Encyclopedia of Evolutionary Psychological Science

Living Edition
| Editors: Todd K. Shackelford, Viviana A. Weekes-Shackelford

Harsh Environments

  • Peter TakacsEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-16999-6_425-1

Synonyms

Definition

Harsh environments are external conditions that present a heightened or unusual challenge to the fitness of individual organisms, the stability of populations and longevity of species, or even the robustness of ecological communities.

Introduction

Harsh environments are external conditions that are detrimental to survival for most forms of life. These conditions limit the growth, abundance, or distribution of organisms and populations in an ecosystem. The challenges posed by such environments are typically conceived of as being abiotic in nature. Although by no means an exhaustive list, severe limitations of essential nutrients or vitamins, resources such as water or energy (in the form of heat or light), space or shelter, and extremes of temperature, pH, salinity, or altitude are all limiting factors that contribute to the harshness of an environment. Humans and many other organisms have nevertheless adapted to survive and even flourish in these conditions.

Disambiguating “Harshness”

An environment may be considered “harsh” for a variety of reasons. It is necessary to distinguish these senses of harshness since each may have substantially different effects on the ecological dynamics of a population or community and the evolutionary dynamics of a species. Two distinct but not necessarily exclusive general criteria for harshness can be captured by using the labels abnormal and unpredictable.

“Statistical abnormality” can be attributed to environments that exhibit extreme values of limiting abiotic factors that fall well beyond the average as calculated across all known species. This form of trans-specific extremeness is typically correlated with lower species diversity. Take, for instance, exposure to sunlight. One extreme value on the spectrum for this limiting factor is realized in habitats hidden well beneath the surface, such as caves and sewers. As well as being a valued source of energy for many species, light is a requirement for even the most basic forms of sightedness. The evolution, ontogenetic development, and maintenance of a complex adaptation like the eye are costly. In many cases, the fitness enhancement that comes with sightedness is well worth the cost. Even the most basic forms of vision, simple photoreceptors, often enable the organisms that have this capacity for detection to evade predators or snare prey that cast shadows, as well as reliably migrate to areas that receive greater or lesser amounts of sunlight and correlated resources. For species of cave-dwelling fish (e.g., Astyanax mexicanus), however, there has been strong selection for the loss of functional eyes and thus blindness because of negligible light levels in their local environments (Cartwright et al. 2017). This is a harsh environment in the sense that relatively few extant species encounter or could survive in conditions where there are no immediate photosynthetic primary producers and no way for them to see.

It is precisely to statistically unusual environments that organisms commonly known as “extremophiles” have adapted (Archibald 2014). Although these are usually microbial life forms that thrive in geochemical or physical conditions that are typically too extreme for complex multicellular forms of life, examples can be found in all three domains of life (Rothschild and Mancinelli 2001). Perhaps, the best-known extremophiles compose a phylum of small invertebrates known as tardigrades (Tardigrada) or “water bears.” Species of this phylum can be found in almost every habitat on Earth. They can withstand temperatures ranging from −200 °C to 151 °C, a complete lack of water or oxygen, boiling alcohol, the low pressure of a vacuum or six times the highest pressures found in the deepest part of the oceans, and more than one thousand times the lethal dose of X-ray radiation for a human (Bordenstein 2019).

A subtly different sort of abnormally harsh environment is one that is unusual for the members of a species when viewed from an evolutionary perspective. A human example is informative in this context. The preference for and occasional overconsumption of fatty or sugary foods was likely adaptive for our hominid ancestors since opportunities to exploit such energy-dense resources were somewhat rare. Evolutionary precursors who exhibited trait variants for effectively exploiting these resources were on average more likely to survive and reproduce than those of our distant ancestors who exhibited less effective trait variants for doing so. Exploitative (i.e., gluttonous) foraging behavior and an enhanced ability to store energy in fat cells thus increased relative inclusive fitness in this “normal” environment for our ancestors, also known as the environment of evolutionary adaptedness, or the environment to which humans became adapted during the Pleistocene. But in most modern societies, this behavioral strategy no longer maintains the fitness advantage that it once held.

To understand why this is so, it must be mentioned that many aspects of the metabolic control system are established early in fetal development. Among these are the craving for food, insulin sensitivity, and the number of fat-storing cells. Normal maternal constraints during pregnancy can generate an upper limit on how much nutrition a fetus can sense. These constraints have the effect of directing the fetus to anticipate an environment that is not quite as bountiful as the one its mother experiences. The developing fetus responds by exhibiting increased insulin resistance and allocating more resources to the development of fat cells than necessary. When energy-dense environments are rare, there is no problem with this response; it can be a useful strategy in cycles of feast and famine. However, energy-dense foods have been readily available in most developed countries since the agricultural revolution. Worse yet, many of the modern foods we consume are explicitly engineered to falsely exhibit the common cues for high energy density (e.g., saltiness without corresponding high protein content) and thereby trigger virtually uncontrollable cravings. The fetus is subsequently born into a modern environment teaming with such resources. Blood glucose levels rise when these foods are consumed, which results in heightened insulin levels. Due to increased insulin resistance, however, the process of restoring normal blood glucose levels becomes biased toward storage of fat rather than more immediate usage. The outcome, of course, is a situation in which obesity and metabolic disorder have become global epidemics. There is a severe mismatch between the environment of evolutionary adaptedness and our statistically normal but nevertheless “harsh” obesogenic environment (Gluckman et al. 2005).

The foregoing forms of harshness are due to statistical or evolutionary abnormality, which involve uncommon extremes of limiting abiotic factors or significant departure from the conditions historically associated with periods of adaptive evolution, respectively. An altogether different form harshness can come in the form of environments that are unpredictable. Essential resources fluctuate in most environments. There are, for example, regular and thus highly predictable daily changes (e.g., light hours per day) as well as seasonal climatic variations (e.g., colder Fall/Winter temperatures giving way to a warmer Spring/Summer). The relative stability of fluctuations like these over a geologic timescale has granted species time to adapt to such conditions on an evolutionary timescale.

Predictable fluctuations in limiting factors are contrasted with what is called “environmental stochasticity” in the relevant scientific literature (Lande et al. 2003). Environmental stochasticity refers to unpredictable spatial or temporal fluctuations in environmental conditions. Notice that the inability of an organism to precisely predict a future state of the system is due to extrinsic ecological features. This should not come as a surprise. For, upon close inspection, most (if not all) natural habitats exhibit highly localized and effectively random spatiotemporal fluctuations in available resources. Given that there is insufficient time for finely tuned adaptive evolution, survival in such adverse spatially or temporally “patchy” conditions requires adopting a suboptimal survival strategy (i.e., allocation of available resources). Since no attainable strategy can reliably make perfect predictions about the future, there will be a continuum of (suboptimal) strategic variation along which some strategies fare better than others.

Unpredictably harsh environments are often the background conditions against which constrained trade-offs in the strategic allocation of resources and the evolution of life history traits are examined (Stearns 1992). This is evinced in the theoretical contrast between the reproductive strategies known as r and K. For present purposes, it is worth noting that unstable or unpredictably harsh conditions generally lead to strong selection for a high fecundity, low investment strategy (r), the idea being that at least a few small and quick-to-mature offspring will survive in the face of high mortality due to environmental instability. Niche construction theory – wherein it is argued that organisms significantly modify their environments and thereby influence selection pressures on some population of recipient organisms – takes the ability of organisms to manage (minimize) the harshness of the environmental conditions to be fundamental (Laland et al. 2014). And research on cooperation suggests that such behavior facilitates the colonization of harsh environments (Cornwallis et al. 2017), which in turn implicates harsh environments as an explanatory factor in the maintenance of altruistic behavior.

The point to note is that environmental harshness due to unpredictability does not involve uniform distribution of or prolonged exposure to statistically extreme and, thereby, unusual values of a limiting abiotic factor. Quite to the contrary, unpredictable environmental fluctuations can mirror the average (statistically normal) conditions present in both the environment of evolutionary adaptedness and current environments. This can happen when (i) the resources available to a population are distributed in a spatially nonuniform (i.e., “clumped” or “patchy”) way over a limited area, or (ii) there are irregular temporal fluctuations in the available amount of a resource within a population’s habitat. Some of the spatial parts or temporal stages of a habitat accordingly experience statistically extreme values of limiting resources. However, the quantitative influence that these locally extreme values have in the calculation of average (arithmetic mean) conditions for the habitat as a whole can be offset when there are enough complementary high/low values from other parts or stages of the habitat. The arithmetic mean value for a limiting factor in a habitat can, therefore, remain unchanged even as environmental variance in the availability of limiting resource, not to mention corresponding uncertainty regarding resource allocation, increases. Environmental stochasticity thus makes for a “normal” but nevertheless harsh environment insofar as it induces individuals to adopt allocation strategies that maximize actual fitness (especially the fitness component of survival) at the expense of expected fitness (maximum fecundity). Following Matthewson and Griffiths (2017), it might be prudent to label these unpredictably harsh conditions “inhospitable” rather than “abnormal.”

Conclusion

The Importance of Harsh Environments

The recognition and study of harsh environments is of vast importance to ecological and evolutionary theorizing. Simply identifying the range of values for limiting factors over which species can thrive is hugely informative. In astrobiology, for example, it is typically the capacities of extremophiles in harsh environments that bound the possibility space of our thinking about whether and where life is likely to be found. For a more “down-to-earth” illustration, we can turn to conservation biology. Human-induced climate change is an unprecedented threat to human and nonhuman life. One way to understand and possibly predict ecological and evolutionary dynamics in the age of dramatic climate change is to examine how organisms have already adapted to harsh environments, past (via paleontology) and present.

Cross-References

Notes

Acknowledgments

I would like to acknowledge the grant that currently funds my research: ARC Australian Laureate Fellowship project A Philosophy of Medicine for the 21st Century (Ref: FL170100160).

References

  1. Archibald, J. (2014). One plus one equals one: Symbiosis and the evolution of complex life. Oxford: Oxford University Press.Google Scholar
  2. Bordenstein, S. (2019). https://serc.carleton.edu/microbelife/topics/tardigraade/index.html. Accessed 23 Jan 2019.
  3. Cartwright, R. A., et al. (2017). The importance of selection in the evolution of blindness in cavefish. BMC Evolutionary Biology, 17(45).  https://doi.org/10.1186/s12862-017-0876-4.
  4. Cornwallis, C. K., et al. (2017). Cooperation facilitates the colonization of harsh environments. Nature Ecology and Evolution, 1(3).  https://doi.org/10.1038/s41559-016-0057.CrossRefGoogle Scholar
  5. Gluckman, P. D., et al. (2005). Environmental influences during development and their later consequences for health and disease: Implications for the interpretation of empirical studies. Proceedings of the Royal Society of London, B, 272, 671–677.CrossRefGoogle Scholar
  6. Laland, K. N., Odling-Smee, J. F., & Turner, S. (2014). The role of internal and external constructive processes in evolution. Journal of Physiology, 592(11), 2413–2422.CrossRefGoogle Scholar
  7. Lande, R., Engen, S., & Saether, B. E. (2003). Stochastic population dynamics in ecology and conservation. Oxford: Oxford University Press.CrossRefGoogle Scholar
  8. Matthewson, J., & Griffiths, P. E. (2017). Biological criteria of disease: Four ways of going wrong. The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine, 42(4), 447–466.CrossRefGoogle Scholar
  9. Rothschild, L. J., & Mancinelli, R. L. (2001). Life in extreme environments. Nature, 409(6823), 1092–1101.CrossRefGoogle Scholar
  10. Stearns, S. (1992). The evolution of life histories. Oxford: Oxford University Press.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Philosophy and Charles Perkins CentreThe University of SydneySydneyAustralia

Section editors and affiliations

  • Haley Dillon

There are no affiliations available