An analysis of epiphytic lichen communities in Tasmanian cool temperate rainforest

Abstract

A three-dimensional compositional pattern in the epiphytic lichen vegetation in Tasmanian cool temperate rainforest is demonstrated using the robust ordination technique, hybrid multidimensional scaling (HMDS). The first two dimensions are correlated with the age of the host tree (and the concomitant change in bark texture) and wetness of the substrate. No measured environmental variable is related to the third dimension, which is tentatively attributed to a gradient in the constancy of the microclimate. Pattems of richness of lichen growth forms and the cover of bryophytes are correlated with the three putative environmental gradients. Possible successional trends between 12 community groups derived by numerical classification are described with respect to changes in substrate age, wetness and microclimatic constancy. Temporal variation of these factors due to tree growth, together with the slow establishment and long persistence of some lichen species, make succession in epiphytic communities very complex. This study demonstrates the value of HMDS in identifying compositional patterns and generating hypotheses about the causal ecological factors. The existence of the postulated microclimatic constancy gradient was not appreciated before the analysis and its discovery illustrates the risk of relying on constrained ordination methods, such as canonical correspondence analysis.

Assessing ecological responses to catastrophic amphibian declines: Patterns of macroinvertebrate production and food web structure in upland Panamanian streams

“…As with production estimates, we tested for significance at a 5 0.10. We performed vector fitting (Faith and Norris 1989;Kantvilas and Minchin 1989) to examine correlations between macroinvertebrate community composition and the following potential explanatory variables: amphibian (pre-decline 5 1, post-decline 5 0); amounts of CPOM, FPOM, VFPOM, and total BOM (monthly standing stock values); and net primary production (NPP). We used the DECODA software package (Minchin 1989) for ordination, ANOSIM, and vector fitting procedures.…”

Austral lichenology: 1690–2008

“…Since the early 1980s Tasmanian lichens have been the fruitful province of Gintaras Kantvilas, who has made a productive and sustained contribution to our understanding of the lichen mycobiota of that region (Kantvilas 1983(Kantvilas , 1987(Kantvilas , 1988a(Kantvilas -c, 1989a(Kantvilas ,b, 1990a(Kantvilas -c, 1991(Kantvilas , 1992a(Kantvilas ,b, 1993(Kantvilas , 1994a(Kantvilas -d, 1995(Kantvilas , 1996a(Kantvilas -c, 1998a(Kantvilas ,b, 1999(Kantvilas , 2000a(Kantvilas ,b, 2001(Kantvilas , 2002a(Kantvilas ,b, 2004a(Kantvilas -m, 2006a(Kantvilas ,b, 2008aHenssen & Kantvilas 1985Kantvilas et al 1985Petersen & Kantvilas 1986;Kantvilas & Elix 1987Kantvilas & James 1987Kantvilas & Jarman 1988Kantvilas & Vězda 1988Kantvilas & Minchin 1989;Ratkowksy et al 1989;Kantvilas & Seppelt 1992Kantvilas & wedin 1992;McCarthy & Kantvilas 1993a,b, 1997Kantvilas & Thor 1993;Pusswald et al 1994;Kantvilas & Coppins 1997;Kantvilas & Jørgensen 1998;Coppins & Kantvilas 2001;Kantvilas & Louwhoff 2004Printzen & Kantvilas 2004).…”

Population Differences in Host Immune Factors May Influence Survival of Gunnison’s Prairie Dogs (Cynomys gunnisoni) during Plague Outbreaks

“…We set up 100 runs with random starting configurations, up to 250 iterations per run, and a stability criterion of 0.0001. We used the best NMDS solution in a vectorfitting procedure (Kantvilas and Minchin, 1989) with up to 10,000 unique random permutations to determine the maximum correlation (R max ) of each biomarker to the final NMDS ordination in DECODA.…”