Maliau insects fungi project

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Fungi and Insects: A Match Made in Heaven

Chris Anderson (Harvard University) and Pagi Toko (University of PNG)




Insects and fungi are incredibly numerous and important to any ecosystem that they inhabit. In their respective ecological domains, insects and fungi reign supreme in any meaningful measure of consequence. It should come as no surprise then that insects and fungi have evolutionarily developed symbiotic relationships. One such example are beetles belonging to the family Scolytidae ( Hulcr, Kolarik and Kirkendall, 2007) that use fungi as their food source, shelter and breeding grounds. However, general knowledge for these kinds of interactions is still unsatisfactory, despite the fact that insects and fungi make up large percentage of the living world.

It is generally accepted that tropical rainforests are the most biologically diverse areas on the planet. The latitudinal gradient in insect species richness that has been observed could be a direct function of plant diversity. It has been suggested by Erwin (1982) that insect species and host specificity on plants shows the same trend, which was however refined by Novotny (2002), who suggested that host specificity did not differ significantly between communities in tropical and in temperate forests. While much work has been done in examining insect diversity as a function of plant diversity and host specificity of insect-plant associations, much less work has been done on obligate insect and fungi associations and their implications for overall insect abundance in the world. With fungi species abundance estimates ranging from 1 million to 9.9 million, such investigations of associations could have huge implications for worldwide insect abundance estimates. Since there is such little information on insect/fungi association specificity, we have tried to see what kinds of patterns of host specificity are visible in insect and fungi associations.

Typical Fruiting Bodies


What are the patterns of host specificity in insect-fungi associations in tropical rainforests?


We expect to find comparable degrees of specialization to temperate models a la Novotny (2002, 2007).


We did our study in Maliau Basin Study Center, Sabah, East of Borneo Island. It is one of the worlds pristine mega diverse rainforest and holds some of the endemic species. We used a line transect method to collect our fungi and insects. We were interested only on the fruiting bodies of the fungi and the insects found associated with it. We ran a total of 6 transects of 10 meters length and a width of 2 meters. We walked slowly and collected all the fruiting bodies of the fungi found in the transect. We also estimated insects flying very close to the fungi. The samples were put in plastics bags and taken back to study center. We used hand-lenses to see insects and identified them down to family level. . We also couldn't identify the fungi so we gave morpho-species.


All analysis was performed by using the statistical analysis platform R. In particular, we made great use of the bipartite package ^1. The bipartite package was originally created for analyzing degrees of specialization in pollinator/host-plant interaction webs, but we felt that the insect/host-fungi model was close enough that any data analyzed using bipartite functions would produce valid results.

The main function that we used for our analysis was H2fun, which calculates a single, weighted connectance value (H2) based on the frequencies that certain insects are found on host-fungi. The H2 value is an integer from 0-1, where a value closer to 0 means that an interaction web is more generalized and a value closer to 1 means that the web is more specialized.

We also calculated a simple connectance (C) value by dividing all observed interactions by all possible interactions. C is easily calculated from an interaction matrix (table1) by dividing the total number of non-zero values (I) by the number of rows (r) multiplied by the number of columns (c). C=I/(r.c)

Results & Discussion

Our analysis of the observed interaction web (table1) yielded a C value of .54 and an H2 value of .2919722. The discrepancy between the C and H2 values is especially interesting. Taken at face value, the C value suggests that this system is moderately to very generalized. The H2 value still suggests a generalized system of interactions, but it is less pronounced that the C value. This is because, even though virtually all of the insect families were observed interacting with several different fungi morphotypes, most showed a clear preference for only one or two morphotypes based on the relative frequencies that they were observed on each fruiting body. This interpretation is corroborated by figure 1. which shows a graphical representation of this interaction web. The thickness of each line is proportional to the strength of the interaction. As can be seen in the figure, lepismatids and poduromorphids show a clear preference for morphotypes 0 and 7 respectively.
Table 1
Figure 1

The calculated H2 value of .29 is similar to an H2 value (.24) that was calculated in a study of a temperate pollination system in Britain. As might be expected, this H2 value is much lower than a similar pollination system that was studied in Argentina (H2=.63). When our H2 value is compared to these two similar systems, we find a pattern that is consistent with Novotony's findings that there are similar levels of host specialization in tropical and temperate systems. This is an interesting finding because it has major implications for worldwide insect species richness estimates. Further study is needed to fully flesh out the levels of host specificity present in tropical insect/fungi interaction systems.

Despite the exciting implications of this study it is important to note several caveats that should color any interpretations drawn from this study. First and foremost, the authors feel that there is are no satisfactory statistical null model generators that have been developed for insect fungi interaction matrices. There are several generators for modeling insect pollinators and plant interaction matrices, and the similarities between these two systems is close enough to fudge it, but the fact still remains that a pollinator interactions are significantly different from an insect that spends its entire larval stage in the fruiting body of a fungi (for example). The former is an ephemeral interaction whereas the latter is much more substantial. The largest consequence of poor null model generators on this study was the authors' inability to carry out a Monte-Carlo null model comparison. Without a significant number of null models with which to compare the test matrix to, no truly meaningful conclusions can be drawn from the test matrix about the overall specificity of the system. Finally, in order to comply with time constraints, there is a marked lack of sampling rigor in this study. Six 10m transects is simply not enough of a sample size to really say anything meaningful about ecological processes.

With the above caveats in mind, there are two key improvements that a future study could make. First and foremost, better statistical analyses, as discussed above, should be a high priority to those wishing to replicate this study. The authors suggest the creation of specific null model generators that take into account geographic closeness as well as phylogenetic similarities in the host-fungi. Secondly, a future study should sample much more and in more varied habitats in order to get a true feel for the levels of specificity present in these systems.

Despite these problems, this study should still be seen as an intriguing pilot study into rainforest insect/fungi ecology. This is a vastly under researched area and there is still much to be discovered. There are literally millions of species of both fungi and insects worldwide, which allows for the possibility of millions of interactions. Since these organisms account for such a large amount of worldwide biomass and are incredibly important to ecosystems we would be remiss if we, as scientists, continued to ignore the research opportunities presented.


Dormann, C.F., Fr"und, J., Bl"uthgen, N. & Gruber B. 2009. Indices, graphs and null models: analyzing bipartite ecological networks. The Open Ecology Journal, 2, 7-24.

Dormann, C.F., Gruber B. & Fr"und, J. (2008). Introducing the bipartite Package: Analysing Ecological Networks. R news Vol 8/2, 8 - 11.

Erwin, T. L.(1982) 'Tropical forests: their richness in Coleoptera and other species'. Coleopterist’s Bull. 36,74–75.

Hulcr. J, Kolarik. M and Kirkendall. L (2007), 'A new record of fungus-beetle symbiosis in Scolytodes bark beetles (Scolytinae, Curculionidae, Coleoptera)', SYMBIOSIS 43

Novotny, V., Basset, Y., Miller, S.E., Weiblen, G.D., Bremer, B., Cizek, L., Drozd, P.(2002), 'Low host specificity of herbivorous insects in a tropical forest'. Nature 416, 841-843.

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