|Title||Comparing Litterfall and Standing Vegetation: Assessing the Footprint of Litterfall Traps, Tropical Forests, Dr. Padmini Sudarshana|
|Publication Type||Book Chapter|
|Year of Publication||2012|
|Authors||Marcela Zalamea, Grizelle González, Gould, WA|
Litterfall traps could preferentially represent certain kinds of leaf litter. Several factors may cause bias while sampling litterfall leading to over- or under-representation of the species present in the surrounding vegetation. For example, species standing precisely above litterfall traps, having big and wide crowns, and/or with high leaf fall rate may be over-represented in litterfall samples. Additionally, species standing upslope or in the windward side of litterfall traps may be more likely to be collected in litterfall traps (Staelens et al., 2003). Conversely, species with big and/or heavy leaves or fronds such as palms or species from the Cecropia and Heliconia genera may be under-represented in litterfall traps (Clark et al., 2001). However, the few studies dealing with patterns of litterfall dispersal and collection have found contradictory results. For example, in Australian rainforests Lowman (1988) found that collected litterfall was not necessarily biased toward leaves coming from trees located precisely above traps. Similarly, in a dry forest in Costa Rica, Burnham (1997) found a low spatial correspondence between location of source stems and litterfall samples. In contrast, for a temperate mixed forest in northeastern Japan, Hirabuki (1991) found that estimated patterns of litterfall spatial distribution corresponded to the distribution of stems in the studied plot. In this chapter we report results from a study that takes advantage of an ongoing experiment in the Luquillo Experimental Forest, Puerto Rico, to examine the correspondence between litterfall samples and standing vegetation. Such correspondence was analyzed at three different spatial scales defined by the sampling units already in place: forest stand (106 m2), sampling blocks (4x104 m2), and plots (4x102 m2). Our first objective was to examine which factors, in addition to relative abundance of species in the vegetation, could affect the relative abundance of species in litterfall samples. Specifically, we evaluated the effect of tree size (measured as height and crown area), leaf size (measured as leaf area), and distance to litter traps using a stepwise regression procedure. We hypothesized that bigger trees (i.e., having high height and crown area) would produce more leaf litter and therefore would tend to occur more abundantly in litterfall samples; while trees with relatively big leaves would be in general under-estimated in litterfall samples because traps would fail to catch those leaves. Finally, if traps were capturing leaves from trees standing precisely above, then trees being closer to litter traps would tend to present higher relative abundances in litterfall samples. Additionally, we analyzed the similarity between litterfall and particular sub-sets of the whole vegetation community. Sub-sets were defined by tree height, crown area, and distance to traps, such that if litter traps were preferentially collecting leaves from any particular sub-set of the vegetation (e.g., bias toward either canopy or understory trees, wide-crowned trees, or trees located closer to traps), those sub-sets should bear a higher compositional similarity with the litterfall samples than the whole vegetation community. The particular experimental set up used in this study (cf., Fig. 1), allowed us also to ask if litter traps located in the center of vegetation plots (i.e., surrounding plots. See Fig. 1) provided more representative samples of the surrounding vegetation than traps located adjacent to vegetation plots (i.e., adjacent plots. See Fig. 1). To address this second objective, we compared the composition and relative abundance of species collected in litter traps with the same parameters of the vegetation from the surrounding and adjacent plots (Fig. 1), using similarity indexes and parametric and non-parametric correlations. We hypothesized that if litter traps were collecting litterfall coming from all directions with the same likelihood, a higher similarity between litterfall samples and vegetation would be found for surrounding than for adjacent plots, both for the scale of the forest as for the scale of individual plots and for particular species. Finally, our third objective was to gain insights for the scaling of litterfall data from the level of sampling plots up to the level of the forest stand. We addressed this by comparing the similarity between vegetation and litterfall across the three different scales mentioned before (i.e., plots, blocks and the forest stand; cf. Fig. 1) using similarity indexes, correlations, multivariate ordinations, and Mantel tests. An important aspect when examining the correspondence between litterfall and vegetation across different spatial scales is related to whether litter traps are capturing leaves from a wide range or only from the near vicinity around traps. On one hand, considering the potential far-ranged and random patterns of leaf dispersal (Jonard et al., 2006), a high compositional similarity between litterfall and vegetation at the scale of the forest type together with a low similarity at the smaller scales of sampling units might be expected. On the other hand, if litter traps are collecting leaf litter mainly from the vegetation in the near vicinity (for example, 10 m around traps), a high similarity between litterfall and vegetation at the scale of sampling units should be encountered as well. Particularly, the following outcomes could be expected: 1) high correlation between litterfall and vegetation dissimilarity matrices calculated for the smallest sampling units (i.e., plots), namely, pairs of plots with high dissimilarity in their vegetation should be also highly dissimilar in their litterfall; 2) litterfall and vegetation samples from the same plots should cluster together in an ordination space accurately representing compositional distances among sampling units; and 3) strong correlation between similarity among pairs of litterfall samples and the physical distance separating those samples (i.e., distance among plots), namely, the more distant the plots were located, the higher the dissimilarity between them would be. Litterfall collection using litter traps has become a ubiquitous method in terrestrial ecology. Thus it is important to understand the relevant variables behind the method and the implications of its limitations. We believe our findings will prove instrumental for the improvement of methods in terrestrial and forest ecology especially in the tropics were the high species diversity and structural complexity of forests impose tough challenges to the study of forest structure and dynamics.