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Brown C, Boyd DS, Sjögersten S, Vane CH. Detecting tropical peatland degradation: Combining remote sensing and organic geochemistry. PLoS One 2023; 18:e0280187. [PMID: 36989287 PMCID: PMC10057786 DOI: 10.1371/journal.pone.0280187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 12/22/2022] [Indexed: 03/30/2023] Open
Abstract
Tropical peatlands are important carbon stores that are vulnerable to drainage and conversion to agriculture. Protection and restoration of peatlands are increasingly recognised as key nature based solutions that can be implemented as part of climate change mitigation. Identification of peatland areas that are important for protection and restauration with regards to the state of their carbon stocks, are therefore vital for policy makers. In this paper we combined organic geochemical analysis by Rock-Eval (6) pyrolysis of peat collected from sites with different land management history and optical remote sensing products to assess if remotely sensed data could be used to predict peat conditions and carbon storage. The study used the North Selangor Peat Swamp forest, Malaysia, as the model system. Across the sampling sites the carbon stocks in the below ground peat was ca 12 times higher than the forest (median carbon stock held in ground vegetation 114.70 Mg ha-1 and peat soil 1401.51 Mg ha-1). Peat core sub-samples and litter collected from Fire Affected, Disturbed Forest, and Managed Recovery locations (i.e. disturbed sites) had different decomposition profiles than Central Forest sites. The Rock-Eval pyrolysis of the upper peat profiles showed that surface peat layers at Fire Affected, Disturbed Forest, and Managed Recovery locations had lower immature organic matter index (I-index) values (average I-index range in upper section 0.15 to -0.06) and higher refractory organic matter index (R -index) (average R-index range in upper section 0.51 to 0.65) compared to Central Forest sites indicating enhanced decomposition of the surface peat. In the top 50 cm section of the peat profile, carbon stocks were negatively related to the normalised burns ratio (NBR) (a satellite derived parameter) (Spearman's rho = -0.664, S = 366, p-value = <0.05) while there was a positive relationship between the hydrogen index and the normalised burns ratio profile (Spearman's rho = 0.7, S = 66, p-value = <0.05) suggesting that this remotely sensed product is able to detect degradation of peat in the upper peat profile. We conclude that the NBR can be used to identify degraded peatland areas and to support identification of areas for conversation and restoration.
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Affiliation(s)
- Chloe Brown
- School of Geography, University of Nottingham, Nottingham, United Kingdom
| | - Doreen S Boyd
- School of Geography, University of Nottingham, Nottingham, United Kingdom
| | - Sofie Sjögersten
- School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Christopher H Vane
- British Geological Survey, Centre for Environmental Geochemistry, Keyworth, United Kingdom
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Boyd DS, Crudge S, Foody G. Towards an Automated Approach for Monitoring Tree Phenology Using Vehicle Dashcams in Urban Environments. Sensors (Basel) 2022; 22:7672. [PMID: 36236771 PMCID: PMC9570992 DOI: 10.3390/s22197672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/03/2022] [Accepted: 10/08/2022] [Indexed: 06/16/2023]
Abstract
Trees in urban environments hold significant value in providing ecosystem services, which will become increasingly important as urban populations grow. Tree phenology is highly sensitive to climatic variation, and resultant phenological shifts have significant impact on ecosystem function. Data on urban tree phenology is important to collect. Typical remote methods to monitor tree phenological transitions, such as satellite remote sensing and fixed digital camera networks, are limited by financial costs and coarse resolutions, both spatially and temporally and thus there exists a data gap in urban settings. Here, we report on a pilot study to evaluate the potential to estimate phenological metrics from imagery acquired with a conventional dashcam fitted to a car. Dashcam images were acquired daily in spring 2020, March to May, for a 2000 m stretch of road in Melksham, UK. This pilot study indicates that time series imagery of urban trees, from which meaningful phenological data can be extracted, is obtainable from a car-mounted dashcam. The method based on the YOLOv3 deep learning algorithm demonstrated suitability for automating stages of processing towards deriving a greenness metric from which the date of tree green-up was calculated. These dates of green-up are similar to those obtained by visual analyses, with a maximum of a 4-day difference; and differences in green-up between trees (species-dependent) were evident. Further work is required to fully automate such an approach for other remote sensing capture methods, and to scale-up through authoritative and citizen science agencies.
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Affiliation(s)
- Doreen S. Boyd
- School of Geography, University of Nottingham, Nottingham NG7 2RD, UK
| | - Sally Crudge
- Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2RD, UK
| | - Giles Foody
- School of Geography, University of Nottingham, Nottingham NG7 2RD, UK
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Higgins EA, Boyd DS, Brown TW, Owen SC, Algar AC. Disentangling controls on animal abundance: Prey availability, thermal habitat, and microhabitat structure. Ecol Evol 2021; 11:11414-11424. [PMID: 34429929 PMCID: PMC8366856 DOI: 10.1002/ece3.7930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 07/05/2021] [Indexed: 11/07/2022] Open
Abstract
The question of what controls animal abundance has always been fundamental to ecology, but given rapid environmental change, understanding the drivers and mechanisms governing abundance is more important than ever. Here, we determine how multidimensional environments and niches interact to determine population abundance along a tropical habitat gradient. Focusing on the endemic lizard Anolis bicaorum on the island of Utila (Honduras), we evaluate direct and indirect effects of three interacting niche axes on abundance: thermal habitat quality, structural habitat quality, and prey availability. We measured A. bicaorum abundance across a series of thirteen plots and used N-mixture models and path analysis to disentangle direct and indirect effects of these factors. Results showed that thermal habitat quality and prey biomass both had positive direct effects on anole abundance. However, thermal habitat quality also influenced prey biomass, leading to a strong indirect effect on abundance. Thermal habitat quality was primarily a function of canopy density, measured as leaf area index (LAI). Despite having little direct effect on abundance, LAI had a strong overall effect mediated by thermal quality and prey biomass. Our results demonstrate the role of multidimensional environments and niche interactions in determining animal abundance and highlight the need to consider interactions between thermal niches and trophic interactions to understand variation in abundance, rather than focusing solely on changes in the physical environment.
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Affiliation(s)
| | | | - Tom W. Brown
- School of GeographyUniversity of NottinghamNottinghamUK
- Kanahau Utila Research and Conservation FacilityIsla de Utila, Islas de BahiaHonduras
| | - Sarah C. Owen
- School of GeographyUniversity of NottinghamNottinghamUK
| | - Adam C. Algar
- Department of BiologyLakehead UniversityThunder BayONCanada
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Jackson TD, Shenkin AF, Majalap N, Bin Jami J, Bin Sailim A, Reynolds G, Coomes DA, Chandler CJ, Boyd DS, Burt A, Wilkes P, Disney M, Malhi Y. The mechanical stability of the world’s tallest broadleaf trees. Biotropica 2020. [DOI: 10.1111/btp.12850] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Tobias D. Jackson
- Forest Ecology and Conservation Group Department of Plant Sciences University of Cambridge Cambridge UK
- Environmental Change Institute School of Geography and the Environment University of Oxford Oxford UK
| | - Alexander F. Shenkin
- Environmental Change Institute School of Geography and the Environment University of Oxford Oxford UK
| | - Noreen Majalap
- Phytochemistry UnitForest Research Centre Sabah Malaysia
| | | | - Azlin Bin Sailim
- South East Asia Rainforest Research Partnership (SEARRP) Sabah Malaysia
| | - Glen Reynolds
- South East Asia Rainforest Research Partnership (SEARRP) Sabah Malaysia
| | - David A. Coomes
- Forest Ecology and Conservation Group Department of Plant Sciences University of Cambridge Cambridge UK
| | | | - Doreen S. Boyd
- School of Geography University of Nottingham Nottingham UK
| | - Andy Burt
- Department of Geography University College London London UK
| | - Phil Wilkes
- Department of Geography University College London London UK
- NERC National Centre for Earth Observation (NCEO) Leicester UK
| | - Mathias Disney
- Department of Geography University College London London UK
- NERC National Centre for Earth Observation (NCEO) Leicester UK
| | - Yadvinder Malhi
- Environmental Change Institute School of Geography and the Environment University of Oxford Oxford UK
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Philipson CD, Cutler MEJ, Brodrick PG, Asner GP, Boyd DS, Moura Costa P, Fiddes J, Foody GM, van der Heijden GMF, Ledo A, Lincoln PR, Margrove JA, Martin RE, Milne S, Pinard MA, Reynolds G, Snoep M, Tangki H, Sau Wai Y, Wheeler CE, Burslem DFRP. Active restoration accelerates the carbon recovery of human-modified
tropical forests. Science 2020; 369:838-841. [DOI: 10.1126/science.aay4490] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 03/03/2020] [Accepted: 06/19/2020] [Indexed: 11/02/2022]
Abstract
More than half of all tropical forests are degraded by human impacts,
leaving them threatened with conversion to agricultural plantations and
risking substantial biodiversity and carbon losses. Restoration could
accelerate recovery of aboveground carbon density (ACD), but adoption of
restoration is constrained by cost and uncertainties over effectiveness. We
report a long-term comparison of ACD recovery rates between naturally
regenerating and actively restored logged tropical forests. Restoration
enhanced decadal ACD recovery by more than 50%, from 2.9 to 4.4 megagrams
per hectare per year. This magnitude of response, coupled with modal values
of restoration costs globally, would require higher carbon prices to justify
investment in restoration. However, carbon prices required to fulfill the
2016 Paris climate agreement [$40 to $80 (USD) per tonne carbon dioxide
equivalent] would provide an economic justification for tropical forest
restoration.
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Affiliation(s)
- Christopher D. Philipson
- School of Social Sciences, University of Dundee, Dundee DD1 4HN, UK
- Department of Environmental Systems Science, ETH Zürich, 8092 Zürich, Switzerland
| | | | - Philip G. Brodrick
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ 85287, USA
| | - Gregory P. Asner
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ 85287, USA
| | - Doreen S. Boyd
- School of Geography, University of Nottingham, Nottingham NG7 2RD, UK
| | - Pedro Moura Costa
- Smith School of Enterprise and the Environment, University of Oxford, Oxford OX1 3QY, UK
| | - Joel Fiddes
- Mountainsense Consulting, 7249 Serneus, Switzerland
- WSL Institute for Snow and Avalanche Research, CH-7260 Davos Dorf, Switzerland
| | - Giles M. Foody
- School of Geography, University of Nottingham, Nottingham NG7 2RD, UK
| | | | - Alicia Ledo
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
| | | | - James A. Margrove
- Department of Environmental Systems Science, ETH Zürich, 8092 Zürich, Switzerland
| | - Roberta E. Martin
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ 85287, USA
| | - Sol Milne
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Michelle A. Pinard
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Glen Reynolds
- South East Asia Rainforest Research Partnership, Danum Valley Field Centre, Lahad Datu, Sabah, Malaysia
| | | | - Hamzah Tangki
- Conservation & Environmental Management Division, Yayasan Sabah Group, 88817 Kota Kinabalu, Sabah, Malaysia
| | - Yap Sau Wai
- Conservation & Environmental Management Division, Yayasan Sabah Group, 88817 Kota Kinabalu, Sabah, Malaysia
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Jackson B, Decker Sparks JL, Brown C, Boyd DS. Understanding the co‐occurrence of tree loss and modern slavery to improve efficacy of conservation actions and policies. Conservat Sci and Prac 2020. [DOI: 10.1111/csp2.183] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Bethany Jackson
- School of GeographyUniversity of Nottingham Nottingham UK
- Rights LabUniversity of Nottingham Nottingham UK
| | - Jessica L. Decker Sparks
- School of GeographyUniversity of Nottingham Nottingham UK
- Rights LabUniversity of Nottingham Nottingham UK
| | - Chloe Brown
- School of GeographyUniversity of Nottingham Nottingham UK
- Rights LabUniversity of Nottingham Nottingham UK
| | - Doreen S. Boyd
- School of GeographyUniversity of Nottingham Nottingham UK
- Rights LabUniversity of Nottingham Nottingham UK
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Waite CE, Heijden GMF, Field R, Boyd DS. A view from above: Unmanned aerial vehicles (
UAV
s) provide a new tool for assessing liana infestation in tropical forest canopies. J Appl Ecol 2019. [DOI: 10.1111/1365-2664.13318] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
| | | | - Richard Field
- School of GeographyUniversity of Nottingham Nottingham UK
| | - Doreen S. Boyd
- School of GeographyUniversity of Nottingham Nottingham UK
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8
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Moat J, Bachman SP, Field R, Boyd DS. Refining area of occupancy to address the modifiable areal unit problem in ecology and conservation. Conserv Biol 2018; 32:1278-1289. [PMID: 29797481 DOI: 10.1111/cobi.13139] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 02/20/2018] [Accepted: 05/09/2018] [Indexed: 05/26/2023]
Abstract
The modifiable areal unit problem is prevalent across many aspects of spatial analysis within ecology and conservation. The problem is particularly manifested when calculating metrics for extinction risk estimation, for example, area of occupancy (AOO). Although embedded in the International Union for the Conservation of Nature (IUCN) Red List criteria, AOO is often not used or is poorly applied. We evaluated new and existing methods for calculating AOO from occurrence records and devised a method for determining the minimum AOO with a uniform grid. We evaluated the grid cell shape, origin, and rotation with real-world and simulated data and reviewed the effects on AOO values and possible impacts for species already assessed on the IUCN Red List. The AOO varied by up to 80%, and a ratio of cells to points of 1:1.21 yielded the maximum variation in the number of occupied cells. These findings potentially impact 3% of existing species on the IUCN Red List and species not yet assessed. Our new method combined grid rotation and moving grid origin and gave fast, robust, and reproducible results and, in the majority of cases, achieved the minimum AOO. As well as determining minimum AOO, our method yielded a confidence interval that should be incorporated into existing tools that support species risk assessment. We recommend when recording AOO and other areal measurements that the methods; summary statistics across multiple iterations; angle and origin of the minimum grid; map projection; and datum be recorded, this will lead to more robust species risk assessments.
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Affiliation(s)
- Justin Moat
- Royal Botanic Gardens, Kew, Richmond, Surrey, TW9 3AE, U.K
- School of Geography, University of Nottingham, Nottingham, NG7 2RD, U.K
| | - Steven P Bachman
- Royal Botanic Gardens, Kew, Richmond, Surrey, TW9 3AE, U.K
- School of Geography, University of Nottingham, Nottingham, NG7 2RD, U.K
| | - Richard Field
- School of Geography, University of Nottingham, Nottingham, NG7 2RD, U.K
| | - Doreen S Boyd
- School of Geography, University of Nottingham, Nottingham, NG7 2RD, U.K
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Bailey JJ, Boyd DS, Field R. Models of upland species' distributions are improved by accounting for geodiversity. Landsc Ecol 2018; 33:2071-2087. [PMID: 30930538 PMCID: PMC6404796 DOI: 10.1007/s10980-018-0723-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 10/03/2018] [Indexed: 06/09/2023]
Abstract
CONTEXT Recent research suggests that novel geodiversity data on landforms, hydrology and surface materials can improve biodiversity models at the landscape scale by quantifying abiotic variability more effectively than commonly used measures of spatial heterogeneity. However, few studies consider whether these variables can account for, and improve our understanding of, species' distributions. OBJECTIVES Assess the role of geodiversity components as macro-scale controls of plant species' distributions in a montane landscape. METHODS We used an innovative approach to quantifying a landscape, creating an ecologically meaningful geodiversity dataset that accounted for hydrology, morphometry (landforms derived from geomorphometric techniques), and soil parent material (data from expert sources). We compared models with geodiversity to those just using topographic metrics (e.g. slope and elevation) and climate data. Species distribution models (SDMs) were produced for 'rare' (N = 76) and 'common' (N = 505) plant species at 1 km2 resolution for the Cairngorms National Park, Scotland. RESULTS The addition of automatically produced landform geodiversity data and hydrological features to a basic SDM (climate, elevation, and slope) resulted in a significant improvement in model fit across all common species' distribution models. Adding further geodiversity data on surface materials resulted in a less consistent statistical improvement, but added considerable conceptual value to many individual rare and common SDMs. CONCLUSIONS The geodiversity data used here helped us capture the abiotic environment's heterogeneity and allowed for explicit links between the geophysical landscape and species' ecology. It is encouraging that relatively simple and easily produced geodiversity data have the potential to improve SDMs. Our findings have important implications for applied conservation and support the need to consider geodiversity in management.
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Affiliation(s)
- Joseph J. Bailey
- School of Geography, University of Nottingham, University Park, Nottingham, NG7 2RD UK
- School of Humanities, Religion and Philosophy, York St John University, Lord Mayor’s Walk, York, YO31 7EX UK
| | - Doreen S. Boyd
- School of Geography, University of Nottingham, University Park, Nottingham, NG7 2RD UK
| | - Richard Field
- School of Geography, University of Nottingham, University Park, Nottingham, NG7 2RD UK
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11
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Baena S, Moat J, Whaley O, Boyd DS. Identifying species from the air: UAVs and the very high resolution challenge for plant conservation. PLoS One 2017; 12:e0188714. [PMID: 29176860 PMCID: PMC5703556 DOI: 10.1371/journal.pone.0188714] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Accepted: 11/11/2017] [Indexed: 11/19/2022] Open
Abstract
The Pacific Equatorial dry forest of Northern Peru is recognised for its unique endemic biodiversity. Although highly threatened the forest provides livelihoods and ecosystem services to local communities. As agro-industrial expansion and climatic variation transform the region, close ecosystem monitoring is essential for viable adaptation strategies. UAVs offer an affordable alternative to satellites in obtaining both colour and near infrared imagery to meet the specific requirements of spatial and temporal resolution of a monitoring system. Combining this with their capacity to produce three dimensional models of the environment provides an invaluable tool for species level monitoring. Here we demonstrate that object-based image analysis of very high resolution UAV images can identify and quantify keystone tree species and their health across wide heterogeneous landscapes. The analysis exposes the state of the vegetation and serves as a baseline for monitoring and adaptive implementation of community based conservation and restoration in the area.
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Affiliation(s)
- Susana Baena
- Royal Botanic Gardens, Kew, Richmond, Surrey, United Kingdom
- School of Geography, University of Nottingham, Nottingham, United Kingdom
| | - Justin Moat
- Royal Botanic Gardens, Kew, Richmond, Surrey, United Kingdom
- School of Geography, University of Nottingham, Nottingham, United Kingdom
| | - Oliver Whaley
- Royal Botanic Gardens, Kew, Richmond, Surrey, United Kingdom
| | - Doreen S. Boyd
- School of Geography, University of Nottingham, Nottingham, United Kingdom
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Arellano P, Tansey K, Balzter H, Boyd DS. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images. Environ Pollut 2015; 205:225-239. [PMID: 26074164 DOI: 10.1016/j.envpol.2015.05.041] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 05/29/2015] [Accepted: 05/30/2015] [Indexed: 06/04/2023]
Abstract
The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest.
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Affiliation(s)
- Paul Arellano
- University of Leicester, Department of Geography, Centre of Landscape and Climate Research, University Road, Leicester, LE1 7RH, UK; Yachay Tech University, School of Geological Sciences & Engineering, San Miguel de Urcuqui, Hacienda San Jose s/n, Imbabura, Ecuador.
| | - Kevin Tansey
- University of Leicester, Department of Geography, Centre of Landscape and Climate Research, University Road, Leicester, LE1 7RH, UK
| | - Heiko Balzter
- University of Leicester, Department of Geography, Centre of Landscape and Climate Research, University Road, Leicester, LE1 7RH, UK; National Centre for Earth Observation, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Doreen S Boyd
- University of Nottingham, School of Geography, Nottingham, NG7 2RD, UK
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Espírito-Santo FDB, Gloor M, Keller M, Malhi Y, Saatchi S, Nelson B, Oliveira Junior RC, Pereira C, Lloyd J, Frolking S, Palace M, Shimabukuro YE, Duarte V, Mendoza AM, López-González G, Baker TR, Feldpausch TR, Brienen RJW, Asner GP, Boyd DS, Phillips OL. Corrigendum: Size and frequency of natural forest disturbances and the Amazon forest carbon balance. Nat Commun 2015; 6:6638. [PMID: 25833221 PMCID: PMC4396392 DOI: 10.1038/ncomms7638] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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Abstract
Landscape-scale gap-size frequency distributions in tropical forests are a poorly studied but key ecological variable. Currently, a scale gap currently exists between local-scale field-based studies and those employing regional-scale medium-resolution satellite data. Data at landscape scales but of fine resolution would, however, facilitate investigation into a range of ecological questions relating to gap dynamics. These include whether canopy disturbances captured in permanent sample plots (PSPs) are representative of those in their surrounding landscape, and whether disturbance regimes vary with forest type. Here, therefore, we employ airborne LiDAR data captured over 142.5 km2 of mature, swamp, and regenerating forests in southeast Peru to assess the landscape-scale disturbance at a sampling resolution of up to 2 m. We find that this landscape is characterized by large numbers of small gaps; large disturbance events are insignificant and infrequent. Of the total number of gaps that are 2 m2 or larger in area, just 0.45% were larger than 100 m2, with a power-law exponent (alpha) value of the gap-size frequency distribution of 2.22. However, differences in disturbance regimes are seen among different forest types, with a significant difference in the alpha value of the gap-size frequency distribution observed for the swamp/regenerating forests compared with the mature forests at higher elevations. Although a relatively small area of the total forest of this region was investigated here, this study presents an unprecedented assessment of this landscape with respect to its gap dynamics. This is particularly pertinent given the range of forest types present in the landscape and the differences observed. The coupling of detailed insights into forest properties and growth provided by PSPs with the broader statistics of disturbance events using remote sensing is recommended as a strong basis for scaling-up estimates of landscape and regional-scale carbon balance.
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Affiliation(s)
- Doreen S Boyd
- School of Geography, University of Nottingham, University Park, Nottingham NG72RD, UK.
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Sanchez-Hernandez C, Boyd DS, Foody GM. Mapping specific habitats from remotely sensed imagery: Support vector machine and support vector data description based classification of coastal saltmarsh habitats. ECOL INFORM 2007. [DOI: 10.1016/j.ecoinf.2007.04.003] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Abstract
The leaf area index (LAI) of boreal forest can be estimated using reflected radiation recorded by satellite sensors. Measurements of visible and near infrared radiation are commonly used in the normalized difference vegetation index (NDVI) to estimate LAI. However, research, mainly in tropical forest, has demonstrated that LAI is related more closely to radiation of middle infrared wavelengths than of visible wavelengths. This paper derives a vegetation index, VI3, based on radiation from vegetation recorded at near and middle infrared wavelengths. For a boreal forest canopy, the relationship between VI3 and LAI was observed to be much stronger than that between NDVI and LAI. In addition, the LAI estimated using VI3 accounted for about 76% of the variation in field estimates of LAI, compared with about 46% when using the NDVI. We conclude that information provided by middle infrared radiation should be considered when estimating the leaf area index of boreal forest.
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Affiliation(s)
- Doreen S. Boyd
- Centre for Earth and Environmental Science Research, School of Geography, Kingston University, Penryhn Road, Kingston-upon-Thames, Surrey KT1 2EE, U.K
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Boyd DS, Curran PJ. Using remote sensing to reduce uncertainties in the global carbon budget: The potential of radiation acquired in middle infrared wavelengths. ACTA ACUST UNITED AC 1998. [DOI: 10.1080/02757259809532357] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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