Integration of remote sensing in spatial ecology: assessing the interspecific interactions of two plant species in a semi-arid woodland using unmanned aerial vehicle (UAV) photogrammetric data

Erfanifard, Yousef; Kraszewski, Bartłomiej; Stereńczak, Krzysztof

doi:10.1007/s00442-021-04928-5

Cited by 6 publications

(3 citation statements)

References 62 publications

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“…At short distances, positive or negative correlations between vegetation patch sizes indicate that they depend on each other (Erfanifard et al, 2021 ; Getzin et al, 2008 ). The positive correlations indicate facilitation between plants such as reducing wind desiccation by above‐ground biomass (Trautz et al, 2017 ).…”

Section: Discussionmentioning

confidence: 99%

Community plant height modulated by aridity promotes spatial vegetation patterns in Alxa plateau in Northwest China

Cheng

Pan

Wang

et al. 2023

Ecology and Evolution

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Spatial vegetation patterns are associated with ecosystem stability and multifunctionality in drylands. Changes in patch size distributions (PSDs) are generally driven by both environmental and biological factors. However, the relationships between these factors in driving PSDs are not fully understood. We investigated 80 vegetation plots along an aridity gradient in the Alxa plateau, Northwest China. The sizes of vegetation patches were obtained from aerial images, and the heights of patch‐forming species were measured in the field. Soil samples were collected on the bare ground between patches for determination of physiochemical properties. Point pattern analysis was used to infer plant–plant interactions. A model selection procedure was employed to select the best predictors for the shape of PSDs and biological factors (vegetation total cover, community plant height, and plant–plant interactions). We then used structural equation modeling to evaluate the direct and indirect effects of environmental and biological factors on the shape of PSDs. In our study area, two types of PSDs coexisted, namely those that best fit to power law distributions and those that best fit to lognormal distributions. Aridity was the main environmental factor, while community mean height and competition between plants were the main biological factors for the shape of PSDs. As aridity and community mean height increased, power law‐like PSDs were exhibited, whereas competition led to deviations of PSDs from power laws. Aridity affected the shape of PSDs indirectly through changes in community mean height. Community mean height was correlated with competition, thereby indirectly affecting the shape of PSDs. Our results suggest the use of community functional traits as a link between the environment and plant–plant interactions, which may improve the understanding of the underlying mechanisms of PSD dynamics.

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Section: Discussionmentioning

confidence: 99%

Community plant height modulated by aridity promotes spatial vegetation patterns in Alxa plateau in Northwest China

Cheng

Pan

Wang

et al. 2023

Ecology and Evolution

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“…UAV‐mounted sensors can quantify structural interactions at much larger scales than is possible through TLS. For example, LiDAR‐derived crown properties can predict how neighbourhood competition drives tree growth (Vanderwel et al, 2020), and UAV photogrammetry‐derived crowns can be used to determine the relative strength of interspecific vs intraspecific competition on growth (Erfanifard et al, 2021). New insights into how individual shape and competitive interactions affect whole‐canopy properties are also emerging; for example, TLS data have shown how crown shape, branching topology and shade tolerance influence crown position and shading interactions (Martin‐Ducup et al, 2021).…”

Section: Sensing the Three‐dimensional Canopy: Competition For Light ...mentioning

confidence: 99%

The shape of trees: Reimagining forest ecology in three dimensions with remote sensing

Lines¹,

Fischer

Owen³

et al. 2022

Journal of Ecology

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Forest ecology has long relied on a simple measure-the diameter of the trunk of a tree at breast height (dbh)-as a way to summarise individual tree status and performance. This measurement, with its origins in forestry, is non-destructive and quick to take, requiring no special equipment or extensive training, and this ease of use has led dbh to be widely adopted as the key measure of an individual tree in forest ecology. It is used to quantify and predict individual tree demography (Lines et al., 2010;Ruiz-Benito et al., 2013), as a proxy for tree age (Stephenson et al., 2014), to estimate key properties including leaf area, height, crown shape and biomass (Chave et al., 2014;

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“…The global need for accurate information concerning forests' impact on the dynamic development of precision forestry is immense [1]. Not only satellite imagery [2] but also LiDAR (Light Detection and Ranging) [3] and UAV (Unmanned Aerial Vehicle) technologies [4], used for forest inventories, are of great interest to researchers all around the world. All these techniques require the use of reference measurements on the ground.…”

Section: Introductionmentioning

confidence: 99%

Rapid Static Positioning Using a Four System GNSS Receivers in the Forest Environment

Brach

2022

Forests

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Global Navigation Satellite Systems (GNSS) are crucial elements used in forest inventories. Forest metrics modeling efficacy depends on the accuracy of determining sample plot locations by GNSS. As of 2021, the GNSS consists of 120 active satellites, ostensibly improving position acquisition in forest conditions. The main idea of this article was to evaluate GIS-class and geodetic class GNSS receivers on 33 control points located in the forest. The main assumptions were operating on four GNSS systems (GPS, GLONASS, Galileo, and BeiDou), keeping a continuous online connection to the network of reference stations, maintaining occupation time-limited to 60 epochs, and repeating all the measurements three times. Rapid static positioning was tested, as it compares the true performance of the four GNSS systems receivers. Statistical differences between the receivers were confirmed. The GIS-class receiver achieved an accuracy of 1.38 m and a precision of 1.29 m, while the geodetic class receiver reached 0.74 m and 0.91 m respectively. Even though the research was conducted under the same data capture conditions, the large variability of positioning results were found to be caused by cycle slips and the multipath effect.

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Integration of remote sensing in spatial ecology: assessing the interspecific interactions of two plant species in a semi-arid woodland using unmanned aerial vehicle (UAV) photogrammetric data

Cited by 6 publications

References 62 publications

Community plant height modulated by aridity promotes spatial vegetation patterns in Alxa plateau in Northwest China

Community plant height modulated by aridity promotes spatial vegetation patterns in Alxa plateau in Northwest China

The shape of trees: Reimagining forest ecology in three dimensions with remote sensing

Rapid Static Positioning Using a Four System GNSS Receivers in the Forest Environment

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