Current research focus
How do we manage environmental systems effectively in the context of imperfect information about system states and dynamics, and a changing climate that is dramatically altering many ecosystems and biophysical processes?
The rapid increase in the human population in recent decades, which at 7.6 billion has doubled since 1970, has profoundly impacted many natural systems. We are in the midst of a sixth great extinction event: rates of extinction are currently more than 100 times greater than background rates (Cabellos et al. 2015 Sci. Adv.).
Even under optimistic IPCC climate projections (RCP2.6), severe climate impacts are expected for the remainder of this century. Coupled with further increases in human population (10 billion people by 2060) and the associated increase in demand for energy, food and natural resources, further increases in impacts on natural systems are expected that will also diminish the services we derive from those systems: agricultural production, foresty, fisheries, hydrological processes, etc.
Hence, environmental management is one of the most pressing, urgent problems of our time. Our actions in the coming decades have far-reaching implications for future states of natural systems, such as how much biodiversity persists.
My work addresses a key knowledge gap: how do we use best-available scientific knowledge to better manage environmental systems? There are three key focuses to my work:
(i) How do we account for uncertainty arising from climate change in decision-making processes, thereby making those decisions more robust to future change?
(ii) How do use best available scientific knowledge to inform decision-making? Much scientific knowledge has low external validity: the generality of the knowledge has not been established, nor how document effects are modified in the context of complex systems. Hence, there is an urgent need to develop better approaches to quantitative, evidence-based decision support.
(iii) What are the processes that govern natural systems and how are those processes likely to change in the future?
I am currently developing these ideas within the following applied problems:
Coral reef conservation planning in the context of climate change
Many corals live in water temperatures that are close to the limits of their fundamental niche. They are, therefore, highly sensitive to temperature increases and may be some of the first ecosystems to be almost completely lost to climate change impacts. For example. it is projected that 90% of corals could be lost by 2050 (Hoegh-Guldberg et al 2017), and in the last two years approximately two-thirds of the Great Barrier Reef has bleached. My work addresses the problem of where to invest resources in coral reef conservation in the context of long-term exposure to key climate-related threatening processes (thermal stress events and cyclones).
Forest restoration planning in Brazil
Brazil is poised to embark on one of the largest forest restoration projects in the world as over 52 million ha of forest will be restored in the Atlantic Forest. The legislative framework that makes this possible the the Forest Code, which prescribes minimum forest cover requirements on private lands. Enforcement of this legislation is currently underway. I am collaborating with a leading NGO (the International Institute for Sustainability) in Rio de Janeiro to develop a market for offset trading that will maximise carbon and biodiversity benefits arising from offsets. Our work also examines the potential for restoration requirements to be met cost effectively using natural regeneration.
Fire management in Australia
Bushfire is a major threat in Australia, resulting in loss of life, assets, ecosystem services, and biodiversity, as well as releasing many megatonnes of carbon into the atmosphere, and increasing soil erosion and sedimentation of waterways. The total cost of fire in Australia is estimated to be around $12 billion p.a., or 1.3% of GDP (Ashe et al 2009), with direct taxpayer funded fire service costing approximately $3.9 billion p.a. (Productivity Commission 2017). Furthermore, climate change will affect fire regimes in Australia, resulting in more frequent, intense and larger fires in many areas (Williams et al 2009). Management of landscapes to reduce the impacts of fire on communities and the natural environment is a complex, costly, and urgent problem.
In collaboration with Prof. Kerrie Wilson (Centre of Excellence for Environmental Decisions, UQ) and the South-east Queensland Fire and Biodviersity Consortium we have been developing a decision support framework for prescribed fire planning to find good-compromise solutions that maximise asset protection and biodiversity benefits (Williams et al 2017). We are now scaling up this framework to include other local government authorities and more mechanistic models of fire hazard.
The role of disease in koala population dynamics
Koala populations in Queensland have declined over the last century as a result of habitat loss (land clearing for agricultre and human settlements), hunting (in the early 20th century), vehicle collisions, dog attacks and disease (Rhodes et al 2011, 2016). Of these effects, disease management is one of the most important opportunities for koala conservation. While it is costly, time-consuming and politically difficult to restore habitat or reduce road deaths, vaccination may provide a cost-effective strategy for controlling disease and greatly improving the rate of koala population growth (Beyer et al, in review; Tisdell et al. 2017).
Of particular concern is Chlamydia which is prevalent among koalas and can cause permanent infertility in females. From the perspective of population dynamics infertility is equivalent to death in the sense that these animals contribute nothing to population recruitment. Managing chlamydial infection can substantially increase recruitment, thereby compensating for the other detrimental impacts on koala populations (Beyer et al. in review).
This work aims to quantify the spatial distribution of koalas in Queensland, the prevalence of disease in these populations, the consequences of vaccination on population dynamics, and optimal strategies for allocating vaccine in the population. It is an example of how quantitative, mechanistic models can usefully inform decisions about the management of wildlife populations.
Development of tools to facilitate better spatial planning
In pursuit of the aforementioned goals I have developed a number of approaches to improving the way that we frame and solve spatial planning problems. Linear programming is a particularly powerful mathematical framework for spatial planning as it is flexible, but can identify exact (optimal) solutions to large problems. Since publishing my initial general paper on the application of linear programming to conservation planning (Beyer et al 2016) I have worked with students and collaborators to apply these techniques to several other problems: mangrove conservation (Runting et al. 2016), zoning for shorebird protection (Stigner et al 2016), fire management in Queensland (Williams et al., 2017), linear infrastructure planning (Bunton et al. 2015), migrant bird conservation planning (Traurig et al., in prep), and forest restoration planning in the Atlantic Forest (Strassburg et al., in prep).