Thoughts on Wildlife Management

Stop for a moment and think about where we are now in the science of wildlife management and conservation. Look at the titles of paper in our scientific journals. The vast majority of the problems and questions being investigated are basically about how to reverse some human-caused folly. Many wildlife scientists, ecologists, and organismal biologists entered science with the goal of understanding natural systems from the ecosystem down to the molecular level but in the past 60 years the focus has had to shift. This shift has occurred almost unnoticed because it has been gradual in the time scale of human employment and turnover. The ecosystems of the world are in a frightful mess, and virtually all the mess is human caused. So while we engage in many discussions about how to define the ‘Anthropocene’ in the geological sciences (Correia et al. 2018; Zalasiewicz et al. 2017) ecological science is left in the dust because it never leads to ‘progress’.

This came home to me when I considered which of the many study sites in which classical ecological research has been carried out over the last century still exist. They have been replaced by suburbs, highways, shopping malls, farms, and industrial sites, and the associated waterways have been altered beyond recognition. A simple consequence is that if you wished to repeat a famous ecological study done 50-100 years ago, you could not do it because the site has been obliterated. One consequence is that if we wish to do field work today, we choose a new site that has so far been protected from development.

The elephant in the room now is climate change, so if you choose to investigate the trophic dynamics of an Amazonian forest area (for example), you face two problems – the site could be obliterated by ‘development’ before your work is completed, or the climate changes expected during the next 80 years will alter the trophic dynamics of your site so that your current results are no guide to the future state of these ecosystems. Whither predictive ecology? Many of us thought that by discovering and analyzing ecological principles, we could closely approach the precision of the physical sciences, the laws of physics and chemistry. But the more we search for generality in ecology the less we find. We retreat to general principles that are too vague to be of any predictive use for the wildlife managers of the future.

The thought has been prevalent that by investigating the changes in communities and ecosystems in the past we would have a guide to the future. This belief guides much of paleo-ecological research as well as the projections from evolutionary research of how species have recovered from the recent ice ages. But the past is perhaps not necessarily a good guide to the future when we add in the human footprint arising from the combination of population growth and climate change. Ecologists are left with the concern that our findings have much current value but perhaps little long-term insight. 

Many current papers on ecological changes assume a simple extrapolation predicting the future state of ecosystems (e.g. Martin et al. 2019; Yu et al. 2019). Testing these kinds of extrapolations is virtually possible within the lifetime of the typical ecologist, and my concern is that management actions that are recommended now may be completely off the mark in 30 years. Several papers have warned about this (e.g. Inkpen 2017; La Marca et al. 2019; Mouquet et al. 2015) but as far as I can determine to little effect.

I think the bottom line might be a recommendation for all predictive papers to state a strong prediction and a defined time frame so that there is hope of testing the predictive model in ecological time. Otherwise we ecologists begin to fall into the realm of science fiction.

Correia, R.A. et al. (2018). Pivotal 20th century contributions to the development of the Anthropocene concept: overview and implications. Current Science 115, 1871-1875. doi: 10.18520/cs/v115/i10/1871-1875.

Inkpen, S.A. (2017). Are humans disturbing conditions in ecology? Biology & Philosophy 32, 51-71. doi: 10.1007/s10539-016-9537-z.

La Marca, W. et al. (2019). The influence of data source and species distribution modelling method on spatial conservation priorities. Diversity & Distributions 25, 1060-1073. doi: 10.1111/ddi.12924.

Martin, D. et al. (2019). Long-distance influence of the Rhône River plume on the marine benthic ecosystem: Integrating descriptive ecology and predictive modelling. Science of The Total Environment 673, 790-809. doi: 10.1016/j.scitotenv.2019.04.010.

Mouquet, N. et al. (2015). Predictive ecology in a changing world. Journal of Applied Ecology 52, 1293-1310. doi: 10.1111/1365-2664.12482.

Yu, F., et al. (2019). Climate and land use changes will degrade the distribution of Rhododendrons in China. Science of The Total Environment 659, 515-528. doi: 10.1016/j.scitotenv.2018.12.223.

Zalasiewicz, J. et al. (2017). The Working Group on the Anthropocene: Summary of evidence and interim recommendations. Anthropocene 19, 55-60. doi: 10.1016/j.ancene.2017.09.001.

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