Impact of land cover and landfills on the breeding effect and nest occupancy of the white stork in Poland.
Ontology highlight
ABSTRACT:
SUBMITTER: Bialas JT
PROVIDER: S-EPMC8012577 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Choosing an appropriate nest site is essential for successful breeding. Changes in land use cause populations of many species to decline although some species adapt to anthropogenic changes. The white stork Ciconia ciconia commonly uses artificial nest sites. Recently, white storks from Western Europe have been using landfills as feeding sites; the beginnings of this process are being observed in Central-Eastern Europe. The study aimed to determine factors influencing the probability of nest occupation and breeding effect in a Central-Eastern European population of white storks. We used long-term data from Western Poland on breeding effect, nest occupation, the structure supporting the nest, the proximity of the nearest landfills, landfill area, and land cover. The probability of nest occupation was significantly dependent on habitat quality (based on the share of the preferred type of land cover), the structure supporting the nest, and landfill proximity within a specific year. The breeding effect was influenced by habitat quality and nesting structure. We demonstrate that the type of nesting structure is an important factor influencing both the probability of nest reoccupation and breeding effect. However, the significance of landfills appears to be growing, and in recent years, storks prefer occupying nests closer to landfills, which may have significant consequences for the population of the white stork.
| S-EPMC7024061 | biostudies-literature
Project description:BackgroundConnections between habitats are key to a full understanding of anthropic impacts on ecosystems. Freshwater habitats are especially biodiverse, yet depend on exchange with terrestrial habitats. White storks (Ciconia ciconia) are widespread opportunists that often forage in landfills and then visit wetlands, among other habitats. It is well known that white storks ingest contaminants at landfills (such as plastics and antibiotic resistant bacteria), which can be then deposited in other habitats through their faeces and regurgitated pellets.MethodsWe characterized the role of white storks in habitat connectivity by analyzing GPS data from populations breeding in Germany and wintering from Spain to Morocco. We overlaid GPS tracks on a land-use surface to construct a spatially-explicit network in which nodes were sites, and links were direct flights. We then calculated centrality metrics, identified spatial modules, and quantified overall connections between habitat types. For regional networks in southern Spain and northern Morocco, we built Exponential Random Graph Models (ERGMs) to explain network topologies as a response to node habitat.ResultsFor Spain and Morocco combined, we built a directed spatial network with 114 nodes and 370 valued links. Landfills were the habitat type most connected to others, as measured by direct flights. The relevance of landfills was confirmed in both ERGMs, with significant positive effects of this habitat as a source of flights. In the ERGM for southern Spain, we found significant positive effects of rice fields and salines (solar saltworks) as sinks for flights. By contrast, in the ERGM for northern Morocco, we found a significant positive effect of marshes as a sink for flights.ConclusionsThese results illustrate how white storks connect landfills with terrestrial and aquatic habitats, some of which are managed for food production. We identified specific interconnected habitat patches across Spain and Morocco that could be used for further studies on biovectoring of pollutants, pathogens and other propagules.
| S-EPMC10045253 | biostudies-literature
Project description:BackgroundA particular type of site fidelity is faithfulness to the nest site, where birds are not only reoccupying breeding territories but also reusing nests built in previous breeding seasons. Staying faithful to the nest site is believed to be an adaptive strategy, and based on the ability to predict an individual's own breeding success, a hypothesis of "win-stay:loose-switch" was proposed. In this study, we aimed to resolve which factors affect the nest-site fidelity of white stork Ciconia ciconia, species known for reusing nests available in the breeding sites. Basing on ring recoveries from 31 years of studies in Western and Southern Poland, we analysed the impact of intrinsic and extrinsic factors on nest-site fidelity.ResultsWe found that increasing age and breeding success (i.e. producing any fledglings or not) increased the probability of reusing the nest, but in the oldest individuals, the probability decreased. In turn, the probability of breeding success increased with age, the increasing number of reproductive events on the particular nest, and the presence on the nest in the previous year. However, the oldest individuals had lower probability of success, as the relationship was curvilinear. The number of fledglings, however, was influenced only by an individual's age. The number of reproductive events on the nest was, in turn, affected by age, with the youngest and oldest individuals using the current nest for the least number of years.ConclusionsOur study shows that the decision process of whether to stay faithful to the nest or switch is based on the experience from the previous breeding event, consistently with the "win-stay:loose-switch" hypothesis. Our results also show that site fidelity benefits white storks, as the probability of breeding success increases if the nest is reused. Results also show the senescence effect that lowers breeding success and site fidelity probabilities.
| S-EPMC10512545 | biostudies-literature
Project description:Wind energy is a growing source of renewable energy with a 3-fold increase in use globally over the last decade. However, wind turbines cause bat mortality, especially for migratory species. The southwest United States has high bat species diversity and is an important area for migratory species, although little is known about their seasonal distribution. To examine potential risk to bats in areas proposed for wind energy development, we characterized bat occupancy spatially and temporally across northern Arizona, identifying use during summer when bats are reproductively active and fall during the migratory season. Our objectives were to determine occupancy of migratory species and species of greatest conservation need and develop a probability of occupancy map for species to identify areas of potential conflict with wind energy development. We selected 92 sites in 10 clusters with potential for development and used acoustic detectors to sample bats in the summer and fall of 2016 and 2017 for 6 nights per site per year. We predicted response of migratory bat species and species of special concern to 9 landscape variables using Program MARK. During summer, higher densities of forest on the landscape resulted in a higher probability of occupancy of migratory species such as hoary bats (Lasiurus cinereus), silver-haired bats (Lasionycteris noctivagans), big free-tailed bats (Nyctinomops macrotis), and species of conservation need such as spotted bats (Euderma maculatum). During the fall, higher concentration of valleys on the landscape predicted occupancy of hoary bats, big free-tailed bats, and spotted bats. High bat occupancy in the fall was also associated with higher elevation and close proximity to forests. We recommend that wind turbines be placed in open, flat grasslands away from forested landscapes and concentrations of valleys or other topographic variation.
| S-EPMC9165840 | biostudies-literature
Project description:The dataset presented in this data paper supports "Linking land cover satellite data with dietary variation and reproductive output in an opportunistic forager: Arable land use can boost an ontogenetic trophic bottleneck in the White Stork Ciconia ciconia" (Orłowski et al. 2019) [1]. Analysis of data on diet and prey composition based on an investigation of 165 pellets of White Storks Ciconia ciconia sampled from 52 nests showed that their diet was based primarily on 'eurytopic prey' (embracing taxa from grassland and a variety of non-cropped habitats), the biomass contribution of which in the diet was disproportionately (3-4-fold) higher than the percentage of available corresponding habitats. Similarly, prey items from water/wetland sites prevailed over the availability of corresponding habitats. The opposite pattern characterized prey taxa from arable habitats and forests, the contribution of which was lower than the availability of the corresponding habitats. The total energy content per pellet (calculated by summing the energy content of all individual prey items across one specific prey group) was the most strongly correlated with the biomass of Orthoptera, thereafter with that of mammals, other vertebrates, earthworms and other invertebrates, but not with the biomass of Coleoptera. White Storks from nests of low productivity pairs (i.e. with 1-2 fledglings) consumed a significantly (up to two-fold) higher biomass of Coleoptera, Orthoptera and all invertebrates, which also translated into a higher total biomass and a higher total energy content compared to the diet of high-productivity pairs (i.e. with 3-4 fledglings). Our data, in particular those relating to energy content in a variety of invertebrate taxa, and their body mass and functional division in terms of habitat preferences should be useful for other researchers to calculate energy budgets of predatory animals living in agricultural landscapes in Europe.
| S-EPMC6230975 | biostudies-literature
Project description:Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.
| S-EPMC5651924 | biostudies-literature
Project description:Human activities pose a major threat to tropical forest biodiversity and ecosystem services. Although the impacts of deforestation are well studied, multiple land-use and land-cover transitions (LULCTs) occur in tropical landscapes, and we do not know how LULCTs differ in their rates or impacts on key ecosystem components. Here, we quantified the impacts of 18 LULCTs on three ecosystem components (biodiversity, carbon, and soil), based on 18 variables collected from 310 sites in the Brazilian Amazon. Across all LULCTs, biodiversity was the most affected ecosystem component, followed by carbon stocks, but the magnitude of change differed widely among LULCTs and individual variables. Forest clearance for pasture was the most prevalent and high-impact transition, but we also identified other LULCTs with high impact but lower prevalence (e.g., forest to agriculture). Our study demonstrates the importance of considering multiple ecosystem components and LULCTs to understand the consequences of human activities in tropical landscapes.
| S-EPMC9271202 | biostudies-literature
Project description:Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002-2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p < 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.
| S-EPMC6715068 | biostudies-literature
Project description:The dynamic interplay between urbanization and its impacts on climate is a subject of recent concern, particularly in rapidly urbanizing cities of Pakistan. This research investigated the spatio-temporal effects of urban growth in terms of Land Use Land Cover changes on the thermal environment (Land Surface Temperature) of the Sialkot city, Pakistan using satellite data spanning four distinct time periods (1989, 2000, 2009 and 2020) and predicted changes for year 2030 by employing Cellular Automata Markov Chain Model. Satellite imagery (Landsat 5, 7 and 8) was processed, and maximum likelihood supervised classification was done to generate LULC maps for each of the aforementioned years. In addition to LULC classification, thermal bands of satellite data (for summer and winter) were processed to compute Land Surface Temperature (LST) of the city. The prediction of LULC changes and LST was done for year 2030 using Cellular Automata Markov Chain Model. The accuracy of classified and prediction maps was checked using Kappa Index. The LULC analysis revealed 4.14% increase in the built-up area and 3.43% decrease in vegetation cover of the city during 1989 to 2020. Both land covers are expected to change in the future (year 2030) by + 1.31% (built-up) and - 1.1% (vegetation). Furthermore, a declining trend in the barren land and water bodies was also observed over time. These LULC changes were found affecting the LST of study area. The transformation of vegetation cover into built-up area resulted in an increase in LST over time. A notable rise of 4.5 °C (summer) and 5.7 °C (winter) in the mean LST of Sialkot was observed during 1989 to 2020 and further increases are anticipated in year 2030. This study calls for attention of the policy makers to reduce human impact on the local climate of the city. The study will also help city developers in analyzing the urban population growth trend, finding suitable location to built new infrastructure by governmental authorities and how the rising temperature can affect energy demand and agriculture production of the city in future.
| S-EPMC10719351 | biostudies-literature
Project description:The rate of deforestation declined steadily in Thailand since the year 2000 due to economic transformation away from forestry. However, these changes did not occur in Nan Province located in northern Thailand. Deforestation is expected to continue due to high demand for forest products and increased agribusiness. The objectives of this paper are (1) to predict land-use change in the province based on trends, market-based and conservation scenarios, (2) to quantify biodiversity, and (3) to identify biodiversity hotspots at greatest risk for future deforestation. This study used a dynamic land-use change model (Dyna-CLUE) to allocate aggregated land demand for three scenarios and employed FRAGSTATS to determine the spatial pattern of land-use change. In addition, the InVEST Global Biodiversity Assessment Model framework was used to estimate biodiversity expressed as the remaining mean species abundance (MSA) relative to their abundance in the pristine reference condition. Risk of deforestation and the MSA values were combined to determine biodiversity hotspots across the landscape at greatest risk. The results revealed that most of the forest cover in 2030 would remain in the west and east of the province, which are rugged and not easily accessible, as well as in protected areas. MSA values are predicted to decrease from 0.41 in 2009 to 0.29, 0.35, and 0.40, respectively, under the trends, market-based and conservation scenarios in 2030. In addition, the low, medium, and high biodiversity zones cover 46, 49 and 6% of Nan Province. Protected areas substantially contribute to maintaining forest cover and greater biodiversity. Important measures to protect remaining cover and maintain biodiversity include patrolling at-risk deforestation areas, reduction of road expansion in pristine forest areas, and promotion of incentive schemes for farmers to rehabilitate degraded ecosystems.
| S-EPMC7751623 | biostudies-literature