Grassland Conditions Research Articles

Immobilization and stabilization of volcanic ash in soil aggregates in semiarid meadows of Northern Patagonia

Although volcanism may be perceived by the society as a phenomenon with mostly negative consequences, this is not always the case especially for natural systems. There is a limited knowledge on how the deposited pristine ash becomes immobilized and stabilized in the soil after the volcanic event. Here, we studied processes of soil aggregates formation in the buried ash layer in an early stage of the succession as well as the influence of the biological legacy (previous land management history) on these processes after the 2011 volcanic event of the Puyehue–Cordón Caulle Volcanic Complex. 5.5 years after the eruption we collected soil cores to a 10 cm depth in wet and mesic meadows with good and poor grassland conditions induced by light and heavy grazing intensity, respectively, in the East semiarid region of North Patagonia, Argentina. The ash layer was observed down to 5 cm from the soil surface, clearly differentiating a newly developed soil layer formed after the volcanic event. Accordingly, the top 5 cm were examined for the distribution of different size fractions of water-stable soil aggregates and their associated organic carbon (C) and total nitrogen (N) contents. We detected signs of physical and physicochemical changes in respect to the pristine ash collected at these sites in 2011. Soil neoformation processes were detected through the presence of large (4%) and small (21%) macroaggregates, although microaggregates (~45%) and silt + clay fractions (~29%) dominated the soil mass (ash-soil matrix: 0–5 cm depth). C and N contents decreased in a sequence: large macroaggregates ≥ small macroaggregates > microaggregates ≥ silt + clay, highlighting the importance of soil organic matter in the formation of larger-size aggregates and their quality (C and N contents). Biological legacy influenced soil aggregate formation and their quality, as reflected by a higher mass of small macroaggregates and a lower mass of microaggregates (only in mesic meadows) and by higher C and N contents under good grassland conditions. The seasonal hydrological conditions of meadow soils (i.e., soil water content, wetting and drying cycles) via effects on biological and physical processes likely resulted in a reduced aggregation in wet meadows. We noticed an incipient but present soil aggregation processes in these semiarid wetlands translated in the immobilization and stabilization of the buried ashes in the soil. The total C content in the new 0–5 cm soil layer increased at a rate of 1.0 Mg C ha−1 yr−1, on average. This indicates a functional recovery of the ecosystem along with a substantial CO2 mitigation potential in the ashes stabilized with soil organic matter, which might partially counterbalance CO2 emitted during the eruption.

Cattle Grazing Exclusion Increases Basal, Crown and Mulch Cover in the Sierra de Órganos National Park, Sombrerete, Zacatecas, Mexico

Objective: To estimate the effects of cattle grazing exclusion on soil and vegetation conditions in grasslands of Sierra de Órganos National Park (SONP), Sombrerete, Zacatecas, Mexico. Design/Methodology/Approach: Four transects with cattle grazing exclusion were strategically established in SONP grasslands. In each transect the basal, crown and organic mulch cover, soil cover, bare soil, and the form of the autumn plant were measured from 2008, 2010, 2012 and 2014. Results: Cattle grazing exclusion caused an increase in basal, crown and organic mulch cover, soil cover, as well as over- rested plants and deteriorated plants; bare soil cover and the percentage of normal plants decreased. Study Limitations/Implications: Increase of organic mulch cover implies the accumulation of combustible material that represents a potential risk of fire occurring in the SONP. Findings/Conclusions: Increase of organic mulch, over-rested plants and deteriorated plants shows that SONP grasslandsare transiting to a less stable ecological state.

Inactive and inefficient: Warming and drought effect on microbial carbon processing in alpine grassland at depth.

Subsoils contain >50% of soil organic carbon (SOC) globally yet remain under-investigated in terms of their response to climate changes. Recent evidence suggests that warmer, drier conditions in alpine grasslands induce divergent responses in SOC decomposition and carbon accrual in top- versus subsoils. However, longer term effects on microbial activity (i.e., catabolic respiration vs. anabolic growth) and belowground carbon cycling are not well understood. Here we utilized a field manipulation experiment on the Qinghai-Tibetan Plateau and conducted a 110-day soil incubation with and without 13 C-labeled grass litter to assess microbes' role as both SOC "decomposers" and "contributors" in the top- (0-10cm) versus subsoils (30-40cm) after 5years of warming and drought treatments. Microbial mineralization of both SOC and added litter was examined in tandem with potential extracellular enzyme activities, while microbial biomass synthesis and necromass accumulation were analyzed using phospholipid fatty acids and amino sugars coupled with 13 C analysis, respectively. We found that warming and, to a lesser extent, drought decreased the ratio of inorganic nitrogen (N) to water-extractable organic carbon in the subsoil, intensifying N limitation at depth. Both SOC and litter mineralization were reduced in the subsoil, which may also be related to N limitation, as evidenced by lower hydrolase activity (especially leucine aminopeptidase) and reduced microbial efficiency (lower biomass synthesis and necromass accumulation relative to respiration). However, none of these effects were observed in the topsoil, suggesting that soil microbes became inactive and inefficient in subsoil but not topsoil environments. Given increasing belowground productivity in this alpine grassland under warming, both elevated root deposits and diminished microbial activity may contribute to new carbon accrual in the subsoil. However, the sustainability of plant growth and persistence of subsoil SOC pools deserve further investigation in the long term, given the aggravated N limitation at depth.

Narrow environmental niches predict land-use responses and vulnerability of land snail assemblages

BackgroundHow land use shapes biodiversity and functional trait composition of animal communities is an important question and frequently addressed. Land-use intensification is associated with changes in abiotic and biotic conditions including environmental homogenization and may act as an environmental filter to shape the composition of species communities. Here, we investigated the responses of land snail assemblages to land-use intensity and abiotic soil conditions (pH, soil moisture), and analyzed their trait composition (shell size, number of offspring, light preference, humidity preference, inundation tolerance, and drought resistance). We characterized the species’ responses to land use to identify ‘winners’ (species that were more common on sites with high land-use intensity than expected) or ‘losers’ of land-use intensity (more common on plots with low land-use intensity) and their niche breadth. As a proxy for the environmental ‘niche breadth’ of each snail species, based on the conditions of the sites in which it occurred, we defined a 5-dimensional niche hypervolume. We then tested whether land-use responses and niches contribute to the species’ potential vulnerability suggested by the Red List status.ResultsOur results confirmed that the trait composition of snail communities was significantly altered by land-use intensity and abiotic conditions in both forests and grasslands. While only 4% of the species that occurred in forests were significant losers of intensive forest management, the proportion of losers in grasslands was much higher (21%). However, the species’ response to land-use intensity and soil conditions was largely independent of specific traits and the species’ Red List status (vulnerability). Instead, vulnerability was only mirrored in the species’ rarity and its niche hypervolume: threatened species were characterized by low occurrence in forests and low occurrence and abundance in grasslands and by a narrow niche quantified by land-use components and abiotic factors.ConclusionLand use and environmental responses of land snails were poorly predicted by specific traits or the species’ vulnerability, suggesting that it is important to consider complementary risks and multiple niche dimensions.

Fractional vegetation cover estimation in southern African rangelands using spectral mixture analysis and Google Earth Engine

Grasslands are under continuous threat of conversion and subsequent degradation, which has a detrimental impact on grassland productivity and grazing capacity, affecting the livestock industry. Fractional vegetation cover as indicator of grassland condition and productivity has been extensively researched, however, existing approaches and products are limited with respect to accessibility, affordability, applicability, and transferability. This study evaluated the use of publicly available satellite imagery, spectral mixture analysis and cloud geoprocessing technologies for dynamic, continuous, and accurate estimation of FVC for sustainable management. A linear spectral mixture model was developed, calibrated, and implemented in Google Earth Engine using Sentinel-2 and Landsat 8 imagery. Model accuracy and spatial and temporal transferability were evaluated using existing benchmark products and field data. It was found that Sentinel-2 performed the best using a feature combination of the SWIR2 band and the NDVI, EVI, MSAVI2 and DBSI indices. Accuracies were further improved by dividing the woody and bare endmembers into subclasses. The approach proved both spatially and temporally transferable, thus this research provides a robust approach to FVC estimation using limited field data and open source remote sensing imagery. The combination of this research with further grassland productivity modelling could prove valuable for sustainable environmental and economical rangeland planning and management.

Impacts of Climate Change on Hydroclimatic Conditions of U.S. National Forests and Grasslands

The conterminous United States includes national forests and grasslands that provide ecological, social, economic, recreational, and aesthetic services. Future climate change can alter long-term hydroclimatic conditions of national forests and grasslands and lead to negative consequences. This study characterizes shifts in hydroclimatology and basin characteristics of US National Forests (NFs) and National Grasslands (NGs) in response to climate change over the 21st century under the DRY, MIDDLE, and WET climate models with the representative concentration pathway (RCP) 8.5 emission scenario. Climatic projections for three climate models ranging from the driest to wettest conditions were obtained from the Multivariate Adaptive Constructed Analogs (MACA) dataset. Then, the variable infiltration capacity (VIC) model was used to model hydrological responses of the selected future climates. Changes in regional hydroclimatic conditions of NFs and NGs were assessed by the magnitude and direction of movements in the Budyko space. The Fu’s equation was applied to estimate changes in basin characteristics. The results indicate that NFs and NGs are likely to experience larger changes in basin characteristics compared to the average of the United States. In general, across the conterminous US, the NFs in mountainous regions are likely to have larger changes in hydroclimatic variables than NFs with lower elevation and NGs. Comparing Forest Service regions, Pacific Northwest, Intermountain, and Northern regions may have a less arid climate with lower freshwater availability. The Southwestern, Northern, Intermountain, and Rocky Mountain regions are likely to experience higher shifts in their basin characteristics. This study can help environmental scientists, and land and water managers improve future land management plans.

Herders’ willingness-to-participate in the Grassland Ecological Compensation and Award Policy in China: a meta-analysis

Since implementation of its first phase, the Grassland Ecological Compensation and Award Policy (GECAP; 2011–2015) has significantly influenced participants’ livelihoods in China. Willingness-to-participate (WTP) is an important component of successful policy implementation. The effects of influential factors on herders’ WTP have received considerable research effort, although no systematic literature review or quantitative analysis has been conducted to provide evidence-based policy insights. Focusing on 3405 observations extracted from 13 empirical studies, this research conducted a meta-analysis and aggregated the effects of factors affecting Chinese herders’ WTP in the GECAP. The study also analysed the heterogeneity in influential factors and its sources. Factors increasing herders’ WTP included a higher formal education level, a higher farm income from raising livestock, access to larger grassland area, improved grassland condition, and better policy understanding. The cumulative effects of the number of livestock and grassland area on herders’ WTP had increased since the policy was implemented. We examined publication bias that may arise from research with favourable results being more likely to be published and found that publication bias was statistically insignificant for the selected case studies. However, we found significant heterogeneity in household income and number of livestock. The sources of heterogeneity included regional differences, publication year, and sampling method. Future policy modification and formulation should better incentivise active participation of herders by targeting specific pastoral regions and herder groups at certain income levels and/or herd size.

Effects of supplementation strategies for beef cattle in tropical grassland conditions

This study was realized to evaluate the dry matter intake, nutrient digestibilities, and animal performance of crossbred steers grazing Brachiaria brizantha cv. Marandu, during the rainy season. Thirty-three crossbred steers with an average weight of 203.5 ± 39.5 kg were distributed in a completely randomized design with three treatments and eleven replications. The results were analyzed using an ANOVA and a Tukey test with a 5% probability of error. The three experimental diets were: MSA – mineral salt ad libitum; MSU - mineral salt + urea ad libitum and PSU - protein supplementation (0.1% of body weight). The dry matter intake of forage and total dry matter intake were similar (P > 0.05) among treatments. The dry matter, organic matter, neutral detergent fiber, crude protein, ether extract, non-fibrous carbohydrates and total carbohydrates digestibilitities coefficients were influenced (P < 0.05) by treatments. The final body weight, average daily gain, and feed efficiency were similar (P > 0.05) among treatments. The supplementation strategies used during the rainy season resulted in a similar performance; therefore, the strategy adopted could be chosen according to the economical and regional conditions of the production.

The impact of inter-observer variability on the accuracy, precision and utility of a commonly-used grassland condition index

Inter-observer variability in ecological surveying can reduce the robustness and reliability of measures used to inform habitat management. Grassland management is important across southern Africa. The Veld Condition Index (VCI) is a technique that combines field data on the relative abundance of grasses identified during a standardised survey with knowledge of how different grass species respond to grazing. This allows calculation of an Ecological Condition Index (ECI) for a particular site. The ECI value is related to threshold values to indicate grazing pressure. Here, for the first time, the effects of inter-observer variation in trained surveyors on condition assessment and resultant management recommendations are examined. There was substantial and statistically significant inter-observer variation in ECI values, driven primarily by differences in the number of times an observer identified grasses within the sample transect as being one of the species listed in the “Decreaser” category of the standardised protocol (i.e. species that decrease with grazing). Variation was random with respect to observers rather than being due to systematic (and thus predicable and potentially correctable) differences between observers. In 44% of sites, inter-observer variation resulted in important differences in assessment of grassland condition because the assessment spanned outcome threshold categories. In such cases, this could result in unnecessary or detrimental management being recommended by some observers including inappropriate burning, needlessly translocating or culling herbivores, or failing to align herbivore populations to the carrying capacity with negative effects on both grazers and veld. We recommend that a cautious approach be taken in using VCI/ECI to inform management and that identification training be focused on species in the Decreaser ecological category that drive inter-individual variation in overall ECI.

Remote Sensing of Grassland Production and Management—A Review

Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.

Effect of Grass Variety and Shade under Palm Oil Plantation on Production and Proportion of Stems, Leaves and Nutrition Content of Grass

Background and Objective: There are several varieties of grass that have resistance to shade and the quality is not disturbed by the shade. Grass that is resistant to shade will have high production and quality even though it grows in shaded areas. This research investigated the effect of grass variety and shade under palm oil plantation on fresh and dry matter production, stems and leaves proportion and nutrition content of grass. Materials and Methods: Split plot with completely randomized design was used in this study. Main plot factor was land condition of land without shade (N0) and land shaded under palm oil plantation (N1) and subplot factor was variety of grass consisted of Pennisetum purpureum (A1), Setaria sphacelata (A2) and Pennisetum purpureum cv. Mott (A3). Duncan multiple range test was performed to investigate the effect of the factors. Results: Results showed that there was interaction (p<0.01) between grass variety and land condition on proportion of stems and leaves of grass with the highest fresh and dry matter production was Pennisetum purpureum on land without shade. Under shade of oil palm plantation, Pennisetum purpureum produced the highest proportion of stems, while Pennisetum purpureum cv. Mott produced the highest proportion of leaves. Shading treatment not significant (p>0.05) on crude protein content, but it affected (p 0.05) on crude protein content, although this factor affected (p<0.05) on crude fiber content. Pennisetum purpureum cv. Mott in palm oil shade produced high crude protein (13.79%) with low crude fiber (24.63%). Conclusion: These results suggested that Pennisetum purpureum cv. Mott could be planted in shaded land.

InVEST Model-Based Estimation of Water Yield in North China and Its Sensitivities to Climate Variables

A revegetation program in North China could potentially increase carbon sequestration and mitigate climate change. However, the responses of water yield ecosystem services to climate factors are still unclear among different vegetation types, which is critically important to select appropriate species for revegetation. Based on the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, we estimated the temporal variations and associated factors in water yield ecosystem services in North China. The result showed that the InVEST model performed well in water yield estimation (R2 = 0.93), and thus can be successfully applied across the study area. The total water yield across North China is 6.19 × 1010 m3/year, with a mean water yield (MWY) of 47.15 mm/year. A large spatial difference in the MWY was found, which is strongly related to temperature, precipitation, and land use types. The responses of the MWY to mean annual precipitation (MAP) are closely tied to temperature conditions in forests and grasslands. The sensitivities of the MWY to climate variables indicated that temperature fluctuation had a positive influence on the forest MWY in humid regions, and the influence of precipitation on grassland water yield was enhanced in warmer regions. We suggest shrub and grass would be more suitable revegetation programs to improve water yield capacity, and that climate warming might increase the water yield of forests and grasslands in humid regions in North China.

Assessing the impact of drought stress on grasslands using multi-temporal SAR data of Sentinel-1: a case study in Eastern Cape, South Africa

ABSTRACT Grasslands are a major component of the natural vegetation in South Africa, it covers almost one-third of the country’s land surface. The current study focuses on assessing the impact of drought stress on communal and commercial grasslands in Eastern Cape Province using multi-temporal analysis of Sentinel-1 SAR data. Data analysis included retrieval of biophysical parameters of grasslands using Sentinel-1 SAR backscattering coefficients. Correlation analysis was performed between SAR data and NDVI values derived from Landsat-8 optical data. A linear mixed-effects regression analysis was performed for detecting the impact of drought on communal and commercial grasslands during a drought and non-drought growing seasons. Our results indicate that vegetation dynamics in grasslands in the study area are highly responsive to the climatic fluctuations. A significant correlation between backscattering coefficients of Sentinel-1 SAR data (VH and VV) and NDVI was observed for both communal and commercial grasslands (R2 = 0.89). Results also demonstrated that communal grasslands are more affected by drought impact than commercial grasslands. In commercial grasslands, management activities can improve the growing conditions of grasslands, reduce the impact of drought, and subsequently increase the resilience and productivity of this ecosystem.

Population and community‐level compositional patterns shape the realized niche of the rare arctic‐alpine species Carex lachenalii Schkuhr

The ability for vegetative growth and development of generative organs often reflects an adaptation to the environment and may be a suitable proxy for understanding population dynamics of rare relict species. An example of such a plant is Carex lachenalii Schkuhr, an arctic‐alpine species, in the temperate zone of Europe only occurring in isolated localities of high‐elevation mountain ranges. We aimed to assess whether there were relationships between flower production and clonal growth of C. lachenalii, both at the tuft and plot level, and how co‐occurring vegetation could modify this relationship. In the study we focused on population‐level traits of C. lachenalii, vegetation traits and components of functional diversity. At the tuft level we found that the proportion of flowering ramets of C. lachenalii decreased with increasing diameter of the tuft. At the plot level, in snowbed vegetation C. lachenalii produced more flowering ramets. We suggest this is due to higher environmental stress, expressed by high importance of habitat filtering (low functional dispersion) in shaping species composition of co‐occurring vegetation. In granite grasslands and milder environment (expressed by higher functional dispersion), C. lachenalii produced more vegetative ramets, which we suggest is a result of a more competitive environment. While in snowbeds investment in flowering ramets could promote successful persistence of C. lachenalii, survival of subpopulations occurring in the highly competitive conditions of granite grasslands may be uncertain due to potentially weak adaptation to competition with graminoids and dwarf shrubs.

Plant functional β diversity is an important mediator of effects of aridity on soil multifunctionality

Previous studies have demonstrated that plant diversity not only plays an important role in maintaining ecosystem functions but can also mediate the impact of climate change on ecosystem functions. However, the relative importance of multiple aspects of diversity at different scales remains unclear. In this study, we investigated species, functional, and phylogenetic aspects of diversity at α and β scales, and measured eight soil functions (aboveground productivity, soil organic carbon, total soil nitrogen, total soil phosphorus, soil available nitrogen, soil available phosphorus, soil carbon-nitrogen ratio, and soil nitrogen-phosphorus ratio) to comprehensively assess the relationship between multiple aspects and scales of plant diversity and soil multifunctionality along an aridity gradient across the grasslands of Inner Mongolia. Diversity at α and β scales explained soil multifunctionality synergistically. Functional diversity explained most of the soil multifunctionality, while phylogenetic diversity explained the least. Aridity had both direct effects on soil multifunctionality, and indirect effects mediated mainly by functional α and β diversity. These findings indicate that in addition to α diversity, β diversity also played an important role in maintaining soil multifunctionality, and was an important mediator for the adverse impact of aridity on soil multifunctionality. Our study highlights the critical role of β diversity, especially regarding functional traits, in predicting the consequences of the increasingly arid conditions in the Inner Mongolian grasslands.

Soil total nitrogen estimation of alpine grassland using visible/near-infrared spectra: a comparison of multivariate techniques with different spectral transformations

Rapid, precise, and quantitative assessment of soil total nitrogen (TN) of alpine grassland is crucial for monitoring the environmental conditions of grasslands. The right choice of preprocessing and calibration methods may improve the model performance of soil property estimation in visible/near infrared reflectance spectroscopy (VNIRS). VNIRS (350 to 2500 nm) measurements were made of 80 soil samples from the northeast part of the Tibetan Plateau. To reduce the signal noise, the Savitzky–Golay technique was implemented and six spectral transformations were evaluated with the aim of identifying the best transformation for predicting soil TN. The performance of three linear calibration models, namely, stepwise multiple linear regression, principal component regression, partial least squares regression (PLSR), and a combination of these models with a nonlinear back propagation neural network (BPNN) was tested for accuracy in the measurement of soil TN. Our results indicate the following: (1) models using the derivative transformations of spectra as inputs perform better than those using nonderivative transformations, and the first derivative of the reciprocal of reflectance [(1 / R) ′ ] is the best spectral transformation for soil TN estimation; (2) models based on the PLSR and companion BPNN-latent variables (LVs) yield better predictions and smallest errors of soil TN. We demonstrate that (1 / R) ′ is the best spectral transformation and consistently improves the estimation models of soil TN. Among multivariate techniques, the BPNN-LVs is recommended for estimation of soil TN with great accuracy.

Mapping Kenyan Grassland Heights Across Large Spatial Scales with Combined Optical and Radar Satellite Imagery

Grassland monitoring can be challenging because it is time-consuming and expensive to measure grass condition at large spatial scales. Remote sensing offers a time- and cost-effective method for mapping and monitoring grassland condition at both large spatial extents and fine temporal resolutions. Combinations of remotely sensed optical and radar imagery are particularly promising because together they can measure differences in moisture, structure, and reflectance among land cover types. We combined multi-date radar (PALSAR-2 and Sentinel-1) and optical (Sentinel-2) imagery with field data and visual interpretation of aerial imagery to classify land cover in the Masai Mara National Reserve, Kenya using machine learning (Random Forests). This study area comprises a diverse array of land cover types and changes over time due to seasonal changes in precipitation, seasonal movements of large herds of resident and migratory ungulates, fires, and livestock grazing. We classified twelve land cover types with user’s and producer’s accuracies ranging from 66%–100% and an overall accuracy of 86%. These methods were able to distinguish among short, medium, and tall grass cover at user’s accuracies of 83%, 82%, and 85%, respectively. By yielding a highly accurate, fine-resolution map that distinguishes among grasses of different heights, this work not only outlines a viable method for future grassland mapping efforts but also will help inform local management decisions and research in the Masai Mara National Reserve.

The mathematical and experimental analysis on the steady-state operating temperature of bifacial photovoltaic modules

The operating temperature of bifacial photovoltaic (PV) module affects its power generation and reliability. Combined with view factor model of ground reflectivity on module backside, a thermal steady-state model is established to analyze the thermal performance of bifacial module in this paper. The module operating temperatures under three different installation conditions of roof cement ground, water surface and grassland are calculated and simulated by ANSYS software, and the experiments are designed to analyze and verify it. Based on the difference of reflectivity and heat capacity of different ground for the PV module installation, the effects of ground type and module material on bifacial module temperature and its mechanism are analyzed quantitatively. According to the simulation and experiment results, the operating temperatures of the bifacial modules installed on the roof cement ground, water surface and grassland are 44.7 °C, 41.5 °C, 43.2 °C respectively, under the setting environment condition with specific irradiance, wind speed and ambient temperature. The temperature difference of 1.7 °C–3.2 °C is caused by ground reflectivity and temperature. The operating temperature difference between glass-glass and glass-backsheet module is less than 0.4 °C under the standard condition. The conductivity and emissivity of encapsulation material does not show strong influence on module operating temperature.

Cooperative grassland management practices promoted by land tenure system transformation benefit social-ecological systems of pastoralism on the Qinghai-Tibetan plateau, China

China has recently implemented the latest rural land tenure reform with the “Separating Three Property Rights” as non-tradable land ownership, non-tradable land contracting right and tradable land use right, leading to a dramatic change in grassland management strategies in vast pastoral areas. However, the impact of this new reform on grassland management practices is widely debated by scholars and policy analysts. To identify the factors impacting the pastoralists' choice of grassland management practice and the social, economic and ecological benefits derived from different grassland management practices, we conducted a field survey of pastoralists (n = 259) in 7 counties on the Qinghai-Tibetan Plateau. The results showed that respondents' gender, grassland area, scale and location of the village, grassland condition perception significantly exerted positive influence on pastoralists' willingness to participate in cooperative grassland management practices, while grassland fence and urban life expectation negatively influenced the willingness. We found that cooperative grassland management practices led to significantly higher household incomes, more equal gender relationships and better-managed grasslands than individual ones. In spite of this, there were still a large number of pastoralists who chose individual grassland management practices due to their long-term customary operations. In conclusion, this new rural land tenure reform has facilitated pastoralists’ choice for diverse grassland management practices and the promoted voluntary large-scale cooperative grassland management practices benefit the social-ecological system of pastoralism.

Using phytolith analysis to reconstruct prehistoric fire regimes in central coastal California

Over the last century, northern coastal scrub has encroached into open grasslands along the central California coast, increasing fire risk in coastal wildland–urban interfaces. Understanding prehistoric ecological conditions is crucial for fire mitigation projects. Current estimates of these conditions in coastal California grasslands and shrublands are largely speculative because tree ring data, lake sediment evidence and ethnographic information are sparse. Phytolith analysis is an alternative palaeoecological tool that has been successfully used to reconstruct the extent of prehistoric grass cover in California. Our study uses phytolith analysis of soil samples from the East Bay hills of the San Francisco Bay region as a novel approach to estimate prehistoric grassland distribution and infer fire frequency in central coastal California. Our data strongly indicate that many areas in the region were dominated by perennial bunchgrasses for at least several hundred years before European contact. Because grass-dominated grasslands in the East Bay hills are disturbance-dependent, our data suggest prehistoric fire frequency was of the order of 5 years or less in the region. Phytolith analysis is a useful technique for prehistoric fire regime reconstruction for grasslands and shrublands worldwide, leading to improved, data-based land management.