Infrastructure projects are expanding rapidly in tropical countries rich in biodiversity and humid rainforests. Investing in a well-developed, modern infrastructure network that can enhance logistic efficiency supporting trade and economic growth is essential to achievE development goals linked to poverty reduction, promotion of well-being and equal access to economic growth opportunities.
However, roads can cause substantial harm to natural ecosystems1. When cutting through previously intact rainforests, they accelerate habitat loss and fragmentation, potential for wildfires, hunting and environmental degradation, largely because they able rapid access to areas previously considered too remote2. Infrastructure expansion can thus prevent countries from addressing development goals linked to biodiversity and life on land as well as to clean air and climate action, the latter two because of intricate relationships between forest structure, climate and atmosphere.
In this PhD, the student will explore the benefits and ecological costs of current infrastructure expansion projects in Brunei Darussalam. Brunei Darussalam is a small country on the island of Borneo, famous for its conservation flagship species that include the Bornean orangutan (Pongo pygmaeus) and the clouded leopard (Neofelis nebulosa), the Malayan sun bear (Helarctos malayanus) and the Sunda Pangolin (Manis javanica).Brunei has largely held on to its forests – unlike neighbouring countries in Borneo- and features a comparatively low-density road network. Brunei supports huge tracts of intact humid rainforests, protected through the Heart of Borneo programme, initiated by the governments of Indonesia, Brunei and Malaysia in 2007. Yet, despite its unique status, Brunei’s mammals remain understudied and camera trapping studies have so far been absent from the country. A recent PhD in our group, implemented by Laura Braunholtz, has started to compare mammal diversity response to paved and unpaved roads in Brunei. In the PhD research proposed here, the student will focus on measuring potential benefits and ecological costs of Temburong Bridge linking the densely populated coastal north of Brunei Bandar Seri Begawan to remote, densely forested Bangar.
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Fig. 1 Map showing the boundaries of Brunei Darussalam and the location of Temburong Bridge
The student will implement the research collaborating with in country partner Dr Ferry Slik (Universiti Brunei Darussalam). The student will focus on mammals to quantify biodiversity responses to infrastructure expansion using a set of techniques and tool to sample mammal diversity.
The PhD will address four key goals:
1. Assess mammal diversity and abundance on Bangar under ‘no impact’ conditions.
2. Assess mammal diversity and abundance on Bangar along gradients of pressures arising from the construction of Temburong Bridge and supporting infrastructure expansion.
3. Develop maps for Bangar showing baselines for current mammal diversity and abundance and showing changes in mammal diversity and abundance in response to above infrastructure developments.
4. Develop ‘least environmental costs scenarios’ based on scenario models of beneficial infrastructure expansion on Bangar.
The student will set up grids to sample mammal abundance and ecological co-variates (e.g. forest structure, signs of hunting pressure). The grids will be set up using stratified random sampling to account for ‘distance from highway’, ‘distance from populated places’, and ‘distance from ecotourism sites’ following experience from our previous work6,7. Structure attributes measured include canopy openness and leaf area, understorey structure and aboveground live tree biomass. The student will collect hunting pressure data by (i) counting signs of poaching indicated for example by the presence of traps, (ii) counting sales points for bushmeat along the road, and (iii) visiting markets to identify bushmeat sold and at what price.
The student will compare baseline estimates (Objective 1) for mammal diversity in Brunei’s undisturbed forests to disturbed forest sites elsewhere in Brunei and on Borneo using ongoing research and collaborations between the PI and the SAFE project in Malaysian Borneo as well as Dr Wearn (Zoological Society of London). The student will develop statistical models linking mammal data to infrastructure data, whilst accounting for hunting and forest structure as confounding factors (Objective 2).
The student will integrate field derived data with remotely sensed data (Satellites, UAVs) to produce maps describing natural baseline of what mammal diversity would look like in rainforests of Borneo if there was no anthropogenic impact. Using the models developed for objective 2, the student will then develop mammal diversity change maps identifying hotspots of change due to infrastructure expansion. (Objective 3). Finally, the student will develop scenarios of road expansion and combine these with the statistical models to identify infrastructure expansion with ‘least impact’ (Objective 4).
All chapters will be written as paper submissions. Spatial statistics used include standard modelling approaches, conditional autoregressive models and in-house developed approaches.
The student will implement a review of the scientific and grey literature to compile the best available information on ecological costs and socio- economic benefits arising from infrastructure expansion projects in the humid tropics (thesis chapter 1). The student will design the sampling protocols and apply for field permits through collaborations with University Brunei Darussalam.
Fieldwork involving collection of (i) mammal data using camera traps and live traps, (ii) vegetation structure and quality data using standard surveying techniques and novel sensor approaches including terrestrial LIDAR, (iii) and hunting pressure data. Data will be processed and analysed: camera trap and live trap data and forest structure data will be processed following established routines. Habitat disturbance will be scored around each trapping point based on forest quality measurements from 1 (intact) to 5 (very disturbed). Pleiades (0.5 m pixel resolution) and Sentinel-2 imagery (10 m pixel resolution) will be used to upscale forest structure metrics developing maps for the region. A species- specific hunting pressure metric will be derived from the hunting pressure data. The student will model mammal diversity and abundance as a function of infrastructure pressure and confounding variables.
The student will develop baseline maps of mammal diversity and abundance (thesis chapter 2). The student will develop maps of changes in mammal diversity and abundance following the infrastructure expansion (thesis chapter 3). The student will generate scenarios of future changes in road networks to support increased traffic flow on Bangar taking into account locations of sites of interest (economic, touristic). The student will use these maps to show impacts on mammal diversity and highlight scenarios with ‘least impacts’ (thesis chapter 4).
The student will finalise analyses and generate outputs for presenting findings to collaborators in Brunei in formats accessible to policy makers. The student will present their research at one major international and one major national ecological conference.
The student will receive training in key skills relevant for conservation and management in changing human- modified tropical landscapes: (i) camera trapping and standard mammal surveying techniques, (ii) standard habitat surveying techniques and novel sensor based approaches to assess habitat structure, (iii) remote sensing data and GIS to analyse and map ecological data in dynamic landscapes, (4) spatial modelling to predict changes in ecological functions under changes in land use and (5) scenario modelling taking into account economic and ecological considerations.
Novelty: The work is interdisciplinary allowing the student to tap into and benefit from research, practice and teaching of the relevant research groups at Newcastle University (Modelling, Evidence and Policy RG at the School of Natural and Environmental Sciences: conservation science, ecological resilience, remote sensing using satellite data; Geomatics RG in the School of Engineering: remote sensing from the ground and using UAVs), the University of Durham (biodiversity modelling), and Universiti Brunei Darussalam (tropical forest biomass and carbon measuring and mapping, secondary forest dynamics, community ecology and functional diversity). Further support will be provided through Dr Wearn (FFI, Vietnam, camera trapping of mammals).
References & further reading
1 Gaveau et al. 2014 PLoS ONE 9(7): e101654
2 Laurance et al. 2014 Nature513: 229-232
3 Sodhi et al. 2010 Biological Conservation 132: 2375-2384
4 Santika et al. 2017 Scientific Reports 7: 4839
5 Macdonald et al. 2017 Biological Conservation 227: 92-103
6 Wearn et al. 2017 Biological Conservation 212: 162-171.
7 Wearn et al. 2013 PLoS ONE 8(11): e77598.
8 Pfeifer et al. 2017 Nature 551: 187-191.
For further information, or if you are interested in applying, contact Dr Pfeifer at firstname.lastname@example.org (cc Dr Gaulton at email@example.com) In your email include: 1) a two-page covering letter detailing your reasons for applying & why you have selected this project, 2) your CV with contact information for â‰¥two references, 3) Full transcripts of previous qualifications obtained to date.