DOI: 10.5061/dryad.1c59zw476
title: Disentangling the effects of population mixing and propagule amount in rare plant translocations

description: Genetic diversity and propagule amount have been identified as crucial
 factors influencing the success of plant translocations. Population
 mixing, serving as an indicator of higher genetic diversity, might enhance
 overall plant fitness and resilience, while a higher propagule amount can
 help buffer against environmental variability. However, mixing populations
 could potentially reduce individual plant fitness in translocations,
 possibly due to maladaptation, and a higher propagule amount might lead to
 higher competition among individuals or attract more pests and pathogens.
 To better understand the impact of population mixing and propagule amount
 on the early fitness of translocated plants, we transplanted material from
 either single or mixed source populations and varied the propagule amount
 by introducing different quantities of plants into translocation plots for
 four threatened herbaceous species in Switzerland. We recorded survival,
 flowering status, and the number of inflorescences per individual for
 reproductive fitness assessment, allowing us to track the fate of each
 plant throughout the two years of monitoring. We then used aster models to
 analyse survival and reproduction data collected over two years and
 evaluate how these factors affected the mean fitness of individual
 plants. Unexpectedly, we found that a higher propagule amount
 negatively impacted plant fitness during the early stages of establishment
 for two species, while population mixing had a slightly negative effect on
 fitness for the other two species. This pattern may be due to increased
 attraction of antagonists or maladaptation and low fitness of the source
 populations. While the long-term effects of our treatment will become
 clearer in future generations, our results suggest that population mixing
 and a higher number of propagules may not always be the best strategies
 for successful early establishment. We recommend creating multiple smaller
 translocation plots instead of fewer larger ones and carefully considering
 the vitality and suitability of source populations when planning plant
 translocations.
description: Four rare and threatened plant species were reintroduced in their
 historic distribution range in the Canton of Bern in Switzerland. There is
 one reintroduction per species. At each reintroduction site, individuals
 of a given species were planted in plots: A full factorial design with six
 rectangular plots representing all combinations of single and mixed
 populations and two propagule-amount levels was used. In mixed-population
 plots, individuals from both source populations per species were mixed.
 For half of the single-population plots, we used individuals exclusively
 from the first source population, and for the remaining half, individuals
 from the second source population. Mixed-population plots are expected to
 have a greater diversity of genotypes and phenotypes compared with
 single-population plots. The propagule amount was manipulated by planting
 four times as many plants in high propagule-amount plots compared to low
 propagule-amount plots. To maintain a constant propagule density, plants
 were always planted at the same distance from each other. On the
 reintroduction day, each reintroduced individual's position was
 recorded within each plot and within the reintroduction site, and the
 length of the longest leaf (i.e., distance between root collar and tip of
 the longest leaf) was measured for initial size assessment. Individuals
 were then monitored in the northern hemisphere's spring and autumn of
 2020 and 2021. Individual survival, flowering status, and the number of
 inflorescences per individual for reproductive fitness assessment were
 recorded. For further information on the methods used
 to conduct the plant reintroductions, whose data are available in the two
 datasets provided here, as well as the assessment of the impact of
 population mixing and propagule number on the individual fitness of the
 reintroduced plants, please refer to the Materials and Methods section of
 the article: Bürli, S., Fischer, M., & Ensslin,
 A. (2025). Disentangling the effects of population mixing and propagule
 amount in rare plant translocations. <em>Biological Conservation,
 </em><em>306</em>, 111132.<em> </em>DOI:
 10.1016/j.biocon.2025.111132
description: # Disentangling the effects of population mixing and propagule amount in
 rare plant translocations Dataset DOI:
 [10.5061/dryad.1c59zw476](10.5061/dryad.1c59zw476) ## Description of the
 data and file structure **Disentangling the effects of population mixing
 and propagule amount in rare plant translocations** ### Files and
 variables Two datasets are provided: PRULAC_CAMCER_dataset_DRYAD.csv is
 the dataset with the data from the reintroductions of *Prunella laciniata*
 and *Campanula cervicaria*. POAREM_CICVIR_dataset_DRYAD.csv is the dataset
 with the data from the reintroductions of *Poa remota* and *Cicuta
 virosa*. **Description of the data and file structure**
 PRULAC_CAMCER_dataset_DRYAD.csv dataset contains Nb of columns: 44 Nb of
 rows: 901. A row corresponds to one reintroduced plant individual.
 POAREM_CICVIR_dataset_DRYAD.csv dataset contains Nb of columns: 40 Nb of
 rows: 1051. A row corresponds to one reintroduced plant individual. Both
 datasets share the same structure and column names, as described below.
 Hereafter, X refers to the monitoring number: 1 for spring 2020, 2 for
 autumn 2020, 3 for spring 2021, and 4 for autumn 2021 for the northern
 hemisphere. Plot: the plot number, where a given plant individual was
 reintroduced. Plot numbers are as follows: 1A = plot with single
 population individuals (pop. A) and high propagule amount. 1B = plot with
 the other single population individuals (pop. B) and high propagule
 amount. 2 = plot with mixed populations and high propagule amount. 3A =
 plot with single population individuals (pop. A) and low propagule amount.
 3B = plot with the other single population individuals (pop. B) and a low
 propagule amount. 4 = plot with mixed populations and low propagule
 amount. Plot_column: the column within the plot (similar to a matrix)
 where a given individual was planted. This provides the y-axis position of
 the individual within the plot. Plot_row: the row within the plot (similar
 to a matrix) where a given individual was planted. This provides the
 x-axis position of the individual within the plot. Reintro_column: the
 column within the reintroduction site (similar to a matrix, where all six
 plots were put next to each other) where a given individual was planted.
 This provides the y-axis position of the individual within the
 reintroduction site. Reintro_row: the row within the reintroduction site
 (similar to a matrix, where all six plots were put next to each other)
 where a given individual was planted. This provides the x-axis position of
 the individual within the reintroduction site. Species: the species of the
 individual. PRULAC = Prunella laciniata, CAMCER = Campanula cervicaria,
 POAREM = Poa remota, and CICVIR = Cicuta virosa. Individual_code: the
 unique plant individual code constructed as:
 SPECIES-POPULATION-SF*-INDIVIDUAL_NB. SF* is the seed-family (i.e., seeds
 from the same mother plant form a seed-family) code *within a species*.
 Population: the population of the individual (for PRULAC: NO, LL; for
 CAMCER: BR, FO2; for POAREM: BE, S4; for CICVIR: IN, WE). For further
 details, see Fig. S1 in the Supporting Material of Bürli, S., Fischer, M.,
 & Ensslin, A. (2025). Disentangling the effects of population mixing
 and propagule amount in rare plant translocations. *Biological
 Conservation, 306*, 111132. DOI: 10.1016/j.biocon.2025.111132 SF_unique:
 the unique code of a seed-family (i.e., seeds from the same mother plant
 form a seed-family) code *within a dataset*. Max_length_reintro_cm: length
 of the longest leaf (i.e., distance between root collar and tip of the
 longest leaf) on the reintroduction day. Survival_bin_MonitoX: whether the
 plant individual was found dead (=0) or alive (=1) at the monitoring X. X
 can take an integer value between 1 and 4, see above. "bin"
 means binary. Nb_leaves_MonitoX: the number of leaves of the plant
 individual at the monitoring X. X can take an integer value between 1 and
 4, see above. Height_largest_leaf_cm_MonitoX: the height of the largest
 leaf in [cm] at the monitoring X. X can take an integer value between 1
 and 4, see above. Width_largest_leaf_cm_MonitoX: the width of the largest
 leaf in [cm] at the monitoring X. X can take an integer value between 1
 and 4, see above. Flowering_bin_MonitoX: whether the plant individual was
 not flowering (=0) or flowering (=1) at the monitoring X. Only for
 PRULAC_&_CAMCER_dataset_DRYAD.csv. X can only take the values 2 or 4,
 see above. "bin" means binary. Nb_inflo_MonitoX: the number of
 inflorescence heads at the monitoring X.* *If Flowering_bin_MonitoX is
 equal to 0 (i.e., not flowering), the Nb_inflo_MonitoX is equal to 0. Only
 for PRULAC_&_CAMCER_dataset_DRYAD.csv. X can only take the values 2 or
 4, see above. Herbivory_%_MonitoX: quantified plant damage in % inflicted
 by herbivores as an approximated percentage of the afflicted plant
 individual. X can take an integer value between 1 and 4, see above.
 Fungal_infection_bin_MonitoX: presence (=1) or absence (=0) of fungal
 infection on the plant individual. X can take an integer value between 1
 and 4, see above. "bin" means binary. Other_damage_bin_MonitoX:
 whether other damages were observed (=1) or not (=0=) on the plant
 individual. X can take an integer value between 1 and 4, see above.
 "bin" means binary. Propagule_amount: whether the plant
 individual was planted in a plot (see the variable "Plot") with
 high or low propagule amount. Can take either the value "high"
 or "low". Population_mixing: whether the plant individual was
 planted in a plot (see the variable "Plot") with individuals
 from the mixed populations or with individuals from a single population.
 Can take either the value "mixed" or "single". NA
 stands for "not applicable". When a plant was recorded as dead
 at a given monitoring (indicated by a 0 in the Survival_bin_MonitoX
 column), the following columns were assigned a value of 0:
 Nb_leaves_MonitoX, Height_largest_leaf_cm_MonitoX,
 Width_largest_leaf_cm_MonitoX, Flowering_bin_MonitoX, and
 Nb_inflo_MonitoX; and the following columns were marked as NA:
 Herbivory_%_MonitoX, Fungal_infection_bin_MonitoX, and
 Other_damage_bin_MonitoX. For further details on these datasets and the
 experiment, please refer to: Bürli, S., Fischer, M., & Ensslin, A.
 (2025). Disentangling the effects of population mixing and propagule
 amount in rare plant translocations. *Biological Conservation, 306*,
 111132. DOI: 10.1016/j.biocon.2025.111132 ## Code/software To analyze
 these data, we suggest using R and aster models (Geyer et al., 2007; Shaw
 et al., 2008 & 2015; aster R package: Geyer, 2014). Geyer, C.J.
 (2014). R package aster (aster models). Version 0.8-30.
 [https://doi.org/10.32614/CRAN.package.aster](https://doi.org/10.32614/CRAN.package.aster) Geyer, C.J., Wagenius, S., & Shaw, R.G. (2007). Aster models for life history analysis. *Biometrika*, *94*(2), 415-426. [https://doi.org/10.1093/biomet/asm030](https://doi.org/10.1093/biomet/asm030) Shaw, R.G., Geyer, C.J., Wagenius, S., Hangelbroek, H.H., & Etterson, J.R. (2008). Unifying life-history analyses for inference of fitness and population growth. *The American Naturalist*, *172*(1), 35-47. [https://doi.org/10.1086/588063](https://doi.org/10.1086/588063) Shaw, R.G., Wagenius, S., & Geyer, C.J. (2015). The susceptibility of *Echinacea angustifolia* to a specialist aphid: eco‐evolutionary perspective on genotypic variation and demographic consequences. *Ecology*, *103*(4), 809-818. [https://doi.org/10.1111/1365-2745.12422](https://doi.org/10.1111/1365-2745.12422) ## Access information NA