8 research outputs found
A new modeling approach estimates the relative importance of different community assembly processes
The relative importance of niche-based (e.g., competitive or stress-based) and stochastic (e.g., random dispersal) processes in structuring ecological communities is frequently analyzed by studying trait distributions of co-occurring species. While filtering processes, such as the exclusion of stress-intolerant species from particular habitats, increase the trait similarity between co-occurring species, other processes, such as resource competition, can limit the similarity of co-occurring species. Comparing the observed trait distribution patterns in communities to null expectations from randomized communities (e.g., a draw of the same observed richness from the regional pool) therefore gives a first indication of the dominant process driving community assembly. However, such comparisons do not inform us about the relative contribution of these different processes in shaping community compositions in case of their joint operation (a likely scenario). Using an Approximate Bayesian Computation approach, we develop a new method that allows inference of the relative importance of dispersal, filtering, and limiting similarity processes for the assembly of observed communities with known species and trait composition. We applied this approach to a tree community data set, collected across 20 plots along strong rainfall and fire gradients in a South African savanna. Based on comparisons with simulations, we find that our new approach is powerful in identifying which community assembly scenario has the highest probability to generate the observed trait distribution patterns, while traditional null model comparisons perform poorly in detecting signs of limiting similarity. For the studied savanna tree communities, our analysis yields that dispersal processes are most important in shaping the functional trait distribution patterns. Furthermore, our models indicate that filtering processes were relatively most important in areas with high fire frequencies, while limiting similarity processes were relatively most important in areas with low fire frequency and high rainfall. We conclude that our new method is a promising improvement on current approaches to estimate the relative importance of community assembly processes across different species groups, ecosystems, and biomes. Future model modifications (e.g., the inclusion of individual-based processes) could provide further steps in uncovering the underlying assembly processes behind observed community patterns
A new modeling approach estimates the relative importance of different community assembly processes
Appendix A. Description of environmental gradients in study area, tree community data, trait data and additional methodology and results of the STEPCAM approach.
Description of environmental gradients in study area, tree community data, trait data and additional methodology and results of the STEPCAM approach
Supplement 1. Plot x species matrix table and a species x traits matrix table.
<h2>File List</h2><div>
<p><a href="plot_x_species.txt">plot_x_species.txt</a> (MD5: 6b850f1de36a0eb9ed03fa4a9713e30d)</p>
<p><a href="species_trait.txt">species_trait.txt</a> (MD5: 00f69112ddfc37a6081b20069bcd89ee)
</p>
</div><h2>Description</h2><div>
<p>plot_x_species.txt<br>
variable names:</p>
<ul>
<li>plot: a column with plot names</li>
<li>ACABOR … ZIZMUC (105 columns in total): columns with abundances of different species. Species names are abbreviated with the first three letters of the genus names and the first three letters of the species name.</li>
</ul>
<p>species_trait.txt<br>
variable names:</p>
<ul>
<li>species: a column with species names</li>
</ul>
<p>SLA, LA, FD, SL, SD, BA, WD, polyphenols, C, N, P, S, K, Ca, Mg, Fe, Mn, Zn, B, Cu: columns with trait values. For more information on trait descriptions, see Appendix.</p>
</div
Appendix A. Description of environmental gradients in study area, tree community data, trait data and additional methodology and results of the STEPCAM approach
Supplement 1. Plot x species matrix table and a species x traits matrix table
File List plot_x_species.txt (MD5: 6b850f1de36a0eb9ed03fa4a9713e30d) species_trait.txt (MD5: 00f69112ddfc37a6081b20069bcd89ee) Description plot_x_species.txt variable names: plot: a column with plot names ACABOR … ZIZMUC (105 columns in total): columns with abundances of different species. Species names are abbreviated with the first three letters of the genus names and the first three letters of the species name. species_trait.txt variable names: species: a column with species names SLA, LA, FD, SL, SD, BA, WD, polyphenols, C, N, P, S, K, Ca, Mg, Fe, Mn, Zn, B, Cu: columns with trait values. For more information on trait descriptions, see Appendix
Appendix A. Description of environmental gradients in study area, tree community data, trait data and additional methodology and results of the STEPCAM approach.
Description of environmental gradients in study area, tree community data, trait data and additional methodology and results of the STEPCAM approach
Supplement 1. Plot x species matrix table and a species x traits matrix table.
File List plot_x_species.txt (MD5: 6b850f1de36a0eb9ed03fa4a9713e30d) species_trait.txt (MD5: 00f69112ddfc37a6081b20069bcd89ee) Description plot_x_species.txt variable names: plot: a column with plot names ACABOR … ZIZMUC (105 columns in total): columns with abundances of different species. Species names are abbreviated with the first three letters of the genus names and the first three letters of the species name. species_trait.txt variable names: species: a column with species names SLA, LA, FD, SL, SD, BA, WD, polyphenols, C, N, P, S, K, Ca, Mg, Fe, Mn, Zn, B, Cu: columns with trait values. For more information on trait descriptions, see Appendix