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Dive into the research topics where Phil Wilkes is active.

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Featured researches published by Phil Wilkes.


Ecology Letters | 2013

Persistent reduced ecosystem respiration after insect disturbance in high elevation forests

David J. P. Moore; Nicole A. Trahan; Phil Wilkes; Tristan Quaife; Britton B. Stephens; Kelly Elder; Ankur R. Desai; José F. Negrón; Russell K. Monson

Amid a worldwide increase in tree mortality, mountain pine beetles (Dendroctonus ponderosae Hopkins) have led to the death of billions of trees from Mexico to Alaska since 2000. This is predicted to have important carbon, water and energy balance feedbacks on the Earth system. Counter to current projections, we show that on a decadal scale, tree mortality causes no increase in ecosystem respiration from scales of several square metres up to an 84 km2 valley. Rather, we found comparable declines in both gross primary productivity and respiration suggesting little change in net flux, with a transitory recovery of respiration 6–7 years after mortality associated with increased incorporation of leaf litter C into soil organic matter, followed by further decline in years 8–10. The mechanism of the impact of tree mortality caused by these biotic disturbances is consistent with reduced input rather than increased output of carbon.


Photogrammetric Engineering and Remote Sensing | 2015

Understanding the Effects of ALS Pulse Density for Metric Retrieval across Diverse Forest Types

Phil Wilkes; Simon D. Jones; Lola Suárez; Andrew Haywood; William Woodgate; Mariela Soto-Berelov; Andrew Mellor; Andrew K. Skidmore

Pulse density, the number of laser pulses that intercept a surface per unit area, is a key consideration when acquiring an Airborne Laser Scanning (ALS) dataset. This study compares area-based vegetation structure metrics derived from multireturn ALS simulated at six pulse densities (0.05 to 4 pl m-2) across a range of forest types: from savannah woodlands to dense rainforests. Results suggest that accurate measurement of structure metrics (canopy height, canopy cover, and vertical canopy structure) can be achieved with a pulse density of 0.5 pl m-2 across all forest types when compared to a dataset of 10 pl m-2. For pulse densities <0.5 pl m-2, two main sources of error lead to inaccuracies in estimation: the poor identification of the ground surface and sparse vegetation cover leading to under sampling of the canopy profile. This analysis provides useful information for land managers determining capture specifications for large-area ALS acquisitions.


Methods in Ecology and Evolution | 2016

Using discrete-return airborne laser scanning to quantify number of canopy strata across diverse forest types

Phil Wilkes; Simon D. Jones; Lola Suárez; Andrew Haywood; Andrew Mellor; William Woodgate; Mariela Soto-Berelov; Andrew K. Skidmore

The vertical arrangement of forest canopies is a key descriptor of canopy structure, a driver of ecosystem function and indicative of forest successional stage. Yet techniques to attribute for canopy vertical structure across large and potentially heterogeneously forested areas remain elusive. This study introduces a new technique to estimate the Number of Strata (NoS) that comprise a canopy profile, using discrete-return Airborne Laser Scanning (ALS) data. Vertically resolved gap probability (P-gap) aggregated over a plot is generalized with a nonparametric cubic spline regression (P-s). Subsequently a count of the positive zero-crossings of second derivative of 1 - P-s is used to estimate NoS. Comparison with inventory derived estimates at 24 plots across three diverse study areas shows a good agreement between the two techniques (RMSE=041 strata). Furthermore, this is achieved without altering model parameters, indicating the transferability of the technique across diverse forest types. NoS values ranged from 0 to 4 at a further 239 plots, emphasizing the need for a method to quantify canopy vertical structure across forested landscapes. Comparison of NoS with other commonly derived ALS descriptors of canopy structure (canopy height, canopy cover and return height coefficient of determination) returned only a moderate correlation (r(2)<04). It is proposed the presented method provides a primary descriptor of canopy structure to complement canopy height and cover, as well as a candidate Ecological Biodiversity Variable for characterizing habitat structure.


Interface Focus | 2018

Weighing trees with lasers : advances, challenges and opportunities

Mathias Disney; M. Boni Vicari; Andrew Burt; Kim Calders; Simon L. Lewis; Pasi Raumonen; Phil Wilkes

Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods.


Agricultural and Forest Meteorology | 2015

Understanding the variability in ground-based methods for retrieving canopy openness, gap fraction, and leaf area index in diverse forest systems

William Woodgate; Simon D. Jones; Lola Suárez; Michael J. Hill; John Armston; Phil Wilkes; Mariela Soto-Berelov; Andrew Haywood; Andrew Mellor


Remote Sensing of Environment | 2017

Data acquisition considerations for Terrestrial Laser Scanning of forest plots

Phil Wilkes; Alvaro Lau; Mathias Disney; Kim Calders; Andrew Burt; Jose Gonzalez de Tanago; Harm M. Bartholomeus; Benjamin Brede; Martin Herold


Agricultural and Forest Meteorology | 2016

Quantifying the impact of woody material on leaf area index estimation from hemispherical photography using 3D canopy simulations

William Woodgate; John Armston; Mathias Disney; Simon D. Jones; Lola Suárez; Michael J. Hill; Phil Wilkes; Mariela Soto-Berelov


Forest Ecology and Management | 2015

An improved theoretical model of canopy gap probability for Leaf Area Index estimation in woody ecosystems

William Woodgate; Mathias Disney; John Armston; Simon D. Jones; Lola Suárez; Michael J. Hill; Phil Wilkes; Mariela Soto-Berelov; Andrew Haywood; Andrew Mellor


Agricultural and Forest Meteorology | 2017

Validating canopy clumping retrieval methods using hemispherical photography in a simulated Eucalypt forest

William Woodgate; John Armston; Mathias Disney; Lola Suárez; Simon D. Jones; Michael J. Hill; Phil Wilkes; Mariela Soto-Berelov


Carbon Balance and Management | 2018

Estimating urban above ground biomass with multi-scale LiDAR

Phil Wilkes; Mathias Disney; Matheus Boni Vicari; Kim Calders; Andrew Burt

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Mathias Disney

University College London

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Andrew Haywood

Cooperative Research Centre

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John Armston

University of Queensland

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Michael J. Hill

University of North Dakota

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Andrew Burt

University College London

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