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

A Global lake ecological observatory network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate processbased ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest

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

Relating Urban Biodiversity to Human Health With the ‘Holobiont’ Concept

A relatively unaccounted ecosystem service from biodiversity is the benefit to human health via symbiotic microbiota from our environment. This benefit occurs because humans evolved alongside microbes and have been constantly exposed to diverse microbiota. Plants and animals, including humans, are organised as a host with symbiotic microbiota, whose collective genome and life history form a single holobiont. As such, there are interdependencies between biodiversity, holobionts, and public health which lead us to argue that human health outcomes could be improved by increasing contact with biodiversity in an urban context. We propose that humans, like all holobionts, likely require a diverse microbial habitat to appropriate resources for living healthy, long lives. We discuss how industrial urbanisation likely disrupts the symbiosis between microbiota and their hosts, leading to negative health outcomes. The industrialised urban habitat is low in macro and microbial biodiversity and discourages contact with beneficial environmental microbiota. These habitat factors, alongside diet, antibiotics, and others, are associated with the epidemic of non-communicable diseases in these societies. We suggest that restoration of urban microbial biodiversity and micro-ecological processes through microbiome rewilding can benefit holobiont health and aid in treating the urban non-communicable disease epidemic. Further, we identify research gaps and some solutions to economic and strategic hurdles in applying microbiome rewilding into daily urban life

Latitude and lake size are important predictors of over-lake atmospheric stability: Atmospheric Stability Above Lakes

Turbulent fluxes across the air‐water interface are integral to determining lake heat budgets, evaporation, and carbon emissions from lakes. The stability of the atmospheric boundary layer (ABL) influences the exchange of turbulent energy. We explore the differences in over‐lake ABL stability using data from 39 globally distributed lakes. The frequency of unstable ABL conditions varied between lakes from 71 to 100% of the time, with average air temperatures typically several degrees below the average lake surface temperature. This difference increased with decreasing latitude, resulting in a more frequently unstable ABL and a more efficient energy transfer to and from the atmosphere, toward the tropics. In addition, during summer the frequency of unstable ABL conditions decreased with increasing lake surface area. The dependency of ABL stability on latitude and lake size has implications for heat loss and carbon fluxes from lakes, the hydrologic cycle, and climate change effects

Slaughter weight rather than sex affects carcass cuts and tissue composition of Bisaro pigs

Carcass cuts and tissue composition were assessed in Bisaro pigs (n=64) from two sexes (31 gilts and 33 entire males) reared until three target slaughter body-weights (BW) means: 17 kg, 32 kg, and 79 kg. Dressing percentage and backfat thickness increased whereas carcass shrinkage decreased with increasing BW. Slaughter weight affected most of the carcass cut proportions, except shoulder and thoracic regions. Bone proportion decreased linearly with increasing slaughter BW, while intermuscular and subcutaneous adipose tissue depots increased concomitantly. Slaughter weight increased the subcutaneous adipose tissue proportion but this impaired intramuscular and intermuscular adipose tissues in the loin primal. The sex of the pigs minimally affected the carcass composition, as only the belly weight and the subcutaneous adipose tissue proportions were greater in gilts than in entire males. Light pigs regardless of sex are recommended to balance the trade-offs between carcass cuts and their non-edible compositional outcomes.Work included in the Portuguese PRODER research Project BISOPORC – Pork extensive production of Bísara breed, in two alternative systems: fattening on concentrate vs chesnut, Project PRODER SI I&DT Medida 4.1 “Cooperação para a Inovação”. The authors are grateful to Laboratory of Carcass and Meat Quality of Agriculture School of Polytechnic Institute of Bragança ‘Cantinho do Alfredo’. The authors are members of the MARCARNE network, funded by CYTED (ref. 116RT0503).info:eu-repo/semantics/publishedVersio

A Global Lake Ecological Observatory Network (GLEON) for synthesising high–frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process-based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest

Rapid and highly variable warming of lake surface waters around the globe

In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade-1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors - from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade-1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade-1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes