Testing a mechanistic dispersal model against a dispersal experiment with a wind-dispersed moss
Number of Authors: 7
2015 (English)In: Oikos, ISSN 0030-1299, E-ISSN 1600-0706, Vol. 124, no 9, 1232-1240 p.Article in journal (Refereed) Published
Wind is the main dispersal agent for a wide array of species and for these species the environmental conditions under which diaspores are released can potentially modify the dispersal kernel substantially. Little is known about how bryophytes regulate spore release, but conditions affecting peristome movements and vibration of the seta may be important. We modelled airborne spore dispersal of the bryophyte species Discelium nudum (spore diameter 25 m), in four different release scenarios, using a Lagrangian stochastic dispersion model and meteorological data. We tested the model predictions against experimental data on colonization success at five distances (5, 10, 30, 50 and 100 m) and eight directions from a translocated point source during seven two-day periods. The model predictions were generally successful in describing the observed colonization patterns, especially beyond 10 m. In the laboratory we established spore release thresholds; horizontal wind speed sd > 0.25 m s(-1) induced the seta to vibrate and in relative humidity < 75% the peristome was open. Our dispersal model predicts that the proportion of spores dispersing beyond 100 m is almost twice as large if the spores are released under turbulent conditions than under more stable conditions. However, including release thresholds improved the fit of the model to the colonization data only minimally, with roughly the same amount of variation explained by the most constrained scenario (assuming both vibration of the seta and an open peristome) and the scenario assuming random release. Model predictions under realised experimental conditions suggest that we had a low statistical power to rank the release scenarios due to the lack of measurements of the absolute rate of spore release. Our results hint at the importance of release conditions, but also highlight the challenges in dispersal experiments intended for validating mechanistic dispersal models.
Place, publisher, year, edition, pages
2015. Vol. 124, no 9, 1232-1240 p.
IdentifiersURN: urn:nbn:se:su:diva-121676DOI: 10.1111/oik.01886ISI: 000360823400013OAI: oai:DiVA.org:su-121676DiVA: diva2:889948