scholarly journals A Phylogeny-Informed Analysis of the Global Coral-Symbiodiniaceae Interaction Network Reveals that Traits Correlated with Thermal Bleaching Are Specific to Symbiont Transmission Mode

mSystems ◽  
2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Timothy D. Swain ◽  
Simon Lax ◽  
Jack Gilbert ◽  
Vadim Backman ◽  
Luisa A. Marcelino

ABSTRACT The complex network of associations between corals and their dinoflagellates (family Symbiodiniaceae) are the basis of coral reef ecosystems but are sensitive to increasing global temperatures. Coral-symbiont interactions are restricted by ecological and evolutionary determinants that constrain partner choice and influence holobiont response to environmental stress; however, little is known about how these processes shape thermal resilience of the holobiont. Here, we built a network of global coral-Symbiodiniaceae associations, mapped species traits (e.g., symbiont transmission mode and biogeography) and phylogenetic relationships of both partners onto the network, and assigned thermotolerance to both host and symbiont nodes. Using network analysis and phylogenetic comparative methods, we determined the contribution of species traits to thermal resilience of the holobiont, while accounting for evolutionary patterns among species. We found that the network shows nonrandom interactions among species, which are shaped by evolutionary history, symbiont transmission mode (horizontally transmitted [HT] or vertically transmitted [VT] corals) and biogeography. Coral phylogeny, but not Symbiodiniaceae phylogeny, symbiont transmission mode, or biogeography, was a good predictor of thermal resilience. Closely related corals have similar Symbiodiniaceae interaction patterns and bleaching susceptibilities. Nevertheless, the association patterns that explain increased host thermal resilience are not generalizable across the entire network but are instead unique to HT and VT corals. Under nonstress conditions, thermally resilient VT coral species associate with thermotolerant phylotypes and limit their number of unique symbionts and overall symbiont thermotolerance diversity, while thermally resilient HT coral species associate with a few host-specific symbiont phylotypes. IMPORTANCE Recent advances have revealed a complex network of interactions between coral and Symbiodiniaceae. Specifically, nonrandom association patterns, which are determined in part by restrictions imposed by symbiont transmission mode, increase the sensitivity of the overall network to thermal stress. However, little is known about the extent to which coral-Symbiodiniaceae network resistance to thermal stress is shaped by host and symbiont species phylogenetic relationships and host and symbiont species traits, such as symbiont transmission mode. We built a frequency-weighted global coral-Symbiodiniaceae network and used network analysis and phylogenetic comparative methods to show that evolutionary relatedness, but not transmission mode, predicts thermal resilience of the coral-Symbiodiniaceae holobiont. Consequently, thermal stress events could result in nonrandom pruning of susceptible lineages and loss of taxonomic diversity with catastrophic effects on community resilience to future events. Our results show that inclusion of the contribution of evolutionary and ecological processes will further our understanding of the fate of coral assemblages under climate change.

2021 ◽  
Vol 2 (1) ◽  
pp. 113-139
Author(s):  
Dimitrios Tsiotas ◽  
Thomas Krabokoukis ◽  
Serafeim Polyzos

Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.


2020 ◽  
Vol 67 (6) ◽  
pp. 1134-1138 ◽  
Author(s):  
Zhongke Gao ◽  
Hongtao Wang ◽  
Weidong Dang ◽  
Yongqiang Li ◽  
Xiaolin Hong ◽  
...  

Author(s):  
Emerson Luiz Chiesse da Silva ◽  
Marcelo De Oliveira Rosa ◽  
Keiko Veronica Ono Fonseca ◽  
Ricardo Luders ◽  
Nadia Puchaslki Kozievitch

2018 ◽  
Vol 55 ◽  
pp. 133-142 ◽  
Author(s):  
Wenyu Hou ◽  
Huifang Liu ◽  
Hui Wang ◽  
Fengyang Wu

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