Refine
Has Fulltext
- yes (3)
Is part of the Bibliography
- yes (3)
Document Type
- Journal article (3)
Language
- English (3)
Keywords
- biodiversity (2)
- species richness (2)
- DNA fingerprinting (1)
- LiDAR (1)
- Physiologische Chemie (1)
- androgen-induced masculinization (1)
- arthropods (1)
- bats (1)
- birds (1)
- elevation (1)
Institute
- Theodor-Boveri-Institut für Biowissenschaften (3) (remove)
The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.
In dooal unisexual vertebrales, the genes specifying the males become dispensable. To study tbe rate of such geoes the gynogeoetic all-female fisb Poecilillfonnolll was treated with androgens. Phenotypic males were obtained that exbibited the complete set of male cbaracteristics of dosely related gooocboristic species, induding body proportions, pigmentation, the extremely complex insemination apparatus of poecilüd fish, sexual bebavior, and spermatogeoesls. Tbe apparent stabllity of such genic structures, induding those involved in androgen regulation, is contrasted by high instability of noncoding sequeaces. Frequent mutations, thelr donal transmission, and at least two truly hypervariable Iod leading to individual difl'ereaces between these othenrise donal organisms were detected by DNA fingerprinting. These observations substantiate the concept that also in "ameiotic" vertebrates certain compartments of the genome are more prooe to mutatiooal alterations than others.
Motivation
The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.
Main types of variables included
The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.
Spatial location and grain
BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).
Time period and grain
BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.
Major taxa and level of measurement
BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
Software format
.csv and .SQL.