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Dive into the research topics where Fiona M. Underwood is active.

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Featured researches published by Fiona M. Underwood.


PLOS ONE | 2012

Making Robust Policy Decisions Using Global Biodiversity Indicators

Emily Nicholson; Ben Collen; Alberto Barausse; Julia L. Blanchard; Brendan T. Costelloe; Kathryn M. E. Sullivan; Fiona M. Underwood; Robert W. Burn; Steffen Fritz; Julia P. G. Jones; Louise McRae; Hugh P. Possingham; E. J. Milner-Gulland

In order to influence global policy effectively, conservation scientists need to be able to provide robust predictions of the impact of alternative policies on biodiversity and measure progress towards goals using reliable indicators. We present a framework for using biodiversity indicators predictively to inform policy choices at a global level. The approach is illustrated with two case studies in which we project forwards the impacts of feasible policies on trends in biodiversity and in relevant indicators. The policies are based on targets agreed at the Convention on Biological Diversity (CBD) meeting in Nagoya in October 2010. The first case study compares protected area policies for African mammals, assessed using the Red List Index; the second example uses the Living Planet Index to assess the impact of a complete halt, versus a reduction, in bottom trawling. In the protected areas example, we find that the indicator can aid in decision-making because it is able to differentiate between the impacts of the different policies. In the bottom trawling example, the indicator exhibits some counter-intuitive behaviour, due to over-representation of some taxonomic and functional groups in the indicator, and contrasting impacts of the policies on different groups caused by trophic interactions. Our results support the need for further research on how to use predictive models and indicators to credibly track trends and inform policy. To be useful and relevant, scientists must make testable predictions about the impact of global policy on biodiversity to ensure that targets such as those set at Nagoya catalyse effective and measurable change.


PLOS ONE | 2011

Global Trends and Factors Associated with the Illegal Killing of Elephants: A Hierarchical Bayesian Analysis of Carcass Encounter Data

Robert W. Burn; Fiona M. Underwood; Julian Blanc

Elephant poaching and the ivory trade remain high on the agenda at meetings of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Well-informed debates require robust estimates of trends, the spatial distribution of poaching, and drivers of poaching. We present an analysis of trends and drivers of an indicator of elephant poaching of all elephant species. The site-based monitoring system known as Monitoring the Illegal Killing of Elephants (MIKE), set up by the 10th Conference of the Parties of CITES in 1997, produces carcass encounter data reported mainly by anti-poaching patrols. Data analyzed were site by year totals of 6,337 carcasses from 66 sites in Africa and Asia from 2002–2009. Analysis of these observational data is a serious challenge to traditional statistical methods because of the opportunistic and non-random nature of patrols, and the heterogeneity across sites. Adopting a Bayesian hierarchical modeling approach, we used the proportion of carcasses that were illegally killed (PIKE) as a poaching index, to estimate the trend and the effects of site- and country-level factors associated with poaching. Important drivers of illegal killing that emerged at country level were poor governance and low levels of human development, and at site level, forest cover and area of the site in regions where human population density is low. After a drop from 2002, PIKE remained fairly constant from 2003 until 2006, after which it increased until 2008. The results for 2009 indicate a decline. Sites with PIKE ranging from the lowest to the highest were identified. The results of the analysis provide a sound information base for scientific evidence-based decision making in the CITES process.


PLOS ONE | 2013

Dissecting the illegal ivory trade: an analysis of ivory seizures data.

Fiona M. Underwood; Robert W. Burn; Tom Milliken

Reliable evidence of trends in the illegal ivory trade is important for informing decision making for elephants but it is difficult to obtain due to the covert nature of the trade. The Elephant Trade Information System, a global database of reported seizures of illegal ivory, holds the only extensive information on illicit trade available. However inherent biases in seizure data make it difficult to infer trends; countries differ in their ability to make and report seizures and these differences cannot be directly measured. We developed a new modelling framework to provide quantitative evidence on trends in the illegal ivory trade from seizures data. The framework used Bayesian hierarchical latent variable models to reduce bias in seizures data by identifying proxy variables that describe the variability in seizure and reporting rates between countries and over time. Models produced bias-adjusted smoothed estimates of relative trends in illegal ivory activity for raw and worked ivory in three weight classes. Activity is represented by two indicators describing the number of illegal ivory transactions – Transactions Index – and the total weight of illegal ivory transactions – Weights Index – at global, regional or national levels. Globally, activity was found to be rapidly increasing and at its highest level for 16 years, more than doubling from 2007 to 2011 and tripling from 1998 to 2011. Over 70% of the Transactions Index is from shipments of worked ivory weighing less than 10 kg and the rapid increase since 2007 is mainly due to increased consumption in China. Over 70% of the Weights Index is from shipments of raw ivory weighing at least 100 kg mainly moving from Central and East Africa to Southeast and East Asia. The results tie together recent findings on trends in poaching rates, declining populations and consumption and provide detailed evidence to inform international decision making on elephants.


Oryx | 2004

Identifying important endemic areas using ecoregions: birds and mammals in the Indo-Pacific

John E. Fa; Robert W. Burn; Mark Stanley Price; Fiona M. Underwood

Concentrations of large numbers of endemic species have been singled out in prioritization exercises as significant areas for global biodiversity conservation. This paper describes bird and mammal endemicity in Indo-Pacific ecoregions. An ecoregion is a relatively large unit of land or water that contains a distinct assemblage of natural communities. We prioritize 133 ecoregions according to their levels of endemicity, and explain how variables such as biome type, whether the ecoregion is on an island or continental mass, montane or non-montane, correlate with the proportion of the total species assemblage that are endemic. Following an exploratory principal components analysis we classify all ecoregions according to the relationship between numbers of endemics and overall species richness. Endemicity is negatively correlated with species richness. We show that plotting the logit transformation of the endemicity of birds and mammals against log of species richness is a more effective and useful way of identifying important ecoregions than simply ordering ecoregions by the proportion of endemic species, or any other single measure. The plot, divided into 16 regions corresponding to the quartiles of the two variables, was used to identify ecoregions of high conservation value. These are the ecoregions with the highest endemicity and lowest species richness. Further analysis shows that island and montane ecoregions, regardless of their biome type, are by far the most important for endemic species.


Science | 2017

Breaking the deadlock on ivory

Duan Biggs; Matthew H. Holden; Alexander R. Braczkowski; Carly N. Cook; E. J. Milner-Gulland; Jacob Phelps; Robert J. Scholes; Robert J. Smith; Fiona M. Underwood; Vanessa M. Adams; James R. Allan; Henry Brink; Rosie Cooney; Yufang Gao; Jon Hutton; Eve Macdonald-Madden; Martine Maron; Kent H. Redford; William J. Sutherland; Hugh P. Possingham

An iterative process that recognizes different value systems may help to protect elephants Poaching for ivory has caused a steep decline in African elephant (Loxodonta africana, see the photo) populations over the past decade (1). This crisis has fueled a contentious global debate over which ivory policy would best protect elephants: banning all ivory trade or enabling regulated trade to incentivize and fund elephant conservation (2). The deep-seated deadlock on ivory policy consumes valuable resources and creates an antagonistic environment among elephant conservationists. Successful solutions must begin by recognizing the different values that influence stakeholder cognitive frameworks of how actions lead to outcomes (“mental models”) (3), and therefore their diverging positions on ivory trade (4). Based on successful conflict resolution in other areas, we propose an iterative process through which countries with wild elephant populations may be able to understand their differences and develop workable solutions in a less confrontational manner.


Environmental and Ecological Statistics | 2012

A framework for adapting survey design through time for wildlife population assessment

Fiona M. Underwood

Sampling strategies for monitoring the status and trends in wildlife populations are often determined before the first survey is undertaken. However, there may be little information about the distribution of the population and so the sample design may be inefficient. Through time, as data are collected, more information about the distribution of animals in the survey region is obtained but it can be difficult to incorporate this information in the survey design. This paper introduces a framework for monitoring motile wildlife populations within which the design of future surveys can be adapted using data from past surveys whilst ensuring consistency in design-based estimates of status and trends through time. In each survey, part of the sample is selected from the previous survey sample using simple random sampling. The rest is selected with inclusion probability proportional to predicted abundance. Abundance is predicted using a model constructed from previous survey data and covariates for the whole survey region. Unbiased design-based estimators of status and trends and their variances are derived from two-phase sampling theory. Simulations over the short and long-term indicate that in general more precise estimates of status and trends are obtained using this mixed strategy than a strategy in which all of the sample is retained or all selected with probability proportional to predicted abundance. Furthermore the mixed strategy is robust to poor predictions of abundance. Estimates of status are more precise than those obtained from a rotating panel design.


Science | 2018

Response—Ivory crisis

Duan Biggs; Robert J. Smith; Vanessa M. Adams; Henry Brink; Carly N. Cook; Rosie Cooney; Matthew H. Holden; Martine Maron; Jacob Phelps; Hugh P. Possingham; Kent H. Redford; Robert J. Scholes; William J. Sutherland; Fiona M. Underwood; E. J. Milner-Gulland

Sekar et al. argue that there is unequivocal evidence that ivory trade bans are necessary for conserving elephants, and that a growing consensus removes the need to consider or incorporate alternative values in this debate. In doing so, they overlook relevant literature [e.g., ([ 1 ][1]–[ 3 ][2


Conservation Biology | 2007

Hunting for consensus: reconciling bushmeat harvest, conservation, and development policy in West and Central Africa.

Elizabeth L. Bennett; Eric Blencowe; Katrina Brandon; David Brown; Robert W. Burn; Guy Cowlishaw; Glyn Davies; Holly T. Dublin; John E. Fa; E. J. Milner-Gulland; John G. Robinson; J. Marcus Rowcliffe; Fiona M. Underwood; David Wilkie


Journal of Hydrology | 2009

Describing long-term trends in precipitation using generalized additive models

Fiona M. Underwood


Climate Dynamics | 2013

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Chun Kit Ho; Ed Hawkins; Len Shaffrey; Fiona M. Underwood

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John E. Fa

Manchester Metropolitan University

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Rosie Cooney

International Union for Conservation of Nature and Natural Resources

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Martine Maron

University of Queensland

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