Biology subjects

Stastny, K.

Publications and source records attributed to Stastny, K..

3 recordsLinked to original sources

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↗

bioRxiv2026

Temporal span of biodiversity monitoring mediates the effects of area and environment

The scale at which diversity is observed shapes the patterns we find. While spatial scale is known to influence biodiversity patterns, the effects of temporal scale, namely the average duration of sampling (known as temporal span), have been mostly overlooked. Here, we investigate how temporal span affects species richness patterns, their environmental drivers, and species richness hotspots. We used species richness data from several large bird datasets from Czechia, with over 7000 observations, a spatial grain ranging from 0.03 to 100 km2, and a temporal span ranging from 1 to 36 years (1985-2017). Using Random Forests, we modelled species richness as a response to temporal span, while also including area, geographic location, time, and environmental and land-cover predictors. We found that the temporal span is consistently among the most important predictors of bird species richness. Moreover, temporal span interacts with key environmental conditions, particularly precipitation and water bodies, modulating their effects on species richness and revealing processes that differ from those traditionally attributed solely to spatial grain. We also found that using different time spans can shift the predicted locations of biodiversity hotspots. Our results provide empirical evidence that temporal span should be included in studies about biodiversity and conservation planning, given the urgent challenges arising from ongoing biodiversity change and the complexity of its drivers.

ecology↗

bioRxiv2025

Spatial autocorrelation of species diversity and distributions in time and across spatial scales

AimSpatial autocorrelation (SAC), also known as aggregation, is a notable property of species distributions and diversity; it reflects species niche and dispersal, has conservation significance, and affects ecological models. Yet, we know little about spatial and temporal patterns of SAC in empirical data. Here, we assess SAC in both observed species distributions and species richness, quantifying its magnitude and prevalence over large extents and across spatial resolutions. We also assess its dynamics over the past 50 years. LocationCzechia, Europe, New York State, Japan Time period1972 - 2017 Major taxa studiedBirds MethodsWe analyzed four temporally replicated gridded bird atlases, each aggregated to multiple grain sizes. To measure SAC in species distributions, we used the Join count statistic (JC) and its deviation from the expectation under a random distribution. We assessed temporal changes in JC and their relationship with changes in occupancy, given their close association. We used Morans I to measure SAC in species richness. ResultsBoth species distributions and diversity were positively autocorrelated across all regions, periods, and grains, and the magnitude of autocorrelation mostly decreased with increasing grain. We found that the temporal change of JC varied across species and regions, with zero average trends in Morans I, JC, and occupancy. However, when JC and occupancy were considered jointly, we found systematic temporal shifts: contracting species became more aggregated (compact) while expanding species became more fragmented (disjoint). Main conclusionsStronger SAC at finer grains suggests greater predictability of diversity and distributions at these scales. Despite zero average change in occupancy or SAC, their coupled shifts highlight the importance of considering both jointly. We found long-distance dispersal (rather than advancing edge) and vulnerability of isolated populations to extinction as the major drivers of range dynamics in temperate birds.

ecology↗