Brett Murphy

Dr. Brett Murphy

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 June 2016 in Philosophical Transactions of the Royal Society B: Biological Sciences
Verified
Journal Article
Open access
DBDavid M.J.S. Bowman
David M.J.S. Bowman
GPGeorge Perry
George Perry
SHSteve I. Higgins
Steve I. Higgins
CJChris Johnson
Chris Johnson
SFSamuel D. Fuhlendorf
Samuel D. Fuhlendorf
BMBrett Murphy
Brett Murphy
Fire positively and negatively affects food webs across all trophic levels and guilds and influences a range of ecological processes that reinforce fire regimes, such as nutrient cycling and soil development, plant regeneration and growth, plant community assembly and dynamics, herbivory and predation. Thus we argue that rather than merely describing spatio-temporal patterns of fire regimes, pyrodiversity must be understood in terms of feedbacks between fire regimes, biodiversity and ecological processes. Humans shape pyrodiversity both directly, by manipulating the intensity, severity, frequency and extent of fires, and indirectly, by influencing the abundance and distribution of various trophic guilds through hunting and husbandry of animals, and introduction and cultivation of plant species. Conceptualizing landscape fire as deeply embedded in food webs suggests that the restoration of degraded ecosystems requires the simultaneous careful management of fire regimes and native and invasive plants and animals, and may include introducing new vertebrates to compensate for extinctions that occurred in the recent and more distant past. This article is part of the themed issue ‘The interaction of fire and mankind’.

19 September 2016 in Philosophical Transactions of the Royal Society B: Biological Sciences
Verified
Journal Article
Open access
BMBrett Murphy
Brett Murphy
AAAlan Andersen
Alan Andersen
CPCatherine L. Parr
Catherine L. Parr
For decades, there has been enormous scientific interest in tropical savannahs and grasslands, fuelled by the recognition that they are a dynamic and potentially unstable biome, requiring periodic disturbance for their maintenance. However, that scientific interest has not translated into widespread appreciation of, and concern about threats to, their biodiversity. In terms of biodiversity, grassy biomes are considered poor cousins of the other dominant biome of the tropics—forests. Simple notions of grassy biomes being species-poor cannot be supported; for some key taxa, such as vascular plants, this may be valid, but for others it is not. Here, we use an analysis of existing data to demonstrate that high-rainfall tropical grassy biomes (TGBs) have vertebrate species richness comparable with that of forests, despite having lower plant diversity. The Neotropics stand out in terms of both overall vertebrate species richness and number of range-restricted vertebrate species in TGBs. Given high rates of land-cover conversion in Neotropical grassy biomes, they should be a high priority for conservation and greater inclusion in protected areas. Fire needs to be actively maintained in these systems, and in many cases re-introduced after decades of inappropriate fire exclusion. The relative intactness of TGBs in Africa and Australia make them the least vulnerable to biodiversity loss in the immediate future. We argue that, like forests, TGBs should be recognized as a critical—but increasingly threatened—store of global biodiversity. This article is part of the themed issue ‘Tropical grassy biomes: linking ecology, human use and conservation’.

19 August 2019 in Mammal Review
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Journal Article
Closed access
PDF file
LWLeigh‐Ann Woolley
Leigh‐Ann Woolley
HGHayley M. Geyle
Hayley M. Geyle
BMBrett Murphy
Brett Murphy
SLSarah M. Legge
Sarah M. Legge
RPRussell Palmer
Russell Palmer
JWJohn Woinarski
John Woinarski

1 June 2016 in Environmental Research Letters
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Journal Article
Open access
PDF file
MBMatthias Boer
Matthias Boer
DBDavid M.J.S. Bowman
David M.J.S. Bowman
BMBrett Murphy
Brett Murphy
GCGeoffrey J Cary
Geoffrey J Cary
MCMark A Cochrane
Mark A Cochrane
RBRoss A Bradstock
Ross A Bradstock

1 October 2018 in Global Change Biology
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Journal Article
Closed access
PDF file
BMBrett Murphy
Brett Murphy
LPLynda Prior
Lynda Prior
MCMark A. Cochrane
Mark A. Cochrane
Grant WilliamsonGrant Williamson
Grant Williamson
DBDavid M.J.S. Bowman
David M.J.S. Bowman

17 January 2025 in Biological Reviews
Verified
Journal Article
Open access
TBTom Bruce
Tom Bruce
ZAZachary Amir
Zachary Amir
BABenjamin Allen
Benjamin Allen
BABrendan F. Alting
Brendan F. Alting
MAMatt Amos
Matt Amos
MLMatthew S. Luskin
Matthew S. Luskin
Camera traps are widely used in wildlife research and monitoring, so it is imperative to understand their strengths, limitations, and potential for increasing impact. We investigated a decade of use of wildlife cameras (2012–2022) with a case study on Australian terrestrial vertebrates using a multifaceted approach. We (i) synthesised information from a literature review; (ii) conducted an online questionnaire of 132 professionals; (iii) hosted an in‐person workshop of 28 leading experts representing academia, non‐governmental organisations (NGOs), and government; and (iv) mapped camera trap usage based on all sources. We predicted that the last decade would have shown: (i) exponentially increasing sampling effort, a continuation of camera usage trends up to 2012; (ii) analytics to have shifted from naive presence/absence and capture rates towards hierarchical modelling that accounts for imperfect detection, thereby improving the quality of outputs and inferences on occupancy, abundance, and density; and (iii) broader research scales in terms of multi‐species, multi‐site and multi‐year studies. However, the results showed that the sampling effort has reached a plateau, with publication rates increasing only modestly. Users reported reaching a saturation point in terms of images that could be processed by humans and time for complex analyses and academic writing. There were strong taxonomic and geographic biases towards medium–large mammals (>500 g) in forests along Australia's southeastern coastlines, reflecting proximity to major cities. Regarding analytical choices, bias‐prone indices still accounted for ~50% of outputs and this was consistent across user groups. Multi‐species, multi‐site and multiple‐year studies were rare, largely driven by hesitancy around collaboration and data sharing. There is no widely used repository for wildlife camera images and the Atlas of Living Australia (ALA) is the dominant repository for sharing tabular occurrence records. However, the ALA is presence‐only and thus is unsuitable for creating detection histories with absences, inhibiting hierarchical modelling. Workshop discussions identified a pressing need for collaboration to enhance the efficiency, quality and scale of research and management outcomes, leading to the proposal of a Wildlife Observatory of Australia (WildObs). To encourage data standards and sharing, WildObs should (i) promote a metadata collection app; (ii) create a tagged image repository to facilitate artificial intelligence/machine learning (AI/ML) computer vision research in this space; (iii) address the image identification bottleneck via the use of AI/ML‐powered image‐processing platforms; (iv) create data commons for detection histories that are suitable for hierarchical modelling; and (v) provide capacity building and tools for hierarchical modelling. Our review highlights that while Australia's investments in monitoring biodiversity with cameras position it to be a global leader in this context, realising that potential requires a paradigm shift towards best practices for collecting, curating, sharing and analysing ‘Big Data’. Our findings and framework have broad applicability outside Australia to enhance camera usage to meet conservation and management objectives ranging from local to global scales. This review articulates a country/continental observatory approach that is also suitable for international collaborative wildlife research networks.