The sending of letters under the pen name ‘St. Valentine’ began back in the middle ages as a way of communicating affection during the practice of courting. Fast forward to 2020 and Valentine’s Day is a day for celebrating romance, but now it typically features the exchange of gifts and cards between lovers.
Researchers from Canada and the USA found that tree and shrub genetics can be used to produce more accurate predictions of when leaves will burst bud in the spring. Their study was published in Methods in Ecology and Evolution.
Although climate sceptics might find it hard to believe with this year’s endless snow and freezing temperatures, climate change is making warm, sunny early springs increasingly common. And that affects when trees start to leaf out. But how much?
–Controlled plant crosses: Chambers which allow you to control pollen movement and paternity of offspring using unpollinated isolated plants and microsatellite markers for parents and their putative offspring. This system has per plant costs and efficacy superior to pollen bags used in past studies of wind-pollinated plants.
–The Global Pollen Project: The study of fossil and modern pollen assemblages provides essential information about vegetation dynamics in space and time. In this Open Access Applications article, Martin and Harvey present a new online tool – the Global Pollen Project – which aims to enable people to share and identify pollen grains. Through this, it will create an open, free and accessible reference library for pollen identification. The database currently holds information for over 1500 species, from Europe, the Americas and Asia. As the collection grows, we envision easier pollen identification, and greater use of the database for novel research on pollen morphology and other characteristics, especially when linked to other palaeoecological databases, such as Neotoma.
“My research is broadly focussed on the evolution of complexity. Many of my projects are related to the evolutionary ecology of programmed cell death (PCD) in unicellular organisms; how PCD impacts microbial communities; and how the philosophy of levels of selection informs our understanding of PCD evolution. I have also examined other aspects of complexity evolution such as the origin of life and group formation in unicellular chlorophytes in response to predation. The model organisms I typically use are phytoplankton. With specific reference to submissions to Methods in Ecology and Evolution, I have used a range of methods in my research, including general cell and molecular biology tools, biochemical assays, microscopy, flow cytometry, bioinformatics and computational algorithms.”
“I’m a molecular ecologist who uses genetic and genomic tools to ask questions ranging from surveillance and monitoring to biodiversity and phylogeography. My work includes development of novel molecular detection tools and metabarcoding applications for aquatic invasive species. I’m also interested in applying molecular tools to ask questions related to the evolution and biodiversity of benthic marine invertebrates in Antarctica.”
“In some years, chum salmon are frequently the bycatch of pollock fishermen” in the Bering Sea, Garvin explained. “Genetically, chum salmon that originate in Western Alaska tend to look very similar. This makes it difficult for stakeholders because management and conservation efforts to address this bycatch can differ among these regions, but the ability to identify them with genetics is not possible.” Continue reading →
Friday was Endangered Species Day – so this is a good time to reflect on what science and scientists can do to support conservation efforts and to reduce the rate of species extinctions. One obvious answer is that we need to study endangered species to understand their habitat requirements as well as their potential for acclimatization and adaptation to changing environmental conditions. This information is crucial to for the design of informed conservation planning. However, for most endangered species the relevant phenotypes are not known a priori, which leaves the well-intentioned scientist asking “which traits should I measure?”. Transcriptome analysis is often a good way to answer to this question.
Basic Techniques for the Arborist Throw-line Launcher
The first of the three videos is a basic overview of the method. In this tutorial, the authors teach you how to find the ideal branch, how to use the throw-line launcher and go through some important safety information. Continue reading →
Shannon entropy and its exponential have been extensively used to characterize uncertainty, diversity and information-related quantities in ecology, genetics, information theory, computer science and many other fields. Its mathematical expression is given in the figure below.
In the 1950s Shannon entropy was adopted by ecologists as a diversity measure. It’s interpreted as a measure of the uncertainty in the species identity of an individual randomly selected from a community. A higher degree of uncertainty means greater diversity in the community.
Unlike species richness which gives equal weight to all species, or the Gini-Simpson index that gives more weight to individuals of abundant species, Shannon entropy and its exponential (“the effective number of common species” or diversity of order one) are the only standard frequency-sensitive complexity measures that weigh species in proportion to their population abundances. To put it simply: it treats all individuals equally. This is the most natural weighing for many applications. Continue reading →
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.