DOI: 10.5061/dryad.2z34tmpwh
title: Identifying knowledge gaps about context dependency in freshwater species invasions

description: The abiotic template of freshwater ecosystems is being altered by human
 activity on a global scale, often promoting the establishment of new
 invasive taxa and increasing the likelihood of facilitation between
 invaders. These positive interactions represent a substantive threat to
 freshwater ecosystems by promoting the establishment and persistence of
 invasive taxa. To assess the threat posed by freshwater invasive species
 under global change, we leveraged the existing literature at the
 intersection of freshwater invasive species and positive biotic
 interactions using systematic review and meta-analysis. Our findings
 revealed critical knowledge gaps in the study of interactions between
 invasive taxa, which may lead to an underestimation of their threat. These
 gaps included a lack of studies that address indirect interactions,
 particularly over long temporal scales. Such interactions were
 understudied for invasive taxa but were often strongly positive.
 Additionally, almost a third of the publications examined documented
 context-dependent interactions, but only a single publication did so
 between invasive organisms. Common forms of anthropogenic change,
 including alterations to habitat quality, nutrient availability, and
 hydrology, were among the most frequent drivers of context dependency. Our
 analysis supports the conclusion that 1) the threat of facilitation
 between freshwater invaders may be underestimated by the current
 literature, and 2) global change may drive context-dependent interactions
 between freshwater invasive species, but there is a lack of research
 addressing this possibility.
description: We based our analysis on a systematic search of the available
 literature on positive species interactions in freshwater ecosystems. The
 core of our corpus was formed by publications that had previously been
 identified by Albertson <em>et al</em>. (2021). These
 publications were augmented by an updated search conducted in ISI Web of
 Science on April 1, 2022, using the following search terms:
 (“aquatic” OR “stream$” OR “river$” OR “freshwater$” OR
 “wetland$” OR “lake$” OR “pond$” OR “vernal”) AND ((“positive interact*”
 OR “mutualis*” OR “commensal*” OR “facilitation” OR “symbios*” OR “habitat
 ameliorat*” OR “stress ameliorat*” OR “ecosystem engineer*” OR “stress
 gradient*”) OR ((“positive interact*” OR “mutualis*” OR “commensal*” OR
 “facilitation” OR “symbios*” OR “habitat ameliorat*” OR “stress
 ameliorat*” OR “ecosystem engineer*” OR “stress gradient*”) AND (“invas*”
 OR “non-native” OR “invad*” OR “non-indigenous”))) NOT
 “blood" The objectives of the updated search were
 to expand the previous corpus to include any new articles that had not
 been published at the time of the Albertson <em>et al</em>.
 (2021) search, and to conduct a more thorough search for publications that
 examined interactions between invasive species.
 <strong>Publication Vetting and Data
 Collection</strong> Following the literature
 search, we examined each publication to determine if it met our criteria
 for inclusion in the meta-analysis. Publications were included if they met
 the following criteria: 1.      A measure of effect
 size for a beneficiary species from both a treatment group (with potential
 facilitator species present) and a control group (no potential facilitator
 species present), reported as the mean response of the beneficiary in both
 groups. These means were derived from observations. Effect sizes derived
 from model estimates (e.g., marginal means obtained from regression
 parameters) or estimated means arising from extrapolation were not
 included. We also excluded observations for which one or both group means
 were zero, since such observations interfered with our calculation of
 effect size (see Eqs. 1 and 2 below). Although we use the terminology
 “beneficiary” and “facilitator” here based on the original authors’
 treatment assignments, a goal of our paper is to describe how the
 potential facilitative interaction ultimately took place (see number 5
 below). 2.      A sample size (n) for both
 groups. 3.      A measure of uncertainty for both the
 treatment and control group means. This could be reported as standard
 deviation, standard error, sample variance, 95% confidence interval of the
 mean, etc., but had to be able to be transformed to yield the within-group
 standard deviation of the mean. 4.      At least one of
 the participants in the interaction had to be an obligate freshwater
 species. 5.      At least one interaction documented in
 the publication had to be positive. We defined positive interactions as
 those for which the mean value of the response variable in the treatment
 group exceeded the mean value in the control group, regardless of
 uncertainty around the mean. We therefore included publications for which
 the difference between the means did not meet author assigned thresholds
 for statistical significance. If a publication met the
 criteria for inclusion, we collected the group means, uncertainty, and
 sample size for any species interactions that reported the relevant
 values.  We collected values when reported in text or tables directly, or
 in cases for which values of group mean, uncertainty, or moderators were
 reported only in figures, we obtained values using the Figure Calibration
 plugin for ImageJ (Schindelin <em>et al</em>., 2012). When
 available, we collected information on several moderating variables. These
 moderators included the temporal scale over which the measurement was
 carried out, the spatial scale of the measurement, whether the measurement
 was collected from a manipulative or observational study, the interaction
 pathway (i.e., direct interaction, indirect interaction, or the net result
 of both types), and the invasion status of the participants.
description: # Identifying knowledge gaps about context dependency in freshwater
 species invasions
 [https://doi.org/10.5061/dryad.2z34tmpwh](https://doi.org/10.5061/dryad.2z34tmpwh) ## Description of the data and file structure The data associated with this project were collected in order to better understand factors which contextualize the outcome of interactions between freshwater species. This includes interactions between both invasive and non-invasive taxa. The intent of this project was to leverage the growing literature on positive biotic interactions in freshwater to highlight knowledge gaps in the study of freshwater invasions. The file structure consists of three .CSV files, one .RMD file, and one .HTML file. The raw data for the analysis are contained in the .CSV files. The .RMD file contains the code needed to reproduce the analysis. The .HTML file is a knitted rendering of the analysis produced by the .RMD file. ### Files and variables #### File: Master_Data.csv **Description:** This file houses the raw data on the outcome of interactions between freshwater species. The variables used for the analysis and creation of figures include:  1. Author. The last name of the lead author on a publication. 2. PubYear. The publication year. 3. Journal. The journal in which the publication appeared. 4. Experiment. A numerical identifier for each unique experiment or study within a publication. 5. Manipulation. A numerical identifier for distinct manipulations or treatments within a given experiment. 6. Metric. A numerical identifier for distinct metrics used to measure the outcome of a given manipulation. 7. ComparitiveManipulative. Whether the observation was collected from a comparative or manipulative study or experiment. 8. DirectIndirect. Whether the interaction in question followed a direct pathway, an indirect pathway, or was the net effect of both. 9. MasterResponse. Broad, reader assigned category for the type of response measured. 10. ResponseVar. More detailed information on the response measured. 11. NumFacilitator and NumBeneficiary. The number of facilitator and beneficiary taxa involved in the interaction. Either an exact number or "multiple" if the exact number is greater than one and ambiguous. 12. FacilitatorTaxon and BeneficiaryTaxon. The taxonomic identity of the facilitator and beneficiary in an interaciton. 13. FacilitatorType and BeneficiaryType. Abbreviations for broad taxonomic categories of the facilitator and beneficiary. Abbreviations are corrected to full words in the .Rmd file. 14. FacilitatorInvasionStat and BeneficiaryInvasionStat. Whether the author of the original work considered the facilitator and beneficiary to be invasive. Left as NA if ambiguous. 15. ResponseUnits. Not used in the analysis, but provides the original units for group means. 16. Days. How long a manipulation or difference between natural control and experimental groups had been occurring when the measurement was taken. 17. PatchSize_m2. The spatial extent over which the measurement occurred in square meters. 18. nT and nC. The sample sizes for each treatment and control group. 19. T and C. Group means for each sample and control group. 20. SE_T and SD_C. Standard errors for each treatment and control group, where reported. 21. Var_T and Var_C. Variance for each treatment and control group, where reported. 22. 95CI_T and 95CI_C. The 95% confidence interval for each treatment and control group, where reported. 23. SD_T and SD_C. Standard deviations for each treatment and control group, where reported. 
 
 #### File: signswitching.csv **Description:** This file houses
 information on potential instances of context dependency documented by the
 publications included in the meta-analysis:  Variables used for joining
 this data to the master data include: 1. Author, PubYear, and Journal. As
 described above, these variables are used only for joining the data.
 Variables used for the analysis include:  1. Sign Switching. Whether or
 not the publication documents a possible instance of context dependency.
 2. Comparative_Manipulative. Whether the context dependency was observed
 in a comparative or manipulative setting. 3. Direct_Indirect. Whether the
 context dependent interaction followed a direct pathway, an indirect
 pathway, or involved the net result of both. 4. Facilitator and
 Beneficiary. The taxonomic identity of both the facilitator and
 beneficiary. 5. Facilitator_Invasive and Beneficiary_Invasive. Whether the
 facilitator and beneficiary were invasive according to the authors of the
 original publication. 6. Switching_Mechanisim. The underlying mechanism
 which the original authors proposed as the driver of context dependency.
 7. Switching_Category. A broad category for the switching mechanisim. 8.
 Switch_Type. The signs taken on by the interaction in question. 
 
 #### File: Paper_Rejection_Reasons.csv **Description:** Publications
 which were selected for additional screening after the literature search,
 with notes on reasons for whether the publication was accepted or rejected
 for the final dataset. Variables include: 1. Authors. The complete author
 list for the publication. 2. Title. The title of the publication. 3. DOI.
 The DOI of the publication. 4. Use_Y_N. Whether or not the publication was
 passed on to the full research team for data extraction. 5.
 Reason_R_Summary. A summary of the reason for rejecting the publication. 
 
 #### File: Final_Meta_Analysis_Code.Rmd **Description:** The code needed
 to reproduce the analysis described in the publication. The code is
 designed to reproduce the full analysis if all chunks are run in order.
 This file should be in the same directory as the .CSV files detailed above
 in order to run the analysis correctly. The file will save multiple .CSV
 tables and large image files to the working directory when run. 
 
 #### File: Final_Meta_Analysis_Code.html **Description:** A knitted
 version of the .Rmd described above. This file contains all relevant
 graphs, results, and comments on the analysis. 
 
 ## Code/software The analysis was run using R version 4.4.1.
 Meta-regression modeling was conducted using the* metafor* package version
 4.6-0. Data wrangling was conducted using* tidyverse* 2.0.0, *readxl*
 version 1.4.3, *openxlsx* version 4.2.6.1, and car version 3.1-2. Data
 visualization was conducted using* ggpubr* version 0.6.0,* ggpp* version
 0.5.8-1,* ggdist* version 3.3.2,* GGally* version
 2.2.1,* *and *lemon* version 0.4.9.  To reproduce the workflow used to run
 the analysis, extract the included .zip file to your chosen dirrectory.
 Then, open the file "Meta_Analysis_for_Distribution.Rmd" in R
 Studio (version 2023.12.1), then choose knit to PDF. ## Access information
 Other publicly accessible locations of the data: * NA Data was derived
 from the following sources: * Various publications described in the full
 data.