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opennotspecifiedSep 2013View details →

FIGURE 5. Male left parameres. A in New species of plant bug associated with pastures in Colombia, and notes on the genera Dolichomiris, Cynodonmiris, and Megaloceroea (Hemiptera: Heteroptera: Miridae)

FIGURE 5. Male left parameres. A—Cynodonmiris corpoicanus; B—Dolichomiris linearis; C—Megaloceroea recticornis; D—Dolichomiris puncticerus (modified from Carvalho, 1975); E—Cynodonmiris costicollis (modified from Carvalho, 1975).

opencc-by-4.0Dec 2023View details →

Data of "Grazing intensity and horn status influence activity on pasture, physiological pre-slaughter reactions and meat quality in beef heifers"

Raw data of the article of "Grazing intensity and horn status influence activity on pasture, physiological pre-slaughter reactions and meat quality in beef heifers". Dataset of 64 crossbred beef heifers. Both experimental independent variables (animal id, horn status, grazing intensity, replicate) and dependent variables (related to physical activity on pasture, behaviour tests, stress physiology and meat quality) are presented.

opencc-by-4.0Dec 2024View details →

An annual 30 m cultivated pasture dataset of the Tibetan Plateau from 1988 to 2021

Cultivated pastures have rapidly developed across the Tibetan Plateau over the past several decades, raising concerns about grassland degradation. Accordingly, considerable attention is focused on the protection of grassland ecosystems. However, the high-resolution spatial distribution of cultivated pastures on the Tibetan Plateau remains poorly understood, primarily due to the difficulty of discriminating cultivated pastures from non-cultivated pastures using remote sensing techniques. The absence of such information hinders efficient agricultural and livestock husbandry management, making it challenging to support ecological protection and restoration efforts. Here, we mapped the cultivated pastures on the Tibetan Plateau at a 30-m resolution for the years 1988 to 2021 using the Landsat data on the Google Earth Engine (GEE) cloud computing platform. We built a Random Forest (RF) binary classification model with inputs of the spectral-temporal metrics of Landsat images acquired in the growing season, as well as ancillary topographic data. The model was trained using carefully selected training samples and validated against 2,000 independent random reference points. The model achieved an overall accuracy of 97.05% ± 0.4% and an F1 spatial consistency score of 82.51% ± 14.22% (Precision: 90.04% ± 6.18%, Recall: 76.74% ± 9.91%), suggesting high confidence in mapping the distribution of cultivated pastures. We produced a dataset of cultivated pasture maps for the years from 1988 to 2021 for Qinghai Province and the Tibet Autonomous Region on the Tibetan Plateau, covering 77% of the plateau. To our knowledge, we are the first to map cultivated pastures on the Tibetan Plateau, and our RF binary classification approach holds promise in identifying cultivated pastures in other regions of the world, which could prove invaluable for scientists, policymakers, ecological conservation practitioners, and herdsmen.

dryad32/100

Predicting pasture and forest landowner intention to create early successional habitat

As human land uses expand across the landscape, the management practices of private landowners are an essential part of effective conservation. Early successional habitats (ESH) and the species that depend on them are a priority in the eastern United States, and efforts to create ESH on private lands has primarily focused on forest landowners and timber harvests. Private pasture lands in a forested landscape present an additional opportunity to create and maintain ESH, yet our understanding of landowner values and attitudes about management strategies in pastures is lacking. To address this, we surveyed private landowners in 5 Virginia counties who own ≥10.1 ha or >610 m elevation (n = 503). Our primary objective was to understand how a variety of factors such as landowner values, past experience with habitat management, and perceived barriers to carrying out habitat management are associated with private landowner intention to carry out 7 ESH management strategies (i.e., reduced mowing, reduced grazing, timber harvests within forest, timber harvests at a field-forest border, prescribed fire, use of machinery, and use of herbicides to control invasive species) for the benefit of wildlife in the next five years. We used boosted regression trees to determine which factors best predicted the intention to carry out each strategy. We were able to effectively predict (accuracy > 75%) landowner intention to engage in open pasture and timber management strategies. Landowner values were not consistent across the different management strategies; landowners likely to reduce mowing or grazing valued ecological aspects of their land (i.e., pollinator habitat water quality) whereas landowners likely to harvest timber valued hunting and revenue. Past experience with wildlife management was the strongest predictor of likelihood to reduce mowing and grazing. Our results suggest that expanding outreach efforts to include pasture management options would engage a broader set of landowners in creation of ESH, especially if such efforts highlighted the benefits to pollinator species, water quality, and enhanced opportunities for hunting and other types of recreation.

opencc-zeroDec 2021View details →

dryad32/100

Pastures and climate extremes: Impacts of cool season warming and drought on the productivity of key pasture species in a field experiment

Shifts in the timing, intensity and/or frequency of climate extremes, such as severe drought and heatwaves, can generate sustained shifts in ecosystem function with important ecological and economic impacts for rangelands and managed pastures. The Pastures and Climate Extremes experiment (PACE) in Southeast Australia was designed to investigate the impacts of a severe winter/spring drought (60% rainfall reduction) and, for a subset of species, a factorial combination of drought and elevated temperature (ambient +3 °C) on pasture productivity. The experiment included nine common pasture and Australian rangeland species from three plant functional groups (C3 grasses, C4 grasses and legumes) planted in monoculture. Winter/spring drought resulted in productivity declines of 45% on average and up to 74% for the most affected species (Digitaria eriantha) during the 6-month treatment period, with eight of the nine species exhibiting significant yield reductions. Despite considerable variation in species' sensitivity to drought, C4 grasses were more strongly affected by this treatment than C3 grasses or legumes. Warming also had negative effects on cool-season productivity, associated at least partially with exceedance of optimum growth temperatures in spring and indirect effects on soil water content. The combination of winter/spring drought and year-round warming resulted in the greatest yield reductions. We identified responses that were either additive such that there was only as significant warming effect under drought (Festuca), or less-than-additive, where there was no drought effect under warming (Medicago), compared to ambient plots. Results from this study highlight the sensitivity of diverse pasture species to increases in winter and spring drought severity similar to those predicted for this region, and that anticipated benefits of cool-season warming are unlikely to be realised. Overall, the substantial negative impacts on productivity suggest that future, warmer, drier climates will result in shortfalls in cool-season forage availability, with profound implications for the livestock industry and natural grazer communities.

opencc-zeroMar 2022View details →

opencc-by-4.0Apr 2022View details →

Raw data for article "Use of molasses-based blocks to modify grazing patterns and increase Highland cattle impacts on Alnus viridis-encroached pastures"

Data supporting the conclusions of the article "Use of molasses-based blocks to modify grazing patterns and increase Highland cattle impacts on Alnus viridis-encroached pastures" published in the journal Frontiers in Ecology and Evolution. Authors: Mia Svensk, Ginevra Nota, Pierre Mariotte, Marco Pittarello, Davide Barberis, Michele Lonati, Eric Allan, Elisa Perotti and Massimiliano Probo.

FIGURES 21–24 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 21–24. Stenodema andina: (21) habitus (dorsal view). 22–24: male genitalia: (22) aedeagus; (23) left paramere; (24) right paramere (redrawn from Carvalho, 1975).

FIGURES 17–20 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 17–20. Neotropicomiris nordicus: (17) habitus (dorsal view). 18–20: male genitalia: (18) aedeagus; (19) left paramere; (20) right paramere (redrawn from Carvalho & Fontes, 1969).

FIGURES 13–16 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 13–16. Cynodonmiris corpoicanus: (13) habitus (dorsal view). 14–16: male genitalia: (14) aedeagus; (15) left paramere; (16) right paramere (redrawn from Ferreira et. al., 2013).

FIGURES 9–12 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 9–12. Collaria scenica: (9) habitus (dorsal view). 10–12: male genitália: (10) aedeagus; (11) left paramere; (12) right paramere (redrawn from Carvalho & Fontes, 1981).

FIGURES 29–32 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 29–32. Stenodema praecelsus: (29) habitus (dorsal view). 30–32: male genitalia: (30) aedeagus; (31) left paramere; (32) right paramere (redrawn from Carvalho, 1975).

FIGURES 1–4 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 1–4. Collaria boliviana: (1) habitus (dorsal view). 2–4: male genitalia: (2) aedeagus; (3) left paramere; (4) right paramere (redrawn from Carvalho, 1990).

FIGURES 5–8 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 5–8. Collaria oleosa: (5) habitus (dorsal view). 6–8: male genitalia: (6) aedeagus; (7) left paramere; (8) right paramere (redrawn from Carvalho & Fontes, 1981).

FIGURES 25–28 in Plant bugs (Hemiptera: Miridae) associated with pastures in Colombia

FIGURES 25–28. Stenodema dohrni: (25) habitus (dorsal view). 26–28: male genitalia: (26) aedeagus; (27) left paramere; (28) right paramere (redrawn from Carvalho, 1975).

opencc-by-4.0May 2019View details →

Data from: Grazing-induced patchiness, not grazing intensity, drives plant diversity in European low-input pastures

Vegetation and soil data from: Tonn, Densing, Gabler, Isselstein: Grazing-induced patchiness, not grazing intensity, drives plant diversity in European low-input pastures, Journal of Applied Ecology The first data sheet contains a description of column names and contents, the second data sheet contains the data set itself.

Fig. 4 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 4. Random Forests (RF) predictor-based variable importance for total abundance of Onthophagus taurus, O. hecate, O. pennsylvanicus, Labarrus pseudolividus, and Blackburneus stercorosus in A) 2013 and B) 2015. Horizontal axes represent the eight predictor variables included in each RF model. Variable importance measures are reported as percentage increase in mean standard error (MSE) of model accuracy when the given predictor was removed from the model. Asterisks indicate significant predictors.

Fig. 3 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 3. Yearly totals by month and farm type for Blackburneus stercorosus in A) 2013, B) 2015 and Labarrus pseudolividus in C) 2013, D) 2015. Sampling months include May (M), June (first J), July (second J), August (A), September (S), and October (O). Mean abundance ± SE per month is shown across all sites (total abundance, gray bars), for sites that did not use chemicals (NCU, black), and for those with chemical usage (CU, blue). Letters are used to indicate the significant differences in total abundance among months. "SI" indicates a significant interaction between "month" and "farm type".

Fig. 2 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 2. Yearly abundance totals by month and farm type for dominant scarabaeine species: Onthophagus taurus in A) 2013 and B) 2015; O. pennsylvanicus in C) 2013 and D) 2015; and O. hecate in E) 2013 and F) 2015. Sampling months include May (M), June (first J), July (second J), August (A), September (S), and October (O). For each month, mean ± SE for total abundance measurements is shown with gray bars, as well as for sites using no chemicals (NCU, black) and those with chemical usage (CU, blue). Letters are used to indicate the significant differences in total abundance among months. Models with significant interactions (farm type*month) are indicated with a red "SI".

Fig. 1 in Relationship of Dung Beetle (Coleoptera: Scarabaeidae and Geotrupidae) Abundance and Parasite Control in Cattle on Pastures throughout Maryland

Fig. 1. Yearly abundance totals by month and farm type pooled across all scarabaeine and aphodiine species. Sampling months include May (M), June (first J), July (second J), August (A), September (S), and October (O). For each month, mean abundance ± SE across all farms (total abundance) is shown with gray bars. Letters indicate a significant difference. Mean abundance ± SE by farm type is also shown; sites using no chemicals (NCU) are black, and those with chemical usage (CU) are blue. Models with significant interactions (farm type*month) are indicated with a red "SI". Plots are as follows: A) Scarabaeine species in 2013, B) Aphodiine species in 2013, C) Scarabaeine species in 2015, and D) Aphodiine species in 2015.