Understanding strategies for seed dispersal by wind under contrasting atmospheric conditions

Abstract

Traits associated with seed dispersal vary tremendously among sympatric wind-dispersed plants. We used two contrasting tropical tree species, seed traps, micrometeorology, and a mechanistic model to evaluate how variation in four key traits affects seed dispersal by wind. The conceptual framework of movement ecology, wherein external factors (wind) interact with internal factors (plant traits) that enable movement and determine when and where movement occurs, fully captures the variable inputs and outputs of wind dispersal models and informs their interpretation. We used model calculations to evaluate the spatial pattern of dispersed seeds for the 16 factorial combinations of four traits. The study species differed dramatically in traits related to the timing of seed release, and a strong species by season interaction affected most aspects of the spatial pattern of dispersed seeds. A rich interplay among plant traits and seasonal differences in atmospheric conditions caused this interaction. Several of the same plant traits are crucial for both seed dispersal and other aspects of life history variation. Observed traits that limit dispersal are likely to be constrained by their life history consequences.atmospheric turbulence ͉ conditional seed release ͉ Coupled Eulerian-Lagrangian closure (CELC) model ͉ long distance dispersal ͉ tropical forest S eed dispersal allows plants to colonize new habitats, reach sites where resources favor regeneration, and escape pests and competition with siblings and mother and sets the spatial template for all post dispersal processes (1, 2). A mechanistic understanding of seed dispersal could lead to progress on many fronts but requires models that recreate the complex interactions between plants and seed dispersal vectors. Mechanistic models are perhaps most advanced for seeds dispersed by wind (3). We use a wind dispersal model developed and validated for forests and grasslands (4-6) to compare spatial patterns of seed dispersal for factorial combinations of four key plant traits observed for two contrasting tropical tree species. These comparisons, made within the conceptual framework provided by movement ecology (7), provide insight into the complex interplay between atmospheric conditions and plant traits that influence seed dispersal by wind.Seed fate motivates seed dispersal through natural selection (2). Wind dispersal models have traditionally focused on a single aspect of seed fate, the distance moved from the mother (3). Long dispersal distances sample more potential regeneration sites and minimize negative interactions with siblings and mother. The implications of coincident arrival in close proximity have been overlooked for wind-dispersed seeds (but see ref. 8 for animal-dispersed seeds). Coincident arrival of siblings increases the potential for sibling competition and pest facilitation, reduces the number of potential regeneration sites reached, and leads to future inbreeding among adults. Thus, coincident arrival impacts seed fate negatively. Dispersal distance an...

Water loss from flower heads predicts seed release in two invasive thistles

“…Our results are broadly applicable to other species because most plants are also xerochastic (Greene and Johnson 1992;Roche 1992;Nathan et al 1999;Mandak and Pysek 2001;Greene et al 2008;Wright et al 2008;Hamilton-Brown et al 2009). The prevalence of xerochasty suggests that seed release under hot, dry conditions may increase plant fitness, potentially by increasing dispersal distances.…”

“…If water supply to capitula is negligible during this period of active drying, then all of the components are available to incorporate with our results and weather data to mechanistically model the effects of evaporative conditions on seed release in the field -with the caveat that in order to know how many seeds release some biological data may be required. The addition of this information to our current knowledge of the effects of wind speed and turbulence on seed release (Greene 2005;Skarpaas et al 2006;Jongejans et al 2007;Wright et al 2008) will greatly improve the predictive power of mechanistic seed release and dispersal models.…”

“…Mechanistic seed release models are a key component necessary to understand under which conditions seeds disperse and how far they travel (Jongejans et al 2007;Soons and Bullock 2008;Wright et al 2008;Nathan et al 2011). Seeds that disperse long distances are more likely to have an appreciable impact on migration and gene flow.…”

“…Therefore, calls have been made for more research on this important topic (Schippers and Jongejans 2005;Kuparinen 2006;Nathan 2006). As more and more researchers investigate the mechanisms underlying seed release, it is becoming increasingly clear that seed release is not a random process, but occurs under certain predictable conditions (Greene and Johnson 1992;Tackenberg et al 2003;Greene 2005;Skarpaas et al 2006;Jongejans et al 2007;Soons and Bullock 2008;Hamilton-Brown et al 2009;Marchetto et al 2010b;Greene and Quesada 2011), which may vary by species (Wright et al 2008).…”

“…Physiologically, we understand what effects dry conditions have on capitula (Smith and Kok 1984;Fahn 1990) and seed attachment structures (Greene and Johnson 1992). Regression models have also been created to relate weather variables to seed release that include temperature (Wright et al 2008) or relative humidity (Greene et al 2008). However, temperature or relative humidity alone is a poor indicator of water loss by plants or of evaporation in general (Anderson 1936;de Bruin and Holtslag 1982;Sumner and Jacobs 2005).…”