Understanding animal movement across varying spatial and temporal scales is an active area of fundamental ecological research, with practical applications in the fields of conservation biology and natural resource management. Advancements in tracking technologies, such as GPS and satellite systems, allow researchers to obtain more location information for a variety of species than ever before. It’s an exciting time for movement ecologists! However, entomologists studying insect movement are still limited because of the large size of tracking devices relative to the small size of insects.
Matrix projection modeling is a mainstay of population ecology. Ecologists working in natural area management and conservation, as well as in theoretical and academic realms such as the study of life history evolution, develop and use these models routinely. Matrix projection models (MPMs) have advanced dramatically in complexity over the years, originating from age-based and stage-based matrix models parameterized directly from the data, to complex matrices developed from statistical models of vital rates such as integral projection models (IPMs) and age-by-stage models. We consider IPMs to be a class of function-based MPM, while age-by-stage MPMs may be raw or function-based, but are typically the latter due to a better ability to handle smaller dataset. The rapid development of these methods can leave many feeling bewildered if they need to use these methods but lack sufficient understanding of scientific programming and of the background theory to analyze them properly.
Senior Editor Bob O’Hara has selected five Featured Articles this month, including methods for predicting pollinator abundance, evaluating species distribution modelling applications and accelerating image‐based ecological surveys using interactive machine learning – find out about all of them below.
We also have 12 articles that are free to read, including five Applications and two Practical Tools articles – no subscription required!
Understanding interactions between predators and prey is of interest to a variety of research fields. These interactions not only hold valuable information about ecological dynamics and food webs but are also crucial in understanding the evolution of predatory and anti-predator traits such as vision, visual signals and behavior. Thus, the “who attacks what and why” is key to approach broad evolutionary and ecological questions.
Aquatic animal telemetry has revolutionized our understanding of the behaviour of aquatic animals. One of the important advantages of telemetry methods, including acoustic telemetry, is that they provide information at the individual level. This is very relevant because it enables investigating the natural variability in behaviour within populations (like here or here), but also because one can investigate what happens to each individual animal and relate it to its natural behaviour. Knowing “what happens to each individual” is normally referred to as “fate” and it can take many forms: some fish may end-up eaten by predators, other may be fished, some of them may disperse, etc. Knowing the fate of each individual fish is crucial as it links ecological processes at the individual level to evolutionary outcomes at the population level.
Senior Editor Aaron Ellison has selected six Featured Articles this month. You can find out about all of them below. We also have eight Applications articles and seven Practical Tools articles in the November issue that are freely available to everyone – no subscription required!
We have a larger issue of 14 articles this month, featuring methods for individual bird recognition, zooplankton sampling, coral health assessment and much more.
Senior Editor Lee Hsiang Liow has selected five featured articles – find out about them below. We also have three Applications, three Practical Tools articles and 11 articles that are freely available to everyone – no subscription required!
This post recalls the journey on how we ended up developing cxr (acronym for CoeXistence relationships in R), an R package for quantifying interactions among species and their coexistence relationships. In other words, it provides tools for telling apart the situations in which different species can persist together in a community from the cases in which one species completely overcomes another.