By: Rob Brown
Disturbances such as climate change, biological invasions, pollution, and many others, have led to organizations to emerge with the purpose of restoring and conserving our natural resources. Both paleo- and modern ecological data can help inform resource managers as they implement restoration and conservation strategies.
Traditionally, the aim of restoration is to restore ecosystems to a natural baseline, or a pre-human disturbance state. However, Jackson and Hobbs (2009) made three observations that complicate finding natural baselines. The first is that ecosystems are constantly changing. This forms the basis for the novel ecosystem concept, which states no modern ecosystem has existed in the past and or will exist again in the future. Second, biological communities are also always changing as their environment changes leading to no-analogue communities, biological communities that have never existed before. Third, there can be multiple baselines that alternate through time. This makes finding a natural baseline difficult. Therefore, the authors propose using ecosystem functions and services, accepting change is inevitable, as a baseline for restoration goals instead of the classic idea of a getting back to pre-disturbance state.
Paleoecology offers a tool to determine the natural variability in ecosystems and guide long-term management of resources, however paleoecology is rarely linked to modern ecology or conservation biology (Birks 2012). The goal of ecology is to have a greater understanding of how the world works. By viewing the past, present, and future as a continuum rather than discrete time units, it becomes possible to link paleoecology and modern ecology. This allows for more informed restoration goals and track the recovery to disentangle how multiple stressors may be offsetting expected recovery (Figure 2; Battarbee et al. 2005). This can keep restoration efforts dynamic and account for the possibility of novel ecosystems.
By linking paleoecological and long term ecological data and focusing on ecosystem functions rather than “natural” baselines, resource managers can develop better management strategies that allow for the ever-changing nature of ecosystems. Paleoecological data can provide the natural variability and provide context for restoration efforts. Meanwhile, long-term ecological data provides the modern setting and the future trajectory of ecosystems. Furthermore, overlap between the two in time allows for paleo-data to be verified by observational records. Finally, further monitoring of ecosystems allows for responses to be tracked and confounding stresses be identified, ultimately allowing for restoration efforts to be flexible in order to achieve goals.
Hollig and Meffe (1996) define a golden rule for natural resource management “…to retain critical types and ranges of natural variation in ecosystems.” This includes maintaining genetic diversity in populations to prevent population crashes, bottlenecks, and inbreeding. Therefore, it would be valuable to know where in a species’ range the greatest genetic diversity is.
When conserving biodiversity in the face of climate change, there is paleoecological evidence that the rear edge of population ranges contain the greatest diversity (Figure 2; Hampe and Petit 2005). This area is thought to be the area where plants and animals retreated to during the last ice age. However, studies using mitochondrial DNA in Europe have found the highest diversity of grasshoppers, hedgehogs, and bears lie in zones just outside of glacial refugia where isolated populations mixed after glacial retreat (Hewitt 2000). The location of greatest genetic diversity appears to depend on the species and constrained by physical barriers.
Once again, by combining paleo and modern ecological data, researchers and resource managers can be better informed when implementing conservation strategies. Understanding where genetic hot spots might lie, resource managers interested in maintaining high genetic diversity can target areas for conservation with the best chance of achieving this goal.
Birks, H. J. B. (2012). Ecological palaeoecology and conservation biology: controversies, challenges, and compromises. International Journal of Biodiversity science, Ecosystem services & Management, 8(4), 292-304.
Battarbee, R. W., John Anderson, N., Jeppesen, E., & Leavitt, P. R. (2005). Combining palaeolimnological and limnological approaches in assessing lake ecosystem response to nutrient reduction. Freshwater Biology, 50(10), 1772-1780.
Jackson, S. T., & Hobbs, R. J. (2009). Ecological restoration in the light of ecological history. Science, 325(5940), 567.
Holling, C. S., & Meffe, G. K. (1996). Command and control and the pathology of natural resource management. Conservation biology, 10(2), 328-337.
Hampe, A., & Petit, R. J. (2005). Conserving biodiversity under climate change: the rear edge matters. Ecology letters, 8(5), 461-467.
Hewitt, G. (2000). The genetic legacy of the Quaternary ice ages. Nature, 405(6789), 907-913.