Resource selection by Sarda cattle in a Mediterranean silvopastoral system.

Knowledge of how grazing cattle utilize heterogeneous landscapes in Mediterranean silvopastoral areas is scarce. Global positioning systems (GPS) to track animals, together with geographic information systems (GIS), can relate animal distribution to landscape features. With the aim to develop a general spatial model that provides accurate prediction of cattle resource selection patterns within a Mediterranean mountainous silvopastoral area, free-roaming Sarda cows were fitted with GPS collars to track their spatial behaviors. Resource selection function models (RSF) were developed to estimate the probability of resource use as a function of environmental variables. A set of over 500 candidate RSF models, composed of up to five environmental predictor variables, were fitted to data. To identify a final model providing a robust prediction of cattle resource selection pattern across the different seasons, the 10 best models (ranked on the basis of the AIC score) were fitted to seasonal data. Prediction performance of the models was evaluated with a Spearman correlation analysis using the GPS position data sets previously reserved for model validation. The final model emphasized that watering point, elevation, and distance to fences were important factors affecting cattle resource-selection patterns. The prediction performances (as Spearman rank correlation scores) of the final model, when fitted to each season, ranged between 0.7 and 0.94. The cows were more likely to select areas lower in elevation and farther from the watering point in winter than in summer (693 ± 1 m and 847 ± 13 m vs. 707 ± 1 m and 635 ± 21 m, respectively), and in spring opted for the areas furthest from the water (963 ± 12). Although caution should be exercised in generalizing to other silvopastoral areas, the satisfactory Spearman correlations scores from the final RSF model applied to different seasons indicate resource selection function is a powerful predictive model. The relative importance of the individual predictors within the model varied among the different seasons, demonstrating the RSF model's ability to interpret changes in animal behavior at different times of the year. The RSF model has proven to be a useful tool to interpret the spatial behaviors of cows grazing in Mediterranean silvopastoral areas and could therefore be helpful in managing and preserving ecosystem services of these areas.

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems.

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R 2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1-10 ha-1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.

Grazing behavior and production characteristics among cows differing in residual feed intake while grazing late season Idaho rangeland.

The objectives were to determine whether cows previously classified during a postweaning test as either low or high residual feed intake (LRFI or HRFI) differed in BW, BCS, and winter grazing activity while consuming poor-quality forage. Thirty Hereford × Angus (LRFI = 16; HRFI = 14) 2-yr-old mid- to late-gestation cows (pregnant with second calf) grazed sagebrush steppe for 78 d beginning 29 September 2015. BW and BCS were collected before and after grazing. Five cows of each RFI classification were fitted with global positioning system (GPS) collars on 16 November 2015 with data collection commencing 3 d later and continuing for 25 d in a 323-ha pasture. The GPS units collected location coordinates every 2 min from which total daily travel distance (DTD) was calculated. Visual counts for bite rate were obtained from collared cows over 8 d. Coordinate data, daily bite rate, BW, and BCS were analyzed as repeated measures using a mixed model, which included RFI group, day, and RFI group × day as fixed effects and cow within RFI group as the random effect. Change in BW and BCS was analyzed by ANOVA with RFI group as the main effect. Cow BCS and BW differed for both day (P < 0.0001) and day × RFI (P < 0.05). Body condition was less (P < 0.05) in LRFI cows at the beginning (5.8 ±â€…0.13 vs. 6.2 ±â€…0.14 BCS), but similar (P = 0.67) to HRFI at the end of the study (4.6 ±â€…0.13 vs. 4.6 ±â€…0.14). BW among the RFI groups did not differ (P = 0.20) prior to going to range. However, BW-change and BCS-change differed (P < 0.05) between RFI groups. Not only did the LRFI cows lose less BW (-50.0 ±â€…5.41 kg vs. -66.6 ±â€…5.78 kg) over the trial, they also were less variable with respect to BW loss. Cows did not differ (P > 0.21) by RFI for DTD or bite rate, but day was significant (P < 0.0001) with cows increasing bite rate as the season of year progressed (55.2 ±â€…5.63 bites/min for day 4 vs. 84.8 ±â€…5.32 bites/min for day 21) and increasing DTD as snow storms occurred. Although LRFI cows were leaner than HRFI cows at the commencement of the project, they lost less BW in a late season rangeland environment.

Bush encroachment dynamics and rangeland management implications in southern Ethiopia.

Rangelands in southern Ethiopia have been undergoing a rapid regime shift from herbaceous to woody plant dominance in the past decades, reducing indigenous plant biodiversity, altering ecosystem function, and threatening subsistence pastoralism. Despite significant rangeland management implications, quantification of spatial encroachment extent and transitional pathways that result in encroachment remain largely under-explored. This paper develops a phenology-based approach to map rangeland vegetation states in southern Ethiopia, and examines transition pathways among states using the state-and-transition model. The results indicate that nearly 80% of landscape was dominated by woody plants in 2013. While stable encroached states have been established in both high and low lands through different transition pathways between 2003 and 2013, we identified spatial locations where bush encroachment occurred rapidly. The multiplicity in the transition pathways indicates opportunities for positive transformation in the entire rangeland system in southern Ethiopia and other semi-arid regions of Africa.

Water quality effects of herded stream crossings by domestic sheep bands.

Livestock impacts on total suspended solids (TSS) and pathogen (e.g., ) levels in rangeland streams are a serious concern worldwide. Herded stream crossings by domestic sheep () are periodic, necessary managerial events on high-elevation rangelands, but their impacts on stream water quality are largely unknown. We evaluated the effects of herded, one-way crossings by sheep bands (about 2000 individuals) on TSS and concentration and load responses in downstream waters. Crossing trials were conducted during the summers of 2005 and 2006 on two reaches within each of three perennial streams in the Centennial Mountains of eastern Idaho and southwestern Montana. Water samples were collected at 2-min intervals at an upstream background station and at stations 25, 100, 500, and 1500 m downstream just before and during each crossing trial. Crossings produced substantial increases in TSS and concentrations and loads downstream, but these concentration increases were localized and short lived. Maximum TSS concentration was highest 25 m downstream, declined as a function of downstream distance, and at 500 m downstream was similar to background. Post-peak TSS concentrations at all downstream stations decreased to <25 mg L within 24 to 48 min after reaching their maxima. Findings for concentration and load responses were similar to that of TSS but less clear cut. Stream-crossing sheep do affect water quality; therefore, producers and resource managers should continue to evaluate the efficacy of herdsmanship techniques for reducing water quality impact.