Evidence for a general species time arearelationship

The species-area relationship (SAR) plays a central role in biodiversity research, and recent work has increased awareness of its temporal analog, the species-time relationship (STR). Here we provide evidence for a general species-time-area-relationship (STAR), in which species number is a function of the area and time span of sampling, as well as their interaction. For eight assemblages ranging from lake zooplankton to desert rodents, this model outperformed a sampling-based model and two simpler models in which area and time had independent effects. In every case the interaction term was negative, meaning that rates of species accumulation in space decreased with the time span of sampling, while species accumulation rates in time decreased with area sampled. Although questions remain about its precise functional form, the STAR provides a tool for scaling species richness across time and space, for comparing the relative rates of species turnover in space and time at different scales of sampling, and for rigorous testing of mechanisms proposed to drive community dynamics. Our results show that the SAR and STR are not separate relationships but two dimensions of one unified pattern. Keywords: community dynamics, spatiotemporal scaling, species diversity, turnover, speciesarea relationship, species-time relationshi

Lake surface temperature [in “State of the Climate in 2017”]

Observed lake surface water temperature anomalies in 2017 are placed in the context of the recent warming observed in global surface air temperature by collating long-term in situ lake surface temperature observations from some of the world’s best-studied lakes and a satellite-derived global lake surface water temperature dataset. The period 1996–2015, 20 years for which satellite-derived lake temperatures are available, is used as the base period for all lake temperature anomaly calculations

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures

Wind and trophic status explain within and among‐lake variability of algal biomass

Phytoplankton biomass and production regulates key aspects of freshwater ecosystems yet its variability and subsequent predictability is poorly understood. We estimated within‐lake variation in biomass using high‐frequency chlorophyll fluorescence data from 18 globally distributed lakes. We tested how variation in fluorescence at monthly, daily, and hourly scales was related to high‐frequency variability of wind, water temperature, and radiation within lakes as well as productivity and physical attributes among lakes. Within lakes, monthly variation dominated, but combined daily and hourly variation were equivalent to that expressed monthly. Among lakes, biomass variability increased with trophic status while, within‐lake biomass variation increased with increasing variability in wind speed. Our results highlight the benefits of high‐frequency chlorophyll monitoring and suggest that predicted changes associated with climate, as well as ongoing cultural eutrophication, are likely to substantially increase the temporal variability of algal biomass and thus the predictability of the services it provides

Forest defoliator outbreaks alter nutrient cycling in northern waters.

Insect defoliators alter biogeochemical cycles from land into receiving waters by consuming terrestrial biomass and releasing biolabile frass. Here, we related insect outbreaks to water chemistry across 12 boreal lake catchments over 32-years. We report, on average, 27% lower dissolved organic carbon (DOC) and 112% higher dissolved inorganic nitrogen (DIN) concentrations in lake waters when defoliators covered entire catchments and reduced leaf area. DOC reductions reached 32% when deciduous stands dominated. Within-year changes in DOC from insect outbreaks exceeded 86% of between-year trends across a larger dataset of 266 boreal and north temperate lakes from 1990 to 2016. Similarly, within-year increases in DIN from insect outbreaks exceeded local, between-year changes in DIN by 12-times, on average. As insect defoliator outbreaks occur at least every 5 years across a wider 439,661 km2 boreal ecozone of Ontario, we suggest they are an underappreciated driver of biogeochemical cycles in forest catchments of this region.Natural Environment Research Council (NE/L006561/1) Ontario Centres of Excellence (OCE/27649) Natural Sciences and Engineering Research Council of Canada (NSERC/509182-17

Impact of extreme weather events frequency and intensity in shaping phytoplankton communities

Lake habitats and communities can often be correlated with general morphometric and geographic characteristics such as depth, latitude, altitude, or watershed area. Further, communities are typically correlated with average environmental conditions such as seasonal temperature and nutrient levels. The frequency and intensity of extreme weather events (rain and wind) are typically not encompassed by average environmental descriptors, yet, can modify the physical habitats of lakes, significantly influencing phytoplankton growth and survival. We tested the hypothesis that lakes with a higher frequency and intensity of extreme weather events have a functionally different phytoplankton assemblage from lakes with a lower frequency of extreme weather events. We compiled long-term (mean = 20±13 years, range 0.6-44 years) phytoplankton datasets for 22 lakes across a wide gradient of altitude, latitude, depth, and trophic state. We classified the phytoplankton genera into morpho-functional groups and C-S-R strategists, and compared among lake phytoplankton assemblages’ characteristics across the gradient of wind and rain conditions experienced by the lakes. We discuss how the frequency of extreme weather events can affect phytoplankton functional groups, the dominance of differing life history strategies and ultimately community structure. The frequency and intensity of extreme events is expected to increase with climate change, with the potential to drive shifts in phytoplankton composition

Wound healing and hyper-hydration - a counter intuitive model

Winters seminal work in the 1960s relating to providing an optimal level of moisture to aid wound healing (granulation and re-epithelialisation) has been the single most effective advance in wound care over many decades. As such the development of advanced wound dressings that manage the fluidic wound environment have provided significant benefits in terms of healing to both patient and clinician. Although moist wound healing provides the guiding management principle confusion may arise between what is deemed to be an adequate level of tissue hydration and the risk of developing maceration. In addition, the counter-intuitive model ‘hyper-hydration’ of tissue appears to frustrate the moist wound healing approach and advocate a course of intervention whereby tissue is hydrated beyond what is a normally acceptable therapeutic level. This paper discusses tissue hydration, the cause and effect of maceration and distinguishes these from hyper-hydration of tissue. The rationale is to provide the clinician with a knowledge base that allows optimisation of treatment and outcomes and explains the reasoning behind wound healing using hyper-hydration

A global dataset on weather, lake physics, and phytoplankton dynamics

We compiled data from over 30 lakes across the globe to address how storms influence thermal structure and phytoplankton community dynamics mediated by lake conditions and functional traits. In addition to (generally) fortnightly phytoplankton samples (mean ± SD temporal coverage across all lakes = 20 ± 13 years), the dataset includes limnological variables from standard long-term monitoring programs (24 ± 15 years coverage), daily weather observations (16 ± 10 years coverage) and, when available, high-frequency lake water temperature and water chemistry profiles (12 ± 7 years coverage). All data have been standardized to similar formats and include complete metadata. We used the dataset to develop an R-package (“algaeClassify”), which assigns phytoplankton genus/species information to multiple functional trait groups, and here we provide a summary of ongoing research using the dataset to investigate: 1) the influence of storm events on seasonal phytoplankton succession, 2) the impact of storms on lake thermal structure, and 3) whether lake phytoplankton communities are shaped by long-term patterns in disturbance frequency and intensity. We give an overview on how to access these data, and we further highlight the opportunities the dataset provides for asking both basic and applied questions in limnology, ecology, climate change, and lake management

Lake-size dependency of wind shear and convection as controls on gas exchange

High-frequency physical observations from 40 temperate lakes were used to examine the relative contributions of wind shear (u*) and convection (w*) to turbulence in the surface mixed layer. Seasonal patterns of u* and w* were dissimilar; u* was often highest in the spring, while w * increased throughout the summer to a maximum in early fall. Convection was a larger mixed-layer turbulence source than wind shear (u */w*-1 for lakes* and w* differ in temporal pattern and magnitude across lakes, both convection and wind shear should be considered in future formulations of lake-air gas exchange, especially for small lakes. © 2012 by the American Geophysical Union.Jordan S. Read, David P. Hamilton, Ankur R. Desai, Kevin C. Rose, Sally MacIntyre, John D. Lenters, Robyn L. Smyth, Paul C. Hanson, Jonathan J. Cole, Peter A. Staehr, James A. Rusak, Donald C. Pierson, Justin D. Brookes, Alo Laas, and Chin H. W