should incorporate such effects.