Kreft, Holger

[["dc.bibliographiccitation.artnumber","S0304380021002866"],["dc.bibliographiccitation.firstpage","109735"],["dc.bibliographiccitation.journal","Ecological Modelling"],["dc.bibliographiccitation.volume","460"],["dc.contributor.author","Petter, Gunnar"],["dc.contributor.author","Kreft, Holger"],["dc.contributor.author","Ong, Yongzhi"],["dc.contributor.author","Zotz, Gerhard"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.date.accessioned","2021-12-01T09:23:33Z"],["dc.date.available","2021-12-01T09:23:33Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1016/j.ecolmodel.2021.109735"],["dc.identifier.pii","S0304380021002866"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/94687"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-478"],["dc.relation.issn","0304-3800"],["dc.title","Modelling the long-term dynamics of tropical forests: From leaf traits to whole-tree growth patterns"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2212"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","Journal of Biogeography"],["dc.bibliographiccitation.lastpage","2224"],["dc.bibliographiccitation.volume","39"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.contributor.author","Kreft, Holger"],["dc.date.accessioned","2017-09-07T11:46:21Z"],["dc.date.available","2017-09-07T11:46:21Z"],["dc.date.issued","2012"],["dc.description.abstract","Aim We present a mechanistic niche model that integrates the demography of competing plant species in a metabolic, stochastic framework. In order to explore the model's ability to generate multiple species and community patterns, we assessed trait composition, richness gradients and spatial distributions of species ranges and abundances of simulated communities. Location Hypothetical, sloped plane. Methods Stage‐structured populations of species differing in traits and habitat requirements competed for space in a grid‐based model. Demographic processes (recruitment, reproduction, mortality, dispersal) and resource competition were explicitly simulated. Demographic rates and carrying capacity followed metabolic constraints. We simulated 50 species pools until reaching stable communities. Species pools were initialized with 400 species that had random traits and habitat requirements. The habitat requirements generated potential distributions of richness, range and abundance, whereas the simulations yielded realized distributions. Results The communities assembled in the simulations consisted of species spread non‐randomly within trait space. Potential species richness peaked at mid‐elevations, whereas realized richness was slightly shifted towards higher elevations. For 11% of all species, the highest local abundances were found not in the most suitable habitat, but in suboptimal conditions. 53% of all species could not fill the climatically determined potential range. The ability to fill the potential range was significantly influenced by species traits (e.g. body mass and Allee effects) and species richness. Main conclusions Spatial and trait properties of surviving species and of equilibrium communities diverged from the potential distributions. Realized richness gradients were consistent both with patterns observed in nature and those expected from null models based on geometrical constraints. However, the divergences between potential and realized patterns of richness, ranges and abundances indicate the importance of demography and biotic interaction for generating patterns at species and community levels. Consequently, bias in correlative habitat models and single‐species mechanistic models may arise if competition and demography are neglected. Additionally, competitive exclusion provides a mechanistic explanation for the low transferability of single‐species niche models. These results confirm the usefulness of mechanistic niche models for guiding further research integrating ecological niche, community ecology and biogeography."],["dc.identifier.doi","10.1111/jbi.12010"],["dc.identifier.gro","3149138"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5789"],["dc.language.iso","en"],["dc.notes.intern","Kreft Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0305-0270"],["dc.title","Linking ecological niche, community ecology and biogeography: insights from a mechanistic niche model"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1569"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Journal of Biogeography"],["dc.bibliographiccitation.lastpage","1581"],["dc.bibliographiccitation.volume","46"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.contributor.author","Whittaker, Robert J."],["dc.contributor.author","Wiegand, Kerstin"],["dc.contributor.author","Kreft, Holger"],["dc.date.accessioned","2020-12-08T07:51:56Z"],["dc.date.available","2020-12-08T07:51:56Z"],["dc.date.issued","2019"],["dc.description.abstract","Aims The general dynamic model (GDM) of oceanic island biogeography predicts how biogeographical rates, species richness and endemism vary with island age, area and isolation. Here, we used a simulation model to assess whether the isolation-related predictions of the GDM may arise from low-level process at the level of individuals and populations. Location Hypothetical volcanic oceanic islands. Methods Our model considers (a) an idealized island ontogeny, (b) metabolic constraints and (c) stochastic, spatially explicit and niche-based processes at the level of individuals and populations (plant demography, dispersal, competition, mutation and speciation). Isolation scenarios involved varying the distance to mainland and the dispersal ability of the species pool. Results For all isolation scenarios, we obtained humped temporal trends for species richness, endemic richness, proportion of endemic species derived from within-island radiation, number of radiating lineages, number of species per radiating lineage and biogeographical rates. The proportion of endemics derived from mainland–island differentiation and of all endemics steadily increased over time. Extinction rates of endemic species peaked later than for non-endemic species. Species richness and the number of endemics derived from mainland–island differentiation decreased with isolation as did rates of colonization, mainland–island differentiation and extinction. The proportion of all endemics and of radiated endemics, the number of radiated endemics, of radiating lineages, and of species per radiating lineage and the within-island radiation rate all increased with isolation. Main conclusions Our results lend strong support to most of the isolation-related GDM predictions. New insights include an increasing proportion of endemics, particularly those arising from mainland–island differentiation, across isolation scenarios, as well as extinction trends of endemics differing from the overall extinction rates, with a much later peak. These results demonstrate how simulation models focusing on low ecological levels provide tools to assess biogeographical-scale predictions and to develop more detailed predictions for further empirical tests."],["dc.identifier.doi","10.1111/jbi.13603"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/69454"],["dc.language.iso","en"],["dc.relation.issn","0305-0270"],["dc.relation.issn","1365-2699"],["dc.relation.orgunit","Abteilung Ökosystemmodellierung"],["dc.subject.gro","BioGEEM"],["dc.subject.gro","general dynamic model"],["dc.subject.gro","interspecific competition"],["dc.subject.gro","island biogeography"],["dc.subject.gro","isolation effects"],["dc.subject.gro","metabolic theory"],["dc.subject.gro","oceanic islands"],["dc.subject.gro","plant endemism"],["dc.subject.gro","process-based models"],["dc.subject.gro","speciation rate"],["dc.title","Assessing predicted isolation effects from the general dynamic model of island biogeography with an eco‐evolutionary model for plants"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Biogeography"],["dc.bibliographiccitation.lastpage","12"],["dc.bibliographiccitation.volume","47"],["dc.contributor.author","Wüest, Rafael O."],["dc.contributor.author","Zimmermann, Niklaus E."],["dc.contributor.author","Zurell, Damaris"],["dc.contributor.author","Alexander, Jake M."],["dc.contributor.author","Fritz, Susanne A."],["dc.contributor.author","Hof, Christian"],["dc.contributor.author","Kreft, Holger"],["dc.contributor.author","Normand, Signe"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.contributor.author","Szekely, Eniko"],["dc.contributor.author","Thuiller, Wilfried"],["dc.contributor.author","Wikelski, Martin"],["dc.contributor.author","Karger, Dirk Nikolaus"],["dc.date.accessioned","2020-12-10T18:28:55Z"],["dc.date.available","2020-12-10T18:28:55Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1111/jbi.13633"],["dc.identifier.eissn","1365-2699"],["dc.identifier.issn","0305-0270"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76457"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Macroecology in the age of Big Data – Where to go from here?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","188"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Functional Ecology"],["dc.bibliographiccitation.lastpage","198"],["dc.bibliographiccitation.volume","30"],["dc.contributor.author","Petter, Gunnar"],["dc.contributor.author","Wagner, Katrin"],["dc.contributor.author","Wanek, Wolfgang"],["dc.contributor.author","Sánchez Delgado, Eduardo Javier"],["dc.contributor.author","Zotz, Gerhard"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.contributor.author","Kreft, Holger"],["dc.date.accessioned","2017-09-07T11:46:23Z"],["dc.date.available","2017-09-07T11:46:23Z"],["dc.date.issued","2016"],["dc.description.abstract","1. Analysing functional traits along environmental gradients can improve our understanding of the mechanisms structuring plant communities. Within forests, vertical gradients in light intensity, temperature and humidity are often pronounced. Vascular epiphytes are particularly suitable for studying the influence of these vertical gradients on functional traits because they lack contact with the soil and thus individual plants are entirely exposed to different environmental conditions, from the dark and humid understorey to the sunny and dry outer canopy. 2. In this study, we analysed multiple aspects of the trait‐based ecology of vascular epiphytes: shifts in trait values with height above ground (as a proxy for vertical environmental gradients) at community and species level, the importance of intra‐ vs. interspecific trait variability, and trait differences among taxonomic groups. We assessed ten leaf traits for 1151 individuals belonging to 83 epiphyte species of all major taxonomic groups co‐occurring in a Panamanian lowland forest. 3. Community mean trait values of many leaf traits were strongly correlated with height and particularly specific leaf area and chlorophyll concentration showed nonlinear, negative trends. 4. Intraspecific trait variability was pronounced and accounted for one‐third of total observed trait variance. Intraspecific trait adjustments along the vertical gradient were common and seventy per cent of all species showed significant trait–height relationships. In addition, intraspecific trait variability was positively correlated with the vertical range occupied by species. 5. We observed significant trait differences between major taxonomic groups (orchids, ferns, aroids, bromeliads). In ferns, for instance, leaf dry matter content was almost twofold higher than in the other taxonomic groups. This indicates that some leaf traits are taxonomically conserved. 6. Our study demonstrates that vertical environmental gradients strongly influence functional traits of vascular epiphytes. In order to understand community composition along such gradients, it is central to study several aspects of trait‐based ecology, including both community and intraspecific trends of multiple traits."],["dc.identifier.doi","10.1111/1365-2435.12490"],["dc.identifier.gro","3149148"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5800"],["dc.language.iso","en"],["dc.notes.intern","Kreft Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0269-8463"],["dc.title","Functional leaf traits of vascular epiphytes: vertical trends within the forest, intra- and interspecific trait variability, and taxonomic signals"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","99"],["dc.bibliographiccitation.issue","7597"],["dc.bibliographiccitation.journal","Nature"],["dc.bibliographiccitation.lastpage","102"],["dc.bibliographiccitation.volume","532"],["dc.contributor.author","Weigelt, Patrick"],["dc.contributor.author","Steinbauer, Manuel Jonas"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.contributor.author","Kreft, Holger"],["dc.date.accessioned","2017-09-07T11:46:31Z"],["dc.date.available","2017-09-07T11:46:31Z"],["dc.date.issued","2016"],["dc.description.abstract","Island biogeographical models consider islands either as geologically static with biodiversity resulting from ecologically neutral immigration–extinction dynamics1, or as geologically dynamic with biodiversity resulting from immigration–speciation–extinction dynamics influenced by changes in island characteristics over millions of years2. Present climate and spatial arrangement of islands, however, are rather exceptional compared to most of the Late Quaternary, which is characterized by recurrent cooler and drier glacial periods. These climatic oscillations over short geological timescales strongly affected sea levels3,4 and caused massive changes in island area, isolation and connectivity5, orders of magnitude faster than the geological processes of island formation, subsidence and erosion considered in island theory2,6. Consequences of these oscillations for present biodiversity remain unassessed5,7. Here we analyse the effects of present and Last Glacial Maximum (LGM) island area, isolation, elevation and climate on key components of angiosperm diversity on islands worldwide. We find that post-LGM changes in island characteristics, especially in area, have left a strong imprint on present diversity of endemic species. Specifically, the number and proportion of endemic species today is significantly higher on islands that were larger during the LGM. Native species richness, in turn, is mostly determined by present island characteristics. We conclude that an appreciation of Late Quaternary environmental change is essential to understand patterns of island endemism and its underlying evolutionary dynamics."],["dc.identifier.doi","10.1038/nature17443"],["dc.identifier.gro","3149169"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5823"],["dc.language.iso","en"],["dc.notes.intern","Kreft Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0028-0836"],["dc.title","Late Quaternary climate change shapes island biodiversity"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2937"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Ecology and Evolution"],["dc.bibliographiccitation.lastpage","2951"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Petter, Gunnar"],["dc.contributor.author","Zotz, Gerhard"],["dc.contributor.author","Kreft, Holger"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.date.accessioned","2021-04-14T08:29:27Z"],["dc.date.available","2021-04-14T08:29:27Z"],["dc.date.issued","2021"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.1002/ece3.7255"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82907"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","2045-7758"],["dc.relation.issn","2045-7758"],["dc.relation.orgunit","Abteilung Biodiversität, Makroökologie und Biogeographie"],["dc.title","Agent‐based modeling of the effects of forest dynamics, selective logging, and fragment size on epiphyte communities"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1784"],["dc.bibliographiccitation.journal","Proceedings of the Royal Society B: Biological Sciences"],["dc.bibliographiccitation.volume","281"],["dc.contributor.author","Cabral, Juliano Sarmento"],["dc.contributor.author","Weigelt, Patrick"],["dc.contributor.author","Kissling, W. Daniel"],["dc.contributor.author","Kreft, Holger"],["dc.date.accessioned","2017-09-07T11:46:25Z"],["dc.date.available","2017-09-07T11:46:25Z"],["dc.date.issued","2014"],["dc.description.abstract","Island biogeographic studies traditionally treat single islands as units of analysis. This ignores the fact that most islands are spatially nested within archipelagos. Here, we took a fundamentally different approach and focused on entire archipelagos using species richness of vascular plants on 23 archipelagos worldwide and their 174 constituent islands. We assessed differential effects of biogeographic factors (area, isolation, age, elevation), current and past climate (temperature, precipitation, seasonality, climate change velocity) and intra-archipelagic spatial structure (archipelago area, number of islands, area range, connectivity, environmental volume, inter-island distance) on plant diversity. Species diversity of each archipelago (γ) was additively partitioned into α, β, nestedness and replacement β-components to investigate the relative importance of environmental and spatial drivers. Multiple regressions revealed strong effects of biogeography and climate on α and γ, whereas spatial factors, particularly number of islands, inter-island distance and area range, were key to explain β. Structural equation models additionally suggested that γ is predominantly determined by indirect abiotic effects via its components, particularly β. This highlights that β and the spatial arrangement of islands are essential to understand insular ecology and evolution. Our methodological framework can be applied more widely to other taxa and archipelago-like systems, allowing new insights into biodiversity origin and maintenance."],["dc.identifier.doi","10.1098/rspb.2013.3246"],["dc.identifier.gro","3149143"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5794"],["dc.language.iso","en"],["dc.notes.intern","Kreft Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0962-8452"],["dc.title","Biogeographic, climatic and spatial drivers differentially affect -,  - and  -diversities on oceanic archipelagos"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]