State Spaces and the wide open spaces

Speaker: Peter Caley (Data61, CSIRO)

Topic: Some issues of inference in abundance trends for wide-ranging wildlife species

Abstract:
Highly mobile species that form aggregations can present special challenges for inferring trends in abundance where aggregations are spatially sparse, highly localised and sometimes transient in nature. Drawing from Australian examples of waterbirds, flying foxes and cockatoos, this talk explores how practitioners have grappled with some of these issues, and appeals to the statistical brains trust to get involved.

Biography:
Peter Caley is a research scientist with CSIRO Data61. He has a background in applying quantitative methods for addressing contemporary problems in the environmental sciences. Topics have included wildlife & human disease epidemiology, vertebrate pest ecology & management, plant & insect biosecurity and extinction inference.

In the lead up to the next Australian Statistics Conference (ASC2018, Melbourne 26-29 August) I have been refreshing my reading around surveys, state spaces and inference. Peter Caley has been using a state space approach to measure rates of decline or growth of populations of wild water birds within the Murray Darling and Lake Eyre catchments based on 30 years of random transect surveying. The thirty years has been punctuated by two major flooding events – early 70s and 80s so the challenge is to filter out a message on the ecological health of inland Australia from expert observations within a fixed collection design – effectively repeated surveys. As birds move readily in response to climate variation, and do not necessarily stay within one catchment there is much scope for leakage, but there has been some success in devising robust inference, using the strengths of this ‘observational experimental’ scheme – namely ability to split numbers by species, with separate counts for 50 or so water birds encountered; consistent method of collection (single wing small planes able to fly along transects at a low altitude; and now accumulated 30 years data series split between two comparable regions with contrasting climate histories. His conclusions were phrased in terms of the individual species – whether or not they were in decline – and after SS correction could say that there was not a case for ‘steep decline’ across the board, and while it is possible to rank species on vulnerability to decline, on the whole most species were holding their own. I wonder if it may be possible to robustify this commentary further by using a multivariate filter and a new diversity index. This may be a better measure: if species presence was weighted as much as breeding numbers. Routine or cyclic Environmental changes will advantage some species at the expense of others; long term trends connected with global phenomena can affect all species adversely both in numbers and support for diversity, with most vulnerable disappearing first. A further opening may be in counting ‘roosts’ that is congregations of birds using a water resource for feeding, breeding, refuge or lay over. Roost numbers may be detectable at a distance even remotely; or by on site observation without disturbing the birds for the purpose of counting. Roost behaviour may be easier to monitor over time, and there may be a way of enduring identification.

Peter’s talk included the fate of the white necked ibis – ubiquitous in the cities as bin scavengers. I have heard a talk on its cousin, the strawnecked ibis of the plains, where radio tracking of individual birds demonstrated how widely they move and their ability to find their way to surface water over long distances. It is also apparent that flocks and individuals give different profiles. This dynamic structure to the populations of free moving creatures is interesting in itself, and would inform any design; it can interfere with inference in a common design like Caley’s but may also be a useful correlate for the overall diversity question. Noone pretends that the system is easily abstracted, making a state space a good choice for inference model.

It strikes me that there is much to be gained by working in step with the scientists monitoring the health of our natural systems subject to global climate challenge. This can only increase confidence in what we are attempting to sustain.