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Application of Earth Observation for Monitoring Biodiversity

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Biogeosciences Remote Sensing".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 8539

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Special Issue Editors

Dr. Joris Timmermans

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Guest Editor

LifeWatch ERIC, Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
Interests: satellite remote sensing; optical; thermal microwave radiative transfer; vegetation ecology; biodiversity; hydrology; data-science; operational applications

Dr. Rosaleen March

E-Mail Website
Guest Editor

Institute of Environmental Sciences (CML), Leiden University, Einsteinweg 2, 2333 CC Leiden, The Netherlands
Interests: environmental remote sensing (optical); ecosystem dynamics; functional biodiversity; vegetation ecology; avian ecology; ecosystem services

Dr. Ranjani W. Kulawardhana

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Guest Editor

Department of Biological and Environmental Sciences, Alabama A&M University, Huntsville, AL 35811, USA
Interests: environmental remote sensing (optical, LiDAR) and GIS; spatial mapping and monitoring of vegetation productivity; land-cover/ land-use; coastal wetland ecology; ecosystem products and services; land-use/ land-cover change

Special Issue Information

Dear Colleagues,

Global biodiversity is declining rapidly, threatening the natural functioning of Earth's ecosystems and the services they provide to society. There is now a general consensus (by, among others, the Convention of Biological Diversity) that to resolve this hazard in 2050, adequate monitoring needs to be performed to characterize the impacts/interactions of biodiversity on/with ecosystem functioning, ecosystem services, and community composition. This can then provide us with specific information to set up measures that protect and conserve these delicate ecosystems and allow for more inclusive and sustainable development of our natural resources. Remote sensing in this perspective is becoming a vital tool, as it provides reliable data and analytical techniques for monitoring biodiversity across large areas and over prolonged periods of time.

Remote sensing offers the tools for mapping and monitoring ecological traits and thereby enabling characterization of the underlying interactions with anthropogenic threats, environmental drivers, and other ecological processes. However, at present, actual applications of earth observation for monitoring impacts/interactions on/with biodiversity are sparse.

Therefore, this Special Issue on "Application of Earth Observation for Monitoring Biodiversity" calls for manuscripts that demonstrate successful applications of (satellite and airborne) remote sensing for biodiversity and ecological monitoring. We welcome i) papers describing what is required of earth observation for monitoring biodiversity, ii) recent methodological innovations to achieve these ecological requirements, and iii) success stories in applying earth observation techniques for monitoring biodiversity (impacts/interactions).

In particular, we invite studies that apply earth observation to understand:

The state and change of biodiversity in terrestrial, coastal, and marine ecosystems at different levels (genetic, functional, species, habitat, ecosystem, etc.) and across variable spatial scales (local, regional, and global)
Ecosystem processes or stability by analyzing/modeling spatial and/or temporal ecological patterns to enable us to identify the risk of (among others) anthropogenic and natural threats
Ecosystem functioning and thereby the services that ecosystems provide to humankind, such as carbon sequestration and water regulation.

We also encourage applications which

show the potential and/or actual application of earth observation data originating from different platforms (including ground-based, airborne, and satellite) and sensors (active/ passive, optical, LiDAR, thermal, microwave, etc.)
integrate different methodologies (such as analytical modeling, empirical relationships, machine learning regression, radiative transfer models) within prototype studies, operational frameworks, and cross-comparison exercises.

All types of original research (including review papers, proof-of-concept manuscripts, validation exercises, and application-oriented contributions) will be considered.

Dr. Joris Timmermans
Dr. Rosaleen March
Dr. Ranjani W. Kulawardhana
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Biodiversity change
Biodiversity monitoring from space
Biodiversity observation time-series
Community reassembly
Ecosystem functioning
Global environmental change
Land use change
Landscape fragmentation
Multiscalar and multitemporal Earth observation
Species range shifts

Published Papers (4 papers)

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16 pages, 5180 KiB

Open AccessArticle

Dynamic Habitat Indices and Climatic Characteristics Explain Species Richness Patterns on the Mongolian Plateau

by Yingbin Liu, Yaping Yang, Xiafang Yue, Xiaona Chen and Yangxiaoyue Liu

Remote Sens. 2023, 15(4), 1092; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15041092 - 16 Feb 2023

Cited by 1 | Viewed by 1700

Abstract

Global climate change affects biodiversity patterns, especially in arid and semi-arid regions such as the Mongolian plateau, one of the most ecologically fragile regions in the world. Three dynamic habitat indices (DHIs) were related to the productivity hypothesis and calculated based on FAPAR [...] Read more.

D H I_{c u m}

indicates the availability of resources such as food supply and habitat in a year, representing available energy), minimum productivity (

D H I_{m i n}

indicates the limitations of food and habitat resources in a year, representing environmental stress), and seasonal productivity (

D H I_{s e a}

denotes the change in productivity in a year, representing environmental stability). In this paper, we investigated the distribution pattern of species richness on the Mongolian Plateau based on the productivity hypothesis. We constructed models of the richness of three species (mammals, birds, and amphibians) using DHIs and climate variables to explain patterns of species richness on the Mongolian Plateau. The results revealed that, on the Mongolian plateau, there is a relatively high correlation between DHIs and species richness, especially with

D H I_{c u m}

(R = 0.59 for mammals, R = 0.73 for birds, and R = 0.58 for amphibians). There was a significant non-linear relationship between DHIs and species richness, as the model predictive power was significantly enhanced with GAM and RF. The inclusion of climate variables significantly improved the explanatory power of various models for the mammal, bird, and amphibian species richness on the Mongolian Plateau, with the best results for RF (0.89, 0.94, and 0.91, respectively). The influence of climate variables on species richness patterns in the importance ranking was higher than that of DHIs. Climate also has an influence on species richness. Vegetation productivity and climatic factors are good determinants of species richness on the Mongolian Plateau and should be carefully considered in future studies. Full article

(This article belongs to the Special Issue Application of Earth Observation for Monitoring Biodiversity)

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24 pages, 4926 KiB

Open AccessArticle

Environmental Performance of Regional Protected Area Network: Typological Diversity and Fragmentation of Forests

by Tatiana Chernenkova, Ivan Kotlov, Nadezhda Belyaeva, Elena Suslova and Natalia Lebedeva

Remote Sens. 2023, 15(1), 276; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15010276 - 03 Jan 2023

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Abstract

Protected areas (PAs) are among the main tools for preserving biodiversity and creating an environment for the natural course of ecological processes. The identification of forest biodiversity is especially important for large metropolitan areas. An obvious problem in assessing the efficiency of the PAs network is the lack of up-to-date cartographic materials representing the typological diversity of vegetation. The aim of the paper is to identify forest biodiversity and fragmentation in the example of the Moscow region (MR)—the largest metropolis in Eastern Europe. The typological classification was carried out at a detailed hierarchical level—33 association groups (ass. gr.) considering the diversity of the land cover. A random forest algorithm was used for cartographic mapping (overall accuracy 0.59). Remote sensing (RS) data included Sentinel-2A, DEM SRTM, and PALSAR radar images. Six fragmentation metrics were calculated based on the raster map of forest typological diversity. A significant correlation between the forest diversity and PAs forest patch fragmentation metrics was noted. It has been established that the PAs proportion of the territory accounts for almost 20% only within the northernmost district and noticeably decreases to the south to 1–2%. At the same time, fragmentation noticeably increases from Northeast to Southwest. The category of PAs does not affect the state of the forest cover. Additionally, there was no direct influence of the anthropogenic factor from both local sources and a large regional source, i.e., the city of Moscow. It is shown that the average area of PAs, supporting 75% of the typological diversity of regional communities, was about 1000 ha. The results of the study suggest that there is a general lack of environmental protection measures in the region. It is recommended to increase the area of PAs, primarily for less fragmented forest patches, including indigenous forest-steppe and forest types of communities. Full article

(This article belongs to the Special Issue Application of Earth Observation for Monitoring Biodiversity)

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Figure 1

15 pages, 5026 KiB

Open AccessArticle

Precipitation Dominates the Distribution of Species Richness on the Kunlun–Pamir Plateau

by Xiaoran Huang, Anming Bao, Junfeng Zhang, Tao Yu, Guoxiong Zheng, Ye Yuan, Ting Wang, Vincent Nzabarinda, Philippe De Maeyer and Tim Van de Voorde

Remote Sens. 2022, 14(24), 6187; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14246187 - 07 Dec 2022

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Abstract

The Kunlun–Pamir Plateau is a globally irreplaceable biodiversity reserve, yet it is still unclear what causes the distribution of species richness. Here, we relied on the productivity and the water–energy dynamics hypotheses to investigate the distribution pattern of species richness (and its determinants) in the Kunlun–Pamir Plateau. The productivity hypothesis is mainly based on five MODIS products (NDVI, EVI, FPAR, LAI and GPP), which were calculated for three Dynamic Habitat Indices (DHIs): (1) cumulative productivity (CumDHI), (2) minimum productivity (MinDHI) and (3) intra-annual variation productivity (VarDHI). The CumDHI was applied to assess whether or not more energy has a higher species richness value. The MinDHI was used to determine and evaluate the higher minimums, leading to a higher species richness. The VarDHI was the annual variation value in productivity and was utilized to assess if the reduced intra-annual variability triggers a higher species richness. We found that the DHIs based on the FPAR correlated slightly higher with the mammal, bird, breeding bird and non-breeding bird richness (than those based on the other four DHIs, and the values were 0.24, 0.25, 0.24 and 0.01, respectively). The correlation between the climate variables and the mammals, birds, breeding birds and non-breeding birds was bigger at 0.24, 0.54, 0.54 and 0.02, respectively, and was mainly dominated by the precipitation-related climatic factors. The water–energy dynamic hypothesis is better suited to the Kunlun–Pamir Plateau than the productivity hypothesis. Our results might provide valuable information regarding the biodiversity conservation in this region. Full article

(This article belongs to the Special Issue Application of Earth Observation for Monitoring Biodiversity)

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16 pages, 8291 KiB

Open AccessTechnical Note

Global Change of Land-Sparing and Land-Sharing Patterns over the Past 30 Years: Evidence from Remote Sensing and Statistics

by Jianqiao Zhao, Yue Cao and Le Yu

Remote Sens. 2021, 13(24), 5090; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13245090 - 15 Dec 2021

Viewed by 2585

Abstract

Agricultural expansion, driven by the increasing demand on crops, poses a severe threat to the global environment and to human welfare. Regarded as an effective landscape pattern for balancing biodiversity and food security, land sparing bears high expectations from ecologists. To reflect the spatial-temporal pattern change of land sparing, we calculate a land sparing/sharing (LSS) index on the basis of a remote sensing dataset. The land-sparing pattern has shown an apparent increasing trend globally, especially in hotspots, including the eastern United States, central South America, northern Europe, Kazakhstan, southeastern China, and the Korean Peninsula. Meanwhile, the land-sharing pattern has been increasing in some other regions, including in the southeast of South America, western Europe, central Europe, southern Europe, and northwestern China. However, according to statistical datasets, contrary to the overall increasing trend of land sparing, passive land sparing, incentivized by lower food prices due to increased yields, is decreasing, especially in countries with high levels of development. Our results reveal the global trends in land sparing and passive land sparing, providing support for balancing biodiversity conservation and food security among countries and ecoregions. Full article

(This article belongs to the Special Issue Application of Earth Observation for Monitoring Biodiversity)

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