scholarly journals Response diversity in corals: hidden differences in bleaching mortality among cryptic Pocillopora species

Ecology ◽  
2021 ◽  
Author(s):  
Scott C. Burgess ◽  
Erika C. Johnston ◽  
Alex S.J. Wyatt ◽  
James J. Leichter ◽  
Peter J. Edmunds
Keyword(s):  

2013 ◽  
Vol 49 (2) ◽  
pp. 322-330 ◽  
Author(s):  
Nissan Yissachar ◽  
Tali Sharar Fischler ◽  
Ariel A. Cohen ◽  
Shlomit Reich-Zeliger ◽  
Dor Russ ◽  
...  


Author(s):  
Shaojie Jiang ◽  
Pengjie Ren ◽  
Christof Monz ◽  
Maarten de Rijke


2014 ◽  
Vol 25 ◽  
pp. 186-193 ◽  
Author(s):  
Helena Kahiluoto ◽  
Janne Kaseva ◽  
Kaija Hakala ◽  
Sari J. Himanen ◽  
Lauri Jauhiainen ◽  
...  
Keyword(s):  


2021 ◽  
Author(s):  
Beatrice M. Jobst ◽  
Selen Atasoy ◽  
Adrián Ponce-Alvarez ◽  
Ana Sanjuán ◽  
Leor Roseman ◽  
...  

AbstractLysergic acid diethylamide (LSD) is a potent psychedelic drug, which has seen a revival in clinical and pharmacological research within recent years. Human neuroimaging studies have shown fundamental changes in brain-wide functional connectivity and an expansion of dynamical brain states, thus raising the question about a mechanistic explanation of the dynamics underlying these alterations. Here, we applied a novel perturbational approach based on a whole-brain computational model, which opens up the possibility to externally perturb different brain regions in silico and investigate differences in dynamical stability of different brain states, i.e. the dynamical response of a certain brain region to an external perturbation. After adjusting the whole-brain model parameters to reflect the dynamics of functional magnetic resonance imaging (fMRI) BOLD signals recorded under the influence of LSD or placebo, perturbations of different brain areas were simulated by either promoting or disrupting synchronization in the regarding brain region. After perturbation offset, we quantified the recovery characteristics of the brain area to its basal dynamical state with the Perturbational Integration Latency Index (PILI) and used this measure to distinguish between the two brain states. We found significant changes in dynamical complexity with consistently higher PILI values after LSD intake on a global level, which indicates a shift of the brain’s global working point further away from a stable equilibrium as compared to normal conditions. On a local level, we found that the largest differences were measured within the limbic network, the visual network and the default mode network. Additionally, we found a higher variability of PILI values across different brain regions after LSD intake, indicating higher response diversity under LSD after an external perturbation. Our results provide important new insights into the brain-wide dynamical changes underlying the psychedelic state - here provoked by LSD intake - and underline possible future clinical applications of psychedelic drugs in particular psychiatric disorders.HighlightsNovel offline perturbational method applied on functional magnetic resonance imaging (fMRI) data under the effect of lysergic acid diethylamide (LSD)Shift of brain’s global working point to more complex dynamics after LSD intakeConsistently longer recovery time after model perturbation under LSD influenceStrongest effects in resting state networks relevant for psychedelic experienceHigher response diversity across brain regions under LSD influence after an external in silico perturbation



2020 ◽  
Author(s):  
Friederike G. Engel ◽  
Birte Matthiessen ◽  
Rosyta Andriana ◽  
Britas Klemens Eriksson

AbstractDisturbance events to coastal habitats such as extreme heat events, storms, or floods have increased in magnitude and frequency in recent years due to anthropogenic climate change and the destruction of habitats. These events constitute a major threat to many ecological communities and global biodiversity. Disturbance history influences ecosystem response to novel disturbances such that communities that have previously been exposed to disturbances should be more resilient to new disturbances compared to previously sheltered communities. This principle is defined as ecological memory. Resilience should also increase with access to a larger species pool, because a larger species pool increases species and response diversity of a community. One possibility of increasing the local species pool is connectivity via adequate dispersal between habitat patches with different species compositions in metacommunities. In a laboratory experiment, we exposed benthic diatom communities of different origin to a mechanical disturbance, simulated dispersal in half of the communities, and measured their chlorophyll a concentration over time. The local diatom communities originated from different locations on an intertidal flat that varied in hydrodynamic exposure history. Hydrodynamic exposure disturbs the sediment, and thereby determines sediment properties and the composition of intertidal diatom communities. In the experiment, disturbance negatively affected chlorophyll a concentration across all treatments. However, the response to disturbance depended on the ecological memory of the communities; the more exposed areas the communities originated from, the less negative was the effect of the mechanical disturbance. Interestingly, dispersal did not mitigate the negative impacts of disturbance in any of the communities. Our results highlight the importance of ecological memory for ecosystem functioning and demonstrate the limitations of patch connectivity to alleviate the impacts of disturbance events in metacommunities.



2015 ◽  
Vol 183 ◽  
pp. 23-30 ◽  
Author(s):  
Hanna Mäkinen ◽  
Janne Kaseva ◽  
Perttu Virkajärvi ◽  
Helena Kahiluoto


2010 ◽  
Vol 13 (1) ◽  
pp. 76-86 ◽  
Author(s):  
Etienne Laliberté ◽  
Jessie A. Wells ◽  
Fabrice DeClerck ◽  
Daniel J. Metcalfe ◽  
Carla P. Catterall ◽  
...  


Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1675 ◽  
Author(s):  
Yingzhong Tian ◽  
Yafei Jia ◽  
Long Li ◽  
Zongnan Huang ◽  
Wenbin Wang

Generative conversational systems consisting of a neural network-based structural model and a linguistic model have always been considered to be an attractive area. However, conversational systems tend to generate single-turn responses with a lack of diversity and informativeness. For this reason, the conversational system method is further developed by modeling and analyzing the joint structural and linguistic model, as presented in the paper. Firstly, we establish a novel dual-encoder structural model based on the new Convolutional Neural Network architecture and strengthened attention with intention. It is able to effectively extract the features of variable-length sequences and then mine their deep semantic information. Secondly, a linguistic model combining the maximum mutual information with the foolish punishment mechanism is proposed. Thirdly, the conversational system for the joint structural and linguistic model is observed and discussed. Then, to validate the effectiveness of the proposed method, some different models are tested, evaluated and compared with respect to Response Coherence, Response Diversity, Length of Conversation and Human Evaluation. As these comparative results show, the proposed method is able to effectively improve the response quality of the generative conversational system.



2014 ◽  
Vol 592 (7) ◽  
pp. 1457-1477 ◽  
Author(s):  
Sarah H. Lindstrom ◽  
David G. Ryan ◽  
Jun Shi ◽  
Steven H. DeVries


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