I'm a computational ecologist. My RESEARCH aims to
understand ecological and evolutionary patterns and processes in nonstable environments, across time and
space. I use real DATA, mathematical models,
statistical analysis and novel SOFTWARE.
INTERESTS Ecological systems are structured, with interacting components, (e.g.
populations of interacting individuals, communities of interacting populations).
Human or environmental events and pressures often affect one component more than another
(e.g. fires kill young, not old, trees), destabilising systems. I'm interested in
nonstable ecological system dynamics (e.g. population growth rates) that result. These dynamics have
consequences for how ecological systems are conserved and managed. I'm also
interested how systems evolve or develop to cope with non-stable environments.
System structures and functions that confer resilience should be favoured.
In a separate line of work, I've recently become interested in applying these approaches to
socio-ecological systems to address inequalities through ecological justice approaches.
STUDY SYSTEMS
I'm fascinated by the diverse life histories of plants and animals,
Different species have vastly different patterns of survival and reproduction across the
their lifetimes. Working with mathematicians, I use population models to understand patterns of life history across species,
how this impacts their resilince, and conversely how those dynamics feed back
into evolutionary processes shaping life history.
I'm determined to use ecological science to improve the lives of people, as most people live
in urban areas and urban ecosystems are vital to human health and wellbeing. As
biodiversity (especially urban forest) is unevenly distributed across cities, access to
green spaces across is unequal across different communities. Working with social and
economic scientists, I believe that ecological models and 'big data' can provide answers to managing
urban green spaces for ecological justice.
METHODS
I work with mathematical models, statistical analysis,
big(-ish) data and novel software. I like a 'systems' approach, which
considers the whole system of interest rather than individual parts: the
ideology and mathematics around this have their roots in engineering,
but borrowed across to ecology. With mathematicians, I have developed many new analytical
tools to understand ecological systems, as well as the software to implement them. I hope to
work with bigger data sets and artificial intelligence approaches in the future.
FUTURE
I'd like to leverage the frameworks, methods and tools in the
study of other ecological systems, particularly to understand links across hierarchies of
biological organisation, e.g. how population resilience impacts community stability.
WHYAGE
WHYAGE is my Marie Skłodowska-Curie Actions fellowship project, funded by the European Union.
Patterns of aging, as measured by rates of survival and reproduction across the life cycle, are
diverse across the tree of life. In this project, myself and colleagues developed new methods of measuring aging, and
new ways of understanding population resilience through nonstable dynamics. I applied
these to survival and reproduction data across diverse species, to see how aging patterns
affect population resilience. This opens a door to understanding how the responses of populations
to disturbances influence the evolution of patterns of aging.
Everything ages. With increasing age, we undergo physiological
decline, meaning we are more likely to die, and less likely to reproduce.
This is called ‘senescence’. Although everything ages, not everything senesces.
Recent research shows that some
organisms show constant or even increasing survival and fertility with age.
Life spans vary from days to thousands of years.
How did such diverse aging evolve? The ‘fittest’ life histories should have
highest population growth, but there’s more than one way to achieve this.
WHYAGE explores whether different types of aging may be adaptations to different
types of environmental disturbance, as different patterns of survival and reproduction
over age are better depending on which ages are most affected by the disturbance.
EXAMPLE
Organism A in the graph
to the right survives better and reproduces more as it gets older (such as many
reptiles). Organism B survives worse and reproduces less as it gets older (such as
many mammals).
Pressures from humans or the environment may force certain population structures
by killing or removing certain individuals from the population more than others: examples are extreme weather events, fire,
disease, or harvesting by humans. If a disturbance were to remove young individuals it would
force the population structure shown in grey.
In this scenario, Organism A ends up with
many older individuals that survive better and reproduce more. It therefore has high population
growth and recovers from the disturbance well. Organism B
lacks individuals that survive and reproduce well, so its population growth is slow and it takes longer
to recover. If the disturbance that forces this population structure is common, then over time there
will be increasing numbers of organism A, because the way it ages is better adapted to living in this particular
environment.
The WHYAGE project tackles these questions using comparative demography.
The empirical part of the project uses demographic data of thousands of
species (www.compadre-db.org), to measure aging across the tree of life
and relate this to population dynamics. The first part of the project
is about method development. Myself and collaborators have
developed new ways of measuring aging using
survival and reproduction data, and
developed a framework for understanding resilience
of populations. These include development of open-source software for use
by any researcher. By analysing the relationships between aging and resilience,
it is possible to understand how an organism's aging affects ecological dynamics
of its populations. This is a first step to understanding how a species'
resiliences to disturbances feed back into evolution of their patterns of aging.
This work has led to cllaborative projects assessing how to understand life history, including
a theoretical assessment of the utility of the 'fast-slow' life history paradigm, and
empirical assessments of (co)variation in components of aging across plants and animals.
My work uses data defined at a broad scale: across many species,
at regional to global levels, but to the highest level of accuracy
possible.
DEMOGRAPHY
Most of my work involves open-access demographic databases.
The COMPADRE AND COMPADRE
plant and animal matrix databases each provide thousands of matrix projection models and
associated metadata, for hundreds of species. These models are built from real
demographic data (survival, reproduction, growth, development)
collected in the field or lab, all over the world.
Matrix projection models can be used to forecast population dynamics, and
to calculate measures of the life history of organisms. Comparing
among many different models can help understand why different
organisms have different population dynamics, how life histories
of organisms differ from one another, and to look for patterns
in these over time, across space, and through evolutionary history.
I work with remotely-sensed, macroecological data sets describing the
geography of the urban areas I study (usually in the UK).
OS Mastermap
is an extremely high-resolution map of land cover from individual
buildings, statues and gardens, to ecosystems such as moorland or forest.
The National Tree Map
is a high-resolution remotely-sensed, AI-processed map of
the UK's forest. These data sets have proven vital for my
work in urban ecology.
Urban areas are highly heterogeneous. Distinct patches of land may be
merely a few metres square, but provide very different ecological
services compared to its surroundings (e.g. a garden surrounded by
buildings). Compared to its sister disciplines, urban ecology
requires far higher-resolution data. Remote sensing technologies are
now providing this. For example, the national tree map pieces together
aerial photography, terrain and surface data, and colour infrared imagery
to create a data set which outlines every single canopy and individual tree,
including crown and height data, for the whole of England and Wales. Data sets
such as these are making accurate contemporary urban ecological studies possible.
SOFTWARE
Part of my research is the development of novel software, mostly
R packages.
popdemo is an
R package designed
to quantify population dynamics in nonstable environments. See the
user guide
for more information. Available on Github
and CRAN.
Rcompadre is an
R package designed
for working with the COMPADRE and COMADRE data sets. See the
user guide
for more information. Available on Github.
Rage is an
R package (pre-release)
designed for caclulating age-based life history information.
Available on Github.
I also develop webapps for exploring data and learning quantitative skills.
ShinyPop
is a webapp designed for exploring the COMPADRE and COMADRE databases, and shocasing
some of the functionality of the popdemo
and Rage packages.
ShinyGLM
is designed to teach data handling, visualisation and general linear models in
R.
My teaching primarily centres on quantitative skills,
but I also have extensive experience teaching ecology,
conservation biology and evolution in the classroom,
lab, field and online. I am currently module co-ordinator for two undergraduate modules:
Data Skills for the Life Sciences (2nd year) and
Practical Skills in Conservation (3rd year). I teach on several
other modules and field courses, and act as a personal tutor and dissertation supervisor.
EQUALITY, DIVERSITY & INCLUSION
Being a gay man led me into working in EDI, and I've since become heavily invested
in changing systems which provide unequal opportunities and support for
minority groups. Although I do my best to stand up for the interests of all
those who are disadvantaged, I work especially to represent the interests of the LGBTQ+
community, and those living with long-term mental health conditions.
In 2020 I was awarded the British Ecological Society's Equality and Diversity Champion award.
I am a member of the British Ecological Society's
Equality and Diversity Working group, help run their LGBT+ network, and organise
LGBT+ articles for the quarterly members' magazine. I'm also on the EDI committees
of the University of Lincoln School of Life Sciences and College of Science.
I previously sat on the Board of Trustees of the British Ecological Society,
representing early career members of the society. During this time
I also sat on the BES Publications Education and Careers, and
Membership Committees.
Most of my work involves open-access demographic databases.
The 
I work with remotely-sensed, macroecological data sets describing the
geography of the urban areas I study (usually in the UK).
