Alien woody plants are more versatile than native, but both share similar therapeutic redundancy in South Africa.

Understanding why alien plant species are incorporated into the medicinal flora in several local communities is central to invasion biology and ethnobiology. Theories suggest that alien plants are incorporated in local pharmacopoeias because they are more versatile or contribute unique secondary chemistry which make them less therapeutically redundant, or simply because they are locally more abundant than native species. However, a lack of a comprehensive test of these hypotheses limits our understanding of the dynamics of plants knowledge, use and potential implications for invasion. Here, we tested the predictions of several of these hypotheses using a unique dataset on the woody medicinal flora of southern Africa. We found that the size of a plant family predicts the number of medicinal plants in that family, a support for the non-random hypothesis of medicinal plant selection. However, we found no support for the diversification hypothesis: i) both alien and native plants were used in the treatment of similar diseases; ii) significantly more native species than alien contribute to disease treatments particularly of parasitic infections and obstetric-gynecological diseases, and iii) alien and native species share similar therapeutic redundancy. However, we found support for the versatility hypothesis, i.e., alien plants were more versatile than natives. These findings imply that, although alien plant species are not therapeutically unique, they do provide more uses than native plants (versatility), thus suggesting that they may not have been introduced primarily for therapeutic reasons. We call for similar studies to be carried out on alien herbaceous plants for a broader understanding of the integration of alien plants into the pharmacopoeias of the receiving communities.

1. Introduction

Elucidating what factors guide the selection of medicinal plants into a local pharmacopoeia is central to our understanding of human-plant interactions. Several alternative hypotheses have been formulated to explain the patterns of plant use by local people (see review in [1]). However, existing studies examined these hypotheses individually [2-4], and this limits our broad understanding of how multiple drivers shape local people’s plant knowledge and use [5]. In the present study, we tested three interlinked hypotheses to explain the integration of alien plants into local medicinal flora: non-random selection, diversification, and versatility hypotheses. The link between these hypotheses can be justified as follows: humans decide to select a given alien plant to be introduced into a new environment (nonrandom selection hypothesis); once the species is introduced, the answers to the following questions determine its susceptibility to integrate local medicinal flora: Is the alien plant abundant or accessible to people (availability hypothesis)? Does it increase local medicinal plant species richness (diversification hypothesis)? Does it have additional uses, apart from medicinal uses, that may justify its selection and introduction to the new environment (versatility hypothesis)?.

The non-random plant selection hypothesis suggests that medicinal plants are not a random subset of total flora; rather, in its original form, the hypothesis predicts that the number of medicinal plants in a given family is predicted to increase linearly with the total number of species in the family [6]. It is now evident that the relationship between medicinal plants and family size is nonlinear [2]. In line with this hypothesis, family becomes a strong predictor of plant use value [7], and consequently, some families are over-utilized whilst others are under-utilized [6,8-10]. Over-utilized families are expected to be exceptionally rich in secondary compounds that are effective in the treatment of diseases [11,12], as opposed to under-utilized alkaloid-poor families [8,11,12].

In parallel, alien plants can also be introduced into a new geographic region originally to provide various services (e.g., food, construction materials, ornamental, etc.) and then later, their medicinal property may be realized, leading to their integration into local pharmacopoeia. Such scenario of multiple uses for the same plant species is predicted by the versatility hypothesis [5,12,13]. This inclusion of alien plants into local medicinal flora leads to an increase of the size of the latter, which, as a result, is now able to offer multiple treatment options to local communities. This increase (of the size of local flora and treatment options) is central to the prediction of the diversification hypothesis [14]. Evidence for the hypothesis has been reported in several studies [5,14-16].

All these hypotheses have been tested across different floristic and geographic regions, including America [6,10,11,17], Asia [18], South America [5,16,19-22], Europe [23], and southern Africa [24]. In southern Africa in particular, a floristically megadiverse region [25-29], we still have, however, a poor understanding of the theoretical basis for ethnobotanical patterns of human-plant interactions (but see [2]. The flora of South Africa, for example, represents 24,000 species, roughly 7% [26] of the world’s 370,000 vascular plant species [12]. Of the South Africa’s diversity, 2062 species are used and traded as medicinal plants [30], representing 10% of the total South Africa’s flora [31] and 61% of all medicinal plants in the entire southern African region [32]. At the same time, several alien plants are introduced to the region for various purposes, including medicinal uses [33]. The lack of general understanding of the processes underlying the patterns of plant use in tropical Africa is due to the fact that most ethnobotanical studies in Africa aimed mostly to create a repertoire of medicinal plants used by local people (e.g. [34-36]).

In the present study, we used a multiple hypotheses approach to investigate the underlying processes of the patterns of plant selection for medicinal uses in southern Africa. Specifically, we first tested if the number of medicinal plants in a family is function of the size of that family (non-random selection hypothesis). Then, we identified families that are over- and under-utilized in the region. Finally, we investigated what drives the integration of alien plants into the regional medicinal flora (versatility and diversification hypotheses).

2. Materials and methods

Ethics

Ethics approval (including permit application) and consent to participate to the study do not apply to this study. This is because the study required no field data collection since all data and information used in the study were retrieved from literature.

Study area

The present study focused on southern Africa, a geographically delimited region comprising seven countries: Botswana, Lesotho, Mozambique, Namibia, South Africa, Swaziland and Zimbabwe. This region is well known for its megadiverse flora used for centuries by a diversity of peoples with different traditions and cultures for various purposes, including the medicinal one [37].

The southern African woody flora

Over a period of seven years (2008–2014), a team of the Botany Department from the University of Johannesburg (UJ), South Africa, has embarked in several botanical expeditions across the southern African region [38,39]. Through these expeditions, native trees and shrubs were identified and plant samples were collected for various herbaria including the UJ herbarium. Our definition of trees follows O’Brien [40]: trees are perennial plants that develop aboveground stem and secondary branches with a maximum height >2.5 m. Our definition of shrubs follows the one adopted in Bezeng et al. [41], i.e., species with a minimum height of 0.5 m. We also included few shrub species sometimes equivocally defined as herbaceous (e.g., Tithonia spp., Hypericum perforatum) [42]. Collectively, we refer to our plant dataset simply as woody plant species.

Our woody dataset also includes alien species introduced into southern Africa. The checklist of alien species is informed by the latest checklist provided in Bezeng et al. [41] who combined the dataset of Henderson [43] with that of the Southern African Plant Invaders Atlas (SAPIA) [44] and Coates-Palgrave [25] with additional consultations with experts from the South African Biodiversity Institute and the Centre for Invasion Biology at Stellenbosch University, South Africa (see ref. [41]).

In total, the plant dataset used in the present study includes 1400 species (1190 native and 210 alien plants), representing 577 genera in 130 families: native (105 families), alien (46 families). All species names were cross-checked for synonyms using [45] and the taxonomy follows the Angiosperm Phylogeny Group IV [46].

Medicinal status and various use categories of plants

An extensive literature search was conducted to document the medicinal status (medicinal or non-medicinal) of all the 1400 plants in our dataset. The main source of information was the publications retrieved from the Prelude Database for Medicinal Plants in Africa [36], a database of most ethnobotanical studies in Africa, country by country, since 1847. All ethnobotanical information on the 54 African countries were regularly updated up to November 2017. From this unique database, we focused only on the selected countries in southern Africa and retrieved information of medicinal status of all species from the studies documented in this database. We additionally explored some other sources such as SANBIPlantZafrica [47] and (ethno)-botanical books that focused on southern Africa woody flora [25-29].

To document other plant use categories, first, we used Web of Science (WoS) to retrieve existing scientific ethnobotanical studies in the region. Second, we performed individual search for each species by using a combination of keywords such as “species name”, “southern Africa”, “Botswana”, “Mozambique”, “Namibia”, “South Africa”, “Swaziland”, “Lesotho”, “Zimbabwe”, “uses”, “usages”, and “benefit”. We also made use of Google and Google Scholar using similar keywords to retrieve online resources such as regional and country-specific journals, proceedings, technical reports, herbarium, and commercial websites informing on the uses of woody plants in our dataset. SAPIA [44] was also consulted. In addition, we consulted key books on the regional flora (e.g. [25,33,48]). All the different uses retrieved from this wide and intensive literature search were grouped into 16 distinct use categories (S2 Table).

Data on diversification and versatility

Our diversification data included the following variables: i) different disease categories, ii) total number of species involved in the treatment of each disease category; and iii) species origin (native versus alien). Information on diseases treated by each of our species in the respective seven countries were retrieved from publications documented in the Prelude Database for Medicinal Plants in Africa [36] and the various literature indicated above. Some diseases were common or treated by the same species in more than one country in our study area. All diseases were grouped into 20 disease categories (S2 Table) based on the human body part concerned with the disease (e.g., kidney disease, etc.), and the data for species origin (native versus alien) were sourced as explained in the section "The southern African woody flora" above. All the different uses were grouped into 16 use categories (S1 Table).

Data analysis

Testing non-random medicinal plant selection

To test if medicinal plants are non-random selection, we first determined the number of medicinal plants in each family and the total number of plants in the family. We then fitted a negative binomial model to the data using number of medicinal plants as response variable. The negative binomial model was preferred to the Poisson model to deal with overdispersion for a count data [49]. Finally, we identified over-utilized families as those with positive residuals (after fitting the negative binomial model); families with negative residuals were categorized as under-utilized. This analysis was done using the combined dataset (native + alien), and separately on native and then alien dataset.

Testing diversification and versatility hypotheses

To test the diversification hypothesis, we used two approaches. First, we calculated the number of native and alien species used in each disease category. Then we fitted the negative binomial generalized linear model (glm.nb) model to the data using the number of native and alien species treating a medical condition as response variable and disease category as predictor variable. To test if the species’ origin (native or alien) made a significant contribution to explaining the number of species used for each disease category, we fitted an alternative glm.nb model including species origin as a co-variable. We selected the best model (between the model with and without species origin) using the Akaike Information Criterion (AIC) score of each model. The model with the lowest AIC score was selected as the best model after comparison of models (ΔAIC). If the best model includes origin, this implies that origin has a significant and unique contribution to the region’s pharmacopoeia.

Second, we determined the medicinal redundancy score for each plant. This score was calculated for a given species as the average number of additional species recorded as treating the same disease with the given species (S3 Table). We then fitted a glm model to the redundancy score using total uses and plant origin (native vs. alien) as co-variables. A lower redundancy score for alien means that alien plants treat unique disease in the region.

In addition, we tested the relationship between the number of diseases treated by plants and their origins (S3 Table). This was done by fitting a negative binomial glm to the number of diseases. This model was fitted because our response variable is a count data and to avoid overdispersion. If alien species treated more diseases than native, this would imply that alien had unique contribution to regional pharmacopoeia.

Finally, to test the versatility hypothesis, we fitted a poisson glm to the total number of use categories using number of disease and origin as co-variables. From the data used, all non-medicinal plants are excluded (S3 Table). The poisson glm was used because the response variable is a count data and there was no overdispersion.

The R script used for the analysis is provided in Supplementary Information.

3. Results

Nonrandom hypothesis

Most families of native and alien woody plants in southern Africa are medicinal (85% and 65%, respectively). In these families, the number of medicinal species increases with the size of the family: native flora (β = 0.09 ± 0.003; z = 25.1, p < 0.001; Fig 1), and alien flora (β = 0.05 ± 0.007; z = 7.98, p < 0.001; Fig 1), supporting the nonrandom hypothesis.

Fig 1

Relationship between number of medicinal plant species and total number of species in native and alien flora of southern Africa.

The red line is the fit line following a negative binomial model. Each dot above the fit line represents an over-utilized family, and each dot below the red line represents an under-utilized family. Over-utilized family = family that contains more medicinal plants than expected, given the model fitted; Under-utilized family = family that contains less medicinal plants than expected.

An implication of this hypothesis is that some families are over-utilized and others are under-utilized. We found that the proportion of over-utilized families in the dataset of native species was ~ 51% (53 families), and the top 10 over-utilized families include Oleaceae (residuals = +1.62), Solanaceae (+1.62), Asphodelaceae (+1.57), Vitaceae (+1.30), Loganiaceae (+1.26), Rutaceae (+1.25), Thymelaeaceae (+1.082), Annonaceae (+1.080), Meliaceae (+1.07) and Apiaceae (+1.06) (Fig 1). It is important to highlight that the alkaloid-poor family Poaceae was also identified as over-utilized (+0.37) and the well-known highly threatened cycad family Zamiaceae was also part of over-utilized families (S4 Table).

The proportion of over-utilized families in the dataset of alien species was ~28%, and the top 10 over-utilized families included Euphorbiaceae (+2.31), Solanaceae (+1.96), Anacardiaceae (+1.78), Moraceae (+1.34), Rutaceae (+1.34), Adoxaceae (+0.72), Asparagaceae (+0.72), Apocynaceae (+0.59), Tamaricaceae (+0.59) and Bignoniaceae (+0.52). It is also important to highlight that the family Oleaceae, which was the top number one over-utilized family of native species now ranked last in the list of under-utilized families of alien species in all models (S4 Table).

Diversification hypothesis

There is no support for the diversification hypothesis due to the following evidence: although we found a significant correlation between number of species used in treatments and diseases treated, the model which includes plant origin as co-variable outcompetes the model without origin (ΔAIC = 31.5) but it is native species that showed significant contribution to treatments (Fig 2; β = 71.20 ± 14.27, t = 4.991, p<0.0001). In particular, native species contributes uniquely to the treatment of parasitic infections (β = 114 ± 45.11, t = 2.52, p = 0.02) and obstetric-gynecological diseases (β = 95.5 ± 45.11, t = 2.11, p = 0.04). For example, no alien plant was reported in the treatment of cancer whilst 15 native plants were used (Fig 2).

Fig 2

Number of species used in the treatment of different diseases.

Disease categories are as follows: 1. Headache_Nervous_Mental_Disease, 2. Oral_Dental_Diseases, 3. Body_Pain_Killer_Anti_Inflammatory, 4. Kidney_Diseases, 5. Fever_Malaria; 6. Diabetes; 7. Burns_Wounds_Injury_Scars; 8. Respiratory_Diseases; 9. Skin_Diseases; 10. Eye disease; 11. Ear disease; 12. Parasitic_Infection_Control; 13. Gastrointestinal diseases; 14. Obstetrics_Gynaecology_Diseases; 15. cardiovascular diseases; 16. Growth disorders; 17. Blood disorder; 18. Anti_Venom_Poison; 19. HIV/AIDS; 20. Cancer.

Even the test of redundancy also confirms no support for the diversification hypothesis. Specifically, although alien plant species had a slightly higher redundancy score and are used to treat a higher number of diseases than natives, this trend did not result in statistically significant difference (Fig 3): therapeutic redundancy (β = -0.02± 0.04, p = 0.596) and number of diseases treated (β = -0.14 ±0.11, p = 0.205).

Fig 3

Patterns of redundancy scores of alien vs. native plants.

Versatility hypothesis

Finally, there was support for versatility hypothesis such that alien plants have significantly more use categories than native plants (β = -0.15±0.06, p = 0.008; Fig 4).

Fig 4

Versatility patterns of alien vs. native plants.

4. Discussion

We found that most families of native and alien woody plants are used for medicine (85% and 65%, respectively); this is perhaps indicative of a vast richness of medicinal knowledge in southern Africa. Our analysis also indicated that this knowledge of medicinal plants is not, however, formed in a random manner. Instead, large plant families contain more medicinal plants than expected, thus supporting the non-random selection hypothesis of medicinal plants. Such positive relationship has been reported in numerous studies across different continents (Asia [18], South America [19,20], and North America [6,17,37,50], including in the Pacific [10], and in Africa [2,4]. Our results, using the southern African flora, provide additional support to the hypothesis, and we therefore suggest that the non-random hypothesis could perhaps be regarded as a generalizable pattern in ethnobotany.

As a consequence of this non-random selection, some families are over-utilized, that is, they contain more medicinal plants than expected, and this is a useful information to guide bio-prospection efforts for discovery of new medicinal plants. Indeed, the top 10 over-utilized families that we identified are variously rich in secondary compounds such as alkaloids, glycoside, and antioxidants [12], and the evidence that these families are widely used in the treatment of various diseases (e.g. fungal, parasitic, bacterial and microbial infections, hypertension and cardiovascular, gynecologic and obstetric problems, cancer and HIV/AIDS) was reported across different geographic regions [45,51-56], including southern Africa [24,35,47,48,57-66]. The convergent use of these families in different regions is perhaps an indication of their richness in secondary compounds, and such families may be targeted for bio-prospection [67]. There are, however, differences in the top 10 over-utilized families of native and alien species; these point perhaps to the evidence that alien plants did contribute to the diversification of local medicinal flora.

Surprisingly, our analysis also identified Poaceae as over-utilized woody family (e.g., Oreobambos buchwaldii, Oxytenanthera abyssinica, and Thamnocalamus tesselatus) in southern Africa (see also [10]). This is indeed surprising because the family Poaceae is an alkaloid-poor family, and its over-utilization in southern Africa could be a result of some unique traditional medicinal knowledge that needs to be further investigated in future studies. It could simply be a result of a historical cultural behavior transmitted across generations, but which is not grounded on any medicinal property. Elsewhere in the Pacific, the overutilization of Poaceae was attributed to its physical properties which make it a fast and dry material to burn and quickly apply for wound healing [68]. Over-utilization might also explain why some species have been listed as threatened in the region [69]. Our finding that the highly threatened family Zamiaceae [31,70] is among the over-utilized families is perhaps an elucidation that over-utilization may indeed lead to negative consequence on the future of some families [70].

Although 85% of native woody plant families are medicinal in southern Africa, we also noted that another 65% of the families of alien woody plants are incorporated in the regional pharmacopoeias. For example, the family Solanaceae of alien plants is over-utilized; so too is this family for native plants. This taxonomic overlap between native and alien species suggests Solanaceae might have high medicinal value in southern Africa’s traditional medicine. Interestingly, the Solanaceae family is also well known for its economic and nutritional values, and alien Solanaceae could potentially be introduced primarily for those values and, later on, be used for medicinal purposes as predicted by the versatility hypothesis [71,72]. For example, the historical introduction of alien woody plants to southern Africa was primarily motivated by the need to meet increased demands for charcoal, timber production, ornaments, and sand dune stabilization [73,74] and at a later stage, some of these introduced plants might have been used for medicinal purpose. Our test of the versatility hypothesis confirmed a significant difference in the number of use categories between native and alien plants, thus supporting our claim. However, native plants were more versatile than alien, thus providing an opportunity to further clarify why alien woody plants were introduced into the regional pharmacopoeia.

A potential alternative reason could be that alien woody plants are used medicinally simply because they are widespread across the geographic region as predicted by the availability hypothesis. Although we found that availability is a significant predictor of plant’s medicinal status in our individual dataset of native and alien plants (see also [5,14,75]), the interaction between availability and plant origin (native versus alien) was not significant. This finding implies that, following Hart et al. [5], the availability of alien plants has no particular significance for their integration in the regional pharmacopoeia. This may point to the higher value attributed to the secondary chemistry or uniqueness of alien species relative to their sheer abundance. Alien species when they are abundance are likely to be invasive which can trigger negative perception from local people and limit their selection for medicine, unless they have unique therapeutic properties. We further investigated this claim by testing the diversification hypothesis in an attempt to explore whether alien plants introduced to southern Africa were actually unique in their contribution to the diversification of medicinal flora. To this end, three approaches were employed.

First, we tested if species’ origin (native or alien) was a significant predictor of the number of plant species used for each disease category. We found that the model that includes plant origin was better than the model without plant origin. However, it was only native origin that showed significant correlation, confirming that alien contribution to medicinal use should be very minimal. The strict regulation and control of alien species introduction in the region (e.g., vast physical removal and destruction of "alien forests", see ref. [76,77] for alien control options in South Africa) may have contributed to limiting the availability of alien plants, and this could account for the non-significant interaction between plant origin and availability.

Second, we compared the redundancy scores of alien plants versus native plants. If alien plants were less redundant, this would mean that they were introduced to fill some therapeutic gaps in the regional pharmacopoeia. Our dataset a priori pointed to a possibility of taxonomic redundancy of alien plants since a very high proportion of alien families was shared with native plants (32 families representing 70% of alien families overlap with native families), suggesting that medicinal alien plants may not have a unique contribution to regional medicinal flora. An illustration of this is that the family Oleaceae is top over-utilized family in the native flora, but in the alien flora, it ranks last in the list of under-utilized families, indicating that, although alien Oleaceae has contributed to diversifying regional medicinal flora, it does not have significant contribution to medicinal purpose. Our analysis revealed indeed a trend towards more utilitarian redundancy for alien plants, albeit not significantly so.

Therapeutic redundancy hypothesis suggests that different species may provide similar medicinal uses to local people [78,79]. Redundancy has some benefits to therapeutically redundant species, which is that, in theory, they suffer less use-impacts due to the diffusion of use pressure among a wider array of plants [78]. However, recent evidence shows that less therapeutically redundant species may not suffer from a greater use pressure [3]. From ethnobotanic perspective, the implication of redundancy is that the loss of some redundant species would not severely compromise local therapeutic practices [79]. However, redundancy may not necessarily result in less use-impacts for versatile species or when a redundant species is of cultural preference by local people [79,80]. In the present study, although alien plants show higher redundancy values than native plants, the difference is not statistically significant. This means that the proportion of alien plants that treat the same disease is similar to that of native plants. Alien plants are not unique in the study area; they are used to treat the same disease native plants treat except for cancer for which no alien plant is recorded. Further studies are necessary to tell the scenario (high or light use-pressure) that applies to the alien woody species included in the present study. Such studies may also include alien herbaceous species which may not necessarily show the same redundancy as the woody species since the latter may not primarily be introduced in the first place for medicinal purpose.

Finally, we also compared native and alien plants in term of the number of disease treatments they are involved in. Again, alien plants tend to treat more diseases than native, but the difference between native and alien was, once more, not significant. One explanation is that communities use common and available plants in their therapeutic practices irrespective of these plant origins. Also, dealing with diverse cultures in southern Africa, the selection or use of woody plants in the region might therefore differ [81] due to people’s preferences [3]. This difference may blur the signature of a particular hypothesis in the context of a large scale ethnobotanic study [5].

Collectively, our multiple tests indicated that medicinal plant selection was not a random behaviour in southern Africa, and that alien plants are more versatility than native plants with which they share similar redundancy. This implies that alien plants were introduced to provide a wider range of use options, the benefit of which could be an increase in the resilience of regional medicinal flora in the face of environmental changes [22]. The lack of strong difference between alien and native in term of therapeutic redundancy may have to do with the scale of the study. Similar lack of evidence was also reported in a recent study conducted at national scale [22]. As pointed out in [22], this lack of evidence could stem from the differences in plant preferences in disease treatments due to differences in preferred biochemical pathways [82] or cultural differences such that the diseases treated by native plants in one environment or communities may be treated preferably by alien plants in another ones. The ethnobotanical force of people’s preference was recently revealed in a study that showed that an increased preference decreases therapeutic redundancy [3]. This opens new windows for further studies at lower scale if we are to comprehend how medicinal plants are selected at village or community level. Future studies are also expected to test the therapeutic redundancy of alien herbaceous species which are not taken into consideration in the present study. We predicted a different outcome from that reported in the present study on woody plants since the latter may not primarily be introduced into South Africa for medicinal purpose unlike the herbaceous plants.

Use categories per species and origin.

(XLS)

Click here for additional data file.

Disease categories for alien and native.

(XLS)

Click here for additional data file.

Data on redundancy and versatility.

(XLS)

Click here for additional data file.

Residual values for each plant family.

(XLS)

Click here for additional data file.

(R)

Click here for additional data file.

28 Sep 2020

PONE-D-20-22274

Therapeutic redundancy of alien medicinal woody plants in the southern Africa’s regional pharmacopoeia

PLOS ONE

Dear Dr. Yessoufou,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Thank you for submitting you paper to Plos One. The reviewers made a god and thoughtful job. Please, pay attention to all the comments, especially regarding to clarify all the hypothesis put under evaluation in your manuscript.

==============================

Please submit your revised manuscript by Nov 12 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Prof. Dr. Ulysses Paulino Albuquerque

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2.Thank you for stating the following in the Acknowledgments Section of your manuscript:

[AEA (ORCID ID 0000-0003-2040-681X) acknowledges

470 funding from the DST-NRF Innovation Doctoral Scholarships (Grant # 98719)

471 and a PhD merit bursary offered by the University of Johannesburg. KY is

472 grateful to the South Africa’s National Research Foundation (NRF) - Research

473 Development Grants for Y-Rated Researchers (Grant No: 112113); OGG was

474 supported by the Carnegie African Diaspora Fellowship and start-up funds

475 from the University of Tennessee Knoxville.]

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

[This research was funded by King Saud University, grant number RSP-2020/118 and the National Research Foundation, South Africa, grant number 112113.]

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

3.We note that [Figure(s) 1] in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

1.    You may seek permission from the original copyright holder of Figure(s) [1] to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

2.    If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The paper aims to test four important hypotheses of ethnobiology (non-random hypothesis, availability hypothesis, versatility hypothesis and diversification hypothesis) using data from woody medicinal plants from southeastern Africa. The publication of this study can be of great contribution to ethnobiology, mainly because it makes a broad analysis about the entry of exotic species in local pharmacopoeias. However, I suggest a major revision before the manuscript is considered for publication. I hope the authors consider trying to clarify some ideas. Below are my comments and suggestions for change.

First, I felt a disconnection between the title and the ideas presented and discussed. The title makes us think that the work is about the redundancy of exotic species, but in fact it is about a greater scope of hypotheses that can explain such redundancy or the absence of it, among other things in the selection of medicinal plants. Redundancy and its implications, after all, is little discussed.

Secondly, I think the hypotheses could be better presented in the background. The diversification hypothesis needs to be better defined, as it seems to be confused with the versatility hypothesis. In addition, there is a lack of dialogue between the non-random hypothesis and the other hypotheses that deal with the entry of exotic species in local pharmacopoeias. Another point about this hypothesis is that, according to what I understand from the non-random hypothesis (and I may be mistaken, so the need to explain it better in the background), the number of medicinal plants in a given family is predicted to NOT increase linearly with the total number of species in the family, precisely because some families are over-utilized whilst others are under-utilized.

In the background the authors define the ways to measure availability, however, in the methodology, they apparently do not use any of the metrics presented to test this hypothesis. Instead, they redefine availability as the total number of countries where the plant occurs. I believe that a plant can occur in many countries but not necessarily be of high availability in those locations. I hope that the authors clarify this measurement, otherwise it would be necessary to rethink whether the study can really propose to test such a hypothesis.

Regarding the test of the diversification hypothesis, the measure for redundancy is very interesting, but I was thinking that a low redundancy score can still reveal an overlap between native and exotic (for example, a disease treated only by two plants, presenting low redundancy, however including a native and an exotic plant). I suggest, in addition to this analysis, to compare the number of medicinal categories in which there are only exotic with those that exist both or only native, which would show that the exotic entered the medical system to fill the gaps (diversification hypothesis). On the third test for diversification, exposed in lines 255-258, I believe it can show how the exotic are more important in the medical system than native or vice versa, but it is not a measure of diversification. One of the consequences of the diversification hypothesis is that exotic species can first enter the medical systems to fill blanks (diversification hypothesis) and then their application can be extended to the other diseases already treated by the native plants, and this would result in a greater number of medicinal categories. In other words, this test is extremely important for the discussion about the unfolding of the diversification hypothesis, and it should present a good discussion, but it is not in itself a measure of diversification.

In general, the paper brings very interesting results, which perhaps deserve to be discussed further, presenting some possible hypotheses for future studies (such as the surprising highlight of the Poaceae family). I believe that many ideas reached the conclusion without being previously discussed, such as the idea that exotic species did not enter to diversify, but to increase redundancy, which would contribute to resilience (I suggest reading Nascimento A.L.B. et al. (2015)* if the authors believe redundancy is an interesting idea to explain their results).

Finally, I think it is important to add a section presenting the limitations of the study. In addition to the observations noted above, any ethnobotanical study based on other studies, whose data collection was carried out by different researchers, probably using different methodologies and rapport efforts, has limitations, which does not invalidate the results (lines 166-167: "a database of all ethnobotanical studies that ever took 167 place in Africa, country by country, since 1847 "). In addition, I think it is important to emphasize the importance of herbaceous species for traditional pharmacopoeias, and that if they were included in the analyzes, perhaps the results would be different.

*Utilitarian Redundancy: Conceptualization and Potential Applications in Ethnobiological Research. In: Albuquerque U., De Medeiros P., Casas A. (eds) Evolutionary Ethnobiology. Springer, Cham. (2015) https://doi.org/10.1007/978-3-319-19917-7_9

Reviewer #2: The study intitled “Therapeutic redundancy of alien medicinal woody plants in the southern Africa’s region pharmacopoeia” contributes to the evaluation of hypotheses that seek to explain the selection of exotic species in different pharmacopeias on a regional scale. However, different aspects throughout the text need to be made clearer. Below, I highlight these points.

-In the introduction, the first sentence indicates “factors guide the selection of medicinal plants". Right after, the paragraph indicates “patterns of plant use” and “drivers shape local people plant knowledge and use". In this sense, I suggest to indicate more clearly that the hypotheses in the paragraph are related to the selection of medicinal plants. In addition, at the end of this paragraph, the following passage is indicated: "However, existing studies examined these hypotheses individually and this limits our global understanding of how multiple drivers shape local people plant knowledge and use [2]." However, the reference “2” contributes to assess theses hypotheses jointly, so it is necessary to highlight what remains to be done, even considering the study “2”.

-At the beginning of the second paragraph, I suggest deleting the following passage to make the text more objective: "rather, the number of medicinal plants in a given family is predicted to increase linearly with the total number of species in the family".

-From line 84, the following passage is indicated: “In parallel, alien plants can also be introduced into a new geographic region primarily for diverse services, including food, construction materials, ornamental, etc. and then be used for medicinal purpose when the need to fill some therapeutic gaps in local pharmacopoeias arises." Next, it is stated that such a scenario involves the versatility hypothesis. However, the last passage: “…and then be used for medicinal purpose when the need to fill some therapeutic gaps in local pharmacopoeias arises" is not necessarily related to the versatility hypothesis, but rather to the diversification hypothesis. The diversification hypothesis in fact indicates that exotic plants are incorporated to fill local therapeutic gaps (Albuquerque 2006, mentioned in the manuscript) and this is not clearly indicated in the work of Bennett and Prance (2000, also mentioned in the manuscript). Although both hypotheses are indicated in the paragraph, it would be interesting to adjust the excerpts in which the hypotheses are presented for that the reader is not confused.

-In line 105, I suggest removing the term “theories”, because so far in the introduction, hypotheses have been presented.

-In the topic “Medicinal status and various use categories of plants”, it would be interesting to clarify whether inclusion and exclusion criteria were used to select documents in the search for literature on the uses of species. In this case, did the documents obtained undergo a methodological quality assessment? Sometimes, many papers in a region may interview a few people and this may lead to the failure to register certain plants that would have medicinal use in a community or region, which would have implications for the results of this research.

-In line 211, it would be interesting to specify whether any criteria were used to organize diseases into 20 different categories.

-In line 231, I suggest changing “dependent variables” to “predictor” or “independent variables”.

-In line 272, would (53 species) actually be (53 families)?

-In line 280, I suggest starting the paragraph by presenting the proportion of over-utilized families for exotic species, just as it was presented for native species.

-In line 313, it is stated that “there was a support for versatility hypothesis such that native plants tend to have more use categories than alien". According to the argument presented in the introduction to the versatility hypotheses, wouldn’t it be the opposite result (exotic species being indicated for a greater number of categories than native) that would support the hypothesis? I have this same question in the discussion topic, on lines 365-370. Thus, I believe that the text can be adjusted.

-In the discussion, there is an indication that over-utilized families are rich in secondary compounds, except the Poaceae family, which is an alkaloid-poor family. It would also be interesting to present in the results the under-utilized families (both for native and exotic species) and indicate in the discussion whether these families tend to have low richness of secondary compounds. In addition, there are differences in the 10 over-utilized families of native and exotic species. It would also be the case to present a discussion on these findings.

-In line 377, I suggest replacing “(native versus native)” to (native versus exotic).

-At the end of the discussion, I missed an explanation about the findings indicating non-significant differences between the redundancy values and the number of treatments between native and exotic species. In this case, in the last paragraph of the discussion, the following excerpt is indicated: “Also, dealing with diverse cultures in southern Africa, the selection or use of woody plants in the region might therefore differ...". It would be interesting to develop a little more that explanation. In the topic of the conclusion, there are moments when possible explanations are presented, considering scenarios (such as the resilience scenario) and evidence presented in the literature. So, I suggest expanding these explanations in the discussion topic and summarizing the information present in the conclusion.

Reviewer #3: In this paper, the authors propose to explore the drivers of medicinal uses of woody plants in the Southern African region (including seven countries). They do so by testing four hypotheses about plant selection and use (non-random, availability, versatility and diversification). The large datasets used for the study are built from literature reviews (for plant uses, including medicinal) and available botanical datasets.

The hypotheses that are being tested are quite clear, the methodology is well described. The analyses that are proposed are conducted correctly - despite some issues with data, see below for details. The main results obtained are i) to show that medicinal plant use in this area is non-random, thus confirming the non-random hypothesis; ii) to identify some possibly over-used families of plants, which open ways for further research, and iii) to show that the three other hypotheses didn’t explain in a significant way the variations observed.

It is an interesting paper, covering a large area; there has been a lot of work involved in literature review and collection of data into coherent datasets.

There is, however, a number of issues that need to be addressed by the authors to make their paper more convincing, regarding the analyses, the datasets, the wording of conceptual elements, and the limits of the study, particularly in relation with the chosen scale of analysis.

Major comments

1. The authors should provide more justification about the choice of the study area: why selecting these seven countries, and not limiting the study to one country, or to one bioclimatic region, which would eliminate some flaws related to the large-scale, while keeping a dataset large enough for statistical analyses?

2. Many dimensions likely to account for plant use are not taken into account in this study (let’s just mention the socio-cultural background). This should be mentioned in a dedicated paragraph, as well as other limits to the study that need to be spelled out clearly.

3. In the same line, while the methods to constitute the datasets are well explained, and show that this task has been carried out with a lot of attention, it is important to also acknowledge the potential limits of these datasets. For example, the sources used to list medicinal uses are likely to reflect only a part of the actual uses, or to be based on individual accounts only (as is sometimes the case with early ethnobotanical studies), thus reflecting only a part of what is happening “on the ground”.

About the non-random hypothesis

4. The way to explain and refer to the non-random hypothesis and associated results in the paper could be clearer. To my understanding, there are two main “components” in this hypothesis, as it is found in the literature.

The first component is that there can be a trend, to be observed in the data, that the number of species with medicinal uses increases in relation with family size. This relation can be linear, logarithmic, and else. However, there is a key point here: if the relation is strictly linear, then it means there is no differences between families, the proportion of medicinal plants being the same across families. It shows that the odds of a species to be medicinal is constant across families, which points towards randomness rather than non-randomness. The second component is then to show, with the help of residuals or any other method, the differences across families, some hosting a higher number of medicinal plants than expected, some a lower. The first component alone is not sufficient; as used by Moerman 1979, it is interesting insofar as it allows to look at the residuals, at the differences between families, and the residuals only will “prove” differences between families (and the removal of families and genera with a strong deviation then lead to a better correlation coefficient - idem). The same point is underlined by Moerman & Estabrook 2003: medicinal uses are related to families - regardless of the size of the families.

So I recommend rephrasing or nuancing the sentences dealing with this hypothesis, as showing that size of families is a predictor of the number of medicinal plants it hosts is not directly a confirmation of the non-random hypothesis “in full” (as differences between families are not revealed this way): abstract (l. 36-38), l.65-69, 112-113, and in the discussion and conclusion (l.321-322: the results don’t show that all large families contain more medicinal plants than expected, only some of them).

5. Many families included in the sample only host one species (out of 127 families, 41 are represented by only 1 species), and many families display zero values for medicinal plants.

The binomial regression models may be affected by a high number of zero counts (cf Zuur et al. 2010): I suggest to provide details about this aspect of the dataset and provide justification about the validity of the results.

(Zuur et al. 2010. A protocol for data exploration to avoid common statistical problems. Methods in Ecology and Evolution (1):3-14.)

About the versatility hypothesis

6. While the versatility hypothesis is introduced in the paper in relation with medicinal plants, the analysis seems to have been conducted with all plant species, including the ones that don’t have any medicinal use - no details are provided (l.260-262, and results 313-315). It would be useful to i) precise if only plants with at least one medicinal use were taken into account, and ii) if not, repeat this analysis with a subset including only plants with a documented medicinal use (826 out of 1400 according to table S2), to keep the analysis in line with the hypothesis it is aiming to test. The results and discussion sections related to this analysis should be changed accordingly.

About the datasets

There are discrepancies in the datasets, that need to be corrected, as well as the analyses depending on these datasets:

7. Table S1: some species are recorded as non-medicinal (col.4) while having medicinal uses counted (col.6): Ekebergia_pterophylla_OM3263 in Meliaceae, several eucalyptus species in Myrtaceae. The residuals in table S4 are probably wrong for these families.

8. Conversely, many species are recorded as medicinal in S1, col.4, but without any precise medicinal use counted in col.6 (408 species in total). The redundancy score is null for all these species. Given that among these 408, 30 are alien and 378 native, it introduces an important bias in the results: redundancy scores are skewed towards zero among the native species. The glm models and W tests testing the diversification hypothesis should be repeated, excluding the species with missing values - another solution would be to complete the data, which I understand can be challenging if the literature is not precise enough. In all cases the authors should mention clearly if they worked with a subset or the whole dataset, why, and how it affects the overall results of their study. The results and discussion sections related to this analysis should be changed accordingly.

Statistics

9. It would be useful to the readers to have a summary table providing the basic descriptive statistics of the variables used in the analyses (e.g. number of medicinal plants per family, average number of medicinal uses per species,...), in a table inserted in the text or in supplementary material. This would allow the reader to get a quick grasp on the structure of the datasets and on variables’ value distribution.

10. In the result section, some basic descriptive analyses could strenghten the key results, and show that exploratory analyses have been conducted. I would suggest to present these first, then move to inferential analyses such as the binomial models. For example, for the non-random hypothesis, the correlation between family size and number of medicinal species should be tested, and results provided and eventually discussed (there is a strong - almost perfect - linear correlation in the case of native flora), before moving to binomial model results.

11. In the same line,in the case of diversification, the results of the Wilcoxon tests should be presented first, before the model results (l.298-311).

12. A similar test should be done in the case of the availability hypothesis (fig.3, l.289-296).

Other comments

13. Regarding the phrasing of the epistemological relation between the hypotheses and the facts they are dedicated to help understand (i.e. plant uses and plant-related knowledge): some sentences should be nuanced to acknowledge the fact that the hypotheses that are being tested in the paper are very general and cannot account by themselves alone for the complexity of human-plant interactions (as can be described e.g. in an ethnographical work). I therefore recommend rephrasing the sentences l. 54-55 and 97-98.

14. Over-utilization as revealed in the results (i.e. as an output of binomial regression models) doesn’t account for the quantity of plants that are being harvested in the environment. So the results point towards a possible over-exploitation, but do not prove it in any way (a species can have many uses but being harvested in small quantities). I recommend nuancing the way this is expressed - e.g. l. 347-351.

15. The authors mention several botanical surveys carried out between 2008 and 2014 (l.138-148). However we don’t know to what extent these surveys contributed to the dataset. How many species or presence of species/families were documented and added during these? Would the datasets have been uncomplete without these? Moreover, if these surveys provided an important part of the botanical datasets, how has data on uses of these species been collected, in relation with the places they were collected in? If some species were previously unknown in some of these areas, one can expect a lack of data on uses and knowledge about them.

16. The title doesn’t reflect appropriately the content of the article.

17. Following PlosOne data policy, a table providing the details of medicinal uses per species should be made available to the readers.

Minor comments:

18. The reference 46 doesn’t seem to be the right one to be cited l.159.

19. The table S.2 counts 826 species with a medicinal use, the S.1 displays 825.

20. The families Monimiaceae and Stangeriaceae don’t appear in the table S4, while being included in S1.

21. It would be useful to add a column with the results of the combined native + alien negative binomial model (for non-random hyp.) to the table S4.

22. L.349-351: the residuals for the Zamiaceae is quite low (0,077, the lowest positive residuals value in the analysis), I wouldn’t interpret it as showing over-utilization.

23. The reference to fig.3, l.292 is not adapted: the figure doesn’t illustrate results of the binomial model.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Matthieu Salpeteur

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

22 Oct 2021

Johannesburg 22nd October 2021

Cover Letter

Dear Editor,

First of all, we thank you for keeping the online resubmission open after such a long time despite your repeated requests to resubmit the paper. The Covid-19 pandemic has disorganized the normal way of academic life, and this explains that.

Second, we have now revised the ms following closely the comments of each of the 3 reviewers, and the response letter is provided below. We also provide a revised ms with track changes so that you can follow all our changes.

We have added the following statement to the caption of Figure 1: “The shapefile to generate Fig 1 was obtained from https://www.diva-gis.org/Data”

We also agree that the funding statement below appears alongside the published paper:

Funding: This research was funded by King Saud University (Grant RSP-2020/118) and the National Research Foundation, South Africa (Grant 112113). KY is grateful to the South Africa’s National Research Foundation (NRF) - Research Development Grants for Y-Rated Researchers (Grant No: 112113); OGG was supported by the Carnegie African Diaspora Fellowship and start-up funds from the University of Tennessee Knoxville. KY also received support from the University of Johannesburg in the form of a salary.

We thank you again,

The Authors

Submitted filename: response to comments.doc

Click here for additional data file.

4 Nov 2021

PONE-D-20-22274R1Alien woody plants are more versatile than native, but both share similar therapeutic redundancy in South AfricaPLOS ONE

Dear Dr. Yessoufou,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. ==============================

The authors submitted a much improved version of their work. I request some additional changes to make reading the text more fluent: Please restructure the results to make a clear and objective allusion to whether a given hypothesis was confirmed or refuted, and then present the results of the analyses.

============================== Please submit your revised manuscript by Dec 19 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Ulysses Paulino Albuquerque

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

8 Nov 2021

We have revised the ms. following the editor comments.

10 Nov 2021

Alien woody plants are more versatile than native, but both share similar therapeutic redundancy in South Africa

PONE-D-20-22274R2

Dear Dr. Yessoufou,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ulysses Paulino Albuquerque

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

18 Nov 2021

PONE-D-20-22274R2

Alien woody plants are more versatile than native, but both share similar therapeutic redundancy in South Africa

Dear Dr. Yessoufou:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ulysses Paulino Albuquerque

Academic Editor

PLOS ONE