53 research outputs found
The roles of vicariance and isolation by distance in shaping biotic diversification across an ancient archipelago: evidence from a Seychelles caecilian amphibian
© 2020 The Authors. Published by BMC. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1186/s12862-020-01673-wBackground
Island systems offer excellent opportunities for studying the evolutionary histories of species by virtue of their restricted size and easily identifiable barriers to gene flow. However, most studies investigating evolutionary patterns and processes shaping biotic diversification have focused on more recent (emergent) rather than ancient oceanic archipelagos. Here, we focus on the granitic islands of the Seychelles, which are unusual among island systems because they have been isolated for a long time and are home to a monophyletic radiation of caecilian amphibians that has been separated from its extant sister lineage for ca. 65–62 Ma. We selected the most widespread Seychelles caecilian species, Hypogeophis rostratus, to investigate intraspecific morphological and genetic (mitochondrial and nuclear) variation across the archipelago (782 samples from nine islands) to identify patterns and test processes that shaped their evolutionary history within the Seychelles.
Results
Overall a signal of strong geographic structuring with distinct northern- and southern-island clusters were identified across all datasets. We suggest that these distinct groups have been isolated for ca. 1.26 Ma years without subsequent migration between them. Populations from the somewhat geographically isolated island of Frégate showed contrasting relationships to other islands based on genetic and morphological data, clustering alternatively with northern-island (genetic) and southern-island (morphological) populations.
Conclusions
Although variation in H. rostratus across the Seychelles is explained more by isolation-by-distance than by adaptation, the genetic-morphological incongruence for affinities of Frégate H. rostratus might be caused by local adaptation over-riding the signal from their vicariant history. Our findings highlight the need of integrative approaches to investigate fine-scale geographic structuring to uncover underlying diversity and to better understand evolutionary processes on ancient, continental islands.Funding for this research was provided by two grants from the National Science Foundation (BSR 88–17453, BSR 90–24505) [funding for fieldwork and lab work], two grants from the National Geographic Society (Grants 1977: 1633, 1743) [funding for fieldwork], three grants from the University of Michigan Office of the Vice President for Research, and a Research Partnership Award from the University of Michigan to RAN [morphology work]; a joint NHM-UCL IMPACT studentship [to fund STM’s PhD, lab work and fieldwork], Mohamed Bin Zayed Species Conservation Fund [funding for fieldwork] and Systematics Research Fund [funding for fieldwork] to STM; an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant #P20GM103408 to LL [funding for lab work]; a NERC/BBSRC SynTax grant [funding for fieldwork and collaboration], and Darwin Initiative (grant 19–002) [funding for fieldwork, lab work and capacity building] with partners Bristol University, Islands Conservation Society, Seychelles Islands Foundation, Seychelles Ministry of Environment, Seychelles National Parks Authority, Seychelles Natural History Museum, University of Kent, Zoological Society of London to MW, DJG, JJD. The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.Published onlin
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Ethnography in Robotics: Communications, Design, and Innovation in the Robotics for Theater Project
Transdisciplinary Technological Futures. An Ethnographic Research Dialogue between Social Scientists and Engineers
- …