Today, we are pleased to be welcoming a new member of the Methods in Ecology and Evolution Associate Editor Board. Res Altwegg joins us from the University of Cape Town, South Africa and you can find out a little more about him below. Res Altwegg “My interests lie at the intersection between ecology and statistics, particularly in demography, population ecology, species range dynamics and community ecology. My work … Continue reading New Associate Editor: Res Altwegg
The standard approach to quantifying natural selection, developed by Lande and Arnold, does not allow for comparable metrics between linear (i.e. selection on the mean phenotype) and nonlinear (i.e. selection on all other aspects of the phenotypic distribution, including variance and the number of modes) selection gradients. Jonathan Henshaw’s winning submission provides the first integrated measure of the strength of selection that applies across qualitatively different selection regimes (e.g. directional, stabilizing or disruptive selection). Continue reading “2017 Robert May Prize Winner: Jonathan Henshaw”
‘Just Google it’ marks an important step in converting ecology to an armchair science. Many species (e.g. owls, hawks, bears) are difficult, time-consuming, expensive and even dangerous to observe. It would be a lot easier if we didn’t have to spend time, energy and risk lives having to observe organisms in the field! Continue reading “2016 Robert May Prize Winner: Gabriella Leighton”
Typically, ecology courses contain at least a day of matrix population models. So most ecologists are somewhat familiar with how simple life cycles (and complex ones) can be depicted and analysed using matrix models. Briefly, these models represent what happens to individuals over a certain time interval (do they die? do they reproduce? if so, how much?). What individuals do in the context of these models can then be used to study the dynamics of a population.
Often, individuals are classified by size in matrix models, as small individuals tend to have different survival, growth and reproduction rates than large ones. But how many classes do you need to model the dynamics of a size-structured population properly? Instead of choosing arbitrary size class boundaries, Easterling, Ellner and Dixon (2000) came up with the idea of using continuous size variables and integrals to define a population model… and that’s how the first Integral Projection Model (‘IPM’ for us friends) came to be.
Naturally, for the development of a new demographic tool to prove useful to the scientific community, it must be flexible enough to be ‘one-size-fits-all’… and the needs of ecologists, evolutionary biologists and conservation biologists – who have to date used extensively size-based matrix models – are rather variable in size, colour and shape. Continue reading “Stage-dependent Demographic Modelling at Your Finger Tips”
Invasive weeds cause environmental and economic harm around the world. Land managers bear a heavy responsibility for the control of infestations in what is often a time-consuming and costly battle.
Understanding the current and future distribution of an invasive species allows managers to better direct their limited resources. However, the direct and strategic management of weeds is tricky and that’s why population models (in particular spatial dispersal models that can be applied without much data) are needed to inform and facilitate action on the ground. Continue reading “A Model Approach to Weed Management”
To understand how species survive in nature, demographers pair field-collected life history data on survival, growth and reproduction with statistical inference. Demographic approaches have significantly contributed to our understanding of population biology, invasive species dynamics, community ecology, evolutionary biology and much more.
As ecologists begin to ask questions about demography at broader spatial and temporal scales and collect data at higher resolutions, demographic analyses and new statistical methods are likely to shed even more light on important ecological mechanisms.
Traditionally, demographers collect life history data on species in the field under one or more environmental conditions. This approach has significantly improved our understanding of basic biological processes. For example, rosette size is a significant predictor of survival for plants like wild teasel (Werner 1975 – links to all articles are at the end of the post), and desert annual plants hedge their bets against poor years by optimizing germination strategies (Gremer & Venable 2014).
Demographers also include temporal and spatial variability in their models to help make realistic predictions of population dynamics. We now know that temporal variability in carrying capacity dramatically improves population growth rates for perennial grasses and provides a better fit to data than models with varying growth rates because of this (Fowler & Pease 2010). Moreover, spatial heterogeneity and environmental stochasticity have similar consequences for plant populations (Crone 2016). Continue reading “Demography and Big Data”
The February issue of Methods is now online! As you may have seen already, it includes the BES cross-journal Special Feature: “Demography Beyond the Population“. There are also eight other wonderful articles to read.
In demography, a set of processes (survival, growth, fecundity, etc.) interacts to produce observable patterns (population size, structure, growth rate, etc.) that change over time. With traditional approaches you follow the individuals of a population over some timespan and track all of these processes.
Demographic patterns and processes (Click to expand)
However, depending on the organism, some processes may be very hard to quantify (e.g. mortality or recruitment in animals or plants with long lifespans). You may have observed the patterns for the organism that you’re studying and, even better, measured some, but not all, of the processes. The question is: can we use this limited information to estimate the processes we couldn’t measure?Continue reading “Inverse Modelling and IPMs: Estimating Processes from Incomplete Information”
Back in 1997 MR was awarded a travel grant from CSIRO to visit Andy Sheppard in Canberra. CSIRO had been collecting detailed long-term demographic data on several plant species and Andy was keen to develop data-driven models for management.
Andy decided Illyrian thistle (Onopordum Illyricum) would be a good place to start, as this was the most complicated in terms of its demography. The field study provided information on size, age and seed production. The initial goal was to quantify the impact of seed feeders on plant abundance, but after a few weeks of data analysis it became apparent that the annual seed production per quadrat was huge (in the 1000s) but there were always ~20 or so recruits. This meant that effects of seed feeders (if any) occurred outside the range of the data, which wasn’t ideal for quantitative prediction.
“Demography Beyond the Population” is a unique Special Feature being published across the journals of the British Ecological Society. The effort evolved from a symposium of the same name hosted in Sheffield, UK last March. Both the meeting and the Special Feature were designed to challenge ecologists from a range of fields whose research focuses on populations.
The participants were charged with sharing how they are pushing the work they do beyond the stage where the population is the focus into research where the population is just the beginning and the focus spans scales, systems and tools. This encompasses a broad suite of biological research, including range modelling, disease impacts on communities, biogeochemistry, evolutionary theory, and conservation biology. The meeting was a great success, and this Special Feature should be equally valuable to the broad readership of the BES journals.
Methods in Ecology and Evolution has a special place in the Special Feature, hosting four papers. These papers not only introduce new efforts in population biology, they provide the methods that other scientists can use to implement them. With the tools provided by these four papers, researchers will be able to advance forest modelling, evolutionary theory, climate change biology and statistical inference of hidden population parameters. Seriously good stuff! Continue reading “Methods Beyond the Population”
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