Biology subjects

Tietje, M.

Publications and source records attributed to Tietje, M..

4 recordsLinked to original sources

bioRxiv2026

Probabilistic species distributions from nine large-scale gridded atlases over five decades

Information on the long-term dynamics of species distributions is essential for assessing global biodiversity change and its causes, and for informed conservation decisions. A valuable source of such historical information are atlases. They provide spatial standardisation, extensive geographic coverage, temporal replication, documented sampling protocols, and span multiple species. Here we present model-based occupancy probabilities for 1,055 bird and 58 butterfly species, derived from nine gridded atlas datasets spanning several editions over the past 50 years. These are: Japan, New Zealand, New York state (US), the states of Alberta, Quebec, and The Maritimes (Canada), Czech Republic, United Kingdom, and Europe. Despite standardisation and coordination during data collection, the raw atlas data still contain some variation in sampling effort. We accounted for this using a two-step process: (1) we estimated a proxy for sampling effort in each grid cell within each atlas period using the Frescalo Algorithm, and (2) we ran a Bayesian spatial occupancy model for each species and atlas period, using the estimated sampling effort as the single predictor of detection in the observation process of the model. As the main product, we provide occupancy probabilities for species across grid cells and atlas periods. We also report uncertainty around each probability estimate and flag ~21% (rare) species per atlas for which the model did not fit well. The probability distributions are fit for purpose and served in a user-friendly database with standardised geographic projection, metadata, and taxonomy.

ecology↗

bioRxiv2026

Opening a standardized, spatially contiguous biodiversity database collected over 40 years: Czech breeding bird atlases 1973-77, 1985-89, 2001-03, and 2014-17

MotivationHigh-quality biodiversity data with temporal replicates, produced using standardized fieldwork protocols, are rare yet essential for studying long-term biodiversity dynamics. Most available large-scale temporal data only date back one or two decades and/or originate from spatially discrete local observations. Here, we release spatially contiguous, systematically collected, and gridded occurrence data for breeding birds in Czechia, covering the periods 1973--1977, 1985--1989, 2001--2003, and 2014--2017. This database represents the monitoring of ca. 41% of European bird species over 40 years, and it is one of the longest-running nationwide bird-monitoring efforts in the world. We also complement the original data with geospatial metrics to characterize the sampling polygons and provide proxies of sampling effort. By making this dataset openly accessible, we aim to strengthen biodiversity change studies, citizen science, and ornithological research with long-term, highly curated records, backed by well-documented methods, and ready for integration with other datasets. Main Types of Variables ContainedA total of 286302 breeding bird detections/non-detections per-grid-cell from 247 species (ca. 41% of the 596 species breeding in Europe). The fourth atlas also contains 9,471 timed species lists totaling 276076 additional records collected with standardized effort and partially random spatial sampling on smaller squares dividing the original grid cells. Spatial Location and GrainCzechia (total area of 78,871 km2) covered by a grid of 887 grid cells of 10 by 10 km for the period 1973--77, and 678 cells of 6 minutes latitude and 10 minutes longitude ([~]11.2 x 12 kilometers) from 1985 onwards. The timed species lists were collected across 4,851 of 9,844 small squares ([~]2.8 x 3 km) that subdivide each original grid-cell into 16 smaller polygons. Time Period and GrainThe sampling years were 1973--1977 (5 breeding seasons), 1985--1989 (5 breeding seasons), 2001--2003 (3 breeding seasons), and 2014--2017 (4 breeding seasons). Major Taxa and Level of MeasurementBirds (Aves). The breeding evidence per species and grid cell was classified following the European Breeding Birds Atlas 2. We provide species-level records matched to the HBW/BirdLife version 9 (2024). FormatThe dataset is available for download from Zenodo and is provided as CSV files with fields standardized to Darwin Core, and a GeoPackage file containing all of the spatial grids used. The data are organized into separate files for records and sampling events, corresponding to each atlas. All data are licensed under CC-BY 4.0.

ecology↗

bioRxiv2024

Trade-offs beget trade-offs: Causal analysis of mammalian population dynamics

Survival and reproduction strategies in mammals are determined by trade-offs between life history traits. In turn, the unique configuration of traits that characterize mammalian species give rise to species-specific population dynamics. The dependence of population dynamics on life history has been primarily studied as the relationship between population density and size-related traits. With the recent accumulation of genomic data, the effective population size (Ne) over million-year timescales has become quantifiable for a large proportion of mammal species. Using phylogenetic path analysis, we compared the dependence of population density and Ne on eleven traits that characterize mammalian allometry, diet and reproduction. We found variable impacts of traits on the two metrics of population dynamics across different classifications of mammalian species. For example, we found a negative association between brain size and both population density and Ne overall, but brain size was positively associated with Ne in carnivorans. Dietary specialization had a negative effect on population density, especially in ungulates. Ne of ungulates and primates was strongly affected by time to maturity and weaning age, respectively, highlighting the difference in reproductive strategy between these orders. The relationship between Ne and adult mass showed a gradient in association strength from cold to warm biomes. Together, our findings demonstrate that trade-offs not only characterize life-history evolution, but also extend across different metrics of population dynamics and vary among species groups. This challenges the static nature of the "energetic equivalence" rule and has major implications for selecting appropriate metrics for species conservation and restoration strategies.

evolutionary biology↗

bioRxiv2022

Socioeconomics and biogeography jointly drive geographic biases in our knowledge of plant traits: a global assessment of the Raunkiaerian shortfall in plants

The traits of plants determine how they interact with each other and their environment, constituting key knowledge for diverse fields. The lack of comprehensive knowledge of plant traits (the "Raunkiaerian shortfall") poses a major, cross-disciplinary, barrier to scientific advancement. Spatial biases in trait coverage may also lead to erroneous conclusions affecting ecosystem management and conservation planning. Thus, there is an urgent need to assess the spatial completeness of plant trait data, understand drivers of geographic biases, and to identify solutions for filling regional gaps. Here, we leverage a comprehensive set of regional species checklists for vascular plants and trait data for 2,027 traits and 128,929 plant species from the TRY database to assess trait data completeness across the globe. We show that trait data availability in TRY is associated with socioeconomic and biological factors influencing sampling likelihood: trait completeness was positively associated with mean species range size, research expenditure, and human population density and negatively associated with endemism and vascular plant species richness. Integration of a second, regional trait database (AusTraits) more than doubled trait completeness for the continent covered, indicating that the creation and integration of regional databases can rapidly expand trait completeness. Plain Language SummaryThe traits of plants determine how they interact with each other and their environment. Our knowledge of plant traits is incomplete, limiting scientific advancement as well as our ability to manage ecosystems and plan conservation actions. We show that there are large biases in trait data availability which are associated with both biological factors (range size, endemism, species richness) and socioeconomic factors (research expenditure, human population density). We also show how regionally-focused efforts can help rapidly expand trait data availability.

ecology↗