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1. Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems

   https://doi.org/10.1002/ecy.4219  

   Siqueira, Tadeu; Hawkins, Charles P.; Olden, Julian D.; Tonkin, Jonathan; Comte, Lise; Saito, Victor S.; Anderson, Thomas L.; Barbosa, Gedimar P.; Bonada, Núria; Bonecker, Claudia C.; et al (February 2024, Ecology)

   Abstract A tenet of ecology is that temporal variability in ecological structure and processes tends to decrease with increasing spatial scales (from locales to regions) and levels of biological organization (from populations to communities). However, patterns in temporal variability across trophic levels and the mechanisms that produce them remain poorly understood. Here we analyzed the abundance time series of spatially structured communities (i.e., metacommunities) spanning basal resources to top predators from 355 freshwater sites across three continents. Specifically, we used a hierarchical partitioning method to disentangle the propagation of temporal variability in abundance across spatial scales and trophic levels. We then used structural equation modeling to determine if the strength and direction of relationships between temporal variability, synchrony, biodiversity, and environmental and spatial settings depended on trophic level and spatial scale. We found that temporal variability in abundance decreased from producers to tertiary consumers but did so mainly at the local scale. Species population synchrony within sites increased with trophic level, whereas synchrony among communities decreased. At the local scale, temporal variability in precipitation and species diversity were associated with population variability (linear partial coefficient, β = 0.23) and population synchrony (β = −0.39) similarly across trophic levels, respectively. At the regional scale, community synchrony was not related to climatic or spatial predictors, but the strength of relationships between metacommunity variability and community synchrony decreased systematically from top predators (β = 0.73) to secondary consumers (β = 0.54), to primary consumers (β = 0.30) to producers (β = 0). Our results suggest that mobile predators may often stabilize metacommunities by buffering variability that originates at the base of food webs. This finding illustrates that the trophic structure of metacommunities, which integrates variation in organismal body size and its correlates, should be considered when investigating ecological stability in natural systems. More broadly, our work advances the notion that temporal stability is an emergent property of ecosystems that may be threatened in complex ways by biodiversity loss and habitat fragmentation. 

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2. Seasonal and interannual changes in a coastal Antarctic zooplankton community

   https://doi.org/10.3354/meps14256  

   Conroy, JA; Steinberg, DK; Thomas, MI; West, LT (February 2023, Marine Ecology Progress Series)

   Seasonal fluctuations are key features of high-latitude marine ecosystems, where zooplankton exhibit a wide array of adaptations within their life cycles. Repeated, sub-seasonal sampling of Antarctic zooplankton is rare, even along the West Antarctic Peninsula (WAP), where multidecadal changes in sea ice and phytoplankton are well documented. We quantified zooplankton biomass, size structure, and composition at 2 coastal time-series stations in the northern WAP over 3 field seasons (November-March) with different sea-ice, temperature, and phytoplankton conditions. Seasonal peaks in zooplankton biomass followed weeks after phytoplankton blooms. Biomass of mesozooplankton (0.2-2 mm) was consistent and low, while high biomass of macrozooplankton (>2 mm) occasionally resulted in a size distribution dominated by krill and salps, which appears to be a characteristic phenomenon of the Southern Ocean. Zooplankton composition and size changed between years and from spring to summer as the water column warmed after sea-ice breakup. Seasonal succession was apparent typically in decreasing zooplankton size and a shift to species that are less dependent upon phytoplankton. Mean central abundance dates varied by 54 d across 14 taxa, and specific feeding preferences and life-history traits explained the different seasonal abundance patterns. In all 3 yr, the dominant euphausiid species switched from Euphausia superba in spring to Thysanoessa macrura in late summer. Various taxa shifted their phenology between years in response to the timing of sea-ice breakup and the onset of phytoplankton productivity, a level of natural environmental variability to which they appear resilient. Nevertheless, the limits to this resilience in response to climate change remain uncertain. 

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3. Sampling Regime Effects on Detecting Spatial Stability of Water Quality

   https://doi.org/10.1029/2024WR038844  

   Dai, Dan; Fernandez, Nicolas; Cohen, Matthew J; Jawitz, James W (September 2025, Water Resources Research)

   Abstract Protecting surface water quality can be complicated by high spatiotemporal variability. Pollutant sources and transport pathways may be identified through sufficiently high‐density monitoring sites and high‐frequency sampling, but practical considerations necessitate tradeoffs between spatial and temporal resolution in water quality monitoring network design. We examined how tradeoffs in sampling density and frequency affect measures of spatiotemporal variability in water quality, emphasizing pattern stability over time. We quantified the spatial stability of stream water quality across >250 monitoring sites in the intensively monitored watershed draining to Lake Okeechobee, FL using Spearman's rank correlations between instantaneous observations and site long‐term means for each parameter. We found that water quality spatial patterns for geogenic, biogenic, and anthropogenic parameters were generally stable on decadal timescales for all solutes, and that sampling densely in space yields more information than sampling frequently in time. Variations in spatial stability decreased with increased sampling density but not with greater sampling frequency, attesting to the dominance of spatial variability over temporal variability. For nutrients, the spatial coefficient of variation (CV) was approximately double the temporal CV. Spatial stability of most solutes was similar across flow conditions, but high‐flow monitoring allows for more sites that effectively capture the long‐term spatial patterns of nutrient sources. Water quality monitoring regimes can be optimized for efficiency in capturing water quality patterns and should be adjusted to focus more on spatial variation. We discuss potential improvements for water quality monitoring, particularly in watersheds where scarce resources necessitate tradeoffs between sampling density and frequency. 

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4. Local environmental conditions structured discrete fish assemblages in Arctic lagoons

   https://doi.org/10.1007/s00300-024-03239-8  

   Laske, Sarah M; von_Biela, Vanessa R; Stanek, Ashley E; Dunton, Kenneth H (June 2024, Polar Biology)

   Abstract Rapid changes in sea ice extent and changes in freshwater inputs from land are rapidly changing the nature of Arctic estuarine ecosystems. In the Beaufort Sea, these nearshore habitats are known for their high productivity and mix of marine resident and diadromous fishes that have great subsistence value for Indigenous communities. There is, however, a lack of information on the spatial variation among Arctic nearshore fish communities as related to environmental drivers. In summers of 2017–2019, we sampled fishes in four estuarine ecosystems to assess community composition and relate fish abundance to temperature, salinity, and wind conditions. We found fish communities were heterogeneous over larger spatial extents with rivers forming fresh estuarine plumes that supported diadromous species (e.g., broad whitefishCoregonus nasus), while lagoons with reduced freshwater input and higher salinities were associated with marine species (e.g., saffron codEleginus gracilis). West–East directional winds accounted for up to 66% of the community variation, indicating importance of the wind-driven balance between fresh and marine water masses. Salinity and temperature accounted for up to 54% and 37% of the variation among lagoon communities, respectively. Recent sea ice declines provide more opportunity for wind to influence oceanographic conditions and biological communities. Current subsistence practices, future commercial fishing opportunities, and on-going oil and gas activities benefit from a better understanding of current fish community distributions. This work provides important data on fish spatial distributions and community composition, providing a basis for fish community response to changing climatic conditions and anthropogenic use. 

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5. Progress and opportunities in advancing near‐term forecasting of freshwater quality

   https://doi.org/10.1111/gcb.16590  

   Lofton, Mary E.; Howard, Dexter W.; Thomas, R. Quinn; Carey, Cayelan C. (April 2023, Global Change Biology)

   Abstract Near‐term freshwater forecasts, defined as sub‐daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near‐term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms) and ecosystem services (e.g., water‐related recreation and tourism). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past 5 years. We found that freshwater forecasting is currently dominated by near‐term forecasts of waterquantityand that near‐term waterqualityforecasts are fewer in number and in the early stages of development (i.e., non‐operational) despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed and that near‐term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end‐user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events 5 days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts will require substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near‐term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management. 

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