scholarly journals A Vegetation and Soil Survey Method for Surveillance Monitoring of Rangeland Environments

2019 ◽  
Author(s):  
Ben Sparrow ◽  
Jeff Foulkes ◽  
Glenda Wardle ◽  
Emrys Leitch ◽  
Stefan Caddy-Retalic ◽  
...  
Keyword(s):  
Soil Survey ◽  
Research Network ◽  
Survey Method ◽  
Permanent Plots ◽  
Differential Gps ◽  
Monitoring Method ◽  
Area Index ◽  
Ecosystem Research ◽  
Soil Attributes ◽  
Advanced Analysis

Ecosystem surveillance monitoring is critical to managing natural resources and especially so under changing environments. Despite this importance, the design and implementation of monitoring programs across large temporal and spatial scales has been hampered by the lack of appropriately standardised methods and data streams. To address this gap, we outline a surveillance monitoring method based on permanent plots and voucher samples suited to rangeland environments around the world that is repeatable, cost-effective, appropriate for large-scale comparisons and adaptable to other global biomes. The method provides comprehensive data on vegetation composition and structure along with soil attributes relevant to plant growth, delivered as a combination of modules that can be targeted for different purposes or available resources. Plots are located in a stratified design across vegetation units, landforms and climates to enhance continental and global comparisons. Changes are investigated through revisits. Vegetation is measured to inform on composition, cover and structure. Samples of vegetation and soils are collected and tracked by barcode labels and stored long-term for subsequent analysis. Technology is used to enhance the accuracy of field methods, including differential GPS r plot locations, instrument based Leaf Area Index (LAI) measures, and three dimensional photo-panoramas for advanced analysis. A key feature of the method is the use of electronic field data collection to enhance data delivery into a publicly-accessible database.Our method is pragmatic, whilst still providing consistent data, information and samples on key vegetation and soil attributes. The method is operational and has been applied at more than 704 field locations across the Australian rangelands as part of the Ecosystem Surveillance program of the Terrestrial Ecosystem Research Network (TERN). The methodology enables continental analyses, and has been tested in communities broadly representative of rangelands globally, with components being applicable to other biomes. Here we also recommend the consultative process and guiding principles that drove the development of this method as an approach for development of the method into other biomes. The consistent, standardised and objective method enables continental, and potentially global analyses than were not previously possible with disparate programs and datasets.

scholarly journals Reference carbon cycle dataset for typical Chinese forests via colocated observations and data assimilation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Honglin He ◽  
Rong Ge ◽  
Xiaoli Ren ◽  
Li Zhang ◽  
Qingqing Chang ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Global Climate ◽  
Meteorological Data ◽  
C Sequestration ◽  
Research Network ◽  
Soil Biology ◽  
Area Index ◽  
Ecosystem Research ◽  
Organic C ◽  
C Cycle

AbstractChinese forests cover most of the representative forest types in the Northern Hemisphere and function as a large carbon (C) sink in the global C cycle. The availability of long-term C dynamics observations is key to evaluating and understanding C sequestration of these forests. The Chinese Ecosystem Research Network has conducted normalized and systematic monitoring of the soil-biology-atmosphere-water cycle in Chinese forests since 2000. For the first time, a reference dataset of the decadal C cycle dynamics was produced for 10 typical Chinese forests after strict quality control, including biomass, leaf area index, litterfall, soil organic C, and the corresponding meteorological data. Based on these basic but time-discrete C-cycle elements, an assimilated dataset of key C cycle parameters and time-continuous C sequestration functions was generated via model-data fusion, including C allocation, turnover, and soil, vegetation, and ecosystem C storage. These reference data could be used as a benchmark for model development, evaluation and C cycle research under global climate change for typical forests in the Northern Hemisphere.

scholarly journals A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981–2015

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhongen Niu ◽  
Honglin He ◽  
Gaofeng Zhu ◽  
Xiaoli Ren ◽  
Li Zhang ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Terrestrial Ecosystem ◽  
Research Network ◽  
Energy Budgets ◽  
Climate Data ◽  
Area Index ◽  
Large Variability ◽  
Ecosystem Research ◽  
Insight Into

Abstract The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface-atmosphere interactions. However, several studies have documented a large variability in T/ET. In this paper, we present a new T/ET dataset (also including transpiration, evapotranspiration data) for China from 1981 to 2015 with spatial and temporal resolutions of 0.05° and 8 days, respectively. The T/ET dataset is based on a model-data fusion method that integrates the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model with multivariate observational datasets (transpiration and evapotranspiration). The dataset is driven by satellite-based leaf area index (LAI) data from GLASS and GLOBMAP, and climate data from the Chinese Ecosystem Research Network (CERN). Observational annual T/ET were used to validate the model, with R2 and RMSE values were 0.73 and 0.07 (12.41%), respectively. The dataset provides significant insight into T/ET and its changes over the Chinese terrestrial ecosystem and will be beneficial for understanding the hydrological cycle and energy budgets between the land and the atmosphere.

scholarly journals Exploring the Potential of DSCOVR EPIC Data to Retrieve Clumping Index in Australian Terrestrial Ecosystem Research Network Observing Sites

2021 ◽  
Vol 2 ◽  
Author(s):  
Jan Pisek ◽  
Stefan K. Arndt ◽  
Angela Erb ◽  
Elise Pendall ◽  
Crystal Schaaf ◽  
...  
Keyword(s):  
Terrestrial Ecosystem ◽  
Earth Observation ◽  
Research Network ◽  
Area Index ◽  
Diverse Range ◽  
General Validity ◽  
Ecosystem Research ◽  
Wide Range ◽  
Clumping Index ◽  
Foliage Clumping

Vegetation foliage clumping significantly alters the radiation environment and affects vegetation growth as well as water, carbon cycles. The clumping index (CI) is useful in ecological and meteorological models because it provides new structural information in addition to the effective leaf area index. Previously generated CI maps using a diverse set of Earth Observation multi-angle datasets across a wide range of scales have all relied on the single approach of using the normalized difference hotspot and darkspot (NDHD) method. We explore an alternative approach to estimate CI from space using the unique observing configuration of the Deep Space Climate Observatory Earth Polychromatic Imaging Camera (DSCOVR EPIC) and associated products at 10 km resolution. The performance was evaluated with in situ measurements in five sites of the Australian Terrestrial Ecosystem Research Network comprising a diverse range of canopy structure from short and sparse to dense and tall forest. The DSCOVR EPIC data can provide meaningful CI retrievals at the given spatial resolution. Independent but comparable CI retrievals obtained with a completely different sensor and new approach were encouraging for the general validity and compatibility of the foliage clumping information retrievals from space. We also assessed the spatial representativeness of the five TERN sites with respect to a particular point in time (field campaigns) for satellite retrieval validation. Our results improve our understanding of product uncertainty both in terms of the representativeness of the field data collected over the TERN sites and its relationship to Earth Observation data at different spatial resolutions.

scholarly journals Enfoque de tarjeta de puntuación para medir la sostenibilidad de cooperativas seleccionadas en la zona de West Shoa, estado regional de Oromia, Etiopía

2021 ◽  
Vol 12 (2) ◽  
pp. e3844
Author(s):  
Muthumariappan Karthikeyan
Keyword(s):  
Environmental Sustainability ◽  
Sampling Method ◽  
Research Network ◽  
Survey Method ◽  
Agricultural Cooperatives ◽  
Competitive Strategies ◽  
Inequality Index ◽  
Score Card ◽  
Multi Stage ◽  
Favourable Situation

The present paper analyzed the economic, social, and environmental dimensions of cooperatives sustainability and examined the sustainability oriented competitive strategies adopted by sample cooperatives. Field survey method will be followed. Multi-stage sampling method was adopted to select study area, cooperatives and respondents. Six cooperatives and by adopting PPS 100 members were selected. The sustainability score card approach advocated by Measuring Cooperative Difference Research Network (MDCRN), Canada and Morris Inequality Index were used. The result shows that the agricultural cooperatives do have better position with economic sustainability, to some extent social sustainability, but they do not have favourable situation in environmental sustainability so that the cooperatives are located at moderate and low level of sustainability condition. With regard to comprehensive cooperative sustainability the same result is seen among sampled cooperatives. Sustainability level and ranking are in consonance with the strategies they adopted and right strategy at right time effectively is advocated.

Building Australia’s Scalable Drone Cloud

2021 ◽  
Author(s):  
Jens Klump ◽  
Tim Brown ◽  
Rohan Clarke ◽  
Robert Glasgow ◽  
Steve Micklethwaite ◽  
...  
Keyword(s):  
Data Management ◽  
Best Practice ◽  
Management Practices ◽  
Agricultural Research ◽  
Terrestrial Ecosystem ◽  
Large Data ◽  
Sensor Data ◽  
Research Network ◽  
Ecosystem Research ◽  
Plant Phenomics

<p>Remotely Piloted Aircraft (RPA), commonly known as drones, provide sensing capabilities that address the critical scale-gap between ground- and satellite-based observations. Their versatility allows researchers to deliver near-real-time information for society.</p><p>Key to delivering RPA information is the capacity to enable researchers to systematically collect, process, manage and share RPA-borne sensor data. Importantly, this should allow vertical integration across scales and horizontal integration across different RPA deployments. However, as an emerging technology, the best practice and standards are still developing and the large data volumes collected during RPA missions can be challenging.</p><p>Australia’s Scalable Drone Cloud (ASDC) aims to coordinate and standardise how scientists from across earth, environmental and agricultural research manage, process and analyse data collected by RPA-borne sensors, by establishing best practices in managing 3D-geospatial data and aligned with the FAIR data principles.</p><p>The ASDC is building a cloud-native platform for research drone data management and analytics, driven by exemplar data management practices, data-processing pipelines, and search and discovery of drone data. The aim of the platform is to integrate sensing capabilities with easy-to-use storage, processing, visualisation and data analysis tools (including computer vision / deep learning techniques) to establish a national ecosystem for drone data management.</p><p>The ASDC is a partnership of the Monash Drone Discovery Platform, CSIRO and key National Collaborative Research Infrastructure (NCRIS) capabilities including the Australian Research Data Commons (ARDC), Australian Plant Phenomics Facility (APPF), Terrestrial Ecosystem Research Network (TERN), and AuScope.</p><p>This presentation outlines the roadmap and first proof-of-concept implementation of the ASDC.</p>

scholarly journals First Effort at Constructing a High-Density Photosynthetically Active Radiation Dataset during 1961–2014 in China

2019 ◽  
Vol 32 (10) ◽  
pp. 2761-2780 ◽  
Author(s):  
Wenmin Qin ◽  
Lunche Wang ◽  
Ming Zhang ◽  
Zigeng Niu ◽  
Ming Luo ◽  
...  
Keyword(s):  
Photosynthetically Active Radiation ◽  
Back Propagation ◽  
Control Process ◽  
High Density ◽  
Research Network ◽  
Bias Error ◽  
Ecosystem Research ◽  
Vegetation Growth ◽  
Active Radiation ◽  
Quality Control Process

Abstract Photosynthetically active radiation (PAR) is a key factor for vegetation growth and climate change. Different types of PAR models, including four physically based models and eight artificial intelligence (AI) models, were proposed for predicting daily PAR. Multiyear daily meteorological parameters observed at 29 Chinese Ecosystem Research Network (CERN) stations and 2474 Chinese Meteorological Administration (CMA) stations across China were used for testing, validating, and comparing the above models. The optimized back propagation (BP) neural network based on the mind evolutionary algorithm (MEA-BP) was the model with highest accuracy and strongest robustness. The correlation coefficient R, mean absolute bias error (MAE), and RMSE for MEA-BP were 0.986, 0.302 MJ m−2 day−1 and 0.393 MJ m−2 day−1, respectively. Then, a high-density PAR dataset was constructed for the first time using the MEA-BP model at 2474 CMA stations of China. A quality control process and homogenization test (using RHtestsV4) for the PAR dataset were further conducted. This high-density PAR dataset would benefit many climate and ecological studies.

scholarly journals Soil carbon stock increases in the organic layer of boreal middle-aged stands

2011 ◽  
Vol 8 (5) ◽  
pp. 1279-1289 ◽  
Author(s):  
M. Häkkinen ◽  
J. Heikkinen ◽  
R. Mäkipää
Keyword(s):  
Soil Carbon ◽  
Carbon Stock ◽  
Geographical Area ◽  
Repeated Measurements ◽  
Soil Survey ◽  
Permanent Plots ◽  
Organic Layer ◽  
Middle Aged ◽  
Soil Carbon Stock ◽  
Soil Organic Layer

Abstract. Changes in the soil carbon stock can potentially have a large influence on global carbon balance between terrestrial ecosystems and atmosphere. Since carbon sequestration of forest soils is influenced by human activities, reporting of the soil carbon pool is a compulsory part of the national greenhouse gas (GHG) inventories. Various soil carbon models are applied in GHG inventories, however, the verification of model-based estimates is lacking. In general, the soil carbon models predict accumulation of soil carbon in the middle-aged stands, which is in good agreement with chronosequence studies and flux measurements of eddy sites, but they have not been widely tested with repeated measurements of permanent plots. The objective of this study was to evaluate soil carbon changes in the organic layer of boreal middle-aged forest stands. Soil carbon changes on re-measured sites were analyzed by using soil survey data that was based on composite samples as a first measurement and by taking into account spatial variation on the basis of the second measurement. By utilizing earlier soil surveys, a long sampling interval, which helps detection of slow changes, could be readily available. The range of measured change in the soil organic layer varied from −260 to 1260 g m−2 over the study period of 16–19 years and 23 ± 2 g m−2 per year, on average. The increase was significant in 6 out of the 38 plots from which data were available. Although the soil carbon change was difficult to detect at the plot scale, the overall increase measured across the middle-aged stands agrees with predictions of the commonly applied soil models. Further verification of the soil models is needed with larger datasets that cover wider geographical area and represent all age classes, especially young stands with potentially large soil carbon source.

The Forest Ecosystem Research Network of Sites (FERNS)

1999 ◽  
Vol 75 (3) ◽  
pp. 481-482 ◽  
Author(s):  
A. K. Mitchell ◽  
C. Lee
Keyword(s):  
Forest Management ◽  
Forest Ecosystem ◽  
Information Exchange ◽  
Management Practices ◽  
Sustainable Forest Management ◽  
Ecosystem Processes ◽  
Research Network ◽  
Ecosystem Research ◽  
Research Investments

The Canadian Forest Service (CFS) has organized a National Forest Ecosystem Research Network of Sites (FERNS). These sites are focussed on the study of sustainable forest management practices and ecosystem processes at the stand level. Network objectives are to promote this research nationally and internationally, provide linkages among sites, preserve the long-term research investments already made on these sites and provide a forum for information exchange and data sharing. The 17 individual sites are representative of six ecozones across Canada and address the common issue of silvicultural solutions to problems of sustainable forest management. While the CFS coordinates and promotes FERNS, the network consists of local autonomous partners nationwide who benefit from the FERNS affiliation through increased publicity for their sites. Key words: long-term, silviculture, network, interdisciplinary, ecozone, ecosystem processes

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