Field Experiment on Direct Seeding Conducted at the Cascata Experimental Station of Embrapa Temperate Climate, 2022
Description
This dataset contains records from a direct seeding experiment conducted in 2022 at the Cascata Experimental Station of Embrapa Temperate Climate. The objectives of the present study were to investigate the effects of season, mulching, and agricultural crops on the emergence and establishment of tree species (pioneer and non-pioneer) through the use of direct seeding in forest restoration under a subtropical climate. The field observations presented show the emergence of the tested forest species over one year of study, as well as their establishment one year after implementation. The different factors tested were agricultural crops (Treatment 1), with the levels presence of agricultural crops (T1) and absence (Control). The mulching factor (Treatment 2), with the levels presence of mulching (Mulching) and absence (Non-mulching). The seasons tested were summer and winter, and finally, the successional groups included pioneer and non-pioneer species.
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Steps to reproduce
Field observations were carried out weekly until the third month after sowing, then biweekly until the sixth month, and monthly thereafter until the end of the experiment (twelve months after sowing). At each data collection, seedling emergence was recorded in every plot, and individual plants were tagged to monitor their establishment over time. Data on emergence and establishment percentages were analyzed both globally (considering the entire seed community) and by successional groups (pioneer vs. non-pioneer species). Statistical analyses were conducted in R, version 4.5.2, with a significance level set at 5% (p < 0.05). A Zero-Inflated Generalized Linear Mixed Model (ZIGLMM) approach was applied, using a beta distribution with a logit link function. The conditional model included second-order interactions among fixed effects (Treatment 1, Treatment 2, Season, and Successional Group), with blocks treated as random effects. The same interaction structure was used to model the zero-inflation component, except in the relative emergence model, where the Season variable was omitted due to high multicollinearity with other predictors. The dispersion component was modeled as a function of Season. Models were fitted using the glmmTMB package.
Institutions
- Universidade Federal de PelotasRio Grande do Sul, Pelotas