Abstracts

Although herbaceous communities are important components of floodplain ecosystems, the factors constraining their restoration and post-restoration dynamics are poorly understood. Over the decade following restoration of a 3.2 km reach of the Merced River and floodplain in California, we tracked herbaceous community composition to distinguish floodplain habitats and utilized perturbations from revegetation treatments and post-restoration flooding to generate community assembly rule hypotheses regarding treatment effectiveness and persistence, with a particular interest in native perennials capable of suppressing non-natives over time if undisturbed. Revegetation treatments comprised combinations of sowing a sterile cover crop, sowing native species, and inoculating mycorrhizae. Most surveyed floodplain areas comprised a low terrace characterized by exceptionally droughty soils, relatively deep groundwater, and occasional flooding lasting into summer. Few species could tolerate both flood and drought to this extent, and the flood year community was generally distinct from that in non-flood years. Both communities were dominated by ruderals capable of avoiding stress and re-establishing following disturbance, including many non-native annual grassland species. Only Artemisia douglasiana responded to the treatments, as most seeded native species failed to establish, including those native perennial grasses expected to suppress non-native annuals, while other seeded native species either established adequately from natural dispersal or failed to persist through moderate flooding. Neither the cover crop nor mycorrhizal inoculation had any meaningful effect. Restoration efforts in naturally ruderal-dominated habitats may be better spent allowing natural regeneration, addressing particularly noxious invasives, and identifying or constructing habitats supporting long-lived native perennials. Although originally developed for population sizes and population growth rates, modern capture-recapture models can estimate demographic rates in complex situations: multistate models for multiple study sites and stage-structured populations, superpopulation entry probability models for recruitment, and multievent models when state assessments are uncertain. However, combinations of these complications, such as recruitment studies with uncertain state assessments, are common, yet no single model has explicitly incorporated all of these elements. Ultimately, these models estimate the same fundamental population process with the same general approach, and we combine them in a generalized hidden process model based upon a simple discrete state and transition population model with Poisson recruitment that can estimate how recruitment and survivorship rates vary with respect to measured covariates from uncertain state assessments for a stage-structured population at multiple sites. Although closely related to the motivating models, the generalized model relaxes the Markov assumption. While we provide the distributions