Disentangling the effects of population mixing and propagule amount in rare plant translocations
Data files
Apr 24, 2025 version files 264.42 KB
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POAREM_CICVIR_dataset_DRYAD.csv
134.76 KB
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PRULAC_CAMCER_dataset_DRYAD.csv
122.08 KB
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README.md
7.59 KB
Abstract
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.
Dataset DOI: 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
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
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
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
Access information
NA
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. Biological Conservation, 306, 111132. DOI: 10.1016/j.biocon.2025.111132