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2. Thresholds for adding degraded tropical forest to the conservation estate

Author

Ewers, Robert M., Orme, C. David L., Pearse, William D., Zulkifli, Nursyamin, Yvon-Durocher, Genevieve, Yusah, Kalsum M., Yoh, Natalie, Yeo, Darren C. J., Wong, Anna, Williamson, Joseph, Wilkinson, Clare L., Wiederkehr, Fabienne, Webber, Bruce L., Wearn, Oliver R., Wai, Leona, Vollans, Maisie, Twining, Joshua P., Turner, Edgar C., Tobias, Joseph A., Thorley, Jack, Telford, Elizabeth M., Teh, Yit Arn, Tan, Heok Hui, Swinfield, Tom, Svátek, Martin, Struebig, Matthew, Stork, Nigel, Sleutel, Jani, Slade, Eleanor M., Sharp, Adam, Shabrani, Adi, Sethi, Sarab S., Seaman, Dave J. I., Sawang, Anati, Roxby, Gabrielle Briana, Rowcliffe, J. Marcus, Rossiter, Stephen J., Riutta, Terhi, Rahman, Homathevi, Qie, Lan, Psomas, Elizabeth, Prairie, Aaron, Poznansky, Frederica, Pillay, Rajeev, Picinali, Lorenzo, Pianzin, Annabel, Pfeifer, Marion, Parrett, Jonathan M., Noble, Ciar D., Nilus, Reuben, Mustaffa, Nazirah, Mullin, Katherine E., Mitchell, Simon, Mckinlay, Amelia R., Maunsell, Sarah, Matula, Radim, Massam, Michael, Martin, Stephanie, Malhi, Yadvinder, Majalap, Noreen, Maclean, Catherine S., Mackintosh, Emma, Luke, Sarah H., Lewis, Owen T., Layfield, Harry J., Lane-Shaw, Isolde, Kueh, Boon Hee, Kratina, Pavel, Konopik, Oliver, Kitching, Roger, Kinneen, Lois, Kemp, Victoria A., Jotan, Palasiah, Jones, Nick, Jebrail, Evyen W., Hroneš, Michal, Heon, Sui Peng, Hemprich-Bennett, David R., Haysom, Jessica K., Harianja, Martina F., Hardwick, Jane, Gregory, Nichar, Gray, Ryan, Gray, Ross E. J., Granville, Natasha, Gill, Richard, Fraser, Adam, Foster, William A., Folkard-Tapp, Hollie, Fletcher, Robert J., Fikri, Arman Hadi, Fayle, Tom M., Faruk, Aisyah, Eggleton, Paul, Edwards, David P., Drinkwater, Rosie, Dow, Rory A., Döbert, Timm F., Didham, Raphael K., Dickinson, Katharine J. M., Deere, Nicolas J., de Lorm, Tijmen, Dawood, Mahadimenakbar M., Davison, Charles W., Davies, Zoe G., Davies, Richard G., Dančák, Martin, Cusack, Jeremy, Clare, Elizabeth L., Chung, Arthur, Chey, Vun Khen, Chapman, Philip M., Cator, Lauren, Carpenter, Daniel, Carbone, Chris, Calloway, Kerry, Bush, Emma R., Burslem, David F. R. P., Brown, Keiron D., Brooks, Stephen J., Brasington, Ella, Brant, Hayley, Boyle, Michael J. W., Both, Sabine, Blackman, Joshua, Bishop, Tom R., Bicknell, Jake E., Bernard, Henry, Basrur, Saloni, Barclay, Maxwell V. L., Barclay, Holly, Atton, Georgina, Ancrenaz, Marc, Aldridge, David C., Daniel, Olivia Z., Reynolds, Glen, and Banks-Leite, Cristina

Published
2024
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6. SLIC-UAV: A Method for monitoring recovery in tropical restoration projects through identification of signature species using UAVs

Author

Williams, Jonathan, Schönlieb, Carola-Bibiane, Swinfield, Tom, Irawan, Bambang, Achmad, Eva, Zudhi, Muhammad, Habibi, Gemita, Elva, and Coomes, David A.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract

Logged forests cover four million square kilometres of the tropics and restoring these forests is essential if we are to avoid the worst impacts of climate change, yet monitoring recovery is challenging. Tracking the abundance of visually identifiable, early-successional species enables successional status and thereby restoration progress to be evaluated. Here we present a new pipeline, SLIC-UAV, for processing Unmanned Aerial Vehicle (UAV) imagery to map early-successional species in tropical forests. The pipeline is novel because it comprises: (a) a time-efficient approach for labelling crowns from UAV imagery; (b) machine learning of species based on spectral and textural features within individual tree crowns, and (c) automatic segmentation of orthomosaiced UAV imagery into 'superpixels', using Simple Linear Iterative Clustering (SLIC). Creating superpixels reduces the dataset's dimensionality and focuses prediction onto clusters of pixels, greatly improving accuracy. To demonstrate SLIC-UAV, support vector machines and random forests were used to predict the species of hand-labelled crowns in a restoration concession in Indonesia. Random forests were most accurate at discriminating species for whole crowns, with accuracy ranging from 79.3% when mapping five common species, to 90.5% when mapping the three most visually-distinctive species. In contrast, support vector machines proved better for labelling automatically segmented superpixels, with accuracy ranging from 74.3% to 91.7% for the same species. Models were extended to map species across 100 hectares of forest. The study demonstrates the power of SLIC-UAV for mapping characteristic early-successional tree species as an indicator of successional stage within tropical forest restoration areas. Continued effort is needed to develop easy-to-implement and low-cost technology to improve the affordability of project management.

Published
2020

7. Carbon flux and forest dynamics: Increased deadwood decomposition in tropical rainforest tree‐fall canopy gaps

Author

Griffiths, Hannah M, Eggleton, Paul, Hemming‐Schroeder, Nicole, Swinfield, Tom, Woon, Joel S, Allison, Steven D, Coomes, David A, Ashton, Louise A, and Parr, Catherine L

Subjects
Biological Sciences, Ecology, Life on Land, Carbon, Carbon Cycle, Ecosystem, Forests, Rainforest, Trees, Tropical Climate, carbon cycling, carbon modelling, disturbance, global change, invertebrates, termites, tree mortality, Environmental Sciences, Biological sciences, Earth sciences, Environmental sciences
Abstract

Tree mortality rates are increasing within tropical rainforests as a result of global environmental change. When trees die, gaps are created in forest canopies and carbon is transferred from the living to deadwood pools. However, little is known about the effect of tree-fall canopy gaps on the activity of decomposer communities and the rate of deadwood decay in forests. This means that the accuracy of regional and global carbon budgets is uncertain, especially given ongoing changes to the structure of rainforest ecosystems. Therefore, to determine the effect of canopy openings on wood decay rates and regional carbon flux, we carried out the first assessment of deadwood mass loss within canopy gaps in old-growth rainforest. We used replicated canopy gaps paired with closed canopy sites in combination with macroinvertebrate accessible and inaccessible woodblocks to experimentally partition the relative contribution of microbes vs. termites to decomposition within contrasting understorey conditions. We show that over a 12 month period, wood mass loss increased by 63% in canopy gaps compared with closed canopy sites and that this increase was driven by termites. Using LiDAR data to quantify the proportion of canopy openings in the study region, we modelled the effect of observed changes in decomposition within gaps on regional carbon flux. Overall, we estimate that this accelerated decomposition increases regional wood decay rate by up to 18.2%, corresponding to a flux increase of 0.27 Mg C ha-1  year-1 that is not currently accounted for in regional carbon budgets. These results provide the first insights into how small-scale disturbances in rainforests can generate hotspots for decomposer activity and carbon fluxes. In doing so, we show that including canopy gap dynamics and their impacts on wood decomposition in forest ecosystems can help improve the predictive accuracy of the carbon cycle in land surface models.

Published
2021

8. Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)

Author

Williams, Jonathan, Schönlieb, Carola-Bibiane, Swinfield, Tom, Lee, Juheon, Cai, Xiaohao, Qie, Lan, and Coomes, David A.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Developing a robust algorithm for automatic individual tree crown (ITC) detection from laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of individual trees to be measured, enabling forest carbon stocks and dynamics to be tracked and understood. Many algorithms exist for structurally simple forests including coniferous forests and plantations. Finding a robust solution for structurally complex, species-rich tropical forests remains a challenge; existing segmentation algorithms often perform less well than simple area-based approaches when estimating plot-level biomass. Here we describe a Multi-Class Graph Cut (MCGC) approach to tree crown delineation. This uses local three-dimensional geometry and density information, alongside knowledge of crown allometries, to segment individual tree crowns from LiDAR point clouds. Our approach robustly identifies trees in the top and intermediate layers of the canopy, but cannot recognise small trees. From these three-dimensional crowns, we are able to measure individual tree biomass. Comparing these estimates to those from permanent inventory plots, our algorithm is able to produce robust estimates of hectare-scale carbon density, demonstrating the power of ITC approaches in monitoring forests. The flexibility of our method to add additional dimensions of information, such as spectral reflectance, make this approach an obvious avenue for future development and extension to other sources of three-dimensional data, such as structure from motion datasets.

Published
2019
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19. Credit credibility threatens forests

Author

Balmford, Andrew, primary, Brancalion, Pedro H. S., additional, Coomes, David, additional, Filewod, Ben, additional, Groom, Ben, additional, Guizar-Couti ño, Alejandro, additional, Jones, Julia P. G., additional, Keshav, Srinivasan, additional, Kontoleon, Andreas, additional, Madhavapeddy, Anil, additional, Malhi, Yadvinder, additional, Sills, Erin O., additional, Strassburg, Bernardo B. N., additional, Venmans, Frank, additional, West, Thales A. P., additional, Wheeler, Charlotte, additional, and Swinfield, Tom, additional

Published
2023
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21. The road to recovery: a synthesis of outcomes from ecosystem restoration in tropical and sub-tropical Asian forests

Author

Banin, Lindsay F., Raine, Elizabeth H., Rowland, Lucy M., Chazdon, Robin L., Smith, Stuart W., Rahman, Nur Estya Binte, Butler, Adam, Philipson, Christopher, Applegate, Grahame G., Axelsson, E. Petter, Budiharta, Sugeng, Chua, Siew Chin, Cutler, Mark E.J., Elliott, Stephen, Gemita, Elva, Godoong, Elia, Graham, Laura L.B., Hayward, Robin M., Hector, Andy, Ilstedt, Ulrik, Jensen, Joel, Kasinathan, Srinivasan, Kettle, Christopher J., Lussetti, Daniel, Manohan, Benjapan, Maycock, Colin, Ngo, Kang Min, O'Brien, Michael J., Osuri, Anand M., Reynolds, Glen, Sauwai, Yap, Scheu, Stefan, Silalahi, Mangarah, Slade, Eleanor M., Swinfield, Tom, Wardle, David A., Wheeler, Charlotte, Yeong, Kok Loong, Burslem, David F.R.P., Banin, Lindsay F., Raine, Elizabeth H., Rowland, Lucy M., Chazdon, Robin L., Smith, Stuart W., Rahman, Nur Estya Binte, Butler, Adam, Philipson, Christopher, Applegate, Grahame G., Axelsson, E. Petter, Budiharta, Sugeng, Chua, Siew Chin, Cutler, Mark E.J., Elliott, Stephen, Gemita, Elva, Godoong, Elia, Graham, Laura L.B., Hayward, Robin M., Hector, Andy, Ilstedt, Ulrik, Jensen, Joel, Kasinathan, Srinivasan, Kettle, Christopher J., Lussetti, Daniel, Manohan, Benjapan, Maycock, Colin, Ngo, Kang Min, O'Brien, Michael J., Osuri, Anand M., Reynolds, Glen, Sauwai, Yap, Scheu, Stefan, Silalahi, Mangarah, Slade, Eleanor M., Swinfield, Tom, Wardle, David A., Wheeler, Charlotte, Yeong, Kok Loong, and Burslem, David F.R.P.

Abstract

Current policy is driving renewed impetus to restore forests to return ecological function, protect species, sequester carbon and secure livelihoods. Here we assess the contribution of tree planting to ecosystem restoration in tropical and sub-tropical Asia; we synthesize evidence on mortality and growth of planted trees at 176 sites and assess structural and biodiversity recovery of co-located actively restored and naturally regenerating forest plots. Mean mortality of planted trees was 18% 1 year after planting, increasing to 44% after 5 years. Mortality varied strongly by site and was typically ca 20% higher in open areas than degraded forest, with height at planting positively affecting survival. Size-standardized growth rates were negatively related to species-level wood density in degraded forest and plantations enrichment settings. Based on community-level data from 11 landscapes, active restoration resulted in faster accumulation of tree basal area and structural properties were closer to old-growth reference sites, relative to natural regeneration, but tree species richness did not differ. High variability in outcomes across sites indicates that planting for restoration is potentially rewarding but risky and context-dependent. Restoration projects must prepare for and manage commonly occurring challenges and align with efforts to protect and reconnect remaining forest areas.

Published
2023

22. Credit credibility threatens forests

Author

Balmford, Andrew, Brancalion, Pedro HS, Coomes, David, Filewod, Ben, Groom, Ben, Guizar-Coutiño, Alejandro, Jones, Julia PG, Keshav, Srinivasan, Kontoleon, Andreas, Madhavapeddy, Anil, Malhi, Yadvinder, Sills, Erin O, Strassburg, Bernardo BN, Venmans, Frank, West, Thales AP, Wheeler, Charlotte, Swinfield, Tom, Balmford, Andrew [0000-0002-0144-3589], Coomes, David [0000-0002-8261-2582], Keshav, Srinivasan [0000-0002-6549-0464], Kontoleon, Andreas [0000-0003-4769-898X], Madhavapeddy, Anil [0000-0001-8954-2428], Apollo - University of Cambridge Repository, and Environmental Geography

Subjects
Greenhouse Gases, Conservation of Natural Resources, Multidisciplinary, Forests, Global Warming, Carbon
Published
2023

24. Avifauna recovers faster in areas less accessible to trapping in regenerating tropical forests

Author

Sagar, HS Sathya Chandra, Gilroy, James J, Swinfield, Tom, Burivalova, Zuzana, Li Yong, Ding, Gemita, Elva, Novriyanti, Novriyanti, Lee, David C, Janra, Muhammad Nazri, Balmford, Andrew, Hua, Fangyuan, Balmford, Andrew [0000-0002-0144-3589], and Apollo - University of Cambridge Repository

Subjects
Birds, Pet trade, Conservation, Reforestation, Nature-based climate solutions, Ecosystem restoration, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation
Abstract

Tropical forest restoration stands to deliver important conservation gains, particularly in lowland Southeast Asia, which has suffered some of the world's highest rates of recent forest loss and degradation. This promise, however, depends on the extent to which biodiversity at forest restoration sites continues to be exposed to threats. A key knowledge gap concerns the extent to which biodiversity recovery in naturally regenerating tropical forests is impacted by trapping for the multi-million-dollar wildlife trade. Here, we use a repeated survey dataset to quantify rates of avian community recovery under forest regeneration, at a flagship restoration site in the lowland rainforests of Sumatra, Indonesia. We show that over a decade, forest regeneration was associated with significant abundance increases for 43.8 % of bird species. However, the apparent negative impacts of trade-driven trapping on avian populations also intensified: the proportion of species dependent on very remote forests increased from 5.4 % to 16.2 %. Moreover, the overall accessibility of the forest increased. We found that 14 % of species did not recover as fast as predicted based on the observed forest regeneration over the study period. We found trapping to disproportionately impact species targeted for trade: compared to opportunistically trapped species, twice more species showed increased abundance only in very remote forests. Our results highlight the potential for rapid avifaunal recovery in regenerating tropical forests, but also emphasize the urgency of tackling the serious threat of wildlife trade to Southeast Asia's biodiversity.

Published
2023

25. The road to recovery: a synthesis of outcomes from ecosystem restoration in tropical and sub-tropical Asian forests

Author

Banin, Lindsay F., primary, Raine, Elizabeth H., additional, Rowland, Lucy M., additional, Chazdon, Robin L., additional, Smith, Stuart W., additional, Rahman, Nur Estya Binte, additional, Butler, Adam, additional, Philipson, Christopher, additional, Applegate, Grahame G., additional, Axelsson, E. Petter, additional, Budiharta, Sugeng, additional, Chua, Siew Chin, additional, Cutler, Mark E. J., additional, Elliott, Stephen, additional, Gemita, Elva, additional, Godoong, Elia, additional, Graham, Laura L. B., additional, Hayward, Robin M., additional, Hector, Andy, additional, Ilstedt, Ulrik, additional, Jensen, Joel, additional, Kasinathan, Srinivasan, additional, Kettle, Christopher J., additional, Lussetti, Daniel, additional, Manohan, Benjapan, additional, Maycock, Colin, additional, Ngo, Kang Min, additional, O'Brien, Michael J., additional, Osuri, Anand M., additional, Reynolds, Glen, additional, Sauwai, Yap, additional, Scheu, Stefan, additional, Silalahi, Mangarah, additional, Slade, Eleanor M., additional, Swinfield, Tom, additional, Wardle, David A., additional, Wheeler, Charlotte, additional, Yeong, Kok Loong, additional, and Burslem, David F. R. P., additional

Published
2022
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30. The impact of logging on vertical canopy structure across a gradient of tropical forest degradation intensity in Borneo

Author

Milodowski, David T., primary, Coomes, David A., additional, Swinfield, Tom, additional, Jucker, Tommaso, additional, Riutta, Terhi, additional, Malhi, Yadvinder, additional, Svátek, Martin, additional, Kvasnica, Jakub, additional, Burslem, David F. R. P., additional, Ewers, Robert M., additional, Teh, Yit Arn, additional, and Williams, Mathew, additional

Published
2021
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31. Riparian buffers act as microclimatic refugia in oil palm landscapes

Author

Williamson, Joseph, Slade, Eleanor M., Luke, Sarah H., Swinfield, Tom, Chung, Arthur Y. C., Coomes, David A., Heroin, Herry, Jucker, Tommaso, Lewis, Owen T., Charles Santhanaraju Vairappan, Rossiter, Stephen J., Struebig, Matthew J., Williamson, Joseph, Slade, Eleanor M., Luke, Sarah H., Swinfield, Tom, Chung, Arthur Y. C., Coomes, David A., Heroin, Herry, Jucker, Tommaso, Lewis, Owen T., Charles Santhanaraju Vairappan, Rossiter, Stephen J., and Struebig, Matthew J.

Abstract

There is growing interest in the ecological value of set-aside habitats around rivers in tropical agriculture. These riparian buffers typically comprise forest or other non-production habitat, and are established to maintain water quality and hydrological processes, while also supporting biodiversity, ecosystem function and landscape connectivity. We investigated the capacity for riparian buffers to act as microclimatic refugia by combining field-based measurements of temperature, humidity and dung beetle communities with remotely sensed data from LiDAR across an oil palm dominated landscape in Borneo. Riparian buffers offer a cool and humid habitat relative to surrounding oil palm plantations, with wider buffers characterised by conditions comparable to riparian sites in continuous logged forest. High vegetation quality and topographic sheltering were strongly associated with cooler and more humid microclimates in riparian habitats across the landscape. Variance in beetle diversity was also predicted by both proximity-to-edge and microclimatic conditions within the buffer, suggesting that narrow buffers amplify the negative impacts that high temperatures have on biodiversity. Synthesis and applications. Widely legislated riparian buffer widths of 20–30 m each side of a river may provide drier and less humid microclimatic conditions than continuous forest. Adopting wider buffers and maintaining high vegetation quality will ensure set-asides established for hydrological reasons bring co-benefits for terrestrial biodiversity, both now, and in the face of anthropogenic climate change.

Published
2021

32. Leech blood-meal invertebrate-derived DNA reveals differences in Bornean mammal diversity across habitats

Author

Drinkwater, Rosie, Jucker, Tommaso, Potter, Joshua H. T., Swinfield, Tom, Coomes, David A., Slade, Eleanor M., Gilbert, M. Thomas P., Lewis, Owen T., Bernard, Henry, Struebig, Matthew J., Clare, Elizabeth L., Rossiter, Stephen J., Drinkwater, Rosie, Jucker, Tommaso, Potter, Joshua H. T., Swinfield, Tom, Coomes, David A., Slade, Eleanor M., Gilbert, M. Thomas P., Lewis, Owen T., Bernard, Henry, Struebig, Matthew J., Clare, Elizabeth L., and Rossiter, Stephen J.

Abstract

The application of metabarcoding to environmental and invertebrate-derived DNA (eDNA and iDNA) is a new and increasingly applied method for monitoring biodiversity across a diverse range of habitats. This approach is particularly promising for sampling in the biodiverse humid tropics, where rapid land-use change for agriculture means there is a growing need to understand the conservation value of the remaining mosaic and degraded landscapes. Here we use iDNA from blood-feeding leeches (Haemadipsa picta) to assess differences in mammalian diversity across a gradient of forest degradation in Sabah, Malaysian Borneo. We screened 557 individual leeches for mammal DNA by targeting fragments of the 16S rRNA gene and detected 14 mammalian genera. We recorded lower mammal diversity in the most heavily degraded forest compared to higher quality twice logged forest. Although the accumulation curves of diversity estimates were comparable across these habitat types, diversity was higher in twice logged forest, with more taxa of conservation concern. In addition, our analysis revealed differences between the community recorded in the heavily logged forest and that of the twice logged forest. By revealing differences in mammal diversity across a human-modified tropical landscape, our study demonstrates the value of iDNA as a noninvasive biomonitoring approach in conservation assessments.

Published
2021

33. Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)

Author

Williams, Jonathan, Schoenlieb, Carola, Swinfield, Tom, Lee, Juheon, Cai, Xiaohao, Qie, Lan, Coomes, David, Williams, Jonathan [0000-0001-6257-6695], Schoenlieb, Carola-Bibiane [0000-0003-0099-6306], Swinfield, Thomas [0000-0001-9354-5090], Coomes, David [0000-0002-8261-2582], and Apollo - University of Cambridge Repository

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, 010504 meteorology & atmospheric sciences, Computer Vision and Pattern Recognition (cs.CV), 0211 other engineering and technologies, Computer Science - Computer Vision and Pattern Recognition, 02 engineering and technology, H610 Electronic Engineering, G400 Computer Science, 15. Life on land, G120 Applied Mathematics, 01 natural sciences, Machine Learning (cs.LG), H240 Surveying Science, C180 Ecology, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences
Abstract

Developing a robust algorithm for automatic individual tree crown (ITC) detection from airborne laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of individual trees to be measured, enabling forest carbon stocks and dynamics to be tracked and understood. Many algorithms exist for structurally simple forests including coniferous forests and plantations. Finding a robust solution for structurally complex, species-rich tropical forests remains a challenge; existing segmentation algorithms often perform less well than simple area-based approaches when estimating plot-level biomass. Here we describe a Multi-Class Graph Cut (MCGC) approach to tree crown delineation. This uses local three-dimensional geometry and density information, alongside knowledge of crown allometries, to segment individual tree crowns from airborne LiDAR point clouds. Our approach robustly identifies trees in the top and intermediate layers of the canopy, but cannot recognise small trees. From these three-dimensional crowns, we are able to measure individual tree biomass. Comparing these estimates to those from permanent inventory plots, our algorithm is able to produce robust estimates of hectare-scale carbon density, demonstrating the power of ITC approaches in monitoring forests. The flexibility of our method to add additional dimensions of information, such as spectral reflectance, make this approach an obvious avenue for future development and extension to other sources of three-dimensional data, such as structure from motion datasets., Jonathan Williams holds a NERC studentship [NE/N008952/1] which is a CASE partnership with support from Royal Society for the Protection of Birds (RSPB). David Coomes was supported by an International Academic Fellowship from the Leverhulme Trust. Carola-Bibiane Schoenlieb was supported by the RISE projects CHiPS and NoMADS, the Cantab Capital Institute for the Mathematics of Information and the Alan Turing Institute. We gratefully acknowledge the support of NVIDIA Corporation with the donation of a Quadro P6000 GPU used for this research.

Published
2020

34. Imaging spectroscopy reveals the effects of topography and logging on the leaf chemistry of tropical forest canopy trees

Author

Swinfield, Tom, Both, Sabine, Riutta, Terhi, Bongalov, Boris, Elias, Dafydd, Majalap‐Lee, Noreen, Ostle, Nicholas, Svátek, Martin, Kvasnica, Jakub, Milodowski, David, Jucker, Tommaso, Ewers, Robert M., Zhang, Yi, Johnson, David, Teh, Yit Arn, Burslem, David F.R.P., Malhi, Yadvinder, Coomes, David, Swinfield, Tom, Both, Sabine, Riutta, Terhi, Bongalov, Boris, Elias, Dafydd, Majalap‐Lee, Noreen, Ostle, Nicholas, Svátek, Martin, Kvasnica, Jakub, Milodowski, David, Jucker, Tommaso, Ewers, Robert M., Zhang, Yi, Johnson, David, Teh, Yit Arn, Burslem, David F.R.P., Malhi, Yadvinder, and Coomes, David

Abstract

Logging, pervasive across the lowland tropics, affects millions of hectares of forest, yet its influence on nutrient cycling remains poorly understood. One hypothesis is that logging influences phosphorus (P) cycling, because this scarce nutrient is removed in extracted timber and eroded soil, leading to shifts in ecosystem functioning and community composition. However, testing this is challenging because P varies within landscapes as a function of geology, topography and climate. Superimposed upon these trends are compositional changes in logged forests, with species with more acquisitive traits, characterized by higher foliar P concentrations, more dominant. It is difficult to resolve these patterns using traditional field approaches alone. Here, we use airborne light detection and ranging‐guided hyperspectral imagery to map foliar nutrient (i.e. P, nitrogen [N]) concentrations, calibrated using field measured traits, over 400 km2 of northeastern Borneo, including a landscape‐level disturbance gradient spanning old‐growth to repeatedly logged forests. The maps reveal that canopy foliar P and N concentrations decrease with elevation. These relationships were not identified using traditional field measurements of leaf and soil nutrients. After controlling for topography, canopy foliar nutrient concentrations were lower in logged forest than in old‐growth areas, reflecting decreased nutrient availability. However, foliar nutrient concentrations and specific leaf area were greatest in relatively short patches in logged areas, reflecting a shift in composition to pioneer species with acquisitive traits. N:P ratio increased in logged forest, suggesting reduced soil P availability through disturbance. Through the first landscape scale assessment of how functional leaf traits change in response to logging, we find that differences from old‐growth forest become more pronounced as logged forests increase in stature over time, suggesting exacerbated phosphorus limitation as

Published
2020

35. Leech blood‐meal invertebrate‐derived DNA reveals differences in Bornean mammal diversity across habitats

Author

Drinkwater, Rosie, Jucker, Tommaso, Potter, Joshua H.T, Swinfield, Tom, Coomes, David, Slade, Eleanor M., Gilbert, M. Thomas P., Lewis, Owen T., Bernard, Henry, Struebig, Matthew J., Clare, Elizabeth L., Rossiter, Stephen J., Drinkwater, Rosie, Jucker, Tommaso, Potter, Joshua H.T, Swinfield, Tom, Coomes, David, Slade, Eleanor M., Gilbert, M. Thomas P., Lewis, Owen T., Bernard, Henry, Struebig, Matthew J., Clare, Elizabeth L., and Rossiter, Stephen J.

Abstract

The application of metabarcoding to environmental and invertebrate‐derived DNA (eDNA and iDNA) is a new and increasingly applied method for monitoring biodiversity across a diverse range of habitats. This approach is particularly promising for sampling in the biodiverse humid tropics, where rapid land‐use change for agriculture means there is a growing need to understand the conservation value of the remaining mosaic and degraded landscapes. Here we use iDNA from blood‐feeding leeches (Haemadipsa picta) to assess differences in mammalian diversity across a gradient of forest degradation in Sabah, Malaysian Borneo. We screened 557 individual leeches for mammal DNA by targeting fragments of the 16S rRNA gene and detected 14 mammalian genera. We recorded lower mammal diversity in the most heavily degraded forest compared to higher quality twice logged forest. Although the accumulation curves of diversity estimates were comparable across these habitat types, diversity was higher in twice logged forest, with more taxa of conservation concern. In addition, our analysis revealed differences between the community recorded in the heavily logged forest and that of the twice logged forest. By revealing differences in mammal diversity across a human‐modified tropical landscape, our study demonstrates the value of iDNA as a non‐invasive biomonitoring approach in conservation assessments.

Published
2020

36. Riparian buffers act as microclimatic refugia in oil palm landscapes

Author

Williamson, Joseph, Slade, Eleanor M., Luke, Sarah H., Swinfield, Tom, Chung, Arthur Y. C., Coomes, David, Heroin, Herry, Jucker, Tommaso, Lewis, Owen, Vairappan, Charles S., Rossiter, Stephen J., Struebig, Matthew J., Williamson, Joseph, Slade, Eleanor M., Luke, Sarah H., Swinfield, Tom, Chung, Arthur Y. C., Coomes, David, Heroin, Herry, Jucker, Tommaso, Lewis, Owen, Vairappan, Charles S., Rossiter, Stephen J., and Struebig, Matthew J.

Abstract

There is growing interest in the ecological value of set‐aside habitats around rivers in tropical agriculture. These riparian buffers typically comprise forest or other non‐production habitat, and are established to maintain water quality and hydrological processes, while also supporting biodiversity, ecosystem function and landscape connectivity. We investigated the capacity for riparian buffers to act as microclimatic refugia by combining field‐based measurements of temperature, humidity and dung beetle communities with remotely sensed data from LiDAR across an oil palm dominated landscape in Borneo. Riparian buffers offer a cool and humid habitat relative to surrounding oil palm plantations, with wider buffers characterised by conditions comparable to riparian sites in continuous logged forest. High vegetation quality and topographic sheltering were strongly associated with cooler and more humid microclimates in riparian habitats across the landscape. Variance in beetle diversity was also predicted by both proximity‐to‐edge and microclimatic conditions within the buffer, suggesting that narrow buffers amplify the negative impacts that high temperatures have on biodiversity. Synthesis and applications. Widely legislated riparian buffer widths of 20–30 m each side of a river may provide drier and less humid microclimatic conditions than continuous forest. Adopting wider buffers and maintaining high vegetation quality will ensure set‐asides established for hydrological reasons bring co‐benefits for terrestrial biodiversity, both now, and in the face of anthropogenic climate change.

Published
2020

38. Leech blood‐meal invertebrate‐derived DNA reveals differences in Bornean mammal diversity across habitats

Author

Drinkwater, Rosie, primary, Jucker, Tommaso, additional, Potter, Joshua H. T., additional, Swinfield, Tom, additional, Coomes, David A., additional, Slade, Eleanor M., additional, Gilbert, M. Thomas P., additional, Lewis, Owen T., additional, Bernard, Henry, additional, Struebig, Matthew J., additional, Clare, Elizabeth L., additional, and Rossiter, Stephen J., additional

Published
2020
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39. Riparian buffers act as microclimatic refugia in oil palm landscapes

Author

Williamson, Joseph, primary, Slade, Eleanor M., additional, Luke, Sarah H., additional, Swinfield, Tom, additional, Chung, Arthur Y. C., additional, Coomes, David A., additional, Heroin, Herry, additional, Jucker, Tommaso, additional, Lewis, Owen T., additional, Vairappan, Charles S., additional, Rossiter, Stephen J., additional, and Struebig, Matthew J., additional

Published
2020
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41. A Research Agenda for Microclimate Ecology in Human-Modified Tropical Forests

Author

Jucker, Tommaso, primary, Jackson, Tobias D., additional, Zellweger, Florian, additional, Swinfield, Tom, additional, Gregory, Nichar, additional, Williamson, Joseph, additional, Slade, Eleanor M., additional, Phillips, Josie W., additional, Bittencourt, Paulo R. L., additional, Blonder, Benjamin, additional, Boyle, Michael J. W., additional, Ellwood, M. D. Farnon, additional, Hemprich-Bennett, David, additional, Lewis, Owen T., additional, Matula, Radim, additional, Senior, Rebecca A., additional, Shenkin, Alexander, additional, Svátek, Martin, additional, and Coomes, David A., additional

Published
2020
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42. Imaging spectroscopy reveals the effects of topography and logging on the leaf chemistry of tropical forest canopy trees

Author

Swinfield, Tom, primary, Both, Sabine, additional, Riutta, Terhi, additional, Bongalov, Boris, additional, Elias, Dafydd, additional, Majalap‐Lee, Noreen, additional, Ostle, Nicholas, additional, Svátek, Martin, additional, Kvasnica, Jakub, additional, Milodowski, David, additional, Jucker, Tommaso, additional, Ewers, Robert M., additional, Zhang, Yi, additional, Johnson, David, additional, Teh, Yit Arn, additional, Burslem, David F. R. P., additional, Malhi, Yadvinder, additional, and Coomes, David, additional

Published
2019
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43. Make EU trade with Brazil sustainable

Author

Kehoe, Laura, Reis, Tiago, Virah-Sawmy, Malika, Balmford, Andrew, Kuemmerle, Tobias, Knohl, Alexander, Antonelli, Alexandre, Hochkirch, Axel, Vira, Bhaskar, Massa, Bruno, Peres, Carlos A., Ammer, Christian, Goerg, Christoph, Schneider, Christoph, Curtis, David, de la Pena, Eduardo, Tello, Enric, Sperfeld, Erik, Corbera, Esteve, Morelli, Federico, Valladares, Fernando, Peterson, Garry, Hide, Geoff, Mace, Georgina, Kallis, Giorgos, Olsson, Gunilla Almered, Brumelis, Guntis, Alexanderson, Helena, Haberl, Helmut, Nuissl, Henning, Kreft, Holger, Ghazoul, Jaboury, Piotrowski, Jan A., Macdiarmid, Jennie, Newig, Jens, Fischer, Joern, Altringham, John, Gledhill, John, Nielsen, Jonas O., Mueller, Joerg, Palmeirim, Jorge, Barlow, Jos, Alonso, Juan C., Presa Asencio, Juan Jose, Steinberger, Julia K., Jones, Julia Patricia Gordon, Cabral, Juliano Sarmento, Dengler, Juergen, Stibral, Karel, Erb, Karlheinz, Rothhaupt, Karl-Otto, Wiegand, Kerstin, Cassar, Louis F., Lens, Luc, Rosalino, Luis Miguel, Wassen, M. J., Stenseke, Marie, Fischer-Kowalski, Marina, Diaz, Mario, Rounsevell, Mark, van Kleunen, Mark, Junginger, Martin, Kaltenpoth, Martin, Zobel, Martin, Weigend, Maximilian, Partel, Meelis, Schilthuizen, Menno, Bastos Araujo, Miguel, Haklay, Muki, Eisenhauer, Nico, Selva, Nuria, Mertz, Ole, Meyfroidt, Patrick, Borges, Paulo A. V., Kovar, Pavel, Smith, Pete, Verburg, Peter, Pysek, Petr, Seppelt, Ralf, Valentini, Riccardo, Whittaker, Robert J., Henrique Faria, Sergio, Ulgiati, Sergio, Loetters, Stefan, Bjorck, Svante, Larson, Sven Ake, Tscharntke, Teja, Domingos, Tiago, Krueger, Tobias, Pascual, Unai, Olsson, Urban, Kati, Vassiliki, Winiwarter, Verena, Reyes-Garcia, Victoria, Vajda, Vivi, Sutherland, William J., de Waroux, Yann le Polain, Buckley, Yvonne, Rammig, Anja, Kasimir, Asa, Crona, Beatrice, Sindicic, Magda, Persson, Martin, Lapka, Miloslav, Di Gregorio, Monica, Hahn, Thomas, Boonstra, Wiebren, Lipsky, Zdenek, Zucaro, A., Roeder, Achim, Lopez Baucells, Adria, Danet, Alain, Franco, Aldina, Nieto Roman, Alejandra, Lehikoinen, Aleksi, Collalti, Alessio, Keller, Alexander, Strugariu, Alexandru, Perrigo, Allison, Fernandez-Llamazares, Alvaro, Salaseviciene, Alvija, Hinsley, Amy, Santos, Ana M. C., Novoa, Ana, Rodrigues, Ana, Mascarenhas, Andre, Martins, Andrea Damacena, Holzschuh, Andrea, Meseguer, Andrea S., Hadjichambis, Andreas, Mayer, Andreas, Hacket-Pain, Andrew, Ringsmuth, Andrew, de Frutos, Angel, Stein, Anke, Heikkinen, Anna, Smith, Annabel, Bjoersne, Anna-Karin, Bagneres, Anne-Genevieve, Machordom, Annie, Kristin, Anton, Ghoddousi, Arash, Staal, Arie, Martin, Arnaud, Taylor, Astrid, Borrell, Asuncion, Marescaux, Audrey, Torres, Aurora, Helm, Aveliina, Bauer, Barbara, Smetschka, Barbara, Rodriguez-Labajos, Beatriz, Peco, Begona, Gambin, Belinda, Celine, Bellard, Phalan, Ben, Cotta, Benedetta, Rugani, Benedetto, Jarcuska, Benjamin, Leroy, Boris, Nikolov, Boris Petrov, Milchev, Boyan Petrov, Brown, Calum, Ritter, Camila Duarte, Gomes, Carmen Bessa, Meyer, Carsten, Munteanu, Catalina, Penone, Caterina, Friis, Cecilie, Teplitsky, Celine, Roemer, Charlotte, Orland, Chloe, Voigt, Christian C., Levers, Christian, Zang, Christian, Bacon, Christine D., Meyer, Christoph, Wordley, Claire, Grilo, Clara, Cattaneo, Claudio, Battisti, Corrado, Banks-Leite, Cristina, Zurell, Damaris, Challender, Dan, Mueller, Daniel, Matenaar, Daniela, Silvestro, Daniele, McKay, David Armstrong, Buckley, David, Frantz, David, Gremillet, David, Mateos, David Moreno, Sanchez-Fernandez, David, Vieites, David, Ascoli, Davide, Arlt, Debora, Louis, Deharveng, Zemp, Delphine Clara, Strubbe, Diederik, Gil, Diego, Llusia, Diego, Bennett, Dominic J., Chobanov, Dragan Petrov, Aguilera, Eduardo, Oliveira, Eduardo, Pynegar, Edwin L., Granda, Elena, Grieco, Elisa, Conrad, Elisabeth, Revilla, Eloy, Lindkvist, Emilie, Caprio, Enrico, zu Ermgassen, Erasmus, Berenguer, Erika, Ochu, Erinma, Polaina, Ester, Nuernberger, Fabian, Esculier, Fabien, de Castro, Fabio, Albanito, Fabrizio, Langerwisch, Fanny, Batsleer, Femke, Ascensao, Fernando, Moyano, Fernando Esteban, Sayol, Ferran, Buzzetti, Filippo Maria, Eiro, Flavio, Volaire, Florence, Gollnow, Florian, Menzel, Florian, Pilo, Francesca, Moreira, Francisco, Briens, Francois, Essl, Franz, Vlahos, George, Billen, Gilles, Vacchiano, Giorgio, Wong, Grace, Gruychev, Gradimir Valentinov, Fandos, Guillermo, Petter, Gunnar, Sinare, Hanna, Mumby, Hannah S., Cottyn, Hanne, Seebens, Hanno, Bjorklund, Heidi, Schroeder, Heike, Lopez Hernandez, Heriberto D., Rebelo, Hugo, Chenet, Hugues, De la Riva, Ignacio, Torre, Ignasi, Aalders, Inge, Grass, Ingo, Chuine, Isabelle, Goepel, Jan, Wieringa, Jan J., Engler, Jan O., Pergl, Jan, Schnitzler, Jan, Vavra, Jan, Medvedovic, Jasna, Cabello, Javier, Martin, Jean-Louis, Mutke, Jens, Lewis, Jerome, da Silva, Jessica Fonseca, Marull, Joan, Carvalho, Joana, Carnicer, Jofre, Enqvist, Johan, Simaika, John P., Noguera, Jose C., Blanco Moreno, Jose M., Bruna, Josef, Garnier, Josette, Fargallo, Juan A., Rocha, Juan Carlos, Carrillo, Juan D., Infante-Amate, Juan, Traba Diaz, Juan, Schleicher, Judith, Simon, Judy, Noe, Julia Le, Gerlach, Justin, Eriksson, K. Martin, Prince, Karine, Ostapowicz, Katarzyna, Stajerova, Katerina, Farrell, Katharine N., Snell, Katherine, Yates, Katherine, Fleischer, Katrin, Darras, Kevin, Schumacher, Kim, Orach, Kirill, Thonicke, Kirsten, Riede, Klaus, Heller, Klaus-Gerhard, Wang-Erlandsson, Lan, Pereira, Laura, Riggi, Laura, Florez, Laura V., Emperaire, Laure, Durieux, Laurent, Tatin, Laurent, Rozylowicz, Laurentiu, Latella, Leonardo, Andresen, Louise C., Cahen-Fourot, Louison, de Agua, Luis Borda, Boto, Luis, Lassaletta, Luis, Amo, Luisa, Sekerka, Lukas, Morales, Manuel B., Macia, Manuel J., Suarez, Manuela Gonzalez, Cabeza, Mar, Londo, Marc, Pollet, Marc, Schwieder, Marcel, Peters, Marcell K., D'Amico, Marcello, Casazza, Marco, Florencio, Margarita, Felipe-Lucia, Maria, Gebara, Maria Fernanda, Johansson, Maria, Garcia, Maria Mancilla, Piquer-Rodriguez, Maria, Tengo, Maria, Elias, Marianne, Leve, Marine, Conde, Marta, Winter, Marten, Koster, Martijn, Mayer, Martin, Salek, Martin, Schlerf, Martin, Sullivan, Martin, Baumann, Matthias, Pichler, Melanie, Marselle, Melissa, Oddie, Melissa, Razanajatovo, Mialy, Borregaard, Michael Krabbe, Theurl, Michaela C., Hernandez, Miguel, Krofel, Miha, Kechev, Mihail Ognianov, Clark, Mike, Rands, Mike, Antal, Miklos, Pucetaite, Milda, Islar, Mine, Truong, Minh-Xuan A., Vighi, Morgana, Johanisova, Nadia, Prat, Narcis, Escobar, Neus, Deguines, Nicolas, Rust, Niki, Zafra-Calvo, Noelia, Maurel, Noelie, Wagner, Norman, Fitton, Nuala, Ostermann, Ole, Panferov, Oleg, Ange, Olivia, Canals, Oriol, Englund, Oskar, De Smedt, Pallieter, Petridis, Panos, Heikkurinen, Pasi, Weigelt, Patrick, Henriksson, Patrik J. G., de Castro, Paula Drummond, Matos-Maravi, Pavel, Duran, Paz, Aragon, Pedro, Cardoso, Pedro, Leitao, Pedro J., Hosner, Peter A., Biedermann, Peter, Keil, Petr, Petrik, Petr, Martin, Philip, Bocquillon, Pierre, Renaud, Pierre-Cyril, Addison, Prue, Antwis, Rachael, Carmenta, Rachel, Barrientos, Rafael, Smith, Rebecca, Rocha, Ricardo, Fuchs, Richard, Felix, Rob, Kanka, Robert, Aguilee, Robin, Padro Caminal, Roc, Libbrecht, Romain, Lorrilliere, Romain, van der Ent, Ruud J., Henders, Sabine, Pueyo, Salvador, Roturier, Samuel, Jacobs, Sander, Lavorel, Sandra, Leonhardt, Sara Diana, Fraixedas, Sara, Villen-Perez, Sara, Cornell, Sarah, Redlich, Sarah, De Smedt, Sebastian, van der Linden, Sebastian, Perez-Ortega, Sergio, Petrovan, Silviu, Cesarz, Simone, Sjoberg, Sissel, Caillon, Sophie, Schindler, Stefan, Trogisch, Stefan, Taiti, Stefano, Oppel, Steffen, Lutter, Stephan, Garnett, Tara, Guedes, Thais, Wanger, Thomas Cherico, Kastner, Thomas, Worthington, Thomas, Daw, Tim, Schmoll, Tim, McPhearson, Timon, Engl, Tobias, Rutting, Tobias, Vaclavik, Tomas, Jucker, Tommaso, Robillard, Tony, Krause, Torsten, Ljubomirov, Toshko, Aavik, Tsipe, Richardson, Vanessa A., Masterson, Vanessa Anne, Seufert, Verena, Cathy, Vet Gibault, Colino Rabanal, Victor, Montade, Vincent, Thieu, Vincent, Sober, Virve, Morin, Xavier, Mehrabi, Zia, Gonzalez, Adriana Trompetero, Sanz-Cobena, Alberto, Christie, Alec Philip, Romero-Munoz, Alfredo, Dauriach, Alice, Queiroz, Allan Souza, Golland, Ami, Evans, Amy Louise, Cordero, Ana Maria Araujo, Dara, Andrey, Rilovic, Andro, Pedersen, Anna Frohn, Csergo, Anna Maria, Lewerentz, Anne, Monserand, Antoine, Valdecasas, Antonio G., Doherty, Anya, Semper-Pascual, Asuncion, Bleyhl, Benjamin, Rutschmann, Benjamin, Bongalov, Boris, Hankerson, Brett, Heylen, Brigitte, Alonso-Alvarez, Carlos, Comandulli, Carolina, Frossard, Carolina M., Mckeon, Caroline, Godde, Cecile, Palm, Celinda, Singh, Chandrakant, Sieger, Charlotte Sophie, Ohrling, Christian, Paitan, Claudia Parra, Cooper, Conor, Edler, Daniel, Roessler, Daniela C., Kessner-Beierlein, Daniela, Garcia del Amo, David, Lopez Bosch, David, Gueldner, Dino, Noll, Domink, Motivans, Elena, Canteri, Elisabetta, Garnett, Emma, Malecore, Eva, Brambach, Fabian, Ruedenauer, Fabian, Yin, Fang, Hurtado, Fernando, Mempel, Finn, de Freitas, Flavio Luiz Mazzaro, Pendrill, Florence, Leijten, Floris, Somma, Francesca, Schug, Franz, De Knijf, Geert, Peterson, Gustaf, Pe'er, Guy, Booth, Hollie, Rhee, Howon, Staude, Ingmar, Gherghel, Iulian, Vila Traver, Jaime, Kerner, Janika, Hinton, Jennifer, Hortal, Joaquin, Persson, Joel, Uddling, Johan, Coenen, Johanna, Geldmann, Jonas, Geschke, Jonas, Juergensen, Jonathan, Lobo, Jorge M., Skejo, Josip, Heinen, Julia Helena, Schuenzel, Julia, Daniel-Ferreira, Juliana, Christophe Piquet, Julien, Murtough, Katie L., Prevel, Leonie, Hissa, Leticia B. V., af Segerstad, Louise Hard, Willemse, Luc, Benavides, Lucia, Sovova, Lucie, Figueiredo, Ludmilla, Leidinger, Ludwig, Piemontese, Luigi, da Fonte, Luis Fernando Marin, Moreta, Lys Sanz, Bhan, Manan, Toledo-Hernandez, Manuel, Engert, Manuela, Davoli, Marco, Mas Navarro, Maria, Voigt, Maria, Zirion, Maria, Wandl, Marie-Theres, Kipson, Marina, Johnson, Mark D., Lukic, Marko, Goula, Marta, Jung, Martin, Nunes, Matheus Henrique, Alvarez, Matheus Rodriguez, van den Burg, Matthijs P., Guerrero, Mayra Daniela Pena, Greenfield, Michael, Lobmann, Michael, Nygren, Michelle, Guth, Miriam Karen, Koh, Niak, Stanek, Nicola, Roux, Nicolas, Karagouni, Niki, Tiralla, Nina, Mairota, Paola, Savaget, Paulo, von Doehren, Peer, Benyei, Petra, Lena, Philippe, Rufin, Philippe, Janke, Rebekka, Santagata, Remo, Motta, Renzo, Battiston, Roberto, Oyanedel, Rodrigo, Bernardo-Madrid, Ruben, Vasconcelos, Sasha, Henriques, Sergio, Bager, Simon L., Qin, Siyu, Ivkovic, Slobodan, Cooke, Sophia, Ernst, Stefan, Schmelzer, Stefan, da Silva, Sven, Faberova, Tamara, Enseroth, Tanja, De Marzo, Teresa, Pienkowski, Thomas, Engel, Thore, Boehnert, Tim, Swinfield, Tom, Kurdikova, Vendula, Chvatalova, Veronika, Lopez-Marquez, Violeta, Arlidge, William, Zhang, Zhijie, Kehoe, Laura, Reis, Tiago, Virah-Sawmy, Malika, Balmford, Andrew, Kuemmerle, Tobias, Knohl, Alexander, Antonelli, Alexandre, Hochkirch, Axel, Vira, Bhaskar, Massa, Bruno, Peres, Carlos A., Ammer, Christian, Goerg, Christoph, Schneider, Christoph, Curtis, David, de la Pena, Eduardo, Tello, Enric, Sperfeld, Erik, Corbera, Esteve, Morelli, Federico, Valladares, Fernando, Peterson, Garry, Hide, Geoff, Mace, Georgina, Kallis, Giorgos, Olsson, Gunilla Almered, Brumelis, Guntis, Alexanderson, Helena, Haberl, Helmut, Nuissl, Henning, Kreft, Holger, Ghazoul, Jaboury, Piotrowski, Jan A., Macdiarmid, Jennie, Newig, Jens, Fischer, Joern, Altringham, John, Gledhill, John, Nielsen, Jonas O., Mueller, Joerg, Palmeirim, Jorge, Barlow, Jos, Alonso, Juan C., Presa Asencio, Juan Jose, Steinberger, Julia K., Jones, Julia Patricia Gordon, Cabral, Juliano Sarmento, Dengler, Juergen, Stibral, Karel, Erb, Karlheinz, Rothhaupt, Karl-Otto, Wiegand, Kerstin, Cassar, Louis F., Lens, Luc, Rosalino, Luis Miguel, Wassen, M. J., Stenseke, Marie, Fischer-Kowalski, Marina, Diaz, Mario, Rounsevell, Mark, van Kleunen, Mark, Junginger, Martin, Kaltenpoth, Martin, Zobel, Martin, Weigend, Maximilian, Partel, Meelis, Schilthuizen, Menno, Bastos Araujo, Miguel, Haklay, Muki, Eisenhauer, Nico, Selva, Nuria, Mertz, Ole, Meyfroidt, Patrick, Borges, Paulo A. V., Kovar, Pavel, Smith, Pete, Verburg, Peter, Pysek, Petr, Seppelt, Ralf, Valentini, Riccardo, Whittaker, Robert J., Henrique Faria, Sergio, Ulgiati, Sergio, Loetters, Stefan, Bjorck, Svante, Larson, Sven Ake, Tscharntke, Teja, Domingos, Tiago, Krueger, Tobias, Pascual, Unai, Olsson, Urban, Kati, Vassiliki, Winiwarter, Verena, Reyes-Garcia, Victoria, Vajda, Vivi, Sutherland, William J., de Waroux, Yann le Polain, Buckley, Yvonne, Rammig, Anja, Kasimir, Asa, Crona, Beatrice, Sindicic, Magda, Persson, Martin, Lapka, Miloslav, Di Gregorio, Monica, Hahn, Thomas, Boonstra, Wiebren, Lipsky, Zdenek, Zucaro, A., Roeder, Achim, Lopez Baucells, Adria, Danet, Alain, Franco, Aldina, Nieto Roman, Alejandra, Lehikoinen, Aleksi, Collalti, Alessio, Keller, Alexander, Strugariu, Alexandru, Perrigo, Allison, Fernandez-Llamazares, Alvaro, Salaseviciene, Alvija, Hinsley, Amy, Santos, Ana M. C., Novoa, Ana, Rodrigues, Ana, Mascarenhas, Andre, Martins, Andrea Damacena, Holzschuh, Andrea, Meseguer, Andrea S., Hadjichambis, Andreas, Mayer, Andreas, Hacket-Pain, Andrew, Ringsmuth, Andrew, de Frutos, Angel, Stein, Anke, Heikkinen, Anna, Smith, Annabel, Bjoersne, Anna-Karin, Bagneres, Anne-Genevieve, Machordom, Annie, Kristin, Anton, Ghoddousi, Arash, Staal, Arie, Martin, Arnaud, Taylor, Astrid, Borrell, Asuncion, Marescaux, Audrey, Torres, Aurora, Helm, Aveliina, Bauer, Barbara, Smetschka, Barbara, Rodriguez-Labajos, Beatriz, Peco, Begona, Gambin, Belinda, Celine, Bellard, Phalan, Ben, Cotta, Benedetta, Rugani, Benedetto, Jarcuska, Benjamin, Leroy, Boris, Nikolov, Boris Petrov, Milchev, Boyan Petrov, Brown, Calum, Ritter, Camila Duarte, Gomes, Carmen Bessa, Meyer, Carsten, Munteanu, Catalina, Penone, Caterina, Friis, Cecilie, Teplitsky, Celine, Roemer, Charlotte, Orland, Chloe, Voigt, Christian C., Levers, Christian, Zang, Christian, Bacon, Christine D., Meyer, Christoph, Wordley, Claire, Grilo, Clara, Cattaneo, Claudio, Battisti, Corrado, Banks-Leite, Cristina, Zurell, Damaris, Challender, Dan, Mueller, Daniel, Matenaar, Daniela, Silvestro, Daniele, McKay, David Armstrong, Buckley, David, Frantz, David, Gremillet, David, Mateos, David Moreno, Sanchez-Fernandez, David, Vieites, David, Ascoli, Davide, Arlt, Debora, Louis, Deharveng, Zemp, Delphine Clara, Strubbe, Diederik, Gil, Diego, Llusia, Diego, Bennett, Dominic J., Chobanov, Dragan Petrov, Aguilera, Eduardo, Oliveira, Eduardo, Pynegar, Edwin L., Granda, Elena, Grieco, Elisa, Conrad, Elisabeth, Revilla, Eloy, Lindkvist, Emilie, Caprio, Enrico, zu Ermgassen, Erasmus, Berenguer, Erika, Ochu, Erinma, Polaina, Ester, Nuernberger, Fabian, Esculier, Fabien, de Castro, Fabio, Albanito, Fabrizio, Langerwisch, Fanny, Batsleer, Femke, Ascensao, Fernando, Moyano, Fernando Esteban, Sayol, Ferran, Buzzetti, Filippo Maria, Eiro, Flavio, Volaire, Florence, Gollnow, Florian, Menzel, Florian, Pilo, Francesca, Moreira, Francisco, Briens, Francois, Essl, Franz, Vlahos, George, Billen, Gilles, Vacchiano, Giorgio, Wong, Grace, Gruychev, Gradimir Valentinov, Fandos, Guillermo, Petter, Gunnar, Sinare, Hanna, Mumby, Hannah S., Cottyn, Hanne, Seebens, Hanno, Bjorklund, Heidi, Schroeder, Heike, Lopez Hernandez, Heriberto D., Rebelo, Hugo, Chenet, Hugues, De la Riva, Ignacio, Torre, Ignasi, Aalders, Inge, Grass, Ingo, Chuine, Isabelle, Goepel, Jan, Wieringa, Jan J., Engler, Jan O., Pergl, Jan, Schnitzler, Jan, Vavra, Jan, Medvedovic, Jasna, Cabello, Javier, Martin, Jean-Louis, Mutke, Jens, Lewis, Jerome, da Silva, Jessica Fonseca, Marull, Joan, Carvalho, Joana, Carnicer, Jofre, Enqvist, Johan, Simaika, John P., Noguera, Jose C., Blanco Moreno, Jose M., Bruna, Josef, Garnier, Josette, Fargallo, Juan A., Rocha, Juan Carlos, Carrillo, Juan D., Infante-Amate, Juan, Traba Diaz, Juan, Schleicher, Judith, Simon, Judy, Noe, Julia Le, Gerlach, Justin, Eriksson, K. Martin, Prince, Karine, Ostapowicz, Katarzyna, Stajerova, Katerina, Farrell, Katharine N., Snell, Katherine, Yates, Katherine, Fleischer, Katrin, Darras, Kevin, Schumacher, Kim, Orach, Kirill, Thonicke, Kirsten, Riede, Klaus, Heller, Klaus-Gerhard, Wang-Erlandsson, Lan, Pereira, Laura, Riggi, Laura, Florez, Laura V., Emperaire, Laure, Durieux, Laurent, Tatin, Laurent, Rozylowicz, Laurentiu, Latella, Leonardo, Andresen, Louise C., Cahen-Fourot, Louison, de Agua, Luis Borda, Boto, Luis, Lassaletta, Luis, Amo, Luisa, Sekerka, Lukas, Morales, Manuel B., Macia, Manuel J., Suarez, Manuela Gonzalez, Cabeza, Mar, Londo, Marc, Pollet, Marc, Schwieder, Marcel, Peters, Marcell K., D'Amico, Marcello, Casazza, Marco, Florencio, Margarita, Felipe-Lucia, Maria, Gebara, Maria Fernanda, Johansson, Maria, Garcia, Maria Mancilla, Piquer-Rodriguez, Maria, Tengo, Maria, Elias, Marianne, Leve, Marine, Conde, Marta, Winter, Marten, Koster, Martijn, Mayer, Martin, Salek, Martin, Schlerf, Martin, Sullivan, Martin, Baumann, Matthias, Pichler, Melanie, Marselle, Melissa, Oddie, Melissa, Razanajatovo, Mialy, Borregaard, Michael Krabbe, Theurl, Michaela C., Hernandez, Miguel, Krofel, Miha, Kechev, Mihail Ognianov, Clark, Mike, Rands, Mike, Antal, Miklos, Pucetaite, Milda, Islar, Mine, Truong, Minh-Xuan A., Vighi, Morgana, Johanisova, Nadia, Prat, Narcis, Escobar, Neus, Deguines, Nicolas, Rust, Niki, Zafra-Calvo, Noelia, Maurel, Noelie, Wagner, Norman, Fitton, Nuala, Ostermann, Ole, Panferov, Oleg, Ange, Olivia, Canals, Oriol, Englund, Oskar, De Smedt, Pallieter, Petridis, Panos, Heikkurinen, Pasi, Weigelt, Patrick, Henriksson, Patrik J. G., de Castro, Paula Drummond, Matos-Maravi, Pavel, Duran, Paz, Aragon, Pedro, Cardoso, Pedro, Leitao, Pedro J., Hosner, Peter A., Biedermann, Peter, Keil, Petr, Petrik, Petr, Martin, Philip, Bocquillon, Pierre, Renaud, Pierre-Cyril, Addison, Prue, Antwis, Rachael, Carmenta, Rachel, Barrientos, Rafael, Smith, Rebecca, Rocha, Ricardo, Fuchs, Richard, Felix, Rob, Kanka, Robert, Aguilee, Robin, Padro Caminal, Roc, Libbrecht, Romain, Lorrilliere, Romain, van der Ent, Ruud J., Henders, Sabine, Pueyo, Salvador, Roturier, Samuel, Jacobs, Sander, Lavorel, Sandra, Leonhardt, Sara Diana, Fraixedas, Sara, Villen-Perez, Sara, Cornell, Sarah, Redlich, Sarah, De Smedt, Sebastian, van der Linden, Sebastian, Perez-Ortega, Sergio, Petrovan, Silviu, Cesarz, Simone, Sjoberg, Sissel, Caillon, Sophie, Schindler, Stefan, Trogisch, Stefan, Taiti, Stefano, Oppel, Steffen, Lutter, Stephan, Garnett, Tara, Guedes, Thais, Wanger, Thomas Cherico, Kastner, Thomas, Worthington, Thomas, Daw, Tim, Schmoll, Tim, McPhearson, Timon, Engl, Tobias, Rutting, Tobias, Vaclavik, Tomas, Jucker, Tommaso, Robillard, Tony, Krause, Torsten, Ljubomirov, Toshko, Aavik, Tsipe, Richardson, Vanessa A., Masterson, Vanessa Anne, Seufert, Verena, Cathy, Vet Gibault, Colino Rabanal, Victor, Montade, Vincent, Thieu, Vincent, Sober, Virve, Morin, Xavier, Mehrabi, Zia, Gonzalez, Adriana Trompetero, Sanz-Cobena, Alberto, Christie, Alec Philip, Romero-Munoz, Alfredo, Dauriach, Alice, Queiroz, Allan Souza, Golland, Ami, Evans, Amy Louise, Cordero, Ana Maria Araujo, Dara, Andrey, Rilovic, Andro, Pedersen, Anna Frohn, Csergo, Anna Maria, Lewerentz, Anne, Monserand, Antoine, Valdecasas, Antonio G., Doherty, Anya, Semper-Pascual, Asuncion, Bleyhl, Benjamin, Rutschmann, Benjamin, Bongalov, Boris, Hankerson, Brett, Heylen, Brigitte, Alonso-Alvarez, Carlos, Comandulli, Carolina, Frossard, Carolina M., Mckeon, Caroline, Godde, Cecile, Palm, Celinda, Singh, Chandrakant, Sieger, Charlotte Sophie, Ohrling, Christian, Paitan, Claudia Parra, Cooper, Conor, Edler, Daniel, Roessler, Daniela C., Kessner-Beierlein, Daniela, Garcia del Amo, David, Lopez Bosch, David, Gueldner, Dino, Noll, Domink, Motivans, Elena, Canteri, Elisabetta, Garnett, Emma, Malecore, Eva, Brambach, Fabian, Ruedenauer, Fabian, Yin, Fang, Hurtado, Fernando, Mempel, Finn, de Freitas, Flavio Luiz Mazzaro, Pendrill, Florence, Leijten, Floris, Somma, Francesca, Schug, Franz, De Knijf, Geert, Peterson, Gustaf, Pe'er, Guy, Booth, Hollie, Rhee, Howon, Staude, Ingmar, Gherghel, Iulian, Vila Traver, Jaime, Kerner, Janika, Hinton, Jennifer, Hortal, Joaquin, Persson, Joel, Uddling, Johan, Coenen, Johanna, Geldmann, Jonas, Geschke, Jonas, Juergensen, Jonathan, Lobo, Jorge M., Skejo, Josip, Heinen, Julia Helena, Schuenzel, Julia, Daniel-Ferreira, Juliana, Christophe Piquet, Julien, Murtough, Katie L., Prevel, Leonie, Hissa, Leticia B. V., af Segerstad, Louise Hard, Willemse, Luc, Benavides, Lucia, Sovova, Lucie, Figueiredo, Ludmilla, Leidinger, Ludwig, Piemontese, Luigi, da Fonte, Luis Fernando Marin, Moreta, Lys Sanz, Bhan, Manan, Toledo-Hernandez, Manuel, Engert, Manuela, Davoli, Marco, Mas Navarro, Maria, Voigt, Maria, Zirion, Maria, Wandl, Marie-Theres, Kipson, Marina, Johnson, Mark D., Lukic, Marko, Goula, Marta, Jung, Martin, Nunes, Matheus Henrique, Alvarez, Matheus Rodriguez, van den Burg, Matthijs P., Guerrero, Mayra Daniela Pena, Greenfield, Michael, Lobmann, Michael, Nygren, Michelle, Guth, Miriam Karen, Koh, Niak, Stanek, Nicola, Roux, Nicolas, Karagouni, Niki, Tiralla, Nina, Mairota, Paola, Savaget, Paulo, von Doehren, Peer, Benyei, Petra, Lena, Philippe, Rufin, Philippe, Janke, Rebekka, Santagata, Remo, Motta, Renzo, Battiston, Roberto, Oyanedel, Rodrigo, Bernardo-Madrid, Ruben, Vasconcelos, Sasha, Henriques, Sergio, Bager, Simon L., Qin, Siyu, Ivkovic, Slobodan, Cooke, Sophia, Ernst, Stefan, Schmelzer, Stefan, da Silva, Sven, Faberova, Tamara, Enseroth, Tanja, De Marzo, Teresa, Pienkowski, Thomas, Engel, Thore, Boehnert, Tim, Swinfield, Tom, Kurdikova, Vendula, Chvatalova, Veronika, Lopez-Marquez, Violeta, Arlidge, William, and Zhang, Zhijie

Published
2019
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45. Monitoring ash dieback (Hymenoscyphus fraxineus) in British forests using hyperspectral remote sensing.

Author

Chan, Aland H. Y., Barnes, Chloe, Swinfield, Tom, Coomes, David A., He, Kate, and Zlinszky, András

Subjects
DIEBACK, REMOTE sensing, MULTISPECTRAL imaging, FISHER discriminant analysis, TEMPERATE forests, ASH (Tree)
Abstract

Large‐scale dieback of ash trees (Fraxinus spp.) caused by the fungus Hymenoscyphus fraxineus is posing an immense threat to forest health in Europe, requiring effective monitoring at large scales. In this study, a pipeline was created to find ash trees and classify dieback severity using high‐resolution hyperspectral imagery of individual tree crowns (ITCs). Hyperspectral data were collected in four forest sites near Cambridge, UK, where 422 ITCs were manually delineated and labelled using field‐measurements of species and dieback severity (for ash trees). Four algorithms, namely linear discriminant analysis (LDA), principal components analysis coupled with LDA (PCA‐LDA), partial least squares discriminant analysis (PLS‐DA) and random forest (RF), were used to build classification models for species and dieback severity classification. The effect of dark‐pixel filtering on classification accuracy was evaluated. The best performing models were then coupled with automatic ITC segmentation to map species and ash dieback distribution over 16.8 hectares of woodland. We calculated and partitioned the coefficient of variation (CV) of the reflected ash spectra to find variable wavebands associated with dieback. PLS‐DA and LDA were most accurate for classifying ITC species identifies (overall accuracy >90%), whereas RF was most accurate for classifying ash dieback severity (overall accuracy 77%). Dark pixel filtering further increased the accuracy of species classification (+6%), but not disease classification. The reflectances of narrow blue (415 nm), red‐edge (680 nm) and NIR (760 nm) bands had high CV across disease classes and should be included if multispectral imagery were to be used to monitor ash dieback. The study demonstrates the possibility of using remote sensing to forward epidemiological research by monitoring forest pathogens in landscape scales, which would allow temperate forest managers to control pathogen outbreaks, assess associated impacts and restore affected forests much more effectively. [ABSTRACT FROM AUTHOR]

Published
2021
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47. Reconciling the contribution of environmental and stochastic structuring of tropical forest diversity through the lens of imaging spectroscopy

Author

Bongalov, Boris, primary, Burslem, David F. R. P., additional, Jucker, Tommaso, additional, Thompson, Samuel E. D., additional, Rosindell, James, additional, Swinfield, Tom, additional, Nilus, Reuben, additional, Clewley, Daniel, additional, Phillips, Oliver L., additional, and Coomes, David A., additional

Published
2019
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49. Canopy structure and topography jointly constrain the microclimate of human-modified tropical landscapes

Author

Jucker, Tommaso, Hardwick, Stephen R., Both, Sabine, Elias, Dafydd M.O., Ewers, Robert M., Milodowski, David T., Swinfield, Tom, Coomes, David A., Jucker, Tommaso, Hardwick, Stephen R., Both, Sabine, Elias, Dafydd M.O., Ewers, Robert M., Milodowski, David T., Swinfield, Tom, and Coomes, David A.

Abstract

Local‐scale microclimatic conditions in forest understoreys play a key role in shaping the composition, diversity and function of these ecosystems. Consequently, understanding what drives variation in forest microclimate is critical to forecasting ecosystem responses to global change, particularly in the tropics where many species already operate close to their thermal limits and rapid land‐use transformation is profoundly altering local environments. Yet our ability to characterize forest microclimate at ecologically meaningful scales remains limited, as understorey conditions cannot be directly measured from outside the canopy. To address this challenge, we established a network of microclimate sensors across a land‐use intensity gradient spanning from old‐growth forests to oil‐palm plantations in Borneo. We then combined these observations with high‐resolution airborne laser scanning data to characterize how topography and canopy structure shape variation in microclimate both locally and across the landscape. In the processes, we generated high‐resolution microclimate surfaces spanning over 350 km2, which we used to explore the potential impacts of habitat degradation on forest regeneration under both current and future climate scenarios. We found that topography and vegetation structure were strong predictors of local microclimate, with elevation and terrain curvature primarily constraining daily mean temperatures and vapour pressure deficit (VPD), whereas canopy height had a clear dampening effect on microclimate extremes. This buffering effect was particularly pronounced on wind‐exposed slopes but tended to saturate once canopy height exceeded 20 m—suggesting that despite intensive logging, secondary forests remain largely thermally buffered. Nonetheless, at a landscape‐scale microclimate was highly heterogeneous, with maximum daily temperatures ranging between 24.2 and 37.2°C and VPD spanning two orders of magnitude. Based on this, we estimate that by the end

Published
2018

50. Occurrence of blood‐feeding terrestrial leeches (Haemadipsidae) in a degraded forest ecosystem and their potential as ecological indicators.

Author

Drinkwater, Rosie, Williamson, Joseph, Swinfield, Tom, Deere, Nicolas J., Struebig, Matthew J., Clare, Elizabeth L., Coomes, David, and Rossiter, Stephen J.

Subjects
BIOINDICATORS, FOREST degradation, LEECHES, TROPICAL forests, DNA fingerprinting
Abstract

Copyright of Biotropica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2020
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