Aboveground Herbaceous Biomass Research Articles

Imaging Spectroscopy‐Based Estimation of Aboveground Biomass in Louisiana's Coastal Wetlands: Toward Consistent Spectroscopic Retrievals Across Atmospheric States

AbstractDeveloping accurate landscape‐scale aboveground biomass (AGB) maps is critical to understanding coastal deltaic wetland resilience, as AGB influences stability and elevation dynamics in herbaceous wetlands. Here we used AVIRIS‐NG imaging spectrometer (or “hyperspectral”) data from NASA's 2021 Delta‐X mission in coastal Louisiana to map seasonal changes in herbaceous AGB across two deltaic basins with contrasting sediment delivery and hydrologic regimes: the Atchafalaya (active) and Terrebonne (inactive). We assessed the impact of atmospheric effects on our retrievals, as high water vapor content in August 2021 caused significant noise in the 880–1,000 and 1,080–1,200 nm near‐infrared (NIR) wavelengths. We hypothesized that correcting these wavelengths with our conditional Gaussian interpolation algorithm would improve AGB estimates due to their association with plant canopy water content. We empirically assessed the performance of the corrected spectra on AGB estimates using Partial Least Squares Regression (PLSR), finding that the corrected NIR bands attained high variable importance and reduced estimation errors. Our Random Forest regression approach based on the corrected spectra attained equivalent error metrics via leave‐one‐out‐cross‐validation as the PLSR models (R2 = 0.43, mean absolute error = 257.3 g/m2) while greatly improving the AGB maps' visual quality, having better captured variability while reducing noise and discontinuities in AGB estimates across flightlines. The maps show differing seasonal growth, with the Atchafalaya and Terrebonne Basins' AGB increasing from means of 4.3–9.4 and 4.6–8.9 Mg/ha, respectively. We demonstrated that imaging spectroscopy can be applied to assess herbaceous biomass stocks, growth patterns, and resilience in coastal ecosystems.

Grazing intensity effects on rangeland condition and tree diversity in Afar, northeastern Ethiopia

This study assessed the effects of different grazing pressures (light, moderate and heavy) on rangeland condition and woody species diversity in northeastern Ethiopia. Rangeland condition was analyzed using common protocols for the assessment of semi-arid rangelands. A total of 4 grasses, 5 herbs, 1 sedge and 14 tree and/or shrub species were identified. Results show that grazing intensity had detrimental effects on condition of the rangeland, and caused undesirable changes in herbaceous species composition. The contribution of undesirable plants to herbaceous aboveground biomass was particularly high (40 %) compared to the 30 % contributed by highly desirable species. Nearly all measures of range condition were negatively affected by grazing. Grass composition, number of seedlings and age distribution, basal and litter cover, soil erosion and compaction decreased significantly as grazing intensity increased. Species richness and diversity (Hill numbers) of woody plants were reduced significantly by grazing. The overall condition of the rangeland was generally poor. The pastoralists perceived that recurring droughts, heavy continuous grazing and inappropriate management interventions, and bush encroachment were the main contributing factors that led to overgrazing and rangeland deterioration in the area. In conclusion, our study shows that livestock grazing in northeastern Ethiopia degrade range condition and woody vegetation, and its effects are sever under moderate and heavy grazing. Management measures such as resting of the rangelands preferably with stock exclusions for 6–12 months or protecting heavily degraded or sensitive areas from livestock activity and reseeding may be the viable options to mitigate declines in range conditions.

Spatial Variability in Salt Marsh Drainage Controlled by Small Scale Topography

AbstractWater movement in coastal wetlands is affected by spatial differences in topography and vegetation characteristics as well as by complex hydrological processes operating at different time scales. Traditionally, numerical models have been used to explore the hydrodynamics of these valuable ecosystems. However, we still do not know how well such models simulate water‐level fluctuations beneath the vegetation canopy since we lack extensive field data to test the model results against observations. This study utilizes remotely sensed images of sub‐canopy water‐level change to understand how marshes drain water during falling tides. We employ rapid repeat interferometric observations from the NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar instrument to analyze the spatial variability in water‐level change within a complex of marshes in Terrebonne Bay, Louisiana. We also used maps of herbaceous aboveground biomass derived from the Airborne Visible/Infrared Imaging Spectrometer‐Next Generation to evaluate vegetation contribution to such variability. This study reveals that the distribution of water‐level change under salt marsh canopies is strongly influenced by the presence of small geomorphic features (<10 m) in the marsh landscape (i.e., levees, tidal channels), whereas vegetation plays a minor role in retaining water on the platform. This new type of high‐resolution remote sensing data offers the opportunity to study the feedback between hydrodynamics, topography and biology throughout wetlands at an unprecedented spatial resolution and test the capability of numerical models to reproduce such patterns. Our results are essential for predicting the vulnerability of these delicate environments to climate change.

Where There's Smoke, There's Fuel: Dynamic Vegetation Data Improve Predictions of Wildfire Hazard in the Great Basin

Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, nonforested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32-yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (> 405 ha) wildfire in the Great Basin based on fine-scale annual and 16-d estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-1-yr-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the past 3 decades driven by widespread changes in fine fuel characteristics.

Estimating herbaceous aboveground biomass in Sahelian rangelands using Structure from Motion data collected on the ground and by UAV.

Herbaceous aboveground biomass (HAB) is a key indicator of grassland vegetation and indirect estimation tools, such as remote sensing imagery, increase the potential for covering larger areas in a timely and cost‐efficient way. Structure from Motion (SfM) is an image analysis process that can create a variety of 3D spatial models as well as 2D orthomosaics from a set of images. Computed from Unmanned Aerial Vehicle (UAV) and ground camera measurements, the SfM potential to estimate the herbaceous aboveground biomass in Sahelian rangelands was tested in this study. Both UAV and ground camera recordings were used at three different scales: temporal, landscape, and national (across Senegal). All images were processed using PIX4D software (photogrammetry software) and were used to extract vegetation indices and heights. A random forest algorithm was used to estimate the HAB and the average estimation errors were around 150 g m−² for fresh mass (20% relative error) and 60 g m−² for dry mass (around 25% error). A comparison between different datasets revealed that the estimates based on camera data were slightly more accurate than those from UAV data. It was also found that combining datasets across scales for the same type of tool (UAV or camera) could be a useful option for monitoring HAB in Sahelian rangelands or in other grassy ecosystems.

Annual and 16-Day Rangeland Production Estimates for the Western United States

Rangeland production is a foundational ecosystem service and resource on which livestock, wildlife, and people depend. Capitalizing on recent advancements in the use of remote sensing data across rangelands, we provide estimates of herbaceous rangeland production from 1986 to 2019 at 16-d and annual time steps and 30-m resolution across the western United States. A factorial comparison of this dataset and three national scale datasets is presented, and we highlight a multiple-lines-of-evidence approach when using production estimates in decision making. Herbaceous aboveground biomass at this scale and resolution provides critical information applicable for management and decision making, particularly in the face of annual grass invasion and woody encroachment of rangeland systems. These readily available data remove analytical and technological barriers allowing immediate utilization for monitoring and management.

Overcoming an “irreversible” threshold: A 15-year fire experiment

A key pursuit in contemporary ecology is to differentiate regime shifts that are truly irreversible from those that are hysteretic. Many ecological regime shifts have been labeled as irreversible without exploring the full range of variability in stabilizing feedbacks that have the potential to drive an ecological regime shift back towards a desirable ecological regime. Removing fire from grasslands can drive a regime shift to juniper woodlands that cannot be reversed using typical fire frequency and intensity thresholds, and has thus been considered irreversible. This study uses a unique, long-term experimental fire landscape co-dominated by grassland and closed-canopy juniper woodland to determine whether extreme fire can shift a juniper woodland regime back to grassland dominance using aboveground herbaceous biomass as an indicator of regime identity. We use a space-for-time substitute to quantify herbaceous biomass following extreme fire in juniper woodland up to 15 years post-fire and compare these with (i) 15 years of adjacent grassland recovery post-fire, (ii) unburned closed-canopy juniper woodland reference sites and (iii) unburned grassland reference sites. Our results show grassland dominance rapidly emerges following fires that operate above typical fire intensity thresholds, indicating that grassland-juniper woodlands regimes are hysteretic rather than irreversible. One year following fire, total herbaceous biomass in burned juniper stands was comparable to grasslands sites, having increased from 5 ± 3 g m−2 to 142 ± 42 g m−2 (+2785 ± 812 percent). Herbaceous dominance in juniper stands continued to persist 15-years after initial treatment, reaching a maximum of 337 ± 42 g m−2 eight years post-fire. In juniper encroached grasslands, fires that operate above typical fire intensity thresholds can provide an effective method to reverse juniper woodland regime shifts. This has major implications for regions where juniper encroachment threatens rancher-based economies and grassland biodiversity and provides an example of how to operationalize resilience theory to disentangle irreversible thresholds from hysteretic system behavior.

Diverse and divergent influences of phenology on herbaceous aboveground biomass across the Tibetan Plateau alpine grasslands

Indirect influences of phenology on productivity (e.g., phenology-functional traits-productivity) could exist due to close associations between phenology and plant functional traits, which may further result in the divergent responses of vegetation biomass to phenology among plant functional groups (PFGs). Here, we introduced functional traits (i.e., plant height and growth rate) to analyse the influences of phenology on aboveground biomass (AGB) of two symbiotic PFGs based on 19-year in-situ observational data for plant phenology at 7 sites across the Tibetan Plateau alpine grasslands. The vegetative growth phase (VGP) and reproductive growth phase (RGP) were calculated according to the observed green-up date, first flowering date and first fruit-ripening date. The commonality analysis and structural equation modelling were applied to explore the paths and degrees of phenological influence on AGB. The results showed that the phenological influences on herbaceous AGB included both direct (“phenology-AGB”) and indirect paths (“phenology-functional traits-AGB”) and differed between two PFGs. Phenological metrics, especially VGP, were the key factors driving the adjustment (path coefficients |w| = 0.19 – 0.67), although maximum plant height (Hmax) contributed to the most to the AGB (|w| = 0.78). Specifically, the grasses had two indirect phenological influence paths on AGB, while the sedges had multiple direct and indirect influence paths. Comparing the differences in phenology and functional traits between two PFGs, our study implied that grasses may tend to preferentially adjust vegetative (stem) growth via phenology, while sedges may tend to preferentially adjust root and reproductive growth via phenology, which could be relevant to the differences in the synthesis, accumulation, allocation, and decomposition of organic matter in diverse organs and the growth and reproduction strategies, competition and symbiosis of different PFGs.

Spatial distribution of fine root biomass in a remnant Eucalyptus tereticornis woodland in Eastern Australia

In forests, the majority of fine roots are located within the upper soil horizons, and fine root biomass decreases with depth. We evaluated spatial patterns in the distribution of fine root biomass and determined relationships with soil properties and vegetation structure in a Eucalyptus tereticornis woodland in East Australia. Fine root biomass (0–50 cm depth) was 678 (± 96.9) g m−2 and decreased exponentially with depth. Total fine root biomass was positively related to aboveground herbaceous biomass and increased with increasing proximity to larger trees, reflecting contributions from both herbaceous understorey plants and mature trees. Plants produced more fine roots in soil patches with lower organic matter content, possibly as a functional response to increase acquisition of essential nutrients in more nutrient-depleted soils. Aboveground plant attributes were more important predictors of fine roots in the shallowest layer, while water availability was a stronger predictor of fine root biomass in deeper layers, likely reflecting the harsh climatic conditions prior to sampling. Fine roots represent an important gap in many ecosystem models despite being key for biogeochemical cycling. Here, we showed that the spatial patterns of fine root biomass can be inferred from soil and vegetation characteristics across remnant Australian Eucalyptus woodlands.

Vegetation Responses to Fixed Stocking Densities in Highly Variable Montane Pastures in the Chinese Altay

Variability in aboveground herbaceous biomass and its quality were studied in response to three different stocking densities during a 2-yr grazing experiment with sheep on a montane summer pasture in the Chinese Altay. We determined herbaceous cover and aboveground biomass in 16 paddocks of 0.25 ha each. Vegetation cover showed high spatial variation, prompting us to implement a randomized block design. Forage intake of one male sheep per paddock was quantified four times per grazing season by collection of total feces and estimation of diet digestibility. Sheep weight was recorded every 3 wk. Aboveground herbaceous dry mass (DM) was characterized by pronounced annual variation. Biomass quality declined with progressing season and increasing sheep density. Daily organic matter intake per sheep ranged from 0.7 to 1.4 kg, which was paralleled by a biomass removal of 710−1 560 kg DM/ha at densities of 8−24 sheep/ha. At 8 sheep/ha, animals gained weight throughout each grazing period, whereas weight losses of 40−100 g/d occurred at higher densities. These results challenge the presently followed concept of a fixed stocking density for summer pastures in Altay Prefecture, Xinjian, China. Such practice may result in low herbage allowances and thus deficient sheep nutrition in one year, as well as underutilization of forage resources in another. Flexible adjustment of stocking densities is also advisable for montane pastures where spatiotemporal variability, although less pronounced than in desert steppes of the Altay foothills, is nonetheless highly relevant.

Cascading effects of mammalian herbivores on ground-dwelling arthropods: Variable responses across arthropod groups, habitats and years.

Large mammalian herbivores are well known to shape the structure and function of ecosystems world-wide, and these effects can in turn cascade through systems to indirectly influence other animal species. A wealth of studies has explored the effects of large mammals on arthropods, but to date they have reported such widely varying results that generalizations have been elusive. Three factors are likely drivers of this variability: the widely varying life-history characteristics of different arthropod groups, the highly variable landscapes that mammalian herbivores commonly inhabit and temporal variation in environmental conditions. Here, we use an 18-year-old exclosure experiment stratified across three distinct coastal prairie habitats in northern California to address the effects of a reintroduced mammalian herbivore, tule elk (Cervus canadensis nannodes) on the composition, richness and abundance of ground-dwelling arthropods over two years with very different precipitation regimes. We found that elk shifted the composition of arthropod communities, increasing the abundance of ants, beetles, spiders and mites, decreasing the abundance of woodlice and bristletails in some but not all habitats types, and having no effect on the abundance of bugs, crickets and springtails. Elk also increased richness and changed the composition of ant genera and beetle morpho-species. Interestingly, the effects of elk on arthropod composition, richness and abundance varied little between years, despite very different precipitation levels, biomass accumulation and thatch height. Elk reduced shrub cover, above-ground herbaceous biomass and thatch height and increased soil compaction, and these changes predicted the abundance and richness of arthropods, although taxonomic groups varied in their responses, presumably due to differences in environmental requirements. Synthesis. Our research highlights the importance of using long-term experiments to assess the cascading effects of large herbivores on the composition of grounddwelling arthropod communities and to identify the mechanisms that indirectly shape arthropod responses to herbivores among variable habitats and years in order to develop a greater understanding of the variable responses of arthropods to large mammalian herbivores.

Interaction of livestock grazing and rainfall manipulation enhances herbaceous species diversity and aboveground biomass in a humid savanna.

Understanding of the interaction of livestock grazing and rainfall variability may aid in predicting the patterns of herbaceous species diversity and biomass production. We manipulated the amount of ambient rainfall received in grazed and ungrazed savanna in Lambwe Valley-Kenya. The combined influence of livestock grazing and rainfall on soil moisture, herbaceous species diversity, and aboveground biomass patterns was assessed. We used the number of species (S), Margalef's richness index (Dmg), Shannon index of diversity (H), and Pileou's index of evenness (J) to analyze the herbaceous community structure. S, Dmg, H and J were higher under grazing whereas volumetric soil water contents (VWC) and aboveground biomass (AGB) decreased with grazing. Decreasing (50%) or increasing (150%) the ambient rainfall by 50% lowered species richness and diversity. Seasonality in rainfall influenced the variation in VWC, S, Dmg, H, and AGB but not J (p = 0.43). Overall, Dmg declined with increasing VWC. However, the AGB and Dmg mediated the response of H and J to the changes in VWC. The highest H occurred at AGB range of 400-800 gm-2. We attribute the lower diversity in the ungrazed plots to the dominance (relative abundance > 70%) of Hyparrhenia fillipendulla (Hochst) Stapf. and Brachiaria decumbens Stapf. Grazing exclusion, which controls AGB, hindered the coexistence among species due to the competitive advantage in resource utilization by the more dominant species. Our findings highlight the implication of livestock grazing and rainfall variability in maintaining higher diversity and aboveground biomass production in the herbaceous layer community for sustainable ecosystem management.

Growing seasonal characteristics of soil and plants control the temporal patterns of bacterial communities following afforestation

Soil microbial communities are closely associated with aboveground plant communities and soil properties. This study explored the dynamics of soil bacterial communities during the plant growing season and their interaction with soil carbon and nitrogen, physicochemical properties, plant biomass and diversity following afforestation. The study investigated afforested lands containing Robinia pseudoacacia L (RP) and Caragana korshinskii Kom (CK), as well as abandoned land (AL) and farmland (FL) in the Loess Hilly Region of northern China. After establishment on former FL for 40 years, the Richness and Shannon's index, above-ground herbaceous biomass (AGB) and below-ground biomass (BGB) in RP and CK increased by 0.5, 0.1, 1.2 and 1.7 times, respectively, compared with AL. Additionally, the soil organic carbon (SOC), total nitrogen (TN), dissolved organic carbon/nitrogen (DOC/N) and microbial biomass carbon/nitrogen (MBC/N) increased by 1.7, 1.9, 0.8 and 2.5 times, respectively, while the soil bacterial abundance and alpha diversity (Shannon index) increased by 4.7% and 2.0% compared with FL. During the growing season, the soil carbon and nitrogen content was higher in August or October than in April or June. Particularly, the AGB, DOC and MBC showed a temporal pattern of normal distribution that was 36.7%, 48.2% and 74.9% higher in August than the rest of the study period. The BGB also increased by 123.5% in October compared with June in all study areas. The soil bacterial abundance in afforested lands was also higher in October, and beta bacterial diversity (Principal coordinates analysis plots: PCoA) was greater in June and August than in April and October. The dominant bacterial taxa, Proteobacteria and Bacteroidetes, were significantly higher in afforested lands than in FL, and Proteobacteria increased from April to October, while Actinobacteria and Acidobacteria peaked in June or August. These seasonal changes in the soil bacterial community were significantly correlated with carbon and nitrogen levels of soil and plant biomass, especially with DOC and BGB. Additionally, soil variables explained 41.2% of the total variation in bacterial-dominant phyla, while plant biomass only explained 20.2% of it, which indicates that soil properties are more important controlling factors of the bacterial community than plant biomass. In conclusion, soil variables change seasonally, which drives the composition and diversity of the soil bacterial community to exhibit a temporal pattern over the growing season after return of AL to forest.

Estimating above ground biomass as an indicator of carbon storage in vegetated wetlands of the grassland biome of South Africa

Wetlands store higher carbon content relative to other terrestrial ecosystems, despite the small extent they occupy. The increase in temperature and changes in rainfall pattern may negatively affect their extent and condition, and thus the process of carbon accumulation in wetlands. The introduction of the Sentinel series (S1 and S2) and WorldView space-borne sensors (WV3) have enabled monitoring of herbaceous above ground biomass (AGB) in small and narrow wetlands in semi-arid areas. The objective of this study was to assess (i) the capabilities of the high to moderate resolution sensors such as WV3, S1A and S2A in estimating herbaceous AGB of vegetated wetlands using SAR backscatter, optical reflectance bands, vegetation spectral indices (including Leaf Area Index or LAI measurements) and band ratio datasets and (ii) whether significant differences exists between the AGB ranges of wetland and surrounding dryland vegetation. A bootstrapped Random Forest modelling approach, with variable importance selection, was utilised which incorporated ground collected grass AGB for model calibration and validation. WorldView-3 (WV3) yielded the highest AGB prediction accuracies (R2 = 0.63 and RMSE = 169.28 g/m2) regardless of the incorporation of bands only, indices only or the combination of bands and indices. In general, the optical sensors yielded higher modelling accuracies (improvement in R2 of 0.04-0.07 and RMSE of 11.48–17.28 g/m2) than the single Synthetic Aperture Radar (SAR) sensor but this was marginal depending on the scenario. Incorporating Sentinel 1A (S1) dual polarisation channels and Sentinel 2A (S2) reflectance bands, in particular, yielded higher accuracies (improvement in R2 of 0.03–0.04 and RMSE of 5.4–16.88 g/m2) than the use of individual sensors alone and was also equivalent to the performance of the high resolution WV3 sensor results. Wetlands had significantly higher AGB compared to the surrounding terrestrial grassland (with a mean of about 80 g/m2 more). Monitoring herbaceous AGB at the scale of the wetland extent in semi-arid to arid grasslands enables improved understanding of their carbon sequestration potential, the contributions to global carbon accounting policies and also serving as a proxy for functional intactness.

Prairie Dog (Cynomys ludovicianus) Influence on Forage Quantity and Quality in a Grazed Grassland-Shrubland Ecotone

Black-tailed prairie dogs (Cynomys ludovicianus) have high dietary overlap with livestock, which can cause forage-centric conflicts between agriculture and conservation. Research suggests prairie dogs can enhance forage quality, but trade-offs between quality and quantity throughout the growing season remain unclear, as well as the degree to which increased forage quality is caused by altered species composition versus altered plant physiology. To assess the effects of prairie dog herbivory on forage in a northern mixed-grass prairie, we collected samples on prairie dog colonies and at sites without prairie dogs during June, July, and August 2016 - 2017 for forage quality, and August 2015 - 2017 for herbaceous biomass. To isolate mechanisms affecting forage quality, we collected both composite samples of all herbaceous species and samples of western wheatgrass (Pascopyrum smithii [Rydb.] Á. Löve). Across years and plant sample types, crude protein, phosphorus, and fat were 12-44% greater and neutral detergent fiber was 6-10% lower on prairie dog colonies than at sites without prairie dogs. The effects of prairie dogs on forage quality persisted throughout the season for western wheatgrass samples (all treatment*time p-values ≥ 0.4). Across years, aboveground herbaceous biomass did not differ significantly between prairie dog colonies and sites without prairie dogs (on-colony: 933 ± 156 kg/ha, off-colony: 982 ± 117 kg/ha). The effects of prairie dogs on herbaceous biomass were significantly influenced by spring precipitation. In years with dry springs, herbaceous biomass was lower on colonies than sites without prairie dogs and this pattern was reversed in years with wet springs. Our results demonstrate season-long enhanced forage quality on prairie dog colonies, indicating that multiple mechanisms are shaping forage quality in this system, including altered species composition, phenological growth stage, and soil condition. Across years, enhanced forage quality may help to offset reductions in forage quantity for agricultural producers.

Controls of the spatial variability of denitrification potential in nontidal floodplains of the Chesapeake Bay watershed, USA

Identifying floodplains with high rates of denitrification will help prioritize restoration projects for the removal of nitrogen. Currently, relationships of denitrification with hydrogeomorphic, physiographic, and climate (i.e., largescale) characteristics of floodplains are relatively unknown, even though these characteristics have datasets (e.g., geographic mapping tools) that are publicly available (or soon-to-become) that could be used to understand denitrification variability. Thus, we investigated control of denitrification by these largescale characteristics in eighteen nontidal floodplains of the Chesapeake Bay watershed (i.e., at regional scale, >100 km, scale), using measurements or compiled data at the scales of the stream reach and respective catchment; floodplain soil and herbaceous vegetation (i.e., local) characteristics were additionally investigated. Soil denitrification potentials were measured in May, July, and August using complementary acetylene-based techniques under an anoxic environment. Linear largescale predictors of denitrification potential measurements included stream nitrogen and phosphorus concentrations (+), channel width-to-depth ratio (+), floodplain sedimentation (+), forested (−) and urban (+) catchment land cover, and seasonal air temperature (−). Three predictors, catchment forested land cover (strongly related to agricultural land cover), catchment urban land cover, and floodplain sedimentation were related to the most number of denitrification potential measurements. Soil structure, soil nutrient concentrations, and herbaceous vegetation characteristics that were seasonally measured (with a few exceptions) were linear predictors of denitrification potentials in May and August, with nitrogen and carbon characteristics the most consistent (positive) predictors across measurements. Nutrient amendment assays further supported the importance of nitrogen and carbon controls. Using the local characteristics as statistical mediators in path analysis, greater non-forested catchment land cover indirectly increased denitrification through greater floodplain soil nitrate, total phosphorus, and herbaceous aboveground biomass. Additionally, greater floodplain sedimentation indirectly increased denitrification through greater soil pH, total phosphorus, and potential carbon mineralization. Due to the consistency of relationships across denitrification potential measurements along with path modeling results, hotspots of floodplain denitrification should be found in urban and agricultural catchments where river-floodplain hydrologic connectivity promotes sedimentation. Largescale predictors explained 43–57% of the variation in denitrification potentials and should be useful for prediction in floodplains. Siting restoration projects in watersheds for maximum nitrate removal using publicly available largescale datasets is both feasible and effective.

Performance of ratio‐based, soil‐adjusted and atmospherically corrected multispectral vegetation indices in predicting herbaceous aboveground biomass in a Colophospermum mopane tree–shrub savanna

AbstractAccurate and near‐real‐time estimation of herbaceous aboveground biomass (AGB) at farm level is crucial for monitoring pasture production and proactive management of stock in semiarid rangelands. Despite its importance, remote sensing has been rarely used by range ecologists and managers in Zimbabwe. This study aimed at assessing the performance of classical multispectral vegetation indices (MVIs) when either singly regressed with measured herbaceous AGB or combined with other visible spectral bands in predicting herbaceous AGB in a Colophospermum mopane savannah. Field herbaceous AGB and corresponding Landsat 8 Operational Land Imager visible spectral data were collected during the 2016–2017 rainy season. Relationships between measured AGB and classical MVIs and extended models of MVIs combined with other visible bands were analysed using bootstrapped simple and stepwise multiple linear regression functions. When MVIs were singly regressed with measured AGB, ratio‐based indices yielded the highest r2 value of 0.64, followed by soil‐adjusted indices (r2 = 0.61), while atmospherically corrected MVIs showed the lowest r2 of 0.58 (p = 0.00). A significant improvement in herbaceous AGB estimation was obtained using a combination of MVIs and other visible bands. Soil‐adjusted MVIs showed the greatest increase (44–46%) in r2, while atmospherically corrected and ratio‐based MVIs poorly improved (<5%). The findings demonstrate that combining MVIs with Landsat 8 optical bands, especially green band, provides the best models for estimating AGB in C. mopane savanna rangelands. These findings emphasize the importance of testing band‐MVI combinations when developing models for estimating herbaceous AGB.

Surface and Subsurface Tillage Effects on Mine Soil Properties and Vegetative Response

Core Ideas Mine soil physical properties improve with increased tillage upon reclamation in the Gulf Coastal Plain. Growth of loblolly pine seedlings increases with higher intensity tillage on reclaimed mined land. Aboveground herbaceous cover and biomass increases with tillage on reclaimed mined land. Soil compaction is an important concern for surface mine operations that require heavy equipment for land reclamation. Excessive use of rubber‐tired equipment, such as scraper pans, may cause mine soil compaction and hinder the success of revegetation efforts. However, information is limited on management strategies for ameliorating the potential compacting effects of scraper pans, particularly during site preparation for loblolly pine (Pinus taeda L.) plantations. Three forms of tillage and one control were replicated five times on surface mined land in the west Gulf Coastal Plain: no tillage (NT), disking (D), single‐ripping + disking (R+D), and cross‐ripping + disking (CR+D). Mine soil physical properties were investigated at 0 to 30, 30 to 60, and 60 to 90 cm. Percent cover and aboveground biomass of an herbaceous winter cover crop, and survival and growth of loblolly pine seedlings were assessed after one growing season. Herbaceous species biomass was highest on the R+D and CR+D plots and lowest on the NT control. Pine seedling survival was highest on the tilled plots (>90%) compared to NT (85%). The highest intensity combination tillage treatment (CR+D) was superior in terms of lowering soil bulk density (mean 1.36 Mg m–3) and soil strength (mean 2220 kPa) and increasing pine seedling volume index growth (mean 32 cm3). Surface tillage (D) alone improved herbaceous cover and pine seedling survival, while CR+D provided the most favorable responses in mine soil physical properties and vegetative growth.

Estimation of aboveground herbaceous biomass using visually ranked digital photographs

Methods for estimating aboveground herbaceous biomass in the field have generally involved calibrating visual estimates against clipped, dried and weighed biomass samples, requiring lengthy periods of estimation and destructive sampling in the field. Here we developed and tested a photographic estimation technique (PET) that minimises field time and provides accurate estimates of aboveground herbaceous biomass. Photographs of the biomass to be estimated taken in the field are ranked against calibration images of known biomass in the laboratory. The study was conducted in New South Wales, Australia, in grassy forest dells and grasslands at Booroolong Nature Reserve in the temperate New England Tablelands Bioregion and in semi-arid grassy shrubland on Naree Station in the arid Mulga Lands Bioregion. Photographs of quadrats containing the herbaceous biomass to be estimated were taken in successive years at both sites. Calibration and validation quadrats were also photographed, and the vegetation clipped, bagged, dried and weighed. The calibration and validation photographs were rank-ordered independently by three observers in terms of estimated dry weight, and the validation quadrats assigned a putative dry weight by reference to the known weights of the calibration images in the rank order. The accuracy of each observer’s estimates was assessed by regressing the estimated weight of each validation quadrat against the actual weight, which was withheld from the observer during the estimation procedure. Regression analysis of visually estimated weights on actual weights of validation quadrats yielded regression coefficients (R2) of 0.80–0.98 and 0.81–0.97 in the temperate-zone and arid-zone sites, respectively. PET was reliably used to visually estimate aboveground herbaceous biomass across a range of communities in two different climatic zones. The benefits of PET include reduced field time, minimisation of destructive sampling and avoidance of observer drift in estimating biomass in the field.

Effects of Feral Horse Herds on Rangeland Plant Communities across a Precipitation Gradient

Feral horses are widespread in the western United States, with the majority of feral horse herds found in the Great Basin. There is a federal mandate to manage these herds in order to maintain “ecological balance”; however, understanding of the specific effects of feral horse grazing on rangeland plant communities in this region is incomplete. To address this research gap, we utilized long-term grazing exclosures and fenceline contrasts to evaluate the impacts of feral horses on several plant community variables (diversity, richness, dominance, and biomass) and species composition. Because the effects of grazing can vary with site precipitation and productivity, we selected 5 sites from 4 different rangeland types (Great Basin Desert, Colorado Plateau, Rocky Mountain grassland, and mixed grass prairie) that spanned a mean annual precipitation gradient of 229 to 413 mm. Our results did not reveal a significant effect of feral horse grazing on plant community composition, species richness, diversity, evenness, or dominance. In contrast, total aboveground herbaceous biomass and grass biomass were significantly reduced with feral horse grazing, but these effects did not vary with mean annual precipitation. Our results suggest that, at least at the sites we studied, feral horses have affected the plant community by reducing herbaceous biomass but have not caused plant community shifts. Additional multisite studies, preferably with standardized exclosures and larger sample sizes, would increase our understanding of feral horse grazing effects and inform management of feral horse herds in the western United States.