Testing the assumptions of the pyrodiversity begets biodiversity hypothesis for termites in semi-arid Australia

Abstract

Fire shapes the composition and functioning of ecosystems globally. In many regions, fire is actively managed to create diverse patch mosaics of fire-ages under the assumption that a diversity of post-fire-age classes will provide a greater variety of habitats, thereby enabling species with differing habitat requirements to coexist, and enhancing species diversity (the pyrodiversity begets biodiversity hypothesis). However, studies provide mixed support for this hypothesis. Here, using termite communities in a semi-arid region of southeast Australia, we test four key assumptions of the pyrodiversity begets biodiversity hypothesis (i) that fire shapes vegetation structure over sufficient time frames to influence species' occurrence, (ii) that animal species are linked to resources that are themselves shaped by fire and that peak at different times since fire, (iii) that species' probability of occurrence or abundance peaks at varying times since fire and (iv) that providing a diversity of fire-ages increases species diversity at the landscape scale. Termite species and habitat elements were sampled in 100 sites across a range of fire-ages, nested within 20 landscapes chosen to represent a gradient of low to high pyrodiversity. We used regression modelling to explore relationships between termites, habitat and fire. Fire affected two habitat elements (coarse woody debris and the cover of woody vegetation) that were associated with the probability of occurrence of three termite species and overall species richness, thus supporting the first two assumptions of the pyrodiversity hypothesis. However, this did not result in those species or species richness being affected by fire history per se. Consequently, landscapes with a low diversity of fire histories had similar numbers of termite species as landscapes with high pyrodiversity. Our work suggests that encouraging a diversity of fire-ages for enhancing termite species richness in this study region is not necessary.

Keywords: fire ecology; fire management; invertebrates; landscape heterogeneity; mallee; pyrodiversity.

Figure 1.

Illustration of the assumptions underlying the pyrodiversity begets biodiversity hypothesis. (a) The first assumption is that fire is a strong driver of vegetation succession such that vegetation changes with time-since-fire. (b) The second assumption is that animal species are tightly related to particular habitat features that change along the time-since-fire continuum. (c) The third assumption is that the strong relationship between animal species and fire-affected habitat features results in species displaying relationships with time-since-fire that vary based on the changes in their preferred habitat feature, peaking in their abundance or probability of occurrence when the habitat feature is most abundant. (d) A series of fire mosaics that differ in their ‘pyrodiversity’, from landscapes composed of a single fire-age to landscape composed of five fire-ages. Different colours represent different fire-age classes that are suitable for different species: black = 0–5 years post-fire, blue = 10–15 years post-fire, red = 20–30 years post-fire, grey = 30–40 years post-fire, yellow = 40–50 years post-fire.

Figure 2.

The Big Desert study region in northeastern Victoria, Australia. Open black circles represent the 20 study landscapes positioned across the region. Five sampling sites were clustered within each of the 20 study landscapes (n = 100 sites), represented by solid black circles in the magnified landscape. The hatched and white areas in the magnified landscape represent the different fire-age classes present.

Figure 3.

The responses of habitat resources to time-since-fire across a 56-year chronosequence within the three dominant vegetation communities in the Big Desert study region. The predicted response curves are represented by the black lines, and the 95% confidence intervals are represented by green for dunefield heath, brown for mallee and orange for sandstone ridge shrubland. Coarse woody debris is measured as volume (cubic centimetres); while woody vegetation cover and leaf litter cover are proportional cover values. Only habitat resources with a significant relationship with either time-since-fire or vegetation type are shown.

Figure 4.

Regression coefficients, indicated in black circles, and associated 85% confidence intervals for GLMMs of termite species occurrence and species richness. Associated habitat predictor variables are considered important if the 85% confidence interval does not overlap zero (red circles). Confidence intervals above the zero line indicate a positive influence, while those below the zero line indicate a negative influence.

Figure 5.

Regression coefficients, indicated in black circles, and associated 85% confidence intervals for GLMs of termite species occurrence and species richness. Associated habitat predictor variables are considered important if the 85% confidence interval does not overlap zero (red circles). Non-overlapping confidence intervals above the zero line indicate a positive influence, while those below the zero line indicate a negative influence. An asterisk indicates the variable was log-transformed.

Figure 6.

The relationship between termite richness and pyrodiversity (Shannon's diversity of fire-age classes) at the landscape scale in semi-arid southern Australia.