Phil Wilkes
RMIT University
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Publication
Featured researches published by Phil Wilkes.
Ecology Letters | 2013
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
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
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
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
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
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
William Woodgate; John Armston; Mathias Disney; Simon D. Jones; Lola Suárez; Michael J. Hill; Phil Wilkes; Mariela Soto-Berelov
Forest Ecology and Management | 2015
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
William Woodgate; John Armston; Mathias Disney; Lola Suárez; Simon D. Jones; Michael J. Hill; Phil Wilkes; Mariela Soto-Berelov
Carbon Balance and Management | 2018
Phil Wilkes; Mathias Disney; Matheus Boni Vicari; Kim Calders; Andrew Burt