Individual traits are often assumed to be linked in a straightforward manner to plant performance and processes such as population growth, competition and community dynamics. However, because no trait functions in isolation in an organism, the effect of any one trait is likely to be at least somewhat contingent on other trait values. Thus, to the extent that the suite of trait values differs among species, the magnitude and even direction of correlation between values of any particular trait and performance is likely to differ among species. Working with a group of clonal plant species, we assessed the degree of this contingency and therefore the extent to which the assumption of simple and general linkages between traits and performance is valid. To do this, we parameterized a highly calibrated, spatially explicit, individual-based model of clonal plant population dynamics and then manipulated one trait at a time in the context of realistic values of other traits for each species. The model includes traits describing growth, resource allocation, response to competition, as well as architectural traits that determine spatial spread. The model was parameterized from a short-term (3 month) experiment and then validated with a separate, longer term (two year) experiment for six clonal wetland sedges, Carex lasiocarpa, Carex sterilis, Carex stricta, Cladium mariscoides, Scirpus acutus and Scirpus americanus . These plants all co-occur in fens in southeastern Michigan and represent a spectrum of clonal growth forms from strong clumpers to runners with long rhizomes.Varying growth, allocation and competition traits produced the largest and most uniform responses in population growth among species, while variation in architectural traits produced responses that were smaller and more variable among species. This is likely due to the fact that growth and competition traits directly affect mean ramet size and number of ramets, which are direct components of population biomass. In contrast, architectural and allocation traits determine spatial distribution of biomass; in the long run, this also affects population size, but its net effect is more likely to be mediated by other traits. Such differences in how traits affect plant performance are likely to have implications for interspecific interactions and community structure, as well as on the interpretation and usefulness of single trait optimality models.Species traits are general, genetically determined characteristics of morphology and physiology. Such traits are often used in ecology to group species; these groups are then used to explain and predict community structure and dynamics (Grime et al.
Abstract. Spatial models predict that long-distance dispersal of offspring provides competitive superiority in open environments. We tested this prediction by artificially aggregating ramets of the spreading clonal species Agrostis stolonifera in an undisturbed environment and in an environment where flooding increased open space. We compared the competitive response of this manipulated Agrostis with both the natural ramet distribution of Agrostis and with the naturally aggregated clonal species Alopecurus pratensis.Our phenotypic manipulation of ramet dispersal significantly increased aggregation of clonal offspring, without altering the number of offspring, and thus provided an adequate test of spatial effects. Regardless of flooding, both Alopecurus and the aggregated Agrostis were more suppressed in species mixtures than the natural dispersed form of Agrostis. This demonstrates that long distance dispersal of ramets enhances competitive ability, at least in early stages of succession.
Physiological integration and foraging behavior have both been proposed as advantages for clonal growth in heterogeneous environments. We tested three predictions concerning their short-and long-term effects on the growth of the clonal perennial sedge Schoenoplectus pungens (Pers.) Volk. ex Schinz and R. Keller:(1) growth would be greatest for clones with connected rhizomes and on heterogeneous soil, (2) clones would preferentially place biomass in the nutrient-rich patches of a spatially heterogeneous environment, and (3) physiological integration would decrease a clone's ability to forage. We tested our predictions by growing S. pungens clones for 2 years in an experimental garden with two severing treatments (connected and severed rhizomes) crossed with two soil treatments (homogeneous and heterogeneous nutrient distribution). Severing treatments were only carried out in the first year. As predicted, severing significantly decreased total biomass and per capita growth rate in year one and individual ramet biomass both in year one and the year after severing stopped. This reduction in growth was most likely caused by severing damage, because the total biomass and growth rate in severed treatments did not vary with soil heterogeneity. Contrary to our prediction, total biomass and number of ramets were highest on homogeneous soil at the end of year two, regardless of severing treatment, possibly because ramets in heterogeneous treatments were initially planted in a nutrient-poor patch. Finally, as predicted, S. pungens concentrated ramets in the nutrient-rich patches of the heterogeneous soil treatment. This foraging behavior seemed enhanced by physiological integration in the first year, but any possible enhancement disappeared the year after severing stopped. It seems that over time, individual ramets become independent, and parent ramets respond independently to the conditions of their local microsite when producing offspring, a life-history pattern that may be the rule for clonal species with the spreading ''guerrilla'' growth form.
Although clonal plants comprise most of the biomass of several widespread ecosystems, including many grasslands, wetlands, and tundra, our understanding of the effects of clonal attributes on community patterns and processes is weak. Here we present the conceptual basis for experiments focused on manipulating clonal attributes in a community context to determine how clonal characteristics affect interactions among plants at both the individual and community levels. All treatments are replicated at low and high density in a community density series to compare plant responses in environments of different competitive intensity. We examine clonal integration, the sharing of resources among ramets, by severing ramets from one another and comparing their response to ramets with intact connections. Ramet aggregation, the spacing of ramets relative to each other, is investigated by comparing species that differ in their natural aggregation (either clumped growth forms, with ramets tightly packed together, or runner growth forms, with ramets loosely spread) and by planting individual ramets of all species evenly spaced throughout a mesocosm. We illustrate how to test predictions to examine the influence of these two clonal traits on competitive interactions at the individual and community levels. To evaluate the effect of clonal integration on competition, we test two predictions: at the individual level, species with greater clonal integration will be better individual-level competitors, and at the community level, competition will cause a greater change in community composition when ramets are integrated (connected) than when they are not. For aggregation we test at the individual level: clumped growth forms are better competitors than runner growth forms because of their ability to resist invasion, and at the community level: competition will have a greater effect on community structure when ramets are evenly planted. An additional prediction connects the individual-and community-level effects of competition: resistance ability better predicts the effects of competition on relative abundance in a community than does invasion ability. We discuss additional experimental design considerations as revealed by our ongoing studies. Examining how clonal attributes affect both the individual-and community-level effects of competition requires new methods and metrics such as those presented here, and is vital to understanding the role of clonality in community structure of many ecosystems.
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