Plant Canopy Cover Research Articles

Effect of Weed Management Practices on Citrus Growth and Cost of Production at Young Mandarin Orchard in Palpa, Nepal

ABSTRACT Although citrus cultivation has a comparative advantage in subtropical climates, meeting the increasing demand is challenging, primarily due to weed pressure contributing 25–33% yield loss. Henceforth, to assess the efficiency of weed management methods, enhance plant growth, and analyze economic treatment costs, research was conducted in a three-year-old mandarin (Citrus reticulata Blanco.) orchard at Citrus Development Center, Tansen, Palpa, in 2022. The experiment was designed in a single factorial randomized complete block design with five treatments: plastic mulch, organic mulch, herbicide, hand weeding, and a control. Fourteen weed species were identified, and the highest weed density was of sedges (45%). Results of the study showed that plastic mulch was an efficient method providing lower average weed diversity (1.7); weed density in all days after treatment (DAT) (0.5, 0.6, 1.9, 6.6, and 1.1 m−2); and weed dry weight at 15, 30, and 45 DAT (0.1, 0.3, and 0.4 gm−2). Plastic mulch observed with higher weed control efficiency (93.9, 87.1, 93.1, 91.8, and 93.4%) and weed control index (89.6%, 85.8%, 93.8%, 90.8%, and 96.35%) in all DAT. Whereas, the weed persistence index was lower in herbicide-treated plots at 30 (0.73), 45 (0.44), and 75 (0.24) DAT. Herbicide-treated plots showed the highest increment in crop growth parameters of plant height (33.7%) and plant canopy cover volume (180.8%) and were also the most economical with the lower annual treatment cost (NPR 210 thousand/ha). The superior plant growth, higher weed control, and lower cost proved herbicide treatment as an effective weed control method. However, plastic mulch, with outcomes resembling herbicide, can be a sustainable approach for weed control.

RGB‐based indices for estimating cover crop biomass, nitrogen content, and carbon:nitrogen ratio

AbstractPlant cover and biochemical composition are essential parameters for evaluating cover crop management. Destructive sampling or estimates with aerial imagery require substantial labor, time, expertise, or instrumentation cost. Using low‐cost consumer and mobile phone cameras to estimate plant canopy coverage and biochemical composition could broaden the use of high‐throughput technologies in research and crop management. Here, we estimated canopy development, tissue nitrogen, and biomass of medium red clover (Trifolium pratense L.), a perennial forage legume and common cover crop, using red‐green‐blue (RGB) indices collected with standard settings in non‐standardized field conditions. Pixels were classified as plant or background using combinations of four RGB indices with both unsupervised machine learning and preset thresholds. The excess green minus red (ExGR) index with a preset threshold of zero was the best index and threshold combination. It correctly identified pixels as plant or background 86.25% of the time. This combination also provided accurate estimates of crop growth and quality: Canopy coverage correlated with red clover biomass (R2 = 0.554, root mean square error [RMSE] = 219.29 kg ha−1), and ExGR index values of vegetation pixels were highly correlated with clover nitrogen content (R2 = 0.573, RMSE = 3.5 g kg−1) and carbon:nitrogen ratio (R2 = 0.574, RMSE = 1.29 g g−1). Data collection were simple to implement and stable across imaging conditions. Pending testing across different sensors, sites, and crop species, this method contributes to a growing and open set of decision support tools for agricultural research and management.

Inversion of Soybean Net Photosynthetic Rate Based on UAV Multi-Source Remote Sensing and Machine Learning

Net photosynthetic rate (Pn) is a common indicator used to measure the efficiency of photosynthesis and growth conditions of plants. In this study, soybeans under different moisture gradients were selected as the research objects. Fourteen vegetation indices (VIS) and five canopy structure characteristics (CSC) (plant height (PH), volume (V), canopy cover (CC), canopy length (L), and canopy width (W)) were obtained using an unmanned aerial vehicle (UAV) equipped with three different sensors (visible, multispectral, and LiDAR) at five growth stages of soybeans. Soybean Pn was simultaneously measured manually in the field. The variability of soybean Pn under different conditions and the trend change of CSC under different moisture gradients were analysed. VIS, CSC, and their combinations were used as input features, and four machine learning algorithms (multiple linear regression, random forest, Extreme gradient-boosting tree regression, and ridge regression) were used to perform soybean Pn inversion. The results showed that, compared with the inversion model using VIS or CSC as features alone, the inversion model using the combination of VIS and CSC features showed a significant improvement in the inversion accuracy at all five stages. The highest accuracy (R2 = 0.86, RMSE = 1.73 µmol m−2 s−1, RPD = 2.63) was achieved 63 days after sowing (DAS63).

Effect of Irrigation and Nitrogen Management on Potato Growth, Yield, and Water and Nitrogen Use Efficiencies

Irrigation and nitrogen management are crucial for sustainable potato (Solanum tuberosum L.) production. A field experiment was conducted during the 2022 and 2023 growing seasons at Farmington, New Mexico, to evaluate the performance of two chip potato varieties (Lamoka and Waneta) under three irrigation regimes (full irrigation (FI), 20% deficit irrigation (DI) and 40% DI) and seven nitrogen fertilizer rates (0, 60, 115, 170, 220, 280, and 340 kg N/ha). The treatment combinations of irrigation regimes, nitrogen rates, and varieties were arranged in a split–split plot design with three replications as main plot, sub-plot, and sub-sub plot, respectively. The two-year results showed that irrigation regimes had the most significant effect on plant growth, physiology, and tuber yield of the potato varieties. For both Lamoka and Waneta, the plant height and canopy cover were lower under 40% DI than under 20% DI and FI treatments. The SPAD meter values were higher under 40% DI, followed by 20% DI and FI treatments, whereas the stomatal conductance was higher under FI, followed by 20% DI and 40% DI during both growing seasons. Regardless of nitrogen rates and variety, a 20% water-saving irrigation strategy reduced the total tuber yield by 4.5% and 22.1% in the 2022 and 2023 growing seasons, respectively, while the 40% water-saving irrigation strategy reduced total tuber yield by 36.8% and 58.2% in the 2022 and 2023 growing seasons, respectively, as compared to full irrigation. Shifting from full irrigation to 20% DI could save 711.2 to 1036.3 m3/ha of irrigation water. For Lamoka, the highest total tuber yield was obtained with 60 kg N/ha under 20% DI and 220 kg N/ha under FI in 2022 and 2023, respectively. For Waneta, the highest total tuber yield was obtained with 115 kg N/ha under 20% DI and 170 kg N/ha under FI in 2022 and 2023, respectively. Maximum water use efficiency (WUE) was obtained at 60 kg N/ha with 20% DI for both Lamoka and Waneta in 2022, while maximum WUE was obtained at 220 kg N/ha under FI for Lamoka and at 170 kg N/ha for Waneta in the 2023 season. The maximum nitrogen use efficiency (NUE) was achieved with 60 kg N/ha under 20% DI for both varieties during both growing seasons. Thus, for sustainable irrigation and nitrogen management, the application of a 20% deficit irrigation strategy with a lower nitrogen rate (60 to 170 kg N/ha) could be the best option to improve WUE and NUE with minimal tuber yield reduction. Our study suggested that 40% deficit irrigation would not be beneficial as compared to both full irrigation and 20% water-saving irrigation.

Spatial and seasonal determinants of arthropod community composition across an agro-ecosystem landscape

We used Malaise traps to sample arthropod community composition at biweekly intervals across an agroecosystem landscape in southern Ontario, Canada, to evaluate the relative impact of site spacing, seasonal timing, weather conditions, local plant community attributes, and agricultural extent across the local landscape on spatial and temporal variation in arthropod community composition. The 15 field sites sampled spanned a wide gradient of agricultural extent that in isolation had a strong impact on spatial variation in arthropod community composition. DNA metabarcoding of the samples identified >10 000 different arthropod biodiversity index numbers. Local variation in plant community composition and canopy cover best explained variation in arthropod community dissimilarity. Weather variables followed closely in explanatory power, driven primarily by seasonal variation in temperature. Significant effects of time remained after accounting for environmental variables, with little independent effect of spatial distance. The proportion of agricultural land at the landscape scale had little detectable effect after controlling for the influence of the other environmental variables. Our results suggest that plant community composition, cover, weather conditions, and seasonality structured the arthropod community to considerable degree.

The Role of Almond-Leaved Pear Pyrus spinosa Forssk. in Mediterranean Pasturelands Carbon Storage and Woodlands Restoration

A large portion of the Mediterranean basin suffers from a lack of organic carbon in the soil and low woody cover percentages, resulting in a very high risk of desertification. In such conditions, knowing the effects on below and above ground carbon sequestration of pioneer woody species is of great importance, although barely assessed at the individual level. In this study, we first investigated whether almond-leaved pear (Pyrus spinosa) individuals influence soil organic carbon (SOC) concentration and stock in comparison with surrounding pasturelands inside a natural reserve in Sicily, Italy. Second, we evaluated inter individual variability on such storage, testing the effects of plant height, basal diameter, canopy cover and tree structure (single or multiple stems). Soils under pear presented, on average, a significantly higher SOC than pasturelands (3.86% and 3.16%, respectively) as well as a lower bulk density (1.09 and 1.28 g cm−3, respectively). Due to a lower soil compaction, SOC stocks (130.3 and 113.9 Mg ha−1, respectively) did not differ significantly. Below and aboveground biomass carbon accounted for a small fraction of carbon stock, while neither pear structure, age nor tree structure significantly influenced SOC concentration and SOC stock. Despite the need of further investigations, our results indicate that pear may represent an excellent tree species to improve carbon storage, both while triggering the restoration of Mediterranean woodlands or increasing biodiversity in pasturelands and agroforestry systems, that, indeed, can hold high SOC if well managed.

Enhancing leaf area index and biomass estimation in maize with feature augmentation from unmanned aerial vehicle-based nadir and cross-circling oblique photography

Rapid and accurate estimation of plant phenotypes plays a vital role in effective breeding and management of maize crops. Unmanned aerial vehicle (UAV) platforms are emerging as a valuable tool in the assessment of crop phenotypes, offering a promising avenue to enhance the accuracy and efficiency of phenotypic analysis. This study executed two UAV photography methods to acquire aerial images for the estimation of leaf area index (LAI) and above-ground biomass (AGB) in summer maize. Nadir photography was implemented to obtain data from three sources including multi-spectral (MS), RGB, and thermal infrared (TIR) sensors. Additionally, RGB imaging-based cross-circling oblique (CCO) photography was implemented to obtain accurate 3D point cloud data. The nadir photography data was processed to generate orthomosaic image and extract features including vegetation index, canopy cover, canopy height, canopy temperature, and textural information. Features including canopy occupation volume, plant area index, canopy cover, and canopy height were extracted from the CCO photography-derived point cloud data. Furthermore, a data augmentation method, called linear regression-based feature augmentation (LRFA), was proposed for augmenting features extracted from nadir and CCO photography. The results showed that the introduction of CCO photography improved the accuracy of LAI and AGB estimation during the big trumpet stage and LAI estimation during the milk stage compared to the integrated multi-source nadir photography data. Notably, the LRFA derived features outperformed raw features in the majority of modeling scenarios, with the random forest achieved an average accuracy (R2) improvement of 6.1% for LAI estimation and 3.7% for AGB estimation. This study highlights the significance of combining different photography technologies and feature augmentation method for estimating maize phenotypes, providing novel opportunities for crop growth monitoring in modern agriculture.

Floral hemp (Cannabis sativa L.) responses to nitrogen fertilization under field conditions in the high desert.

While most studies on floral hemp (Cannabis sativa L.) concur that additions of nitrogen (N) increase plant growth, the performance of floral hemp is heavily influenced by environmental conditions, management and cultivar selection. In regions with a short growing season, the availability of soil N may determine plant developmental rates, final inflorescence biomass and cannabinoid concentrations, but no studies have addressed this for field-grown hemp under high-desert conditions. This field study evaluated the effect of no supplemental N and N fertilization at 90 kg ha-1 on three hemp cultivars (Berry Blossom, Red Bordeaux, and Tahoe Cinco) in Northern Nevada. N increased plant height, canopy cover, stem diameter and shoot biomass, but other physiological parameters were dependent on cultivar. For instance, inflorescence biomass and inflorescence-to-shoot ratio in Red Bordeaux was not affected by N fertilization. Similarly, cannabinoid concentrations were affected by timing of harvest and cultivar but not by N treatment. We evaluated the use of a SPAD meter for ease of determining leaf N deficiency, and correlations with leaf chlorophyll content showed that the SPAD meter was a reliable tool in two cultivars but not in Tahoe Cinco. N treatment increased overall CBD yield, which was driven by increases in inflorescence biomass. Tahoe Cinco was the best CBD yielding cultivar, as it maintained a high inflorescence-to-shoot ratio regardless of N treatment. Our study suggests that even though hemp may have a positive response to soil N management, adjustments based on genotype by environment interaction should be aimed at maximizing cannabinoid yield either by increasing biomass and/or CBD concentrations as long as THC levels are within the permissible <0.3% for U.S. industrial hemp cultivation.

Agronomic and forage nutritive responses of Kentucky bluegrass dominated pastures in the northern Great Plains

AbstractKentucky bluegrass (Poa pratensis L.) has become dominant in many portions of the northern Great Plains. During hot and/or dry periods, pastures consisting of mostly cool‐season grasses will most likely lack the productivity and diversity needed to provide sufficient forage for livestock. Determining the impact of weather conditions on the variation of forage production and nutritive response of Kentucky bluegrass is becoming increasingly important to agricultural producers. Sampling occurred at the USDA Northern Great Plains Research Laboratory near Mandan, North Dakota, USA. Kentucky bluegrass samples were clipped every 2–3 weeks in mowed and unmowed unfertilized rangeland plots during the growing seasons of 2017 and 2018. Samples were dried, weighed, ground to pass a 1‐mm sieve, and analysed for nutritive value. There are differences between the modelled supply of metabolizable energy and metabolizable protein and the requirements for cow‐calf pairs for all years and most months. Early defoliation of Kentucky bluegrass decreases productivity and nutritive value as the grazing season progresses. Adjusting management to allow an adequate growth interval and plant canopy cover throughout the year can ensure a more consistent supply of Kentucky bluegrass. Our data and models provide a glimpse into future scenarios, which allow producers to be more proactive in dealing with Kentucky bluegrass and projected changes in climate.

Cotton Growth Modelling Using UAS-Derived DSM and RGB Imagery

Modeling cotton plant growth is an important aspect of improving cotton yields and fiber quality and optimizing land management strategies. High-throughput phenotyping (HTP) systems, including those using high-resolution imagery from unmanned aerial systems (UAS) combined with sensor technologies, can accurately measure and characterize phenotypic traits such as plant height, canopy cover, and vegetation indices. However, manual assessment of plant characteristics is still widely used in practice. It is time-consuming, labor-intensive, and prone to human error. In this study, we investigated the use of a data-processing pipeline to estimate cotton plant height using UAS-derived visible-spectrum vegetation indices and photogrammetric products. Experiments were conducted at an experimental cotton field in Aliartos, Greece, using a DJI Phantom 4 UAS in five different stages of the 2022 summer cultivation season. Ground Control Points (GCPs) were marked in the field and used for georeferencing and model optimization. The imagery was used to generate dense point clouds, which were then used to create Digital Surface Models (DSMs), while specific Digital Elevation Models (DEMs) were interpolated from RTK GPS measurements. Three (3) vegetation indices were calculated using visible spectrum reflectance data from the generated orthomosaic maps, and ground coverage from the cotton canopy was also calculated by using binary masks. Finally, the correlations between the indices and crop height were examined. The results showed that vegetation indices, especially Green Chromatic Coordinate (GCC) and Normalized Excessive Green (NExG) indices, had high correlations with cotton height in the earlier growth stages and exceeded 0.70, while vegetation cover showed a more consistent trend throughout the season and exceeded 0.90 at the beginning of the season.

Evaluation of riparian enhancement actions in the Columbia River Basin

Riparian enhancement is a common restoration technique in the Columbia River Basin (CRB) and the Pacific Northwest. However, relatively few studies have evaluated its success and even fewer studies include long-term monitoring. Forty-one riparian planting projects located in the CRB, each with a paired treatment and control reach, were evaluated in the summer of 2018 and 2019 using an extensive post-treatment (EPT) design. At each reach, we quantified woody plant abundance, richness, diversity, and vegetation and canopy cover as riparian response variables, and measured terrace height and documented individuals with bud browse, deceased, and with predator protection as potential explanatory variables. Species richness, woody plant abundance (all height classes combined and within shrub height class), and the proportion of woody plants with bud browse or deceased were all higher in treatment than control reaches. However, no significant improvements were observed for any other riparian response or explanatory variables. Implementation techniques, including invasive species removal efforts, follow-up planting, watering, and the type of restoration project (floodplain restoration and planting, in-stream restoration and planting, or solely planting) were also considered as potential explanatory variables and were found to have significant impacts on restoration response for abundance and cover variables. Our results suggest that planting implementation methods, site level physical factors, and time since planting all influence the success of riparian planting projects and if not addressed in restoration design and implementation can contribute to a lack of detectable response.

Evaluating Growth, Biomass and Cannabinoid Profiles of Floral Hemp Varieties under Different Planting Dates in Organic Soils of Florida

Hemp production has been permitted as a new agricultural commodity in Florida and may serve as a potential rotational crop. Field trials were conducted in the Everglades Agricultural Region with multiple varieties planted at different dates. Data were collected on plant growth parameters, final biomass at harvest, and temporal cannabidiol (CBD) and Δ-9-tetrahydrocannabinol (THC) content in developing flowers. Results showed that at the United States Sugar Corporation (USSC) location, the BaOX variety had higher biomass compared to other varieties and at Everglades Research and Education Center (EREC), varieties ACDC and Cherry wine recorded the highest biomass compared to other varieties. Moreover, plant growth parameters such as plant height, canopy cover and SPAD were significantly affected by variety and planting date. Total CBD and THC content in plants increased over time for most varieties except for Early bird and Cherry abacus under second planting. There was a significantly high correlation between total CBD and THC content (R2 = 0.75 to 0.98, slope = 16.8 to 22.8). The THC content in most varieties exceeded the legal limit of 0.3% at some stage of the growing season. The results of this study indicate that the variety performance was largely affected by genetics compared to the planting date.

Productivity, Morphology and Chemical Composition of Brachiaria spp. Ecotypes, under Two Solar Illumination Intensities, in Yucatan, Mexico

There are mixed reports about the advantages and disadvantages of the presence of shade produced by trees over the understory-growing grasses; thus, it is urgent to test grass species and cultivars with potential to develop in shaded conditions associated with trees that occur in silvopastoral systems. The objective of the present study was to identify Brachiaria spp. ecotypes adapted for cultivation under tree shade, typical of silvopastoral systems. The study was conducted at Kampepen ranch, located 14 km south of Merida, Yucatan, Mexico. A factorial 6 (ecotypes) x 2 (sunlight intensities) treatment structure was used, arranged in split-plot design; with sunlight intensity levels being the plots and ecotypes the subplots, with three replications. The ecotypes were T1: Brachiaria hybrid cv. Mulato II, T2: Brachiaria hybrid cv. Cayman Blend, T3: Brachiaria hybrid cv. Talisman (BR05/1467), T4: Brachiaria hybrid cv. Camello Blend, T5: Brachiaria brizantha cv. Marandu and T6 (the control): M. maximus cv. Mombasa, while the two sunlight intensity levels were higher and lower sunlight reductions with respect to full sunlight (25% and 50% light transmission with respect to full sunlight, respectively). Variables were plant height, forage yield and chemical composition; leaf, stem and dead material fractions and leaf:stem ratio; plant canopy cover, plant maturity, and growth rate. Significant (p &lt; 0.050) ecotype x sunlight intensity interactions were recorded for most of the studied variables. Independent of the shading levels, ecotype Talisman showed superior performance compared with the other assessed ecotypes, yielding up to 20 ton ha−1 under the highest light intensity, means across light intensities for crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF) of 11.8%, 59.7%, and 34.7%, respectively, and more than 90% plant canopy cover. It is concluded that Talisman has promising characteristics for cultivation under silvopastoral systems, where tree shading is common, in the dry tropics of Yucatan, Mexico.

Estimation of spinach (Spinacia oleracea) seed yield with 2D UAV data and deep learning

Precision agriculture has drawn much attention in the last few years because of the benefits it has on reducing farming costs while maximizing the harvest obtained. Yield prediction is of importance for farmers to fertilize accordingly to reach the potential yield. However, this task is still relying on manual work, which is expensive and time-consuming. Instance segmentation has been implemented in the last years for fruit detection and yield estimation, obtaining state-of-the-art metrics, and reducing the labor required. This research presents a novel approach for spinach seed yield estimation for seed production purposes, that consists of correlating the number of plants and two phenotyping variables (plant area and canopy cover percentage) with the number of harvested seeds and the thousand seed weight. Mask R-CNN is applied to count the number of detections of spinach plants and obtain the object mask from which the plant area is derived. The results show that there is a high linear correlation between a multivariate linear mixed model of the three variables and the number of seeds, with an R2adj of 0.80. Furthermore, 77.42% of the variation in the weight of thousand seeds can be explained by the number of plants. For future studies, the algorithm should be trained with more spinach images from different locations and under varying weather conditions to allow it to generalize for the crop worldwide. It can be concluded, until further research, that Mask R-CNN can be applied for spinach counting and the computation of its individual plant area, with promising results.

Characteristics of Soil Hydraulic Conductivity in Natural Forest, Agricultural Land, and Green Open Space Area

Soil hydraulic conductivity is one of the important soil characteristics that determines the amount and proportion of water that will be infiltrated into the soil column and flowing as surface runoff. It is strongly influenced by soil porosity and soil characteristics that affect the soil porosity such as soil texture and structure and soil organic matter content (internally factors) as well as land management and the intensity of plant canopy cover (external factors). This research is aimed to identify the character of soil hydraulics conductivity in different landuse that consist of forest, agricultural land (moor land, cacao plantations, intensive and conservation annual crops), and green open space areas. The results showed that: a) forest conversion into agricultural land led to the decline of soil quality such as decreased levels of soil organic matter, soil porosity and distribution of soil pores so that the conversion of forest land into agricultural land decreases the soil hydraulic conductivity of both for the initial value and saturated hydraulic conductivity; b) forets canopy cover density affects the soil quality and soil hydraulics conductivity, where high canopy cover has the higher value of soil hydraulics conductivity compared to medium and low canopy forest; c) Situgede tourism forest has the lowest soil hydraulics conductivity compared to other forest types; d) soil hydraulics conductivity in conservation annual crops is higher than intensive annual crops land and Situgede tourism forest and it’s not significantly different from the soil hydraulics conductivity in low canopy forest; and e) soil hydraulics conductivity in green open spaces area were strongly determined by the naturalness of landscape and human intervention level on its formation and management, where the UI city forest and Lembah Gurame city park which were function as ecotourism areas has the lower soil hydraulics conductivity compared to great forest park.

Bryophyte diversity and microhabitat characteristics of bryophyte-dominated biological soil crusts development in water-wind erosion crisscross region of the northern Loess Plateau, China

Microhabitat factors play an important role in regulating bryophyte species distribution and the development of bryophyte-dominated biological soil crusts (hereafter bryophyte crusts). We investigated the distribution and development of bryophytes in eight microhabitats in the water-wind erosion crisscross region of the Loess Pla-teau. We used the line intercept transects to explore and quantify the influencing pathways of microhabitat factors on bryophyte diversity and analyzed the influencing pathways of plant cover, slope aspect, and slope gradient by using structural equation model to quantify influencing coefficients. Our results showed that: 1) The Patrick, Shannon, Pielou, and Simpson indcies of bryophytes under plant canopy were 63.4%, 66.6%, 91.0%, and 68.3% lower than that without plant canopy, respectively, while the thickness, biomass, and chlorophyll content of bryophyte crusts were 0.5, 0.2, and 1.3 times higher than that without plant canopy, respectively. 2) The Patrick, Shannon, Pielou, and Simpson indexes of bryophytes on the north slope were 0.6, 0.9, 5.6, and 0.9 times higher than those on the south slope, while the thickness, biomass, and chlorophyll content of bryophyte crusts were 0.3, 0.3, and 0.6 times higher than those on the south slope, respectively. 3) As the slope increasing from 14° to 34°, the Patrick, Shannon, Pielou, and Simpson indexes of bryophyte were decreased by 59.8%, 84.1%, 57.3% and 68.0%, and the thickness, biomass, and chlorophyll content of bryophyte crusts were decreased by 15.2%, 25.0%, and 16.5%, respectively. 4) The importance of the three microhabitat factors on bryophyte diversity and the development of bryophyte crusts followed an order of plant canopy cover > slope aspect > slope gradient. The primary influencing pathway varied among the microhabitat factors. In conclusion, plant cover, slope aspect, and slope gradient significantly affected the distribution of bryophytes species and developmental level of bryophyte crusts through direct and indirect pathways. Therefore, full consideration should be given to microhabitat conditions when using bryophyte crusts to control desertification.

The Clean Water Act and biosolids: A 45‐year chronological review of biosolids land application research in Colorado

The 1972 U.S. Clean Water Act set forth the generation of biosolids. In Colorado, biosolids land application research began in 1976 and continues today. Pastureland research suggested that sewage effluent could effectively be land applied to benefit aboveground plant growth and to polish water prior to reaching receiving waters. Forest wildfire-affected ecosystems can also benefit from biosolids applications; application rates of up to 80 Mg ha-1 can lead to greater plant establishment, soil microbial activity, and nutrient turnover and reduced nutrient and heavy metal concentrations in runoff below livestock and USEPA drinking water standards. Long-term (24-yr) observations in oil shale-mined lands showed that biosolids (up to 224 Mg ha-1 ) can have a positive effect on microbial-mediated nutrient cycling and, in turn, on aboveground plant community structure. Biosolids applications of up to 40 Mg ha-1 in high-elevation shrubland ecosystems, dominated by Mo-containing shale deposits, can aid in reducing imbalances between Mo and Cu in soils and plants; excessive plant Mo, when consumed by ruminants, can lead to molybdenosis. Biosolids and lime applications (both at 224 Mg ha-1 ) have been shown to improve long-term reclamation success on acid-generating, heavy metal-containing fluvial mine tailings. Thirty years of grazing land research, focused on soil and aboveground plant benefits, illustrate that soil health and plant productivity can be improved to the greatest extent at biosolids application rates close to 10 Mg ha-1 . Finally, 40 yr of dryland agroecosystem research (a) have helped identify biosolids N fertilizer equivalency (∼8kg N Mg-1 ) and thus dryland winter wheat application rates (e.g., 4.5-6.7 dry Mg ha-1 ); (b) have identified first-year mineralization rates of 25-32%; (c) dispute the "time bomb" theory by showing that plant metal uptake follows an exponential rise to a maximum; (d) showcase economic return to producers via increased wheat grain protein content; (e) suggest that biosolids-borne proteins and their degradation products are labile C and N sources; (f) have led to long-term tracking of micronutrients and heavy metals in soils and revealed that plants-soil concentrations will not lead to groundwater degradation and that plants are safe for human consumption; and (g) have shown that biosolids provide Zn, helping to overcome soil deficiencies and enhancing Zn biofortification in wheat grain. This latter point is important because ∼2 billion people globally suffer from Zn deficiencies. Forty-five years of research in Colorado have proven that biosolids can enhance environmental quality, improve soil health, and produce healthy food products.

Daytime diet of the lesser sac-winged bat (Saccopteryx leptura) in a Colombian Pacific Island

Insectivorous bats represent more than half of all the Chiropterans of the world. Although they are important stabilizers of insect populations within their habitat due to their feeding habits, just few studies have been focused on the diet of insular bat species. The lesser sac-winged bat, Saccopteryx leptura, is widely distributed in the new world tropics, but little is known about its prey selection. In this study we determined the diet composition of the population of S. leptura from Gorgona Island, Colombia, using stomach and intestinal content samples. We focused our research on their atypical daytime feeding behavior to evaluate differences in prey selection considering two main factors: 1) plant canopy cover and 2) bat sex. We found prey representatives of nine orders of insects, with Hymenoptera, Coleoptera and Hemiptera as the most consumed according to their abundance and volume percentage. We identified two new records at genus level in S. leptura´s diet, Camponotus (Formicidae) and Trigona (Apidae). In general terms, we did not find differences in the diet between canopy covers nor sexes. However, when analyzing the consumed percentage volume by order, there were significant differences in consumption of Psocoptera in both factors. Our results suggest that S. leptura has an opportunistic diet, as they tend to feed on prey of a wide range of sizes, usually the most abundant and available in the environment.

Effect of Boron on Growth and Yield Parameters of Cauliflower (Brassica oleracea var botrytis cv Snow Mystique) in Terhathum, Nepal

A study was conducted to determine the effect of different levels of boron on growth and yield parameters of Snow Mystique variety of cauliflower at farmer's field in Myanglung, Terhathum, Nepal during the winter season of 2019 AD. Five levels of boron viz, control (0 kg/ha), 0.5 kg/ha, 1.0 kg/ha, 1.5 kg/ha, and 2.1 kg/ha were applied in the field that was laid out in Randomized Complete Block Design (RCBD) with four replications. Data were recorded regarding plant height, canopy cover, and leaf number at 30, 45, 60, and 75 days after transplanting while yield parameters like curd diameter, curd yield, and biological yield after harvest. Days to curd initiation, days to harvest, and incidence of hollowing were also recorded in this study. Results revealed that boron had significant effect on growth as well as yield parameters of cauliflower, where the value of these parameters were higher at higher boron dose. Boron at the rate of 2.1 kg/ha produced significantly higher curd yield (67.59 t/ha), curd diameter (25.21 cm) and biological yield (72.27 t/ha) whereas the value of these parameters were lowest with control. Similarly, boron had significant effect on incidence of hollowing where the application of boron at the rate of 2.1 kg/ha recorded the minimum incidence of hollowing (15.27 %). Results from this experiment concludes that application of boron at the rate of 2.1 kg/ha could be suggested for cauliflower growing farmers of Terhathum district for increased growth and yield of cauliflower.&#x0D; Int. J. Appl. Sci. Biotechnol. Vol 10(1): 41-49.

Climate‐mediated shifts toward bunchgrass dominance 40 years after grazing cessation in Saguaro National Park, Arizona, USA

AbstractQuestionsVegetation transects were surveyed in Saguaro National Park, Arizona, in 1976 and 2007 as part of a grazing study. We resurveyed the same transects in 2018 and accessed fire and climate data in order to examine trends in plant community structure. We asked the question: has the plant community shifted in species’ density, canopy cover and diversity in the past 40 years since grazing cessation? And if so, do these shifts favor a specific species, or plant functional guild? We also asked if climate and time since fire influenced plant community structure?LocationSaguaro National Park East is located in the Sonoran Desert and Madrean Sky Island ecoregion interface in Tucson, Arizona, United States.MethodsPlots (10) were 20 m × 50 m, with 21 20‐m transects within each plot used to gather plant canopy cover and density of perennial species with the line‐intercept method. Data were aggregated by plot and analyzed using generalized linear mixed‐effects modeling and non‐metric multi‐dimensional scaling.ResultsOverall canopy cover, density, and Shannon diversity increased significantly between 1976 and 2018. Ferns, forbs, graminoids, subshrubs and vines increased significantly in cover and density between 1976 and 2018. Wildfire recency was significantly negatively correlated with forb density, and density or cover of five dominant species (mostly woody). Shifts in plant community structure between survey years was correlated with increased temperature, precipitation, and vapor pressure differential.ConclusionAfter 40 years of grazing cessation, significant increases in herbaceous cover, and a lack of significant increase in woody encroachment are signs of recovery. Increases in temperature may be responsible for accelerating shifts to warm‐season species‐dominant communities. Fire was unexpectedly not a significant factor in plant community structure; however, park management will likely need to address increased wildfire risk given the increase in herbaceous cover and density.