New study: Which species drive my conservation priorities?


Pilot whale wondering where to go next. —- Photo by By Barney Moss (Watching Whales 4) [CC BY 2.0], via Wikimedia Commons

In conservation planning, we often need to divide resources between multiple species. As conservation budgets virtually never meet the needs of adequate conservation, it’s important that every dollar is spent efficiently. Since many conservation actions have a spatial component, that is, they include the question of where the money should be spent, the question of how to divide resources quickly becomes about how to divide them between locations.If all target species are found in the same location, this question is easily solved. But species practically never have identical distributions, and under fixed budgets targeting one location and the species present there comes with the obvious trade-off of having less money left for other species occurring elsewhere in the landscape. Spatial solutions therefore need to be balanced between different locations. A set of location that together deliver the greatest benefit to all species are typically considered as priority for conservation actions.

I recently led a study with Dr Ascelin Gordon (RMIT) and Prof Atte Moilanen (Uni Helsinki) that looked at how the distribution patterns of target species dictate the way priority patterns emerge in multi-species conservation problems. We asked the following question: if we have a fixed budget (e.g. we can only protect a fixed area of land) and we want to maximize the outcome for species included in the plan, how much does the addition of one species change the plan? We then compared the observed change to the spatial characteristics of the species.


Species distributions can indicate the level of trade-offs that need to be made between species under fixed conservation budget. The upper panel shows a potential reserve network that would protect the core habitats (shown in green) of masked owls and squirrel gliders in the Hunter Valley. With little modifications, same amount of area could be used to also protect core habitats of powerful owls, as it shares most of its habitats with the first two species. On the other hand, including tiger quoll, which has more dissimilar distribution, incurs larger changes to the reserve network configuration.

We made several interesting findings. First, when resources are divided between many species so to maximize gains for all, it is the intermediately rare species inhabiting species poor environments that shape the distribution of priority areas the most. This might feel somewhat surprising, because we often think of locations with rarest species to be the most irreplaceable (which they are), and it would seem logical to think that they dictate conservation plans the most. However, if a species is very rare (e.g, a critically endangered orchid that only occurs in one or two confined location) it can be protected with a relatively little land area. Hence, when a very rare species is added to a conservation plan only minor spatial changes are needed, even if the species occurs in total isolation from all other species. On the other hand, as the distribution of a species gets larger, so does the likelihood of it sharing the space with other species. It therefore becomes increasingly likely that the existing plan already captures at least parts of the new species’ distribution, and that again relatively minor adjustments are needed. So there exists a sweet point on the rarity axis at which species are most influential. This naturally interacts with the way species co-occur with other species, and for which species the original plan was even built for.


Relationship between species spatial characteristics and its influence on a conservation plan, shown for the two study regions (GH = Greater Hunter, FIN = Finland.). Each dot represents a species. The y-axis shows how much priority rankings of candidate locations are changed when the species is added to a plan that includes 10 (green), 20 (blue) or 100 (red) species. Regional coverage gives the proportion of study area occupied by the species, indicating rarity. Mean Jaccard index describes how similar the species distribution is to all other species in the plan. Richness within distribution gives the mean species richness inside the species distribution, and Spearman correlation shows how spatially correlated the species distribution is to the plan made without it. This graph shows how the influence of any single added species drops as the total number of species in the plan is increased (green to red).

Which leads to our second finding, that conservation plans become increasingly stable the more species they are based on. This is because species are not randomly distributed in space but tend to co-occur in loose clusters, even in the most species poor environments. Hence, the more species are used to build a plan the more likely it is that they capture the habitats of the non-included species. Consequently, when >100 species are used, the addition of one new species makes very little difference to the overall plan.

Our third major finding was that the stability of the most and least important areas behave differently: the addition of a new species to a plan is likely to change the location of least important areas more than that of the most important areas. This has ramifications to some of the current practices, such as Environmental Impact Assessments (EIAs), that use information on species distributions to guide development into areas of lower impact. If these assessments are based on just a few number of species, which they often are, they may give false indication of how damaging it is to clear the proposed areas. Naturally, understanding the full impact of any development requires far more complicated analyses, but it all starts from not wiping out the core habitats of species.

We tested these aspects using two independent data sets that differed in data type, resolution, scale and taxonomic composition: a multi-taxa data set of modelled species distributions (from Greater Hunter, NSW, Australia) and single taxon atlas data based on observations (Finnish bird atlas). The results were surprisingly similar across both data sets, indicating that our findings are robust to different data types and locations, although more testing would be needed to validate this. There are also many other factors that influence how spatial priorities shape up across space. These include things like species weights and conservation targets, the methods used to identify priority areas across multiple species and the many economical and sociopolitical factors that often also need to be accounted for.

Understanding the relative impact any single species is likely to have on a conservation plan is nevertheless advantageous for conservation scientists and practitioners, because it helps to:

  • disentangle the different drivers that dictate how priorities for multiple species become distributed in space, making the process and outputs more transparent,
  • anticipate potential changes (or the lack of) when considering including new data into analyses,
  • clarify how additional weights given to species shape the prioritization results (giving a high weight to already highly influential species may not result in greatly improved outcomes for that species), and
  • is highly relevant from the perspective of input data uncertainty and value of information: uncertainties in the distribution information of a highly influential species are most likely to be of greater interest than those of less influential ones.


More details in the Open Access article published in Methods in Ecology and Evolution:
Kujala H, Moilanen A, Gordon A. (2018) Spatial characteristics of species distributions as drivers in conservation prioritization. Methods Ecol Evol. Early view online.


One thought on “New study: Which species drive my conservation priorities?

  1. Pingback: Dbytes #316 (18 January 2018) | Dbytes

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