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Zhang F, Wu W, Li L, Liu X, Zhou G, Xu Z. Predicting community traits along an alpine grassland transect using field imaging spectroscopy. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2023; 65:2604-2618. [PMID: 37837189 DOI: 10.1111/jipb.13572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/12/2023] [Indexed: 10/15/2023]
Abstract
Assessing plant community traits is important for understanding how terrestrial ecosystems respond and adapt to global climate change. Field hyperspectral remote sensing is effective for quantitatively estimating vegetation properties in most terrestrial ecosystems, although it remains to be tested in areas with dwarf and sparse vegetation, such as the Tibetan Plateau. We measured canopy reflectance in the Tibetan Plateau using a handheld imaging spectrometer and conducted plant community investigations along an alpine grassland transect. We estimated community structural and functional traits, as well as community function based on a field survey and laboratory analysis using 14 spectral vegetation indices (VIs) derived from hyperspectral images. We quantified the contributions of environmental drivers, VIs, and community traits to community function by structural equation modelling (SEM). Univariate linear regression analysis showed that plant community traits are best predicted by the normalized difference vegetation index, enhanced vegetation index, and simple ratio. Structural equation modelling showed that VIs and community traits positively affected community function, whereas environmental drivers and specific leaf area had the opposite effect. Additionally, VIs integrated with environmental drivers were indirectly linked to community function by characterizing the variations in community structural and functional traits. This study demonstrates that community-level spectral reflectance will help scale plant trait information measured at the leaf level to larger-scale ecological processes. Field imaging spectroscopy represents a promising tool to predict the responses of alpine grassland communities to climate change.
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Affiliation(s)
- Feng Zhang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wenjuan Wu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lang Li
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaodi Liu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Guangsheng Zhou
- Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Zhenzhu Xu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
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Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage. REMOTE SENSING 2022. [DOI: 10.3390/rs14040854] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle.
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Zakharova L, Meyer K, Seifan M. Trait-based modelling in ecology: A review of two decades of research. Ecol Modell 2019. [DOI: 10.1016/j.ecolmodel.2019.05.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Abstract
Towards the need for sustainable development, remote sensing (RS) techniques in the Visible-Near Infrared–Shortwave Infrared (VNIR–SWIR, 400–2500 nm) region could assist in a more direct, cost-effective and rapid manner to estimate important indicators for soil monitoring purposes. Soil reflectance spectroscopy has been applied in various domains apart from laboratory conditions, e.g., sensors mounted on satellites, aircrafts and Unmanned Aerial Systems. The aim of this review is to illustrate the research made for soil organic carbon estimation, with the use of RS techniques, reporting the methodology and results of each study. It also aims to provide a comprehensive introduction in soil spectroscopy for those who are less conversant with the subject. In total, 28 journal articles were selected and further analysed. It was observed that prediction accuracy reduces from Unmanned Aerial Systems (UASs) to satellite platforms, though advances in machine learning techniques could further assist in the generation of better calibration models. There are some challenges concerning atmospheric, radiometric and geometric corrections, vegetation cover, soil moisture and roughness that still need to be addressed. The advantages and disadvantages of each approach are highlighted and future considerations are also discussed at the end.
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Li Z, Sun Z, Tian Y, Zhong J, Yang W. Impact of Land Use/Cover Change on Yangtze River Delta Urban Agglomeration Ecosystem Services Value: Temporal-Spatial Patterns and Cold/Hot Spots Ecosystem Services Value Change Brought by Urbanization. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16010123. [PMID: 30621215 PMCID: PMC6338953 DOI: 10.3390/ijerph16010123] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 12/18/2018] [Accepted: 12/29/2018] [Indexed: 11/16/2022]
Abstract
Land use/cover change (LUCC) from increased urbanization significantly impacts regional ecosystem services. Based on a cold/hot spots analysis, this paper used grain yield, food prices, price index statistics, and a land use thematic map to study the impact of LUCC on four ecosystem services values (ESVs) in the Yangtze River Delta urban agglomeration, and determine the spatial differences resulting from the rapid urbanization LUCC. The correlation between the four ecosystem services was then studied and sensitivity analyses conducted to investigate whether any changes in the ESVs could lead to unacceptable unit value transfer uncertainties. It was found that most urban land was converted from farmland, and that before 2000, the total ESVs and the regulating services values (RSVs) increased significantly, after which it declined, the provisioning services values (PSVs) declined year on year, the habitat services value (HSV) and cultural and amenity services value (CSV) declined sharply after 2000, and the spatial distribution of the four ESVs were significantly different. Over time, it was found that the hot spots were shrinking and the cold spots were spreading. The provisioning services were found to be negatively correlated with habitat services and cultural and amenity services, the regulating services were weakly positively correlated with the provisioning services and significantly positively correlated with the habitat services and cultural and amenity services, and the habitat services were significantly positively correlated with cultural and amenity services. In the Yangtze River Delta urban agglomeration, the water area is the most important for the total ESVs, followed by non-bush forest. Paddy field is ranked third. Dryland, bush, grassland, and wetland are less important. The importance of barren land is almost zero. This research provides the government with a scientific basis from which to formulate spatial planning and environmental protection policies for ecological sustainable development in the Yangtze River Delta urban agglomeration.
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Affiliation(s)
- Zhigang Li
- College of Management Science, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
- Key Laboratory of GeoSpatial Information Technology of Ministry of Land and Resources, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
| | - Zishu Sun
- College of Earth Sciences, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
| | - Yangjie Tian
- College of Earth Sciences, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
| | - Jialong Zhong
- College of Earth Sciences, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
| | - Wunian Yang
- Key Laboratory of GeoSpatial Information Technology of Ministry of Land and Resources, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
- College of Earth Sciences, Chengdu University of Technology, No.1 Dongsan Road, Erxian Bridge, Chenghua District, Chengdu 610059, China.
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Roces-Díaz JV, Vayreda J, Banqué-Casanovas M, Díaz-Varela E, Bonet JA, Brotons L, de-Miguel S, Herrando S, Martínez-Vilalta J. The spatial level of analysis affects the patterns of forest ecosystem services supply and their relationships. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 626:1270-1283. [PMID: 29898535 DOI: 10.1016/j.scitotenv.2018.01.150] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 01/15/2018] [Accepted: 01/15/2018] [Indexed: 06/08/2023]
Abstract
The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation.
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Affiliation(s)
- José V Roces-Díaz
- CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; Agroscope, Reckenholzstr. 191, CH-8046 Zurich, Switzerland.
| | - Jordi Vayreda
- CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain
| | | | - Emilio Díaz-Varela
- ECOAGRASOC Research Group, Department of Agricultural and Forestry Engineering, University of Santiago de Compostela, Escola Politécnica Superior, Campus Universitario, s/n. E27002 Lugo, Galicia, Spain
| | - Jose A Bonet
- Forest Science Center of Catalonia (CTFC), E25280 Solsona, Catalonia, Spain; Department of Crop and Forest Sciences, Universitat de Lleida-Agrotecnio Center (UdL-Agrotecnio), Av. Rovira Roure, 191, E25198 Lleida, Catalonia, Spain
| | - Lluis Brotons
- CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; Forest Science Center of Catalonia (CTFC), E25280 Solsona, Catalonia, Spain; Consejo Superior de Investigaciones Científicas (CSIC), E08193 Cerdanyola del Valles, Catalonia, Spain
| | - Sergio de-Miguel
- Department of Crop and Forest Sciences, Universitat de Lleida-Agrotecnio Center (UdL-Agrotecnio), Av. Rovira Roure, 191, E25198 Lleida, Catalonia, Spain
| | - Sergi Herrando
- CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; Catalan Ornithological Institute, Natural History Museum of Barcelona, E08019 Barcelona, Catalonia, Spain
| | - Jordi Martínez-Vilalta
- CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; Universitat Autònoma de Barcelona, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain
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Roces-Díaz JV, Burkhard B, Kruse M, Müller F, Díaz-Varela ER, Álvarez-Álvarez P. Use of ecosystem information derived from forest thematic maps for spatial analysis of ecosystem services in northwestern Spain. LANDSCAPE AND ECOLOGICAL ENGINEERING 2016. [DOI: 10.1007/s11355-016-0298-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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