scholarly journals Can pesticides, copper and seasonal water temperature explain the seagrass Zostera noltei decline in the Arcachon bay?

2018 ◽  
Vol 134 ◽  
pp. 66-74 ◽  
Author(s):  
Perrine Gamain ◽  
Agnès Feurtet-Mazel ◽  
Régine Maury-Brachet ◽  
Isabelle Auby ◽  
Fabien Pierron ◽  
...  
2016 ◽  
Vol 179 ◽  
pp. 4-11 ◽  
Author(s):  
Cristina Ribaudo ◽  
Martin Plus ◽  
Florian Ganthy ◽  
Isabelle Auby

2018 ◽  
Vol 200 ◽  
pp. 1-13 ◽  
Author(s):  
S. Rigaud ◽  
B. Deflandre ◽  
O. Maire ◽  
G. Bernard ◽  
J.C. Duchêne ◽  
...  

2018 ◽  
Vol 140 ◽  
pp. 87-104 ◽  
Author(s):  
Mathis Cognat ◽  
Florian Ganthy ◽  
Isabelle Auby ◽  
Frédéric Barraquand ◽  
Loïc Rigouin ◽  
...  

Author(s):  
Paula Hatum ◽  
Kathryn McMahon ◽  
Kerrie Mengersen ◽  
Paul Wu

Ecological models are extensively and increasingly used in support of environmental policy and decision making. Dynamic Bayesian Networks (DBN) as a tool for conservation have been demonstrated to be a valuable tool for providing a systematic and intuitive approach to integrating data and other critical information to help guide the decision-making process. However, data for a new ecosystem are often sparse. In this case, a general DBN developed for similar ecosystems could be applicable, but this may require the adaptation of key elements of the network. The research presented in this paper focused on a case study to identify and implement guidelines for model adaptation. We adapted a general DBN of a seagrass ecosystem to a new location where nodes were similar, but the conditional probability tables varied. We focused on two species of seagrass (Zostera noltei and Z. marina) located in Arcachon Bay, France. Expert knowledge was used to complement peer-reviewed literature to identify which components needed adjustment including parameterisation and quantification of the model and desired outcomes. We adopted both linguistic labels and scenario-based elicitation to elicit from experts the conditional probabilities used to quantify the DBN. Following the proposed guidelines, the model structure of the DBN was retained, but the conditional probability tables were adapted for nodes that characterised the growth dynamics in Zostera spp. population located in Arcachon Bay, as well as the seasonal variation on their reproduction. Particular attention was paid to the light variable as it is a crucial driver of growth and physiology for seagrasses. Our guidelines provide a way to adapt a general DBN to specific ecosystems to maximise model reuse and minimise re-development effort. Especially important from a transferability perspective are guidelines for ecosystems with limited data, and how simulation and prior predictive approaches can be used in these contexts.


2014 ◽  
Vol 514 ◽  
pp. 71-86 ◽  
Author(s):  
G Bernard ◽  
ML Delgard ◽  
O Maire ◽  
A Ciutat ◽  
P Lecroart ◽  
...  

2016 ◽  
Vol 545 ◽  
pp. 109-121 ◽  
Author(s):  
B Villazán ◽  
FG Brun ◽  
V González‑Ortiz ◽  
F Moreno‑Marín ◽  
TJ Bouma ◽  
...  

Author(s):  
Alexander G. Okhapkin ◽  
Tabet Hhedairia

The preliminary estimation of composition and structure of diatoms in the benthos of the Oka River allowed to determine the clear spatiotemporal confinedness of structure in such communities of them which has the most diverse composition in the low water period while water temperature decreasing.


2020 ◽  
Vol 3 (1) ◽  
pp. ACCEPTED
Author(s):  
Rho-Jeong Rae

This study investigated the boreal digging frog, Kaloula borealis, to determine the egg hatching period and whether the hatching period is affected by incubation temperature. The results of this study showed that all the eggs hatched within 48 h after spawning, with 28.1% (±10.8, n=52) hatching within 24 h and 99.9% (±0.23, n=49) within 48 h after spawning. A significant difference was noted in the mean hatching proportion of tadpoles at different water temperatures. The mean hatching rates between 15 and 24 h after spawning was higher at a water temperature of 21.1 (±0.2) °C than at 24.1 (±0.2) °C. These results suggest that incubation temperature affected the early life stages of the boreal digging frog, since they spawn in ponds or puddles that form during the rainy season.


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