Rangeland Ecology & Management最新文献

Precipitation and temperature inputs are the primary factors affecting net primary plant production across rangeland ecoregions. Skillful seasonal climate forecasts have the potential to directly aid in informing management for multiple agricultural and natural resource applications across the western United States. A key limitation in using these forecasts has been the availability of high-resolution climate forecasts across rangeland ecoregions given the high spatiotemporal heterogeneity in precipitation and temperature across these regions. This study examines the skill, or the correlation between of a climate forecast to actual data. Seasonal climate forecasts at lead times of up to 7 months lead times are statistically downscaled from models participating in the North American Multi-Model Ensemble (NMME). The skill of seasonal climate forecasts has typically been assessed at regional scales which may obscure forecast utility for site-specific management applications. Skill assessments are also typically only conducted on individual models, or the ensemble mean of all models which may overlook value-added skill by subsampling models. Here, we evaluated the skill of statistically downscaled monthly precipitation and temperature forecasts derived from seven NMME models for multiple rangeland ecoregions across the western United States. We found that multimodel aggregate forecasts often had synergistic skill when compared to both individual model forecasts as well as the ensemble mean. We also found that forecast skill was dependent on location, the month in which the forecast was made, and the forecast length. We suggest that a site and time-specific optimization of multimodel ensemble skill would increase the potential utility of these forecasts to inform rangeland management decision-making.

Demographic studies suggest that mortality of emerging bunchgrass seedlings limits restoration success across North American cold desert rangelands, but how variation in seedling resilience to ecophysiological stress contributes to this is unclear. We measured light-saturated photosynthetic rate (A_sat), apparent CO₂ assimilation quantum yield (ΦCO₂), and light-adapted PSII yield (Φ_PSII) of seedlings from two native perennial bunchgrasses (Elymus elymoides, Pseudoroegneria spicata) during and in recovery from acute water stress (6% soil moisture). All seedlings of both species survived the 14-d dry-down and recovery, and both had ∼95% reduction in A_sat and ΦCO₂ by day 3 of the dry-down but had divergent recoveries from the acute water stress. E. elymoides took a single day to recover A_sat and ΦCO₂ to prestress levels, while it took P. spicata 6 d to have 50% recovery from acute water stress. Especially notable is that after reduction in Φ_PSII on d 7 of the dry-down, E. elymoides recovered within 1 d at a lower Φ_PSII compared with pretreatment, while P. spicata had an additional 1-d lag in Φ_PSII recovery. These results suggest that E. elymoides (Turkey Lake germplasm) seedlings are more physiologically resilient to acute water stress than P. spicata (Anatone germplasm), which has implications for restoration planning and native plant breeding.

Plant communities in a stable, long-term state with high sagebrush cover and low desirable perennial herbaceous cover and/or relatively high invasive annual cover are widespread across the Great Basin and distinct from areas affected by wildfire. Restoring these areas, collectively called “degraded sagebrush understories,” and preventing future degradation are management challenges that require maintaining desirable levels of sagebrush cover while simultaneously increasing understory perennial abundance and diversity. Defining degradation based on a firm grasp of current and potential vegetation composition is a fundamental aspect of setting restoration goals and selecting methods. Assigning degraded status to any given site is also a considerable challenge in many sagebrush landscapes due to widespread (and long-standing) lack of intact herbaceous plant communities in some landscapes, as well as high interannual variation in herbaceous community composition (particularly cover). In this manuscript, we provide a workflow for defining degraded understories and present a framework for identifying restoration approaches emphasizing the pathways (causes) of degradation in this system, such as historical cultivation, inappropriate grazing, invasive species, and drought, as well as the size and extent of degraded areas. We also describe the relative paucity of well-documented successful restoration approaches for degraded understories, particularly for one-time restoration treatments. This lack of success may be due to lack of propagules, potential competition from sagebrush, invasive species, and/or altered soil conditions. Multiple restoration treatments in specific sequences and/or years may increase success; however, the effectiveness of these techniques is uncertain due to infrequent implementation and rigorous evaluation across a range of environmental conditions. Due to the extent of degraded understories in Great Basin sagebrush ecosystems, meeting biome-level conservation goals will likely require additional research to characterize the types and development pathways of the degraded understories, spatiotemporal recovery or ongoing degradation patterns, and targeted restoration techniques.

Mule deer (Odocoileus hemionus) populations have declined steadily across their geographic range due to a multitude of factors including habitat degradation associated with the encroachment of invasive annual grasses including cheatgrass (Bromus tectorum), medusahead (Taeniatherum caput-medusae), and North Africa grass (Ventenata dubia). These grasses can drive changes in vegetation composition that significantly reduce the quantity and quality of summer mule deer forage. Application of annual grass selective herbicides is a management tool being used in efforts to restore invaded grasslands. We assessed the effect of an imazapic application on mule deer use, home range size, and proportional overlap with treatment areas. We evaluated differences in summer (June−August) use between fifteen 8-ha paired control and treatment plots, comparing responses among pretreatment, 1 yr post treatment, and 2 yr post treatment. Results from tests were statistically insignificant but suggest a weak positive response by mule deer to imazapic-treated areas. Proportional use of treatment plots in the first summer post treatment was 4.4% higher than use of control plots and was greater than pretreatment use of the same plots. In the second summer post application, use of treatment plots decreased and returned to pretreatment levels. Mule deer increased use of treatment plots in alignment with improvements in crude protein and digestible energy content of forage. As annual grasses began reinvading and nutritional quality of forage was no longer higher than the control, use of treatment plots declined and returned to pretreatment levels.

Mineral nutrition deficiencies commonly occur in extensive sheep production systems, yet often coincide with critical production periods of breeding and gestation when quality and quantity of winter range are most limited. Ewe productivity may be limited by clinical and subclinical mineral deficiencies when grazing extensive rangelands during the winter months. The objectives of this study were to utilize fecal meta-barcoding DNA (f.DNA) to estimate dietary composition of ewes by plant morphological group (monocots and dicots), and quantified plant nutritional composition from clipped biomass to estimate adequacy of macro- and micro-minerals of the basal diet across extensively grazed sheep operations. Ewe fecal samples for f.DNA were collected from 19 extensive sheep operations across Wyoming and Colorado, USA, and analyzed at the plant morphological group level to estimate dietary composition as 1) Monocot (≥ 70%), 2) Dicot (≥ 70%), or 3) Mixed (monocot and dicot co-dominated, both proportions < 70%). Pooled forage species nutritional composition within morphological group (monocot vs. dicot) was then multiplied by the proportion of monocotyledonous species or dicotyledonous species and intake estimates of 2% of BW on an 80 kg ewe to estimate macro- and micro-mineral intake. Results from f.DNA indicated 36% of operations were categorized as Monocot (≥ 70% dietary component), 42% Dicot (≥ 70% dietary component), or 21% Mixed. A significant effect of plant morphological group category was observed for CP, Ca, K, Mg, and S (P < 0.05) where dicot dominated rangelands contained higher concentrations of these minerals compared to monocot or mixed monocot-dicot rangelands. Overall, dicot dominated rangelands provided greater macro- and micro-mineral content ultimately meeting more requirements for breeding and gestation than monocot or mixed monocot-dicot rangelands. Therefore, targeted supplementation must be considered for ewes on monocot or mixed monocot-dicot rangelands during winter months that coincide with critical production stages.

Improved techniques are needed to estimate the dietary species composition of grazing animals. The fecal DNA metabarcoding technique has been proposed as a noninvasive method to determine dietary species composition. However, studies suggest that it is more effective to qualitatively estimate species composition of wild and domestic animals than for accurately quantifying diet composition. The technique, using the trnL barcode, was evaluated with 10 individually penned goats, which were fed hand-harvested plant materials that were collected fresh each morning before known amounts of each type of plant materials were fed and completely consumed by the goats. Goats were fed at 3% of their body weight on a DM basis. Broadleaf plant materials fed were Russian olive (Elaeagnus angustifolia), silver buffaloberry (Shepherdia argentea), western snowberry (Symphoricarpos occidentalis), and wormwood sage (Artemisia absinthium) plus a mixture of predominantly smooth bromegrass (Bromus inermis), which also included small amounts of other grasses such as Kentucky bluegrass (Poa pratensis) and forbs such as leafy spurge (Euphorbia esula). Estimates of the dietary composition of the goats were different (P ≤ 0.04) from those of their known dietary composition, except for wormwood sage when expressed on a crude protein basis (P = 0.98), regardless of whether known composition was expressed on a dry matter or crude protein basis. Therefore, we conclude that the fecal DNA metabarcoding technique for estimating the dietary composition of goat diets is useful qualitatively but needs further development to be a better quantitative technique.

Fritillaria imperialis L., an indicator plant species in Iran, is facing threats and its population has declined in recent years. To provide insights into the drivers affecting its loss, this research aims to identify the effects of three groups of factors, including climate, soil, and physiographic variables, on the current and future spatial distributions of F. imperialis. For this purpose, we used five machine learning algorithms as well as an ensemble forecasting of species distribution approach to explain the geographical distributions of the species as a function of these factors. In addition, we used two shared socio-economic pathways scenarios – SSP 1-2.6 and SSP 5-8.5 – to project the future distributions of F. imperialis in 2030, 2050, 2070, and 2090. Based on evaluation indices, area under the ROC curve (AUC) and true skill statistic (TSS), the Random Forest (RF) model generated the strongest prediction of the distribution of F. imperialis (TSS>0.9 and AUC>0.9). No significant difference observed among the three datasets (climate-only variables, climate + physiography variables, and climate + physiography + soil variables) in terms of AUC values. In models using climate + physiography + soil datasets, soil electrical conductivity, clay, and pH emerged as the most important variables affecting the growth and development of F. imperialis while climate factors played a lesser role in its distribution. Future projections revealed different patterns when using the optimistic (SSP 1-2.6) and pessimistic (SSP 5-8.5) socio-economic pathway scenarios and either the climate only or climate + physiography models. The climate + physiography + soil model produced similar prediction patterns for the scenarios. The climate-only models predicted larger areas suitable for crown imperial in the future than did the climate + physiography + soil model. These results emphasize the consideration of factors beyond climate scenarios when modeling biological responses to global warming and regional climate change.

Adaptive multipaddock (AMP) grazing is a form livestock management that uses high stock density, frequent herd rotation, and long adaptive plant recovery periods to produce punctuated disturbances within pastures. This form of livestock management may benefit pasture biodiversity and ecosystem function. Arthropods are key to ecosystem functionality through the fulfillment of many ecological niches in pasture ecosystems like dung burial, pest control, and pollination. However, the effect of AMP grazing on arthropod communities has not been well studied. We assessed the effect of AMP grazing on arthropod community composition. Foliar, soil, and dung arthropod communities were collected from AMP and conventionally grazed (CG) pastures located in the southeastern US. Arthropod abundance, species richness, diversity, and guild composition were compared between grazing treatments. The herbaceous standing plant diversity was recorded in the immediate vicinity of arthropod sampling. AMP grazed pastures exhibited higher foliar arthropod species richness, along with higher foliar and dung guild diversity. The effects of AMP grazing on the arthropod community were likely correlated to changes to the vegetative community resulting from AMP grazing. No differences in pest abundance or species diversity were found between the AMP and CG pastures. This study shows AMP pasture management has a positive effect of arthropod community composition, which is likely to be an important mechanism to facilitating ecosystem services in AMP pastures.

Eastern redcedar (ERC) (Juniperus virginiana L.) encroachment into grassland ecosystems, facilitated by shelterbelt planting and fire suppression threatens the long-term health of the Great Plains grasslands. Goats browse (defoliate and debark) juniper tree trunks and branches. Since ERC do not resprout, trunk girdling may kill the tree, making targeted browsing with goats a potential ERC control tool. However, little field experimentation exists. The objective was to investigate how goats browse ERC of different heights and the impact on tree mortality. A randomized complete block design was used with five sites comprised of four replicate paddocks browsed two consecutive summers. Up to ten ERC in five height classes (< 50, 51–100, 101–150, 151–200, and 201–250 cm) were tagged permanently in each paddock and browsing measurements and forage disappearance were recorded. Juniper height was positively related with debarking (y = 0.12x; R² = 0.29; where x = plant height in cm) and negatively related with defoliation (y = –0.28x + 72.1; R² = 0.39; where x = plant height in cm). Two sites consistently showed that taller trees had more foliage browning (P < 0.001). Thus, since taller trees are more likely debarked, debarking may be related to tree death. On these sites, ERC trees 151–200 cm had more (P < 0.05) browned foliage and higher (P = 0.01) mortality. Sites with more deciduous browse had less debarking and mortality. Therefore, ERC debarking and mortality success with targeted browsing with goats will most likely depend on site plant community composition characteristics where juniper trees should be the only woody component. Targeted browsing with goats could be an effective ERC site pretreatment when integrated with prescribed fire or other control methods.