Mapping the structure of Borneo's tropical forests across a degradation gradient

Pfeifer, Marion; Kor, Laura; Nilus, Reuben; Turner, Edgar C.; Cusack, Jeremy J.; Lysenko, Igor; Khoo, MinSheng; Khen, Chey Vun; Chung, AC; Ewers, RM

doi:10.1016/j.rse.2016.01.014

Cited by 93 publications

(114 citation statements)

References 77 publications

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“…Our ACD estimates of 10.0 Mg C ha −1 for a 8-year-old plantation and 18.3 Mg C ha −1 for a 14-year-old plantation are similar to those reported in previous studies. mean ACD of oil palm in the SAFE landscape was estimated as 17.9 Mg C ha −1 by [45] using optical satellite imagery (age of stands not distinguished), while elsewhere in Sabah, the ACD of a 3-year-old oil palm plantation was given as 1.1 Mg C/ha, rising to an average value of 24.4 Mg C ha −1 for plantations ranging from 4 to 19 years old [18].…”

Section: Discussionmentioning

confidence: 99%

Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches

et al. 2017

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Southeast Asia is the epicentre of world palm oil production. Plantations in Malaysia have increased 150% in area within the last decade, mostly at the expense of tropical forests. Maps of the aboveground carbon density (ACD) of vegetation generated by remote sensing technologies, such as airborne LiDAR, are vital for quantifying the effects of land use change for greenhouse gas emissions, and many papers have developed methods for mapping forests. However, nobody has yet mapped oil palm ACD from LiDAR. The development of carbon prediction models would open doors to remote monitoring of plantations as part of efforts to make the industry more environmentally sustainable. This paper compares the performance of tree-centric and area-based approaches to mapping ACD in oil palm plantations. We find that an area-based approach gave more accurate estimates of carbon density than tree-centric methods and that the most accurate estimation model includes LiDAR measurements of top-of-canopy height and canopy cover. We show that tree crown segmentation is sensitive to crown density, resulting in less accurate tree density and ACD predictions, but argue that tree-centric approach can nevertheless be useful for monitoring purposes, providing a method to detect, extract and count oil palm trees automatically from images.

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Section: Discussionmentioning

confidence: 99%

Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches

et al. 2017

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“…Rapid canopy structure assessments such as those based on hemispherical photography are increasingly implemented following standardised sampling designs and allow for rapid and cost-effective retrieval canopy lead area index and fraction of absorbed photosynthetically active radiation (Pfeifer et al, 2012, which mechanistically link to microclimate (Hardwick et al, 2015). These field estimates can then be up-scaled to landscape structure maps using increasingly available high spatial-resolution satellite data (Pfeifer et al, 2016), which can be utilised for detailed analyses and interpretation of biodiversity changes induced by fragmentation. Future analyses could use vegetation productivity or tree cover maps created directly from Landsat images acquired as close as possible to the sampling date in the field.…”

Section: Implications For Biodiversity Samplingmentioning

confidence: 99%

“…Future analyses could use vegetation productivity or tree cover maps created directly from Landsat images acquired as close as possible to the sampling date in the field. Whilst future campaign sampling biodiversity in fragmented forested landscapes could make use of recent developments in remote sensing and ecological sciences, acquiring measures of canopy cover following standardised sampling designs in the field and using remotely sensed data to upscale those measures to landscape maps (Pfeifer et al, 2016).…”

Section: Implications For Biodiversity Samplingmentioning

confidence: 99%

Abundance signals of amphibians and reptiles indicate strong edge effects in Neotropical fragmented forest landscapes

Schneider‐Maunoury

Lefebvre

Ewers

et al. 2016

Biological Conservation

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Fragmentation and habitat loss contribute considerably to global declines of amphibians and reptiles. However, few studies focus on forest edges, created during the fragmentation process, as proximate drivers of the local demographic structure of populations. Here, we use abundance data of amphibians and reptiles to study their responses to forest edges in nine fragmented forested landscapes of the Neotropics. Species-specific abundance data were collected in plots established at varying distances from their respective nearest forest edge. We tested for edge effects on the abundance of species, and used curve clustering techniques to group species with similar edge responses, i.e. species with either increasing or decreasing abundance from the matrix towards the forest interior. We also grouped species that showed no change in abundance with respect to the nearest forest edge and those whose abundance response was unimodal, peaking in either forest habitat or the surrounding matrix habitat. We found that 96% of all amphibians and 90% of all reptiles showed an edge response, with the abundance of 74.5% of amphibians and 57.3% of reptiles decreasing with increasing proximity to forest edges. However, species-specific edge effects were not always consistent, with some species having opposite edge responses when measured in different landscapes. The depth of edge effects exhibited by forest species, i.e. species that increased in abundance in the forest interior, extended up to one kilometre away from forest edges. We show that the median edge effect on forest species extends to 250 m within the forest interior, indicating that tropical forest patches with a mean diameter < 500m (minimum area ≈ 78 ha) are unsuitable for half of forest-dependent species considered in this study.

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“…The opening of LandSat RS portals as well as an increasingly more common data policy of freely available RS data and data products such as the Copernicus missions (Sentinel 1-5) or the hyperspectral (EnMAP) satellite missions makes extensive spatio-temporal data available to SDM. Determining the growth period [194] deriving global NDVI trends [458], recording shifts in biochemical traits [82,84,162,194], recording changes in land-use [459], land-use intensity [460] or long-term deforestation dynamics as well as quantifying structural forest characteristics like fragmentation, spatial distribution, structure, heterogeneity or homogeneity configuration of forest patterns are all factors that provide us with crucial information [143,257,259,271]. Deblauwe et al, [461] used remotely-sensed temperatures and precipitation data derived from RS-data to improve species distribution modelling in tropical forest areas.…”

Section: Modelling Stress and Disturbances In Species Distributions Amentioning

confidence: 99%

“…Garnier et al, [50] were able to prove a direct relationship between plant traits (regeneration traits such as reproductive plant height and flowering phenology) as a response to land-use changes and disturbance regimes. Crucial changes to forest traits can be measured by spatial-temporal analyses of forest heterogeneity patterns [258], 3D distribution of forest canopy species patches [257], forest fragmentation [267][268][269][270][271], mapping of forest structures [259], or estimating forest area and forest biomass with TanDEM-X and RapidEye RS Data [143]. For more examples, see Table 1.…”

Section: Monitoring Stress On Vegetation In Fes With Rsmentioning

confidence: 99%

Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

et al. 2016

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Anthropogenic stress and disturbance of forest ecosystems (FES) has been increasing at all scales from local to global. In rapidly changing environments, in-situ terrestrial FES monitoring approaches have made tremendous progress but they are intensive and often integrate subjective indicators for forest health (FH). Remote sensing (RS) bridges the gaps of these limitations, by monitoring indicators of FH on different spatio-temporal scales, and in a cost-effective, rapid, repetitive and objective manner. In this paper, we provide an overview of the definitions of FH, discussing the drivers, processes, stress and adaptation mechanisms of forest plants, and how we can observe FH with RS. We introduce the concept of spectral traits (ST) and spectral trait variations (STV) in the context of FH monitoring and discuss the prospects, limitations and constraints. Stress, disturbances and resource limitations can cause changes in FES taxonomic, structural and functional diversity; we provide examples how the ST/STV approach can be used for monitoring these FES characteristics. We show that RS based assessments of FH indicators using the ST/STV approach is a competent, affordable, repetitive and objective technique for monitoring. Even though the possibilities for observing the taxonomic diversity of animal species is limited with RS, the taxonomy of forest tree species can be recorded with RS, even though its accuracy is subject to certain constraints. RS has proved successful for monitoring the impacts from stress on structural and functional diversity. In particular, it has proven to be very suitable for recording the short-term dynamics of stress on FH, which cannot be cost-effectively recorded using in-situ methods. This paper gives an overview of the ST/STV approach, whereas the second paper of this series concentrates on discussing in-situ terrestrial monitoring, in-situ RS approaches and RS sensors and techniques for measuring ST/STV for FH.

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Mapping the structure of Borneo's tropical forests across a degradation gradient

Cited by 93 publications

References 77 publications

Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches

Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches

Abundance signals of amphibians and reptiles indicate strong edge effects in Neotropical fragmented forest landscapes

Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics

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