Search Results (103)

We investigated the dispersal ability of Euphydryas aurinia provincialis in a local-scale analysis within a single habitat patch of the Colfiorito highlands metapopulation. Our findings indicate that inside a single node, the organization of nesting patches can be conceptualized as a metapopulation itself, where reproductive sites, despite their spatial proximity, can act as either source or sink habitats depending on environmental conditions. We conducted fieldwork in six nesting patches inside a single node, capturing, marking, and recapturing individuals to assess their spatial distribution and movement tendencies at a large landscape scale. We found a high degree of site fidelity among individuals, with many recaptures occurring within the original marking site, but also a sex-based difference in movement patterns; females dispersed farther than males, likely driven by reproductive strategies, while males remained more localized, prioritizing mate-searching. Our findings suggest a complex dynamic in habitat connectivity: pastures and abandoned fields, despite being open, seem to act like sink areas, while breeding sites with shrub and tree cover act as source habitats, offering optimal conditions for reproduction. Individuals, especially females, from these source areas were later compelled to disperse into open habitats, highlighting a nuanced interaction between landscape structure and population dynamics. These results highlight the importance of maintaining habitat corridors to support metapopulation dynamics and prevent genetic isolation; the abandonment of traditional grazing practices is leading to the rapid closure of these source habitats, posing a severe risk of local extinction. Conservation efforts should prioritize the preservation of these source habitats to ensure the long-term viability of E. a. provincialis populations in fragmented landscapes. Full article

Assessing the ranging and dispersal behavior of apex predators and its consequences for landscape connectivity is of paramount importance for understanding population and ecosystem effects of anthropogenic land use change. Here, we synthesize ranging and dispersal ecological information on pumas (Puma concolor) and present estimates of how different land uses affect the space use and dispersal of pumas on fragmented landscapes in an ecotone between biodiversity hotspots in southeastern Brazil. Additionally, we evaluate the effect of animal translocations on dispersal and movement patterns. Using location data for 14 GPS-collared pumas and land use data, we assessed when, how long, and how far individuals dispersed; how forest loss and infrastructure influenced puma home range size; and how movement patterns changed according to land use and proximity to infrastructure, during ranging and dispersal, for residents, natural dispersers, and translocated individuals. We present the first detailed record on the dispersal of pumas in Brazil and in the tropics, including long-distance dispersals, and show that pumas moved faster and more linearly during dispersal than during ranging. Their movement was slower and their home ranges were smaller in more forested areas, underscoring the importance of forest as habitat. In contrast, movement rates were higher in open pastures, mainly during dispersal. Our study underscores the scarcity of research on puma space use and dispersal in South America and reveals partial divergences in dispersal behaviors compared to North America and temperate regions, especially concerning dispersal ages. Furthermore, we give the first steps in presenting how land cover and human infrastructure affect the movement of this apex predator in a tropical ecosystem, an important subsidy for land use management. We call for more comprehensive studies on the movement ecology of carnivores combined with long-term population monitoring, to allow linking individual behavior with metapopulation dynamics and landscape connectivity and drawing more effective measures to sustain their populations. Full article

Mediterranean wood pastures are the result of traditional silvo-pastoral uses that shaped these ecosystems into a mosaic of trees and open grassland. This ecosystem structure is generally associated with increased soil fertility under tree canopies. However, the response of herbaceous plant functional types (PFTs)—grasses, legumes, and non-legume forbs—to these heterogeneous microenvironments (under the canopy vs. open grassland) remains largely unknown, particularly regarding carbon (C) and nitrogen (N) acquisition and use. Even less is known about how different tree species and environmental conditions influence these responses. In this study, we aim to assess how tree canopies influence carbon and nitrogen cycling by comparing the effects of traditional oak stands and pine plantations on herbaceous PFTs and soil dynamics. For that we use C and N content and natural isotopic abundances (δ¹³C and δ¹⁵N) as proxies for biogeochemical cycling. Our results show that ecosystem C and N patterns depend not only on herbaceous PFTs and the presence or absence of tree canopies but also on tree species identity and environmental conditions, including climate. In particular, pine-dominated plantations exhibited lower nitrogen availability compared to those dominated by oak, suggesting that oak stands may contribute more effectively to enhance soil fertility in Mediterranean wood pastures. Furthermore, the canopy effect was more pronounced under harsher environmental conditions, highlighting the role of trees in buffering environmental stress, particularly in arid regions. This suggests that changes in tree cover and tree species may drive complex changes in ecosystem C and N storage and cycling. Full article

Livestock production systems can negatively affect soil structure, resulting in negative changes in physical–hydraulic properties, compromising soil functioning and productivity. This research aimed to evaluate the effects of rotational silvopastoral systems on soil physical–hydraulic functioning in their second year of implementation. The study was performed under Oxisol soil with a loamy sand texture in Southeast Brazil. We considered four grazing systems: an intensive silvopastoral system with Panicum maximum in consortium with Leucaena leucocephala (ISPS + L), an intensive silvopastoral system with Panicum maximum in consortium with Tithonia diversifolia (ISPS + T), an silvopastoral system with Panicum maximum (SPS) with tree row (TRs), and open pasture under a rotational grazing system with Panicum maximum (OP). The treatments ISPS + L, ISPS + T, and SPS had tree rows (TRs) every 20 m composed of Khaya ivorenses, Leucaena leucocephala, Eucalyptus urograndis, Acacia mangium, and Gliricidia sepium. Nine physical–hydraulic indicators were evaluated in the first 0.40 m of depth: bulk density (Bd), total porosity (TP), macroporosity (MaP), microporosity (MiP), field capacity (FC), permanent wilting point (PWP), available water content (AWC), total soil aeration capacity (ACt), and S-index. The soil physical–hydraulic properties were sensitive to the effects of the livestock systems. The use of silvopastoral systems in consortium with grass (ISPS + L and ISPS + T) allowed for better soil water retention, resulting in higher FC and AWC than the OP, SPS, and TR. The indicators Bd, ACt, MaP, FC, MiP, and S-index presented the greatest variance; however, FC, ACt, MaP, and MiP enabled the greatest differentiation among systems. Therefore, these properties are important in studies on soil physical quality since they provide information about the soil porous status and its ability to retain water and exchange soil air and gases. Therefore, enhancing the physical–hydraulic attributes of the soil in silvopastoral systems with shrub species is crucial for ensuring long-term productive sustainability and strengthening environmental resilience against future climate challenges. Full article

This study employs a multidisciplinary approach, integrating geoarchaeology, geomorphology, archaeometry, and palynology to analyze settlement patterns and land use in the surroundings of Capua (southern Italy) during the medieval transition. Borehole sampling and stratigraphic studies indicate significant landscape transformations due to human activity, particularly deforestation and agricultural expansion. Radiocarbon dating confirms settlement activity from antiquity through the early medieval period. Results suggest that Capua’s elevated position provided natural flood protection, influencing its continuous habitation. Pollen analysis reveals a shift from forested landscapes to open pastures, indicating intensive land use. Future research will focus on refining the chronology and archeological context of this transition, further clarifying Capua’s historical and environmental development. Full article

The transformation of the Cerrado biome into areas with different levels of activity and anthropic pressure negatively impacts biodiversity. This study evaluated the response of the dung beetle community to changes in land use systems: forests, rubber trees, pastures, and soybeans. Five areas were sampled in each system with a minimum distance of 2 km between them. Dung beetles were collected using pitfall traps, and both local (vegetation density, basal area of wooded vegetation, fractal dimension, litter height, electrical conductance (mV), water content in the soil (%), and soil resistance (kPa)) and landscape-related environmental variables (land use and overall composition and configuration of the landscape surrounding the sampling areas) were measured. In total, 2294 specimens were collected and distributed among 34 species and 18 genera. There was no significant difference in abundance between the systems, but differences in the number of species and biomass were observed between forest and soybean systems, as well as a separation of communities between the tree-covered (forest and rubber tree) and open (pasture and soybean) systems. Density and arboreal basal area were the main predictive variables for the diversity of the dung beetle community, reinforcing the importance of vegetation cover for maintaining diversity, whereas local and landscape-related variables influenced community composition. Full article

La Crosse virus (LACV) is a rare cause of pediatric encephalitis, yet identifying and mitigating transmission foci is critical to detecting additional cases. Neurologic disease disproportionately occurs among children, and survivors often experience substantial, life-altering chronic disability. Despite its severe clinical impact, public health resources to detect and mitigate transmission are lacking. This study aimed to design a Bayesian modelling approach to effectively identify and predict LACV incidence for geospatially informed public health interventions. A Bayesian negative binomial spatio-temporal regression model best fit the data and demonstrated high accuracy. Nine variables were statistically significant in predicting LACV incidence for the Appalachian Mountain Region. Proportion of children, proportion of developed open space, and proportion of barren land were positively associated with LACV incidence, while vapor pressure deficit index, year, and proportions of developed high intensity land, evergreen forest, hay pasture, and woody wetland were negatively associated with LACV incidence. Model prediction error was low, less than 2%, indicating high accuracy in predicting annual LACV human incidence at the county level. In summary, this study demonstrates the utility of Bayesian negative binomial spatio-temporal regression models for predicting rare but medically important LACV human cases. Future studies could examine more granular models for predicting LACV cases from localized variables such as mosquito control efforts, local reservoir host density and local weather fluctuations. Full article

The quality and production of viticulture are profoundly shaped by climate and soil, which are vital for enhancing plant growth, maximizing productivity, and facilitating carbon sequestration and phytoremediation. Any degradation in soil quality resulting from production practices—such as salinization and increased acidity—jeopardizes the long-term sustainability of vineyard operations. It is crucial that we prioritize the health of our soil to ensure the future success of our vineyards. This study aims to (1) assess soil fungal diversity under various management practices, (2) compare the relative abundance of sequence reads for different taxa in response to these practices, and (3) analyze shifts in functional guild composition in relation to these management practices. In this investigation, the fungal community composition was analyzed using molecular tools across five locations with distinct land management practices on the same basaltic soil. The findings indicate that vineyard management practices had a substantial impact on fungal diversity, as evidenced by taxonomic alpha diversity metrics, with significant differences observed in comparison to natural pasture and open field conditions. A permutational analysis of variance (PERMANOVA) revealed a highly significant effect of management practices (p < 0.0001) on fungal community structure. The land management practices were found to induce significant (p < 0.05) differences in species diversity between organic sites (organic and conventional) and the natural control site. Furthermore, the composition and functionality of the fungal communities appear to be shaped by the distinct abiotic factors associated with different management strategies that increase the abundance of total soil microorganisms that are affecting the grape yield and its quality. Full article

European grasslands are vital carbon (C) sinks, contributing to climate change mitigation. Grazing intensity significantly influences soil C and nitrogen (N) cycles through effects on soil conditions and microbial communities. While heavy grazing is linked to soil C loss and altered N processes, existing studies show conflicting outcomes. This study examines the impact of cattle grazing on soil C and N cycles in a historical alpine pasture in the eastern Italian Alps (1868 m a.s.l.). The following three grazing intensities were analyzed: heavy (8.19 LU ha⁻¹), moderate (0.59 LU ha⁻¹), and light (0.06 LU ha⁻¹). Soil was sampled from two depth layers (0–5 cm, 5–10 cm) and analyzed for bulk density, C and N content, C/N ratio, exchangeable N, δ¹⁵N, and microbial genes targeting general abundance (16S), N fixation (nifH), nitrification (amoA), and denitrification (nirK, nosZ) using real-time PCR. The results revealed decreased C and N concentrations with increasing grazing intensity, exclusively in the 0–5 cm soil layer. Higher δ¹⁵N and enhanced nitrification and denitrification suggest a more open N cycle under heavy grazing. These findings highlight the potential of microbial gene markers and δ¹⁵N isotopic ratios to monitor N cycle dynamics in alpine pastures, informing sustainable grazing management. Full article

Improvements in immersive technology are opening up new opportunities for land management and urban planning, enabling the creation of detailed virtual models for examining and simulating real-world short-, medium-, and long-term scenarios. The goal of this research is to present the creation of an urban digital twin based on a virtual reality city replica, that models and visualizes the urban environment in three dimensions using advanced geomatics techniques and IoT technologies. The methodology focuses on two case studies that utilize environmental analysis and virtual simulation: assessing hydrogeological risk and evaluating public light pollution. The Cesium platform was employed to build high-precision 3D models based on topographic, meteorological, and infrastructure data. The proposed methodology calculated a correlation between light pollution and CO₂ equal to 0.51 and a correlation between precipitation, slope, and risk area higher than 0.80. The most critical and high-risk classes are as follows: Dense Discontinuous Urban Fabric, Roads and Associated Lands, Pastures, and Forests. Results show how an urban digital twin can be a powerful tool for monitoring and territorial planning, with concrete applications in the public and risk management fields. This study also highlights the importance of geomatics technologies in the creation of realistic and functional virtual environments for the assessment and sustainable management of urban resources. Full article

Predicting forage biomass yield is critical in managing livestock since it impacts livestock stocking rates, hay procurement, and livestock marketing strategies. Only a few biomass yield prediction studies on pasture and rangeland exist despite the need. Therefore, this study focused on developing a biomass yield prediction methodology through remote sensing satellite imagery (multispectral bands) and climate data, employing open-source software technologies. Biomass ground truth data were obtained from local pastures, where Kentucky bluegrass is the predominant species among other forages. Remote sensing data included spatial bands (6), vegetation indices (30), and climate data (16). The top-ranked features (52 tested) from recursive feature elimination (RFE) were short-wave infrared 2, normalized difference moisture index, and average turf soil temperature in the machine learning (ML) model developed. The random forest (RF) model produced the highest accuracy ($R^2=0.83$) among others tested for biomass yield prediction. Applications of the developed methodology revealed that (i) the methodology applies to other unseen pasters ($R^2=0.79$), (ii) finer satellite spatial resolution (e.g., CubeSat; 3 m) better-predicted pasture biomass, and (iii) the methodology successfully developed for a combination of Kentucky bluegrass and other forages, extended to high-value alfalfa hay crop with excellent yield prediction accuracy ($R^2=0.95$). The developed methodology of RFE for feature selection and RF for biomass yield modeling is recommended for biomass and hay forage yield prediction. Full article

This study examined the grazing pressure and interactions between four species of wild kangaroos (Red Kangaroo Osphranter rufus, Common Wallaroo O. robustus, Eastern Grey Kangaroo Macropus giganteus, Western Grey Kangaroo M. fuliginosus), free-ranging feral goats (Capra hircus) and European rabbits (Oryctolagus cuniculus), and stocked Merino sheep (Ovis aries). The study site comprised two contiguous pairs of stocked and unstocked paddocks, one a sloping run-off zone, the other a flat run-on zone, covering a total area of 2158 ha. These paddocks on Fowlers Gap Station in far north-western New South Wales, Australia, are representative of the arid chenopod (Family: Chenopodiaceae) shrublands stocked with sheep. Sheep and red kangaroos dominate the mammalian herbivores by biomass. The study examined the relative grazing pressure exerted by the seven species of mammalian herbivores in stocked and unstocked conditions, where only sheep were confined, across a three-year period that included rain-deficient (drought) months. The effects of climate (especially rainfall and temperature) and herbivore density on the standing biomass of pasture were teased out at a macro-scale. Herbivory at a micro-scale was examined using open and exclosed plots with detection of herbivore species by fecal deposition and time-lapse videography. Sheep exerted the highest grazing pressure and there was no compensatory increase in grazing pressure by other herbivores in unstocked paddocks. Rainfall was a key driver of pasture biomass and condition and loss by senescence typically outweighed grazing pressure. Grazing effects at a micro-scale were plot-specific and complex. The results are discussed in relation to the sustainable management of rangelands for production and wildlife. Full article

Grasslands are key components of land ecosystems, providing valuable ecosystem services and contributing to local carbon sequestration. Australian grasslands, covering approximately 70% of the continent, are vital for agriculture, pasture, and ecosystem services. Ongoing climate change introduces considerable uncertainties about the dynamic responses of different types of grasslands to changes in regional climate and its variation. This study, bringing together high-resolution meteorological data, calibrated long-term satellite NDVI data, and NPP and statistical models, investigated the spatiotemporal variability of NDVI and NPP and their predominant drivers (temperature and soil water content) across Australia’s grassland zones from 1992 to 2021. Results showed a slight, non-significant NDVI increase, primarily driven by improved vegetation in northern savannah grasslands (SGs). Areal average annual NPP values fluctuated annually but with a levelled trend over time, illustrating grassland resilience. NDVI and NPP measures aligned spatially, with values decreasing from the coastal to the inland regions and north to south. Most of the SGs experienced an increase in NDVI and NPP, boosted by abundant soil moisture and warm weather, which promoted vegetation growth and sustained a stable growing biomass in this zone. The increased NDVI and NPP in northern open grasslands (OGs) were linked to wetter conditions, while their decreases in western desert grasslands (DGs) were ascribed to warming and drier weather. Soil water availability was the dominant driver of grassland growth, with NDVI being positively correlated with soil water content but being negatively correlated with temperature across most grasslands. Projections under the SSP126 and SSP370 scenarios using ACCESS-ESM1.5 showed slight NPP increases by 2050 under warmer and wetter conditions, though western and southern grasslands may see declines in vegetation coverage and carbon storage. This study provides insights into the responses of Australian grasslands to climate variability. The results will help to underpin the design of sustainable grassland management strategies and practices under a changing climate for Australia. Full article

This study evaluated the effects of gaseous pollutants and vegetation on the structure of fruit-feeding butterfly communities (some subfamilies of Nymphalidae) in a Caatinga area in Brumado, BA, between 2016 and 2018. Two transects were established: Transect “I” (presence of pollutant plumes) and Transect “II” (absence), encompassing a forest fragment and pasture. Bait traps were installed in each transect, and the butterfly communities were analyzed using faunistic indices, including species richness, Shannon diversity index, abundance, and dominance. The canopy opening was also assessed. The composition of fruit-feeding butterfly communities was influenced by both pollutants and vegetation. Gaseous pollutants increased butterfly abundance, diversity, and species richness, though species dominance remained unaffected. Notably, the abundance of Hamadryas februa was particularly sensitive to pollutant exposure. Conversely, increased canopy opening was negatively associated with butterfly abundance and diversity. A relationship between canopy opening and the presence of gaseous pollutants may reflect changes in the abundance and diversity of fruit-feeding butterfly species in the study region. Long-term community monitoring is important, as interannual differences in population fluctuations are common. A better understanding of the patterns found is essential to for devise devising conservation strategies for frugivorous butterfly communities in mining ventures. Full article

This study evaluates two expedient electronic sensors, a rising plate meter (RPM) and a “Grassmaster II” capacitance probe (GMII), to estimate pasture dry matter (DM, in kg ha⁻¹). The sampling process consisted of sensor measurements, followed by pasture collection and a laboratory reference analysis. In this comparative study, carried out throughout the 2023/2024 pasture growing season, a total of 288 pasture samples were collected in two phases (calibration and validation). The calibration phase (n = 144) consisted of measurements on three dates (6 December 2023, 29 February and 10 May 2024) in 48 georeferenced sampling areas of the experimental field “Eco-SPAA” (“M_G” field), located at Mitra farm (Évora, Portugal). This pasture is a permanent mixture of various botanical species (grasses, legumes, and others) grazed by sheep, and is representative of biodiverse dryland pastures. The validation phase (n = 144) was carried out between December 2023 and April 2024 in 18 field tests (each with eight pasture samples), in three types of representative pastures: the same mixture for grazing (“M_G” field), a commercial and annual mixture for cutting (mowing) and conservation (“M_M” field), and legumes for grazing (“L_G” field). The best estimation model for DM was obtained based on measurements carried out in February in the case of the GMII probe (R² = 0.61) and December 2023 and February 2024 in the case of RPM (R² = 0.76). The estimation decreased very significantly for both sensors based on measurements carried out in May (spring). The validation phase showed greater accuracy (less RMSE) in “M_G” field tests (RMSE of 735.4 kg ha⁻¹ with GMII and 512.3 kg ha⁻¹ with the RPM). The results open perspectives for other works that would allow the testing, calibration, and validation of these electronic sensors in a wider range of pasture production conditions, in order to improve their accuracy as decision-making support tools in pasture management. Full article