The idea that “bigger is better” is a prevalent one in biology. Body size has a significant impact on fitness, the ability of organisms to survive and reproduce, across all branches of life. In wolves, a larger body size gives them greater success in grappling and subduing large prey like moose or elk (MacNulty et al., 2009). In dall sheep, a larger body size gives males a reproductive advantage when they compete for the right to mate, and since adult sheep may lose up to 16% of their body mass during winter, those with a higher body mass are more likely to survive (U.S. National Park Service, 2020). However, “bigger” is not always a “better” lifestyle method for some animals, and can be actively harmful to their chances of survival.
Insects and arthropods are limited in their body size because they breathe by soaking in oxygen like a sponge. If they are too large, they cannot absorb sufficient oxygen and die of hypoxia. It was only during the Paleozoic, when oxygen concentrations reached as high as 35% during the Carboniferous period, that insects were capable of gigantism, with some dragonflies as large as seagulls (Harrison et al., 2010). Furthermore, it is costly to support a large body mass: the larger the body, the greater the energy requirements and the more food is required to sustain the animal. There are also factors of predation, where a larger body size may reduce agility, increase detection by predators, or increase costs to reproduction (Blanckenhorn, 2000). In essence, how natural selection acts on size is complex. Understanding how size correlates with survival is important, particularly when we are examining the salmon populations of Alaska.
In today’s world with an increasing human footprint across the natural world, scientists believe we may be entering a sixth mass extinction. Fragmented habitats, introduction of invasive species, and climate change are just some of the factors leading to this mass extinction. A lot of species still have yet to be recorded, so the number of extinctions of populations and species documented by scientists are likely to be large underestimates (Barnosky et al. 2011). Climate change is one factor among many that is leading to the loss of biodiversity. Therefore, it is important for scientists to understand how populations respond to rapid environmental change. It is known that evolutionary history may affect risk of extinction within populations due to the accumulation of mutations, or pleiotropy. In one environment certain mutations will be favored, but in others they may have detrimental effects that reduce fitness, or reproductive success of a certain genotype in a population. (genotype being the genetic makeup of an individual) This would lower a population’s ability to withstand environmental change due to the accumulation of mutations which aren’t suited for the new environment. (MacLean et al. 2004) Understanding evolutionary history is crucial for understanding how populations will respond to environmental change caused by climate change. In the October edition of the Journal of Evolutionary Biology there was a study looking at how evolutionary history affects extinction probability. Its title is “The effect of selection history on extinction risk during severe environmental change’. This study looked at how the extinction risk of populations of the green algae Chlamydomonas reinhardtii changed with various stressful environments (Lachapelle et al. 2017).
Coral reefs are known as pristine locations, and the ability of the coral making them up to create environments supporting myriads of fish species is astounding. Comparisons between corals ability to create a niche for complex and diverse ecosystems has been compared to that of rain forests on land, with almost a third of marine fish being found, despite covering less than 1% of the ocean bed (Adey 1998). In fact, many of the species that live within these reefs owe survival to coral health (Komyakova et al 2013). However, the home of Nemo and Ariel has been under recent threat over the years, due to climate change and ocean acidification (Hoegh-Guldberg et a. 2007). Just this last year alone, the great barrier reef saw the worst coral bleaching, thanks to rising water temperatures (Griffith 2016). While exploration of ways to change the impact we are having on corals, and therefore the impact on the reefs ecological webs as a whole, interest has also developed in what the corals responses to these changes in their environment have been (Putnam et al. 2016). The value of this data provides an extreme example of phenotypic plasticity, the ability of an organism to respond to its environmental conditions.Continue reading “Coral Reefs and Phenotypic Plasticity: Responses to a Changing Climate”
Whether migratory birds will respond successfully to rapid climate change is unclear. Birds migrate to take advantage of seasonal peaks in resource availability: Food and habitat become abundant quickly during summer at northern latitudes, but decline quickly in the fall. Timely arrival on the summer range is vital for many species (Alerstam and HedenstrÃ¶m 1998). Continue reading “Evolutionary advantage of learning to cope with change”
Timing is everything for bringing new life into the natural world. Every year, species such as the great tit (Parus major), one of the many song birds found on the British Isles, rely on abundant food to be able to provide enough nutrients for their growing young. The presence of this food is the result of a large cascade–like a line of dominos–that begin with the smallest of microorganisms responding to environmental factors such as temperature and salt concentration. If the timing of one of these falling dominoes is slightly off, many organisms further down the line suffer and may be unable to find food at the most critical times of early offspring growth. Two particular organisms that share the same line of dominoes as the great tit are the pendunculate oak (Quercus robur) and the various caterpillars which feed on the oak’s leaves. Continue reading “Great Tits and Climate Change: An Experiment to Transform Current Prediction Models”