Pyric–Herbivory and Cattle Performance in Grassland Ecosystems

AbstractArbuscular mycorrhizal (AM) fungi can successfully enhance photosynthesis (Pn) and plants growth in agricultural or grassland ecosystems. However, how the symbionts affect species restoration in sunlight-intensive areas remains largely unexplored. Therefore, this study’s objective was to assess the effect of AM fungi on apricot seedling physiology, within a specific time period, in northwest China. In 2010, an experimental field was established in Shaanxi Province, northwest China. The experimental treatments included two AM fungi inoculation levels (0 or 100 g of AM fungal inoculum per seedling), three shade levels (1900, 1100, and 550 µmol m−2 s−1), and three ages (1, 3, and 5 years) of transplantation. We examined growth, Pn, and morphological indicators of apricot (Prunus sibirica L.) seedling performances in 2011, 2013, and 2015. The colonization rate in mycorrhizal seedlings with similar amounts of shade is higher than the corresponding controls. The mycorrhizal seedling biomass is significantly higher than the corresponding non-mycorrhizal seedling biomass. Generally, Pn, stomatal conductance (Gs), transpiration rate (Tr), and water use efficiency are also significantly higher in the mycorrhizal seedlings. Moreover, mycorrhizal seedlings with light shade (LS) have the highest Pn. WUE is increased in non-mycorrhizal seedlings because of the reduction in Tr, while Tr is increased in mycorrhizal seedlings with shade. There is a significant increase in the N, P, and K fractions detected in roots compared with shoots. This means that LS had apparent benefits for mycorrhizal seedlings. Our results also indicate that AM fungi, combined with LS, exert a positive effect on apricot behavior.

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Using UAV Imagery to Detect and Map Woody Species Encroachment in a Subalpine Grassland: Advantages and Limits

Remote Sensing ◽

10.3390/rs13071239 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1239

Author(s):

Ludovica Oddi ◽

Edoardo Cremonese ◽

Lorenzo Ascari ◽

Gianluca Filippa ◽

Marta Galvagno ◽

...

Keyword(s):

Reference Data ◽

Woody Species ◽

Accurate Method ◽

Machine Learning Algorithms ◽

Italian Alps ◽

Photo Interpretation ◽

Tree Detection ◽

Grassland Ecosystems ◽

Object Based ◽

Rgb Images

Woody species encroachment on grassland ecosystems is occurring worldwide with both negative and positive consequences for biodiversity conservation and ecosystem services. Remote sensing and image analysis represent useful tools for the monitoring of this process. In this paper, we aimed at evaluating quantitatively the potential of using high-resolution UAV imagery to monitor the encroachment process during its early development and at comparing the performance of manual and semi-automatic classification methods. The RGB images of an abandoned subalpine grassland on the Western Italian Alps were acquired by drone and then classified through manual photo-interpretation, with both pixel- and object-based semi-automatic models, using machine-learning algorithms. The classification techniques were applied at different resolution levels and tested for their accuracy against reference data including measurements of tree dimensions collected in the field. Results showed that the most accurate method was the photo-interpretation (≈99%), followed by the pixel-based approach (≈86%) that was faster than the manual technique and more accurate than the object-based one (≈78%). The dimensional threshold for juvenile tree detection was lower for the photo-interpretation but comparable to the pixel-based one. Therefore, for the encroachment mapping at its early stages, the pixel-based approach proved to be a promising and pragmatic choice.

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Are arthropod communities in grassland ecosystems affected by the abundance of an invasive plant?

Oecologia ◽

10.1007/s00442-020-04833-3 ◽

2021 ◽

Author(s):

Jordann G. Foster ◽

Chantalle A. Gervan ◽

Matthew G. Coghill ◽

Lauchlan H. Fraser

Keyword(s):

Invasive Plant ◽

Arthropod Communities ◽

Grassland Ecosystems

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N Management of European Grasslands: Can the Exchange of Gaseous N Species Be Influenced at the Operational Level?

The Scientific World JOURNAL ◽

10.1100/tsw.2001.373 ◽

2001 ◽

Vol 1 ◽

pp. 652-657 ◽

Cited By ~ 1

Author(s):

P. Calanca ◽

A. Neftel ◽

J. Fuhrer

Keyword(s):

Late Summer ◽

Fertilizer Application ◽

Effective Control ◽

Management Options ◽

Total N ◽

Model Calculations ◽

Weather Forecasts ◽

Grassland Ecosystems ◽

Order Of Magnitude ◽

N Management

Grassland ecosystems can be regarded as biochemical reactors in which large amounts of organic nitrogen (N) are converted into inorganic N, and vice versa. If managed in a sustainable manner, grasslands should operate in a quasi steady state, characterized by an almost perfect balance between total N input and output. As a consequence, the exchange of gaseous N species (NH3, NO, NO2, N2O, and N2) between grasslands and the atmosphere is very small compared to the total N turnover. In this study, the effects of two management options (mowing and fertilization) on production and emission of nitrous oxide (N2O) from a grass/clover crop were examined on the basis of observations and model results referring to an experiment carried out on the Swiss Plateau in late summer of 2000. It was found that production and emission of N2O induced by mowing were of the same order of magnitude as those brought about by fertilization, suggesting a possible transfer of N from clover to the soil after defoliation. Emissions were strongly modulated by precipitation on time scales ranging from 1 day to 1 week. This indicates that effective control of N2O emissions through management on a day-to-day basis requires reliable medium-range weather forecasts. Model calculations were not able to reproduce essential characteristics of the emissions. The model slightly overestimated the background emissions, but severely underestimated the emission peaks following fertilizer application, and largely failed to reproduce emission induced by mowing. Shortfalls in the model used for this study were found in relation to the description of soil-water fluxes, soil organic matter, and the physiology of clover.

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Spatial-Temporal Patterns and Controls of Evapotranspiration across the Tibetan Plateau (2000–2012)

Advances in Meteorology ◽

10.1155/2017/7082606 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 12

Author(s):

Hao Zhang ◽

Jian Sun ◽

Junnan Xiong

Keyword(s):

Tibetan Plateau ◽

Environmental Factors ◽

Vegetation Type ◽

Middle Part ◽

Rate Of Change ◽

Ecological Indicator ◽

The Tibetan Plateau ◽

Grassland Ecosystems ◽

Key Factor ◽

Positive Correlations

Evapotranspiration (ET) is a key factor to further our understanding of climate change processes, especially on the Tibetan Plateau, which is sensitive to global change. Herein, the spatial patterns of ET are examined, and the effects of environmental factors on ET at different scales are explored from the years 2000 to 2012. The results indicated that a steady trend in ET was detected over the past decade. Meanwhile, the spatial distribution shows an increase of ET from the northwest to the southeast, and the rate of change in ET is lower in the middle part of the Tibetan Plateau. Besides, the positive effect of radiation on ET existed mainly in the southwest. Based on the environment gradient transects, the ET had positive correlations with temperature (R>0.85, p<0.0001), precipitation (R > 0.89, p < 0.0001), and NDVI (R > 0.75, p < 0.0001), but a negative correlation between ET and radiation (R = 0.76, p < 0.0001) was observed. We also found that the relationships between environmental factors and ET differed in the different grassland ecosystems, which indicated that vegetation type is one factor that can affect ET. Generally, the results indicate that ET can serve as a valuable ecological indicator.

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Potential and Limitations of Grasslands α-Diversity Prediction Using Fine-Scale Hyperspectral Imagery

Remote Sensing ◽

10.3390/rs13142649 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2649

Author(s):

Hafiz Ali Imran ◽

Damiano Gianelle ◽

Michele Scotton ◽

Duccio Rocchini ◽

Michele Dalponte ◽

...

Keyword(s):

Species Richness ◽

Well Being ◽

Hyperspectral Data ◽

Hyperspectral Images ◽

Grassland Species ◽

Biodiversity Indices ◽

Grassland Ecosystems ◽

Natural Grasslands ◽

Α Diversity ◽

Diversity Metrics

Plant biodiversity is an important feature of grassland ecosystems, as it is related to the provision of many ecosystem services crucial for the human economy and well-being. Given the importance of grasslands, research has been carried out in recent years on the potential to monitor them with novel remote sensing techniques. In this study, the optical diversity (also called spectral diversity) approach was adopted to check the potential of using high-resolution hyperspectral images to estimate α-diversity in grassland ecosystems. In 2018 and 2019, grassland species composition was surveyed and canopy hyperspectral data were acquired at two grassland sites: Monte Bondone (IT-MBo; species-rich semi-natural grasslands) and an experimental farm of the University of Padova, Legnaro, Padua, Italy (IT-PD; artificially established grassland plots with a species-poor mixture). The relationship between biodiversity (species richness, Shannon’s, species evenness, and Simpson’s indices) and optical diversity metrics (coefficient of variation-CV and standard deviation-SD) was not consistent across the investigated grassland plant communities. Species richness could be estimated by optical diversity metrics with an R = 0.87 at the IT-PD species-poor site. In the more complex and species-rich grasslands at IT-MBo, the estimation of biodiversity indices was more difficult and the optical diversity metrics failed to estimate biodiversity as accurately as in IT-PD probably due to the higher number of species and the strong canopy spatial heterogeneity. Therefore, the results of the study confirmed the ability of spectral proxies to detect grassland α-diversity in man-made grassland ecosystems but highlighted the limitations of the spectral diversity approach to estimate biodiversity when natural grasslands are observed. Nevertheless, at IT-MBo, the optical diversity metric SD calculated from post-processed hyperspectral images and transformed spectra showed, in the red part of the spectrum, a significant correlation (up to R = 0.56, p = 0.004) with biodiversity indices. Spatial resampling highlighted that for the IT-PD sward the optimal optical pixel size was 1 cm, while for the IT-MBo natural grassland it was 1 mm. The random pixel extraction did not improve the performance of the optical diversity metrics at both study sites. Further research is needed to fully understand the links between α-diversity and spectral and biochemical heterogeneity in complex heterogeneous ecosystems, and to assess whether the optical diversity approach can be adopted at the spatial scale to detect β-diversity. Such insights will provide more robust information on the mechanisms linking grassland diversity and optical heterogeneity.

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