Search Results (12)

Land management decisions and conservation value are heavily influenced by land ownership, land cover, and land use. Our research aimed to examine ownership and land cover distribution, classify landowners based on land cover composition, and evaluate the ability of land cover clustering to be predictive of landowner motivations and behaviors in Maryland, USA. We tabulated a high-resolution land cover map against ownership boundaries, applied hierarchical clustering, and identified five landowner types characterized by a dominant land cover: (1) forest, (2) turf grass, (3) developed, (4) hay/pasture, and (5) crops. We analyzed a landowner survey of 3344 respondents to reveal how clusters predicted recreation, conservation, income, and other motivations. We found a skewed ownership distribution: 95.3% of smaller ownerships (<5 acres) cover 27.3% of the land, while 4.7% of larger owners hold 72.7%. Ownership patterns vary by cover, with forests and wetlands showing bimodal distributions, unimodal for cropland and hay/pasture, and turf grass concentrated in smaller properties. Survey analysis showed that crop, hay/pasture, and forest clusters had income percentages increasing with property size, with crop and hay/pasture accelerating more; conservation interest rose with size for forest and crop, but not hay/pasture; hunting motivation was highest in forest but increased with size similarly across clusters; non-hunting recreation motivation was highest in smaller hay/pasture properties, but decreased with size for all. Although each landowner has unique motivations and goals, our results reveal trends mediated by size of property and land cover that can be used to target outreach and improve conservation outcomes across Maryland’s diverse landscape. Full article

Predicting forage biomass yield is critical in managing livestock since it impacts livestock stocking rates, hay procurement, and livestock marketing strategies. Only a few biomass yield prediction studies on pasture and rangeland exist despite the need. Therefore, this study focused on developing a biomass yield prediction methodology through remote sensing satellite imagery (multispectral bands) and climate data, employing open-source software technologies. Biomass ground truth data were obtained from local pastures, where Kentucky bluegrass is the predominant species among other forages. Remote sensing data included spatial bands (6), vegetation indices (30), and climate data (16). The top-ranked features (52 tested) from recursive feature elimination (RFE) were short-wave infrared 2, normalized difference moisture index, and average turf soil temperature in the machine learning (ML) model developed. The random forest (RF) model produced the highest accuracy ($R^2=0.83$) among others tested for biomass yield prediction. Applications of the developed methodology revealed that (i) the methodology applies to other unseen pasters ($R^2=0.79$), (ii) finer satellite spatial resolution (e.g., CubeSat; 3 m) better-predicted pasture biomass, and (iii) the methodology successfully developed for a combination of Kentucky bluegrass and other forages, extended to high-value alfalfa hay crop with excellent yield prediction accuracy ($R^2=0.95$). The developed methodology of RFE for feature selection and RF for biomass yield modeling is recommended for biomass and hay forage yield prediction. Full article

With global warming, the cultivation area of bermudagrass is moving northwards in the Mediterranean area despite its winter dormancy and loss of green color. The most common solution is overseeding with perennial ryegrass, which can be complicated to remove in spring. DLF breeders have released a new cultivar of annual ryegrass that is stress tolerant and easy to transition in spring. A trial was carried out on a sod farm in Pisa, Italy. Twenty-nine varieties of cool-season grasses, encompassing both forage and turf species, were overseeded on a hybrid bermudagrass variety ‘Tifway’ (Cynodon dactylon x transvaalensis). The aim of this trial was to compare the overseeding potential of various cool-season turfgrass species and cultivars and to identify which ones perform best in terms of cleanness of cut when overseeded on hybrid bermudagrass in autumn and maintained at a mowing height of 25 mm. Moreover, the following parameters were also assessed: actual turf height (cm); cumulated height (cm); turf visual color and quality (1–9 scale); and visual ground cover (%). Plots were managed with an autonomous mower, which adopted a daily mowing frequency and was set to work with systematic trajectories. The results showed differences between cultivars, and the annual ryegrass showed the best spring transition (scoring a mean value of 96% green cover in July 2023) compared to the other entries. The best result of CoC was measured for rough-stalked meadow grass ‘Sabrena 1’ and tall fescue ‘Turfway’ with 0.9 mm. Full article

Turfgrass systems hold significant climate change mitigation value, but their management often negates the beneficial effects due to the intense adoption of external inputs. The research objective in this paper was to assess the nitrogen fertilization rate able to maintain the ideal esthetic characteristics of Zoysia turfgrass, reducing the environmental impacts associated with greenhouse gas (GHG) emissions. A two-year open field experiment was conducted. Nitrogen was added to the soil at six rates (0, 50, 100, 150, 200, and 250 kg ha⁻¹). The GHG emissions were monitored using a portable gas analyzer and the static chamber methodology. Cumulative environmental impacts were calculated from the inclusion of CO₂, CH₄, and, N₂O using the Global Warming Potential (GWP). The quality assessment of the turf was assessed through a visual and instrumental approach. Higher CO₂ and N₂O fluxes were linked to high nitrogen rates, ranging from 83.55 to 87.50 and from 0.046 to 0.047 g N-N₂O ha⁻¹ day⁻¹ for 200 and 250 kg N ha⁻¹, respectively. CH₄ emissions were not correlated to nitrogen rates. Higher GWP impacts were linked to high N rate treatments. A rate of 100 kg N ha⁻¹ is recommended as the best strategy to reduce GHG emissions while maintaining high turf quality. Full article

Lawns, introduced in Australia through English colonial heritage, dominate public spaces in cities, serving various ecosystem functions. Australian lawns consist of non-native grasses that differ from native original vegetation and require intensive management and maintenance. This study explores public perspectives on urban lawns in Perth, Western Australia, an area largely overlooked in ecological and social research in the context of Australia compared to Europe and North America. This paper presents empirical research on public perceptions of urban lawns and alternatives in Perth, Western Australia. The study explores social values and preferences regarding traditional lawns and new options, considering visual appearance, uses, and maintenance. Findings from an online questionnaire, involving 171 respondents, identified seven categories based on a content analysis of lawn definitions: flat area; ground covered by grass; maintained; non-native vegetation; open space; recreational space; and turf grass. The results revealed that respondents most value lawns for aesthetics, cooling and recreation (exercises, walking pets, as a transit area, passive recreation, and social gatherings). At the same time, participants demonstrated an environmental awareness of lawns and the necessity of revisiting the existing planning and maintenance routine based on irrigation and intensive mowing by considering several alternative solutions. While valuing new solutions such as Scaevola patches in dedicated areas and “weedy lawns”, participants still preferred alternatives closest in appearance to a conventional lawn (e.g., lawn grass with Dichondra and lawn grass with clover). The study emphasizes the need for a ‘blended model’ of urban lawns, combining durability with heat-resistant, biodiverse vegetation to address social values and environmental concerns. Full article

The urgency of addressing the climate crisis has heightened the need to make sustainable decisions. Universities and research institutions are uniquely able to help develop and disseminate useful information for industry, specifically small and medium enterprises. This case study examines the collaboration between the Guelph Turfgrass Institute (GTI) and the turfgrass industry that culminated in the creation of a “Turf Net Present Value Model”. This model enables turfgrass installers, managers, and local municipalities to determine the structure of their turfgrass systems, natural or artificial, and estimate the net present value (NPV) over an extended period. A conceptual model for effective industry-university collaboration is then used to evaluate the knowledge transfer between academia and industry, showcasing a knowledge-transfer framework for improved decision-making and sustainability in sports facilities. Full article

Robotic solutions and technological advances for turf management demonstrated excellent results in terms of quality, energy, and time consumption. Two battery-powered autonomous mowers (2 WD and 4 WD) with random patterns were evaluated according to different trampling levels (control, low, medium, high) on a typical warm season turfgrass at the DAFE, University of Pisa, Italy. Data on the percentage of area mowed, the distance traveled, the number of passages, and the number of intersections were collected through RTK devices and processed by a custom-built software (1.8.0.0). The main quality parameters of the turfgrass were also analyzed by visual and instrumental assessments. Soil penetration resistance was measured through a digital penetrometer. The efficiency significantly decreased as the trampling level increased (from 0.29 to 0.11). The over-trampled areas were mainly detected by the edges (on average for the medium level: 18 passages for the edges vs. 14 in the central area). The trampling activity caused a reduction in turf height (from about 2.2 cm to about 1.5 cm). The energy consumption was low and varied from 0.0047 to 0.048 kWh per cutting session. Results from this trial demonstrated suitable quality for a residential turf of the Mediterranean area (NDVI values from 0.5 to 0.6), despite the over-trampling activity. Soil penetration data were low due to the reduced weight of the machines, but slightly higher for the 4 WD model (at 5 cm of depth, about 802 kPa vs. 670 kPa). Full article

In nature conservation today, there is a global problem with the aggressive expansion of invasive plant species and the conservation of valuable grassland vegetation. Based on this, the following question has been formed: Is the domestic water buffalo (Bubalus bubalis) appropriate for managing various habitat types? How does grazing by water buffalo (Bubalus bubalis) affect on grassland vegetation? This study was carried out in four areas of Hungary. One of the sample areas was in the Mátra Mountains, on dry grassland areas where grazing had been applied for two, four and six years. The other sample areas were in the Zámolyi Basin, where wet fens with a high risk of Solidago gigantea and in a typic Pannonian dry grassland were investigated. In all areas, grazing was carried out with domestic water buffalo (Bubalus bubalis). During the study, we carried out a coenological survey, examining the change of cover of plant species, their feed values and the biomass of the grassland. According to the results, both the number and cover of economically important grasses (from 28% to 34.6%) and legumes (from 3.4% to 25.4%) increased in Mátra as well as the high proportion of shrubs (from 41.8% to 4.4%) shifted toward grassland species. In the areas of the Zámolyi Basin, invasive Solidago has been suppressed completely, the pasture has been converted completely (from 16% to 1%) and the dominant species has become Sesleria uliginosa. Thus, we have found that grazing with buffalo is suitable as a habitat management method in both dry grasslands and wet grasslands. Therefore, in addition to its effectiveness in the control of Solidago gigantea, grazing with buffalo is successful in both nature conservation and economic aspects of grassland vegetation. Full article

The biggest threat to cattle production in most South African communal areas is poor management of grazing, which negatively affects vegetation and soil structures. This study was conducted to assess the spatial variation of grass species density, production potential and quality in Breyten (Hutton soil type), Davel (Avalon soil type), and Wesselton (Clovelly soil type) communal rangelands in the highveld region of Mpumalanga province. Three 100 m transects per grazing area, placed at 50 m intervals (0, 50, and 100 m) were used to collect soil samples at 200 mm depth. A 100 m permanent line point method, replicated three times (50 m apart) per site, was used to identify and collect grass species samples. Grass species were classified according to life form, palatability, ecological status, and abundance. Grasses species were also harvested for chemical composition and in vitro ruminal dry matter degradability determination. Soils from the study areas had an acidic pH range (3.5–4.5). Hutton soil had the highest (p < 0.05) nitrate (N-NO₃) concentration (0.770 mg/kg) compared to Clovelly (0.030 mg/kg) and Avalon (0.533 mg/kg) soil types. Thirty-one grass species composed of 28 turf perennials, two weak perennials and one perennial creeping grass were identified across the study areas. About 16% of identified grass species were classified as highly palatable, 39% as moderately palatable, and 32% as unpalatable. Across all the soil types, Digitaria eriantha had the highest (p < 0.05) crude protein (CP) (106.5 g/kg DM) content when compared to other grass species. In the Avalon soil type, D. eriantha had the lowest (p < 0.05) neutral detergent fiber (NDF) (696.4 g/kg DM). Across all soils, D. eriantha, Aristida congesta, Eragrostis curvula, Eragrostis gummiflua, and Eragrostis plana grasses had the same (p > 0.05) 48-h in vitro ruminal dry matter degradability Hutton soil had a higher proportion of common and dominant grass species as well as more palatable species with higher crude protein content than Avalon and Clovelly soils. However, for all three rangelands, there is a need for supplementary feeding to enhance the production efficiency of livestock given that the nutritive value of grasses was low. Full article

As the drought conditions persist in California and water continues to become less available, the development of methods to reduce water inputs is extremely important. Therefore, improving irrigation water use efficiency and developing water conservation strategies is crucial for maintaining urban green infrastructure. This two-year field irrigation project (2018–2019) focused on the application of optical and thermal remote sensing for turfgrass irrigation management in central California. We monitored the response of hybrid bermudagrass and tall fescue to varying irrigation treatments, including irrigation levels (percentages of reference evapotranspiration, ET_o) and irrigation frequency. The ground-based remote sensing data included NDVI and canopy temperature, which was subsequently used to calculate the crop water stress index (CWSI). The measurements were done within two hours of solar noon under cloud-free conditions. The NDVI and canopy temperature data were collected 21 times in 2018 and 10 times in 2019. For the tall fescue, a strong relationship was observed between NDVI and visual rating (VR) values in both 2018 (r = 0.92) and 2019 (r = 0.83). For the hybrid bermudagrass, there was no correlation in 2018 and a moderate correlation (r = 0.72) in 2019. There was a moderate correlation of 0.64 and 0.88 in 2018 and 2019 between tall fescue canopy minus air temperature difference (dt) and vapor pressure deficit (VPD) for the lower CWSI baseline. The correlation between hybrid bermudagrass dt and VPD for the lower baseline was 0.69 in 2018 and 0.64 in 2019. Irrigation levels significantly impacted tall fescue canopy temperature but showed no significant effect on hybrid bermudagrass canopy temperature. For the same irrigation levels, increasing irrigation frequency slightly but consistently decreased canopy temperature without compromising the turfgrass quality. The empirical CWSI values violated the minimum expected value (of 0) 38% of the time. Our results suggest NDVI thresholds of 0.6–0.65 for tall fescue and 0.5 for hybrid bermudagrass to maintain acceptable quality in the central California region. Further investigation is needed to verify the thresholds obtained in this study, particularly for hybrid bermudagrass, as the recommendation is only based on 2019 data. No CWSI threshold was determined to maintain turf quality in the acceptable range because of the high variability of CWSI values over time and their low correlation with VR values. Full article

In the context of the Urban Heat Island effect, landscape professionals need practical guidance to design for managing surface urban heat. The apparent surface temperatures of samples of 19 hard and soft landscape elements (LEs) found in Perth (Australia) were measured. Thermal images of LE samples on an oval were taken at a 1 m height. The study was conducted in two phases. Phase 1 LE surface temperatures relative to ambient (ΔT) were measured over one day in all four seasons. LEs were ranked by average ΔT, and maintained a similar order across seasons, with summer LEs the hottest. Some LEs were 30–44 °C above ambient in spring and autumn, so these seasons are also significant. Phase 2 repeated the summer test, but used only 14 larger LEs, which were well-coupled to the ground, i.e. more representative of in situ LEs. ΔT values were averaged over daytime and evening periods. Larger LEs were generally hotter than corresponding smaller LEs, with the effect more evident for heavier, denser LEs in the evenings. Future tests should be performed as per phase 2. Averaged measured values of grey pavers were the hottest, whilst ground-cover plants were the coolest. In the evening, grey pavers were also the hottest, whilst decking, soil and turf grass were the coolest. This data will help landscape professionals to assess and compare the thermal performance of different landscape designs, particularly when considering the time of use. Full article

Green roofs are important infrastructures to address the effects of climate change in urban areas. However, most studies and applications have been done in cooler and wetter regions of the northern hemisphere. Climate change will lead to more extreme weather events, such as increased drought and decreased precipitation with intense flash rain events. Increase desertification is expected especially in the Mediterranean Basin, where in summer, radiation and temperature are high and water is scarce. Therefore, while vascular plants increase water consumption in green roofs during warmer periods, mosses present themselves as potential candidates due to their poikilohydric nature, responding to the environmental availability of water, completely drying out and recovering upon rehydration. Although criteria for the selection of vascular plants adapted to the Mediterranean and suitable for green roofs have been developed, no information is available regarding the selection of mosses based on scientific criteria. Here we propose selection criteria for moss species based on ecological preferences according to Ellenberg’s values and help to define moss traits suitable for a nonirrigated, nature-based green roof that tolerates the Mediterranean climate. The main result is a table of potential candidate mosses that can be either used as standalone or in conjunction with vascular plants to decrease water usage and/or manage stormwater through an easily applicable selection methodology. For green roof practitioners, we proposed that acrocarpous mosses exhibiting turf/cushion life forms and colonist or perennial life strategies best fit the requirements for such a green infrastructure in extreme climate regions with scarce water resources. Full article