Forecasting the temporal trend of a focal species (its range expansion or retraction) provides crucial information regarding population viability. To this end
we require the accumulation of temporal records which is time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution
across large scales (techniques such as remote sensing and geographical information systems; methods such as site-occupancy models and species niche modelling), resulting in
a spatial underpinning of current conservation planning.
It would be useful to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields
of range dynamics, occupancy scaling and spatial autocorrelation, C·I·B researcher Dr. Cang Hui devised a model for forecasting population trends solely from the
spatial distribution of a species. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in range sizes
and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a snapshot of its current
Ecologists need not wait to see the trend of a focal species; the current species distribution, its scaling pattern of occupancy per se, has already provided clues
to its future. Measuring the scaling pattern of species distribution thus provides a swift tool for assessing and forecasting the population dynamics of species. This enables the
inclusion of population trend as an indicator for species conservation status. For instance, the model suggests that the positive relationship between the change of range size and
occupancy for British butterflies could indicate the existence of an Allee-effect threshold where rare species decline and common species increase.
Two kinds of species specifically require constant monitoring and rapid assessment of their population trends: endangered species and invasive species. For instance,
historic records for well-known invasive species are often readily available, but rare for endangered species. This could mean that the model is more relevant to endangered species
than to invasive species. Besides conserving the remaining habitat and individuals for endangered species, prioritization should be given to the strategies of habitat management that
can forecast an increase of population size. In the same way, control and eradication plans for invasive species should be assessed a priori to ensure a negative population
trend for mitigating its potential impact on the recipient environment. Using this model in biodiversity conservation to forecast population trends is possible and warrants further
Read the paper:
Hui, C. (2011) Forecasting population trend from the scaling pattern of occupancy.
Ecological Modelling, 222, 442-446.
A snapshot of the spatial distribution of the population in a 40×40 cellular automaton; dark cells indicate the presence of individuals, whereas white cells
indicate the absence of individuals. By combining four adjacent cells into a bigger cell at coarser scales, we can have a spatial map for the same metapopulations at a scale of
4 times cell size than before.