Modeling of populations in biodiversity management

In our attempts to correct the damage caused by ourselves, humans, population management of species is becoming increasingly important as a professional discipline in our society. Whether for conservation work of species and ecosystems or for controlling invasive species, gathering population data, modelling populations, and making future predictions is essential.

Population Management: What is it and why is it necessary?

As is well known, due to the impact caused by the spread and growth of human populations in recent centuries, many ecosystems have been negatively affected. Much of the change that has taken place in this regard is somehow linked to the population dynamics of one or more animal species.

Species extinction, or at first, the decline in their populations, often stems from damage inflicted on the ecosystem they are part of. A clear example of this is the degradation and fragmentation of habitats of many species, which happens after large-scale logging for monoculture plantations. However, the population decline of certain species and, in general, the loss of biodiversity, pose an added problem for the often already degraded ecosystems they inhabit, as they lead to further imbalance. Partially frugivorous species like large macaws, for example, are negatively affected by deforestation, which deprives them of the nesting sites they need to reproduce. In such cases, their populations are reduced, which in turn deprives the ecosystem of their role as seed dispersers, ultimately impacting any potential ecosystem recovery that could take place.

The placement of artificial nests is a strategy to mitigate the devastating effects that deforestation has had on macaw populations across much of their range. - Photograph by Noelia Sánchez.

On the other hand, the opposite case can also occur. Throughout history, humans have introduced species into geographic regions where they do not naturally belong, as is the case with many mammal species in New Zealand (rats, cats, mustelids…), or parrots of various types around the world (a particularly adaptable example is the monk parakeet, Myiopsitta monachus). In these cases, we encounter populations that, due to the lack of predators or other ecosystem functions that regulate their populations, can grow at rapid speeds, potentially putting local species at risk and, consequently, threatening the entire ecosystem.

In either of these situations, human intervention can help in several ways to restore the balance of the ecosystem (which we ourselves have contributed to disrupting), working to regulate (either positively or negatively) the population of a particular species. In ecology, a population is defined as a group of individuals of the same species living in a specific area and at a particular time.

The Argentine parakeet is an invasive species in Spain; however, population management efforts began to be implemented late (more than 30 years after its introduction), locally and in a disorganized manner, resulting in no progress on population control. Not to mention the ethical implications of how the issue has been handled on many occasions, but that’s another topic. - Original photograph.

What are models and how can they help us in population management?

Broadly speaking, a model can be defined as a representation that describes and can predict how a population changes, and therefore the variables that make it up, over time. The more a model reflects what truly happens in the population it is meant to represent, the more reliable the predictions it can generate will be. The goal of any professional working in population modelling is, therefore, to create models that best represent the reality of what is happening in the ecosystem. This also involves having accurate field data about the population in question and/or the individuals that make it up.

To create a model, data obtained from previous research (such as individual survival rates, growth rates, carrying capacity, etc.) are used. By applying these data through a series of logical or mathematical operations that represent what happens with the population being studied, the model is obtained. Once developed, models can provide us with the population dynamics simply by entering a series of variables, such as the initial population size, the rate of loss of a key resource in its habitat, and so on. Although, of course, models can deliver erroneous results (due to being based on inaccurate or biased information, or simply misinterpreting how the "system" works), their utility lies not only in predicting the future—which they also do—but in predicting alternative futures. This, which sounds like science fiction, actually means that we can model different future scenarios, each of which implements a different population management strategy.

Prediction of the population size evolution over time following different efforts applying an monk parakeet birth control strategy consisting of egg poking. - Original creation.

One model I worked on a couple of years ago aimed to represent the population dynamics of monk parakeets (Myiopsitta monachus) in a municipality in the pre-litoral region of Barcelona (and the potential effects of different control strategies). This municipality planned to carry out a series of actions to reduce the parakeet population in the town. I developed a mathematical model representing the population growth of parakeets over time, using census data from other locations in Catalonia, which presumably could apply to this municipality, following an exponential growth structure. From there, the effect of different population management strategies was modeled according to data obtained from scientific literature, such as birth and mortality rates, among others. This allowed us to estimate how the population would evolve in different scenarios and compare it to what would happen if no population control measures were taken. In this case, it was an aggregated or mathematical model, which treats the entire population as a homogeneous mass, without delving into details about each individual. These models use averages and overall rates to describe the population's behavior, instead of using variables that refer to the individual organisms within it.

Interface and display of the program in operation. - Original creation.

On the other hand, there are models that, instead of treating the population as a uniform block, simulate the dynamics of each individual separately. This means that they take into account each organism’s behavior individually, considering factors such as age, sex, health status, or even location. Individual-Based Models (IBMs), although harder to develop accurately, are especially useful when we want to capture complex ecological processes whose dynamics depend heavily on individual interactions. In my last year at university, I developed such a model to represent the dynamics of a macaw population in a deforesting tropical forest, as well as the effect of installing artificial nests as a conservation strategy for the species. As you can see, models are incredibly useful tools for predicting what might happen in the future of an ecosystem, and in population management, they help us determine the best strategy to take—not just in technical or purely ecological terms, but also in terms of resource management (human, economic, etc.), whether it be in public or private funding projects.

Example of a simulation that represents not only the effect of deforestation on the macaw population, but also the effect of placing artificial nests as a conservation strategy. - Original creation.

I hope this blog post has been interesting and helped you better understand how population management works in the field of ecology and conservation. As always, feel free to leave your comments, questions, or suggestions in the section below. See you in the next post!

Roger Valls Martínez