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72 results for “Biodiversity dynamics”
Trade-offs between biodiversity and agriculture are moving targets in dynamic landscapes
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Impact of Pleistocene eustatic fluctuations on evolutionary dynamics in Southeast Asian biodiversity hotspots
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Spatio-temporal dynamics of abiotic and biotic properties explain biodiversity-ecosystem functioning relationships
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Ancient geological dynamics impact neutral biodiversity accumulation and are detectable in phylogenetic reconstructions
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Figure 3 in Terrestrial isopods and myriapods in a forested scree slope: subterranean biodiversity, depth gradient and annual dynamics
Figure 3. Activity dynamics of isopod Ligidium germanicum (LIGE); diplopods Mecogonopodium carpathicum (MECA), Polydesmus denticulatus (PODE), Trachysphaera acutula (TRAC); and centipedes Harpolithobius anodus (HAAN), Lithobius forficatus (LIFO), during the period November 2008– November 2009.
Figure 2 in Terrestrial isopods and myriapods in a forested scree slope: subterranean biodiversity, depth gradient and annual dynamics
Figure 2. The non-metric multidimensional scaling ordination analysis (NMS) diagram of Isopoda and Myriapoda collected during both sampling periods; variance explained by axes 1 and 2 as 87.0% and 8.7%, respectively (triangles – depths, dots – species). Abbreviations: i – Isopoda: LIGE – Ligidium germanicum, MEGR – Mesoniscus graniger, TRCA – Trichoniscus carpaticus; d – Diplopoda: JUCU – Julus curvicornis, LEMA – Leptoiulus mariae, LETR – L. trilobatus, MECA – Mecogonopodium carpathicum, POCO – Polydesmus complanatus, PODE – Polydesmus denticulatus, TRAC – Trachysphaera acutula, STST – Strongylosoma stigmatosum; c – Chilopoda: HAAN – Harpolithobius anodus, LI - Lithobius sp. juv., LIFO – Lithobius forficatus, LILU – Lithobius lucifugus; STAC – Strigamia acuminata, STTR – Strigamia transsilvanica.
Data from: Biodiversity dynamics and environmental occupancy of fossil azooxanthellate and zooxanthellate scleractinian corals
Scleractinian corals have two fundamentally different life strategies, which can be inferred from morphological criteria in fossil material. In the non-photosymbiotic group nutrition comes exclusively from heterotrophic feeding, whereas the photosymbiotic group achieves a good part of its nutrition from algae hosted in the coral's tissue. These ecologic differences arose early in the evolutionary history of corals but with repeated evolutionary losses and presumably also gains of symbiosis since then. We assessed the biodiversity dynamics and environmental occupancy of both ecologic groups to identify times when the evolutionary losses of symbiosis as inferred from molecular analyses might have occurred and if these can be linked to environmental change. Two episodes are likely: The first was in the mid-Cretaceous when non-symbiotic corals experienced an origination pulse and started to become more common in deeper, non-reef habitats and on siliciclastic substrates initiating a long-term offshore trend in occupancy. The second was around the Cretaceous/Paleogene boundary with another origination pulse and increased occupancy of deep-water settings in the non-symbiotic group. Environmental factors such as rapid global warming associated with mid-Cretaceous anoxic events and increased nutrient concentrations in Late Cretaceous–Cenozoic deeper waters are plausible mechanisms for the shift. Turnover rates and durations are not significantly different between the two ecologic groups when compared over the entire history of scleractinians. However, the deep-water shift of non-symbiotic corals was accompanied by reduced extinction rates, supporting the view that environmental occupancy is a prominent driver of evolutionary rates.
Supplementary material 1 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Detailed design of the Field Experiment
Supplementary material 2 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Brief description of the Field Experiment
Figure 1 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 1 A. Conceptual diagram of the mechanistic approach of the planned Research Unit. B. Conceptual scheme of the proposed evolutionary niche shifts in plant monocultures and mixtures. This idea feeds into our understanding of how evolutionary history influences the ecological interactions of species that compete for growth factors, ultimately defining biotope space (gray rectangle; Hutchinson 1978). Graphically depicted, species (ellipses) in mixture will show increasing niche differentiation over time due to competition (niche overlap). Thus, history of selection in diverse communities is expected to result in greater interspecific differences (less overlap of ellipses) and more specialization (smaller ellipses) than a history of isolation (monocultures). In monocultures, species will experience strong selection pressure by accumulating soil-borne pathogens, and species may invest energy in chemical and morphological defense traits (depicted by ellipses shifting towards the same corner of the habitat space). Plants in mixtures together may exploit more available biotope space than single monocultures, causing increasing diversity effects on ecosystem functions over time. However, there is limited support for this assumption for traits related to light (e.g., Lipowsky et al. 2015, Roscher et al. 2015) and resource use (Jesch et al. 2018) so far.
Figure 4 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 4 Experimental design and hypotheses of the Ecotron Experiment. Briefly, four treatments will be established based on monoliths from a selection of the 9-year old Trait-Based Experiment (TBE; Ebeling et al. 2014) and from bare ground plots of the Jena Experiment as well as two seed sources: the respective plots and the original seed material that was used for the set-up of the TBE. (1) With plot-specific plant history and with plot-specific soil history; (2) without plot-specific plant history and with plot-specific soil history; (3) with plot-specific plant history and without plot-specific soil history; and (4) without plot-specific plant history and without plot-specific soil history. We expect the biodiversity–ecosystem function relationships to differ among the four treatments (see main text for details).
Figure 3 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 3 Hypothesized slope of BEF relationships in the different treatments of the Field Experiment (see main text for details). Note that the 'with plant history, with soil history' only serves as a control in the Field Experiment, and effects of plant history can only be tested in the planned Ecotron Experiment. Redrawn after Vogel et al. (2019). '+', with; '-', without.
Supplementary material 4 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Detailed design of the Ecotron Experiment
Supplementary material 5 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Brief description of the Ecotron Experiment
Figure 2 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 2 Structure of the proposed Research Unit. Three complementary experimental approaches are envisaged to study long-term biodiversity-ecosystem function (BEF) relationships, and how these are influenced by plant history and soil history. BEF patterns are studied in the Field Experiment with long-term plant diversity plots and manipulations of soil-history effects. BEF mechanisms are studied in the Ecotron Experiment and in Microcosm Experiments. In the Ecotron Experiment, plant history and soil history are independently crossed and detailed process measurements are possible. The Microcosm Experiments zoom in on focal interactions. In the Field Experiment and in the Ecotron Experiment, studies are conducted at the community level as well as at the plant individual level (magnifier; see detailed design of studies in the Appendices). Subprojects' (SPs') participation in experiments are illustrated with lines. The SPs of the proposed Research Unit fall into two tightly linked main categories (in gray) with two research areas each that aim at exploring variation in community assembly processes, micro-evolutionary changes, and resulting differences in biotic interactions as determinants of the long-term BEF relationship. Subprojects under "Microbial community assembly" (blue) and "Assembly and functions of animal communities" (red) mostly focus on plant diversity effects on the assembly of communities and their feedback effects on biotic interactions and ecosystem functions, while subprojects under "Mediators of plant-biotic interactions" (orange) and "Intraspecific diversity and micro-evolutionary changes" (green) mostly focus on plant diversity effects on plant trait expression and micro-evolution. PIs with requested personnel are underlined.
Supplementary material 3 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Plant species lists of the Field Experiment and the Ecotron Experiment
Figure 3 in Biodiversity and population dynamics of litter-dwelling cockroaches in Belezma National Park (Algeria)
Figure 3. Parameter diversity of cockroach species caught in different forest types (S: Pinus halepensis, S: Juniperus 1 2 phoenicea, S 3: Quercus ilex) of Belezma National Park (Northeast Algeria).
Multiple stressors drive multitrophic biodiversity and ecological network dynamics in a shrinking sandy lake
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Supplementary material 3 from: Ariza GM, Jácome J, Esquivel HE, Kotze DJ (2021) Early successional dynamics of ground beetles (Coleoptera, Carabidae) in the tropical dry forest ecosystem in Colombia. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 877-906. https://doi.org/10.3897/zookeys.1044.59475
Table S3
Figure 1 from: Ariza GM, Jácome J, Esquivel HE, Kotze DJ (2021) Early successional dynamics of ground beetles (Coleoptera, Carabidae) in the tropical dry forest ecosystem in Colombia. In: Spence J, Casale A, Assmann T, Liebherr JК, Penev L (Eds) Systematic Zoology and Biodiversity Science: A tribute to Terry Erwin (1940-2020). ZooKeys 1044: 877-906. https://doi.org/10.3897/zookeys.1044.59475
Figure 1 Geographic location of the study sites A the location of Armero and Cambao in Colombia B Armero C Cambao. Abbreviations: F = forest, ES = early succession, P = pasture. Maps courtesy of DIVA-GIS 7.5 and Google Earth Image 2020. For more details, see the online map at https://www.google.com/maps/d/u/3/edit?mid=1le-kQOQFh8RumUibWP3D8ghtxVvGM-eF&usp=sharing
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.