Red listing isn’t all black and white: embracing the grey areas of a penguin conservation assessment

Blog written by Christina Hagen and Andrew de Blocq. Read the full paper here.

The International Union for the Conservation of Nature’s (IUCN) Red List of Threatened Species is a useful conservation tool for prioritising conservation and tracking the status of species. During a Red List assessment, a species’ extinction risk is given as one of nine categories ranging from Extinct to Least Concern. There are five criteria used to classify extinction risk which look at changes in population size or geographic range, quantitative analysis showing probability of extinction and the special cases of small populations. By far the mostly commonly used criterion examines the rate of decrease in the population over 10 years or three generations (whichever is longer).

While the criteria are quite clear-cut, the interpretation and analytical methods can differ between assessors and species. Some species are incredibly difficult to count (e.g. if they live in difficult-to-access areas or are cryptic) and this can lead to incomplete, inaccurate, or irregular population estimates. While there are different methods for filling missing data points, most consider the “true” population to follow a deterministic (without randomness) trend which is not realistic in terms of what we know about the real world.

JARA (Just Another Red List Assessment) is a new decision-support tool for assessments using the rate of population change criterion. JARA is notreally just another assessment tool, but rather one that takes uncertainty into account. Essentially, this algorithm considers the uncertainty in population estimates and plots the probability distribution of the population decline against the ICUN Red List categories. This means that a species can be classified as Endangered with 70% confidence, for instance, but with the likelihood that the assessment may have been too harsh (and should be Vulnerable) or too soft (and should be Critically Endangered). If for example, there was a 25% chance that the assessment should have been Critically Endangered, then more urgent action is needed, which may not be recognised without incorporating the uncertainty. Another useful way to use JARA is to plot these trends over time. This shows whether a species’ status is declining steadily or at an accelerating rate, stabilizing, or increasing either slowly or quickly. One can also use the JARA method on different sub-populations to see if the extinction risk differs spatially.

Penguins should normally make burrows in guano, but guano harvesting until the 1960s removed this insulating layer, forcing birds to nest on the surface, putting chicks at risk from predation and the elements. Photo: Andrew de Blocq

In our paper, we use JARA to analyse the decline in African Penguin numbers over the last 40 years. The African Penguin breeds only in South Africa and Namibia, with 32 colonies across the two countries. The colonies are clustered into three regions each separated by about 600 km: Namibia, South Africa’s Western Cape, and the Eastern Cape. Our results support the classification of this species as Endangered, with a high probability (97%). However, using the JARA framework also allowed us to deconstruct the trends over space and time, showing that the African Penguin has not decreased equally across its range nor over time. This is important as understanding the causes of the variation allows conservationists to prioritise different management strategies in each subpopulation.

The Namibian population has declined more slowly than the other regions, enough to allow it to be regionally classified as Vulnerable. However, this masks the fact that the population had decreased by over 70% prior to the start of our dataset in 1986. This is due to the collapse of the Namibian sardine stocks in the 1970s, and the species is at critically low levels compared to when fish stocks were healthy. The Namibian population also experienced an outbreak of avian influenza in 2018 which was much more lethal than a similar outbreak in the Western Cape colonies, so this again shows the importance of considering spatial differences in subpopulations when assessing risk.

The decreases in the South African population have been much more rapid over recent years. The decrease in penguin numbers has coincided with a decrease in sardine and anchovy biomass and the eastward displacement of spawning sardine and anchovy, which when combined with fishing pressure has decreased the availability of prey for penguins to the north of Cape Town. This region is changing the most rapidly, with decreases of 10% per year for the last 20 years. The Eastern Cape population, after decreases in the 2000s and late 2010s, has been relatively stable and now hosts the largest proportion of the global population.

African Penguins at the iconic Boulders Beach colony, a major tourist attraction but historically one of the smaller colonies that has remained relatively stable. Photo: Christina Hagen

The African Penguin is at serious risk as a species. However, it is also clear from our study that these declines are different for the three regional populations and that we cannot implement a one-size-fits-all conservation approach. Ongoing population monitoring is needed in Namibia to keep track of this vulnerable population. The Western Cape was traditionally seen as the stronghold for African Penguins, but with changing environmental conditions and the lack of food, the Eastern Cape has overtaken it as the new population stronghold. This mirrors the southwards and eastward shift shown by other marine species and raises the concern that the bulk of the penguin population is now on the edge of the species’ range. This should influence the priority of conservation action, especially with the colonies in Algoa Bay now facing novel threats from increased ship traffic and marine pollution related to ship-to-ship bunkering and the development of the local harbour.

The IUCN Red List is used extensively to inform scientific and conservation work, policies, and funding resource allocation. This means that assessment methods need to be as robust and transparent as possible, which includes an acknowledgement of the uncertainty that is inherent in each assessment and the breakdown of risk in space and time. The JARA method incorporates observation error (i.e. errors made during data collection or processing) and the variation that is part of any biological process.

Amid the current biodiversity crisis with many competing conservation priorities, we cannot afford for threatened species to be misclassified due to imperfect count data. We also need to make sure that conservation actions are appropriate and will address the correct threats at the correct sites and scales. JARA is a decision-support tool that can be applied to many taxa and can shed light on some of the inevitable uncertainty surrounding population trends.

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