Rangeland Species Research Articles

Proximate analysis of five plants species in Rangeland enclosures in Khartoum State, Sudan.

Proximate analysis of five plants species in Rangeland enclosures in Khartoum State, Sudan.

Assessing the proximate compositions of indigenous forage species in Yemen's pastoral rangelands.

Plant diversity in southern Yemen is crucial for maintaining rangeland ecosystem functions. This diversity contributes to the resilience of local pastoral communities, by providing essential forage and resources. However, high stocking density has led to the overuse of palatable species, resulting in increased competition for forage. This study evaluates the nutritional value of 25 indigenous forage species from the natural rangelands of Lahij Governorate. Significant variations were observed among the Forage species, with moisture content ranging from 4 to 39.6%, crude protein from 5.5 to 21.4%, non-fiber carbohydrates from 31.8 to 66.4%, crude fiber from 8.3 to 42.65%, and ash content from 9.2 to 34.6%. Clitoria ternatea, Lycium barbarum, Senegalia mellifera, Vigna sinensis, Albizia lebbeck, and Acacia trees with crude protein content higher than 16% showed substantial potential as livestock feed due to their favorable proximate compositions. Incorporating these high-potential species into regular livestock diets could significantly enhance the sustainability and productivity of pastoral systems in southern Yemen, addressing the current fodder shortage.

Modeling the Distribution and Environmental Preferences of the Ladakh Urial in the Arid Himalayas.

Mountains play a crucial role in shaping the climate of an area and subsequently, the environments and species that are suited to those particular conditions. Understanding the relationships between environmental conditions and their influence on the occurrence of a species is necessary to make informed decisions when conserving relevant habitats. This study evaluated and compared the potential for different interactions between climatic variables to describe the environmental preferences and the range of the Ladakh urial, a narrowly distributed sub-species of Ovis vignei, in the arid Himalayas. Species distribution models were created from spatially thinned presence-only occurrence data of 50 locations using a Maximum Entropy (Maxent) model. For this, we subdivided the modeled distribution into environmental categories with varying degrees of suitability. We identified a high cold precipitation to annual precipitation ratio typical of cold desert climates well suited to describe the highest quality environments for urial. The inverse, low warm precipitation to annual precipitation ratio was found to better describe the urial's range at the lower end of potential habitat. In this comparison, we observed that with the exclusion of unsuitable cold steppe habitat with a higher warm precipitation to annual precipitation ratio, we were able to refine the extent of this species range but at a trade-off to the accurate description of high-quality environments. This study demonstrated the strong potential of cold arid climatic conditions to describe the distribution of urial in India, which have implications for identifying important areas for the conservation and management of the species in the high altitude rangelands of Ladakh.

Phenol identification and mapping of rangeland species at laboratory and landscape scales using PRISMA hyperspectral data

ABSTRACT Secondary metabolites have high ecological and economic values. Measuring the amounts of these metabolites in plants through laboratory analysis is time-consuming and expensive. On the other hand, the laboratory results cannot be generalized to a wide area of rangelands with diverse climates, topography, and soil. Therefore, the present study aims to evaluate the potential of PRISMA hyperspectral data to estimate the rangeland phenol concentration at landscape scale in western Isfahan province, Iran. Phenol concentration and spectral signatures were extracted from 42 plant individuals, including Astragalus adscendens, Astragalus verus, Daphne mucronata, Anabasis aphylla, and Phlomis olivieri using laboratory methods and spectroscopy in the range of 350 to 2500 nm. Phenol-sensitive bands were identified by establishing a relationship between phenol concentration and all spectral bands by the Partial Least Square Regression (PLSR) method. The map of phenol spatial changes was then produced with the Bayesian Regularized Artificial Neural Network Model (BRNN), Random Forest (RF), Generalized Linear Model (GAM), Generalized Additive Model (GLM), and Gaussian Process Regression (GPR) in rangelands. The results showed that the phenol concentration in different individuals was between 3.65 and 20.13 (mgGAE/gDW), and species spectral absorptions ranged from 1.650 to 1.660. The very high coefficient of determination of phenol concentration with spectral data (R2 = 0.94) confirmed the use of these data in phenol mapping at the landscape scale. The maximum estimated phenol concentration by GLM, GAM, RF, BRNN, and GPR models was 36.40, 26.76, 18.07, 22.74, and 32.92 GAE/g DW, respectively; which RF model had the highest (R2 = 0.955) and GLM had the lowest accuracy (R2 = 0.816). The findings show that hyperspectral data can estimate secondary metabolites at the landscape scale and can supplement laboratory methods in managing rangeland plants.

Using multisource remotely sensed data and cloud computing approaches to map non-native species in the semi-arid savannah rangelands of Mpumalanga, South Africa

ABSTRACT Semi-arid savannah rangelands are diverse environments (in terms of species) that play an important role in sustaining biodiversity and providing ecosystem services. However, the emergence of non-native species, as well as bush encroachment, are currently threatening these (semi-arid rangeland and grassland) ecosystems. The purpose of this study was therefore to map and quantify the spatial extents of non-native woody vegetation in the Kruger National Park and surrounding communal areas in Mpumalanga, South Africa. To achieve the study’s objectives, Sentinel-1 and Sentinel-2 remotely sensed data were combined and analysed using the random forest (RF) machine-learning algorithm in the Google Earth Engine (GEE) cloud computing platform. Specifically, spectral bands and selected spectral derivatives, e.g. enhanced vegetation index (EVI2), normalized difference moisture index (NDMI) and normalized difference phenology index (NDPI) were computed and used to map non-native woody vegetation. After optimizing the model combination, the classification outputs had an overall accuracy of 70%, with class accuracies such as producer’s accuracy (PA) and user’s accuracy (UA) ranging from 67% to 95%.It was shown in this study that using Sentinel-2 and Sentinel-1 data together led to better overall accuracy than using single sensor models when mapping semi-arid savannah rangelands. It was also found in this study that the overall classification accuracy of non-native (invasive) species using optical sensors was higher than in previous studies. On a free platform like GEE, it was possible to utilize advanced classification processes to fully exploit the informative content of Sentinel-1 and Sentinel-2 data.

Influence of different temperatures on seedling growth and development of Calobota sericea, a semi-arid rangeland species of South Africa

This study determined how temperature affected the early growth of seedlings of Calobota sericea (Thunb.) Boatwr. & B.-E.van Wyk. One-month-old C. sericea seedlings were grown at constant temperatures of 2.5, 5, 10 and 20 °C for 30 days. After 30 days the plants were removed and shoot length, root length, stem thickness, number of leaves, middle leaflet length, leaf width, petiole length, shoot fresh and dry mass, and cell membrane stability through electrolyte leakage from the leaves, and shoot water content were measured. Results showed that the optimum temperature for C. sericea seedling growth was approximately 10 °C. Significant seedling mortality was observed at 20 °C, while no mortality was observed between 2.5 and 5 °C, and less than 4% of seedlings died at 10 °C. The majority of measured morphological variables in this study increased significantly from 2.5 °C and 5 °C, reaching a maximum at 10 °C before decreasing significantly at 20 °C. Electrolyte leakage from leaves was significantly more at 2.5 °C and at 20 °C, suggesting that seedlings were more stressed at these temperatures. In conclusion, even though C. sericea has a wide optimum germination temperature range, early seedling growth requires a narrow temperature range for optimum growth and development.

DNA barcoding and morphological identification of Astragalus in Iran: Advantages to molecular approach

Astragalus is a crucial forage plant in the rangelands of northeastern Iran. However, identifying different species of Astragalus can be challenging due to their overlapping morphological features. In this study, we aimed to determine the relationships between 12 Astragalus species using both morphological and molecular traits. We also evaluated the effectiveness of DNA barcoding as a tool for identifying rangeland species of Astragalus in Northeast Iran. We examined five DNA barcodes, including three cpDNA regions (trnH-psbA, rpl32-trnL(UAG), and matK) and two nuclear sequences (ITS and ETS). We found that the plastid markers (rpl32-trnL(UAG, matK) were the most effective in differentiating between species. We also found that morphological data, as represented by the Neighbor-Net network and UPGMA dendrogram, had the potential to separate Astragalus species. We identified matK as the best and most accurate marker for barcoding, as trnH-psbA had some defects due to sequence size and alignment issues. Our study highlights the importance of using barcoding for quick and accurate recognition of plant species and shows the plastid markers were the most effective in differentiating between species.

Phytochemicals, Essential Oils Composition and Antioxidant Activity of Astragalus spp., Phlomis olivieri and Daphne mucronata in Habitats of Central Iran.

This study evaluated several secondary metabolites, essential oils (EOs) compositions, and antioxidant activity in four medicinal plants that originated in Isfahan rangelands. The species were Astragalus verus, Astragalus adscendens, Daphne mucronata, and Phlomis olivieri. Thirty-two genotypes of these species were evaluated for different biochemical traits. Based on the evaluation of EOs compounds, GC/MS analysis revealed the total number of identified compounds. These compounds were 25, 22, 12, and 22 for A. adscendens, A. verus, D. mucronata, and P. olivieri, respectively. The dominant compounds were phthalate (59.88 %) in A. adscendens, phytol (38.02 %) in A. verus, hexanoic acid (32.05 %) in D. mucronata and β-cubebene (30.94 %) in P. olivieri. Phytochemical analysis showed that D. mucronata, A. adscendens, and P. olivieri had the highest total phenolics content (TPC) (18.24 mg gallic acid equivalent/g dry weight), total flavonoids content (5.57 mg QE/g DW), and total anthocyanins content (0.23 mg/g DW), respectively. The highest total chlorophyll (0.27 mg/g DW), total carotenoids (0.03 mg/g DW), and antioxidant activity (71.36 %) were observed in A. adscendens, A. adscendens and A. verus, respectively. Among all genotypes, the highest TPC (20.1 mg GAE/g DW) was observed in genotype 5 of D. mucronata. This study provided new information on the chemical compounds within the distribution range of these ecologically dominant rangeland species in Isfahan province, Iran. The data revealed that superior genotypes from these species are rich in natural antioxidants and bioactive compounds. Thus, they can be used in ethno pharmacological fields, food, and industrial applications.

Identification of Brush Species and Herbicide Effect Assessment in Southern Texas Using an Unoccupied Aerial System (UAS)

Cultivation and grazing since the mid-nineteenth century in Texas has caused dramatic changes in grassland vegetation. Among these changes is the encroachment of native and introduced brush species. The distribution and quantity of brush can affect livestock production and water holding capacity of soil. Still, at the same time, brush can improve carbon sequestration and enhance agritourism and real estate value. The accurate identification of brush species and their distribution over large land tracts are important in developing brush management plans which may include herbicide application decisions. Near-real-time imaging and analyses of brush using an Unoccupied Aerial System (UAS) is a powerful tool to achieve such tasks. The use of multispectral imagery collected by a UAS to estimate the efficacy of herbicide treatment on noxious brush has not been evaluated previously. There has been no previous comparison of band combinations and pixel- and object-based methods to determine the best methodology for discrimination and classification of noxious brush species with Random Forest (RF) classification. In this study, two rangelands in southern Texas with encroachment of huisache (Vachellia farnesianna [L.] Wight & Arn.) and honey mesquite (Prosopis glandulosa Torr. var. glandulosa) were studied. Two study sites were flown with an eBee X fixed-wing to collect UAS images with four bands (Green, Red, Red-Edge, and Near-infrared) and ground truth data points pre- and post-herbicide application to study the herbicide effect on brush. Post-herbicide data were collected one year after herbicide application. Pixel-based and object-based RF classifications were used to identify brush in orthomosaic images generated from UAS images. The classification had an overall accuracy in the range 83–96%, and object-based classification had better results than pixel-based classification since object-based classification had the highest overall accuracy in both sites at 96%. The UAS image was useful for assessing herbicide efficacy by calculating canopy change after herbicide treatment. Different effects of herbicides and application rates on brush defoliation were measured by comparing canopy change in herbicide treatment zones. UAS-derived multispectral imagery can be used to identify brush species in rangelands and aid in objectively assessing the herbicide effect on brush encroachment.

Biomass and Leaf Nutrition Contents of Selected Grass and Legume Species in High Altitude Rangelands of Kashmir Himalaya Valley (Jammu & Kashmir), India.

The yield and nutritional profile of grass and legume species in Kashmir Valley's rangelands are scantly reported. The study area in this paper included three types of sites (grazed, protected, and seed-sown) divided into three circles: northern, central, and southern Kashmir. From each circle, three districts and three villages per district were selected. Most sites showed higher aboveground biomass (AGB) compared to belowground biomass (BGB), which showed low to moderate effects on biomass. The comparison between northern, central, and southern Kashmir regions revealed that AGB (86.74, 78.62, and 75.22 t. ha-1), BGB (52.04, 51.16, and 50.99 t. ha-1), and total biomass yield (138.78, 129.78, and 126.21 t. ha-1) were the highest in central Kashmir region, followed by southern and northern Kashmir regions, respectively. More precisely, AGB and total biomass yield recorded the highest values in the protected sites of the central Kashmir region, whereas BGB scored the highest value in the protected sites of southern Kashmir region. The maximum yield (12.5 t. ha-1) recorded among prominent grasses was attributed to orchard grass, while the highest crude fiber and crude protein contents (34.2% and 10.4%, respectively), were observed for Agrostis grass. The maximum yield and crude fiber content (25.4 t. ha-1 and 22.7%, respectively), among prominent legumes were recorded for red clover. The highest crude protein content (33.2%) was attributed to white clover. Those findings concluded the successful management of Kashmir rangelands in protected sites, resulting in high biomass yields along with the considerable nutritional value of grasses and legumes.

The Influence of Induced Drought Stress on Germination of Cenchrus ciliaris L. and Cenchrus setigerus Vahl.: Implications for Rangeland Restoration in the Arid Desert Environment of Kuwait

Drought impacts in arid desert ecosystems can result in decreased ecosystem productivity and biodiversity. Implementation of restoration projects in arid desert environments is largely dependent on water availability and soil moisture condition. This study investigated the influence of induced drought stress by using polyethylene glycol (PEG-6000) solution on germination viz. Cenchrus ciliaris and Cenchrus setigerus as the important rangeland species. The water stress potential treatments were 0 (control), –0.5 MPa, –1.0 MPa, –1.5 MPa, and –2.0 MPa. The extent of seed germination was severely affected by decreased water stress potential. As drought increased, the percentage of germination decreased in both Cenchrus’ species. The water deficit at –0.5 MPa showed a significant (P < 0.001) reduction in the final germination percentage in the case of C. setigerus and C. ciliaris by 65% and 42.5%, respectively. At –1.0 MPa to –1.5 MPa, changes in intermediate germination were observed in C. ciliaris (from 35% to 17.5%, respectively) and C. setigerus (from 22.5% to 11.25% respectively). Higher levels of water stress (–2.0 MPa) prevented the survival of both species. Understanding the germination strategies of native desert plant species associated with drought stress and identifying favorable conditions during the germination process can be useful for restoration practices and rangeland management actions to improve desert ecosystems and maintain biodiversity.

Rangeland species potential mapping using machine learning algorithms

Documenting habitats of rangeland plant species is required to properly manage rangelands and to understand ecosystem processes. A reliable rangeland species potential map can help managers and policy makers design a sustainable grazing system on rangelands. The aim of this study is to map the plant species in the Qurveh City rangelands, Kurdistan Province, Iran, using state-of-the-art machine learning algorithms, including Support Vector Machine (SVM), Artificial Neural Network (ANN), Naïve Bayes (NB), Bayes Net (BN) and Classification and Regression Tree (CART). A total of 185 rangeland species were used in the study, together with 20 conditioning factors, to build and validate models. The One-R feature section technique and multicollinearity test were used, respectively, to determine the most important factors and correlations between them. Model validation was performed using sensitivity, specificity, accuracy, F1-measure, Matthews correlation coefficient (MCC), Kappa, root mean square error (RMSE), and area under the receiver operating characteristic curve (AUC). Results showed that topographic wetness index (TWI), slope angle, elevation, soil phosphorus and soil potassium were the five most important factors to increase the rangeland plants habitat suitability. The Naïve Bayes algorithm (AUC = 0.782) had the highest performance and prediction accuracy and best consistency across the species in the investigated rangeland, followed by the SVM (AUC = 0.763), ANN (AUC = 0.762), CART (AUC = 0.627), and BN (AUC = 0.617) models.

Superabsorbent Polymer Use in Rangeland Restoration: Glasshouse Trials

Post-disturbance rangeland restoration efforts are often thwarted due to soil moisture deficits. Superabsorbent polymers (SAPs) absorb hundreds of times their weight in water, increasing soil moisture when the SAP is mixed with soil. The objective of this study was to evaluate banded SAPs under the soil surface to increase plant available water and thus seedling establishment for perennial rangeland species during restoration efforts. Five glasshouse experiments with two rangeland perennial grass species, bottlebrush squirreltail (Elymus elymoides) or Siberian wheatgrass (Agropyron fragile), were conducted. Treatments varied, including SAP rates ranging from 11–3000 kg ha−1 with placement mostly banded at depths extending from the surface up to a 15 cm depth. Generally, SAPs increased soil moisture at all rates and depths for up to 49 days. However, rates ≥ 750 kg ha−1 caused the soil to swell and crack, potentially hastening soil drying later in the season. Seedling longevity was increased up to 12 days, especially at the high SAP band rate of 3000 kg ha−1 when the band was 8 or 15 cm deep. Further work is needed to verify banded SAP rates and placement depths in the field, ascertain conditions to reduce soil displacement, and evaluate benefits across species.

Land use and dingo baiting are correlated withthe density of kangaroos in rangeland systems.

Rangelands worldwide have been subject to broadscale modification, such as widespread predator control, introduction of permanent livestock water and altered vegetation to improve grazing. In Australia, these landscape changes have resulted in kangaroos (i.e. large macropods) populations increasing over the past 200 years. Kangaroos are a key contributor to total grazing pressure and in conjunction with livestock and feral herbivores have been linked to land degradation. We used 22 years of aerial survey data to investigate whether the density of 3 macropod species in the southern rangelands of Western Australia was associated with: (i) land use, including type of livestock, total livestock, density of feral goats, type of land tenure, and kangaroo commercial harvest effort; (ii) predator management, including permitted dingo control effort, estimated dingo abundance, and presence of the State Barrier Fence (a dingo exclusion fence); and (iii) environmental variables: ruggedness, rainfall, fractional cover, and total standing dry matter. Red kangaroos (Osphranter rufus) were most abundant in flat, open vegetation, on pastoral land, where area permitted for dingo control was high, and numbers were positively associated with antecedent rainfall with a 12-month delay. Western grey kangaroos (Macropus fuliginosus) were most abundant on flat, agricultural land, but less abundant in areas with high permitted dingo control. Euros (Osphranter robustus) were most abundant in rugged pastoral land with open vegetation, where permitted dingo control was high. While environmental variables are key drivers of landscape productivity and kangaroo populations, anthropogenic factors such as land use and permitted dingo control are strongly associated with kangaroo abundance.

Identification and nutrients composition of different rangeland species (grasses, herbs, shrubs, and trees) grazed by small and large ruminants in Balochistan: Kharan region

Identification and nutrients composition of different rangeland species (grasses, herbs, shrubs, and trees) grazed by small and large ruminants in Balochistan: Kharan region

Heterogeneity-Based Management Restores Diversity and Alters Vegetation Structure without Decreasing Invasive Grasses in Working Mixed-Grass Prairie

Non-native plants can reduce grassland biodiversity, degrade wildlife habitat, and threaten rural livelihoods. Management can be costly, and the successful eradication of undesirable species does not guarantee the restoration of ecosystem service delivery. An alternative to the eradication of invasive species in rangelands is to target the restoration of diversity and heterogeneous plant structure, which have direct links to ecosystem function. In this study, we evaluate patch-burn grazing (PBG) with one and two fires per year and variably stocked rotational grazing in Poa pratensis- and Bromus inermis-invaded grasslands using traditional (cover) and process-based (diversity and vegetation structural heterogeneity) frameworks in central North Dakota, USA. Within 3–4 years of initiating management, we found little evidence of decreased Poa pratensis and Bromus inermis cover compared to continuous grazing (Poa pratensis F3,12 = 0.662, p = 0.59; Bromus inermis F3,12 = 0.13, p = 0.13). However, beta diversity increased over time in all treatments compared to continuous grazing (tPBG1 = 2.71, tPBG2 = 3.45, tRotational = 3.72), and variably stocked rotational treatments had greater increases in spatial heterogeneity in litter depth and vegetation structure than continuously grazed pastures (tvisual obstruction= 2.42, p = 0.03; tlitter depth = 2.59, p = 0.02) over the same time period. Alternative frameworks that promote grassland diversity and heterogeneity support the restoration of ecological services and processes in invaded grasslands.

High Altitude Rangelands Invasion by Non-Palatable Plant Species in the Perception of Yak Herders

The biological and socio-ecological dimensions of alpine rangelands degradation by invasive species have been considered in a field survey conducted in two yaks (Bos grunniens) rearing areas i.e., Langtang National Park (LNP) and Kanchanjunga Conservation Area (KCA). Data were collected by herder’s interview using the well-prepared and pretested set of questionnaires (60), followed by a focus group discussion (FGD) and key informants survey (KIS) each five at each site by following a set of checklists. There was a common perception about the invasive species among the herders in the study sites. The Rumex nepalensis was the most invasive species reported (75% of the respondents) at altitudes up to 3000 m in the KCA, while it was additionally with Eupatorium adenophorum (60%) in the LNP, while the Lyonia and Juniperus were the common invasive species in both sites. Altogether, twelve plant species were reported as invasive and non-palatable species from various botanical groups were indifferent to the changes made by invasive species in rangelands soil characteristics but gave well insight into the declining productivity of grasslands and herbage productivity and quality. Herders established bush clearance and slash and burn agriculture in rangelands as traditional adaptation measures to control the invasive species. Mapping of risk zones of invasive and alien species in the alpine rangelands is necessary across the alpine rangelands of Nepal and a long-term monitoring framework is desirable to confirm the herder's information on invasive alpine species of Nepalese Himalayas.

Trade‐offs between utility‐scale solar development and ungulates on western rangelands

Utility‐scale solar energy (USSE) has become an efficient and cost‐effective form of renewable energy, with an expanding footprint into rangelands that provide important habitat for many wild ungulate populations. Using global positioning system data collected before and after construction, we documented the potential impacts of USSE on pronghorn (Antilocapra americana), including direct habitat loss, indirect habitat loss, and barrier effects to both resident and migratory population segments. Our case study highlights the challenges that USSE poses to ungulate conservation, including (1) impermeable security fencing that blocks access to and reduces connectivity between formerly available habitats, and (2) the lack of guidelines for minimizing USSE impacts on ungulates. Improved siting and ungulate‐specific best management practices would help to minimize habitat loss and retain landscape connectivity. Ungulate biodiversity and ecosystem services (for example, services provided by long‐distance migratory species) in arid rangelands are important considerations when balancing the global benefits of renewable energy with local wildlife impacts.

Comparison of Cultivated and Wild Relatives of Several Forage Species in Mixed Rangeland Based on Some Nutritional Characteristics

Cultivated forage species may have higher nutrients contents (NC) and forage quality indicators (FQI) than their wild relatives. Nine forage samples collected five times from a mixed rangeland and an experimental field during two consecutive years was analysed for ash, crude protein (CP), ether extract (EE) and neutral detergent (NDF) and acid detergent (ADF) fibres. Then, their FQI such as digestible dry matter (DDM), dry matter intake (DMI), metabolizable energy (ME) and relative forage quality (RFQ) were calculated. Data were performed in a linear model with fixed effects (forage plant type [PT] and species [PS]) to NC and FQI, and subjected to hierarchical two-way clustering analysis. Cultivated and wilds relatives varied in CP (12.0-18.9% and 8.8-23.3%), ADF (20.9-33.1% and 39.3-73.5%) and NDF (37.2-61.6% and 26.7-46.1%) contents and ME (8.7-9.7 MJ kg-1 DM and 7.0-9.6 MJ kg-1 DM) and RFQ (98.8-186.7 and 74.6-161.7) values. There were interactions between PT and PS for all NC and FQI, except for CP and EE contents. In general, the CP, EE, ADF, ME and RFQ of cultivars were higher, whereas NDF was lower than those of the wilds. The most notable differences (NDF, ADF and RFQ) between the PT represented the differences in nutritional traits based on the clustering analysis. The cultivated and wilds relatives are comprised of NC and FQI that respond differently under same circumstances.

Ruminal Digestibility and In-Vitro Methane Emissions of Native Plant Species in Subtropical Rangelands

Enteric methane (CH4) emissions from livestock represent a significant agricultural source of greenhouse gas worldwide. The aim of this study was to determine the effect of plant species and season on nutritional value and methanogenic potential of Florida native rangelands. Treatments consisted of a 4 × 2 factorial arrangement of plant species (creeping bluestem [Schizachyrium scoparium var. stoloniferum {Nash} Wipff], lopsided Indiangrass [Sorghastrum secundum {Elliott} Nash], maidencane [Panicum hemitomon Schult.], and saw-palmetto [Serenoa repens {W. Bartram} Small]) and season (summer or autumn) distributed in a randomized complete block design with four replicates. Samples were analyzed for crude protein (CP), neutral detergent fiber, in-vitro CH4 production, and in-situ ruminal digestibility. The greatest digestive matter (DM) effective degradability was observed in the summer for creeping bluestem (422 g kg−1), followed by lopsided Indiangrass (379 g kg−1), maidencane (380 g kg−1), and saw-palmetto (250 g kg−1). The DM effective degradability decreased from summer to autumn for all species, except saw-palmetto. Maidencane had the greatest CP effective degradability in the summer (491 g kg−1), followed by lopsided Indiangrass (350 g kg−1), creeping bluestem (279 g kg−1), and saw-palmetto (170 g kg−1); however, lopsided Indiangrass and maidencane decreased CP effective degradability from summer to autumn. There was no difference in CH4 production among creeping lopsided Indiangrass and maidencane (mean of 7 mg g−1 DM), and saw-palmetto had the least CH4 emissions (2 mg g−1 DM). Grazing lopsided Indiangrass and maidencane in the summer was an effective strategy to optimize the use of native plant species with greater nutrient digestibility than autumn. Management practices intended to increase rangeland productivity, and the proportion of native grass species relative to saw-palmetto are expected to increase CH4 production. Further research is warranted to evaluate the impacts on rangeland management on animal performance and greenhouse gas balance.