Global mismatch of policy and research on drivers of biodiversity loss

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1 SUPPLEMENTARY Brief Communication INFORMATION In the format provided by the authors and unedited. Global mismatch of policy and research on drivers of biodiversity loss Tessa Mazor 1,3 *, Christopher Doropoulos 1,3 *, Florian Schwarzmueller 1, Daniel W. Gladish 1, Nagalingam Kumaran 1, Katharina Merkel 1,2, Moreno Di Marco 1 and Vesna Gagic 1 1 Commonwealth Scientific and Industrial Research Organisation, Dutton Park, Queensland, Australia. 2 Queensland University of Technology, Brisbane City, Queensland, Australia. 3 These authors contributed equally: Tessa Mazor, Christopher Doropoulos. * Tessa.Mazor@csiro.au; Christopher.Doropoulos@csiro.au Nature Ecology & Evolution Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

2 Global mismatch of policy and research on drivers of biodiversity loss Tessa Mazor 1, *, Christopher Doropoulos 1, *, Florian Schwarzmueller 1, Daniel W Gladish 1, Nagalingam Kumaran 1, Katharina Merkel 1, 2, Moreno Di Marco 1, Vesna Gagic 1 1 Commonwealth Scientific and Industrial Research Organisation, Dutton Park, Queensland, Australia, Queensland University of Technology, Brisbane City, Queensland, Australia, 4000 * Joint and corresponding authors: Tessa.Mazor@csiro.au; Christopher.Doropoulos@csiro.au Supplementary Information Supplementary Methods Systematic map methodology following Campbell Collaboration and Cochrane guidelines Explanation of approach to derive values for Figure 2 and Supplementary Figure 1 Supplementary Figure 1 Threats to biodiversity and policy targets Supplementary Figure 2 Flow chart of methods of how articles were classified into different systems: terrestrial, marine, freshwater and other Supplementary Figure 3 Trends of research on drivers per system over the time of our review (in percent of total papers per year) Supplementary Figure 4 Comparison of resulting driver and system classifications from Scenario 1 (only the specific driver word was used) and Scenario 2 (words which had >50% agreement between authors on this paper) Supplementary Table 1 Number of articles extracted the Web of Science (retrieved 3 rd April 2017) from 21 peer-reviewed ecology and conservation journals during Supplementary Table 2 Words used to categorise articles into drivers of biodiversity loss Supplementary Table 3. Results from the Fleiss Kappa test comparing agreements among authors for the keywords used to classify drivers of biodiversity loss Supplementary Table 4 Number of articles categorised into drivers and combinations of drivers Supplementary Table 5 Validation results of successfully categorising articles by title, keywords and abstract searches Supplementary Table 6 Comparing the results of the database categorised into system from this paper with results from Menge et al Supplementary Table 7 Results of drivers of biodiversity loss classified into systems comparing two different scenarios of word selection Supplementary References

3 Supplementary Methods Systematic map methodology following Campbell Collaboration guidelines 2 1. Criteria for including and excluding studies 1. Downloaded all journals from the ISI Web of Science in the field of Ecology and Biodiversity Conservation with a 2016 Impact Factor = 34 journals. 2. Journals required 10 years of continuous data from = 30 remaining. 3. Journals categorised as generic or specialised: a. Generic = primary research journals for all areas of ecology b. Specialised = include journals that are: i. reviews, opinions, commentaries (e.g. Trends in Ecology and Evolution) ii. system specific (e.g. Landscape and Urban Planning) iii. technical (e.g. Molecular Ecology Resources) 4. Only Generic journals used = 21 remaining and used for the analysis. See Table S1 for the full list of journals, articles and their classification according to our criteria. 2. Search strategy and details of coding categories Publications marked in Web of Science as biographical item, book review, correction, editorial material, letter, news item, retracted publication, retraction, or review excluded; those marked as articles included. Articles with missing title, keywords or abstract were excluded. To maximise article inclusion, for those articles with missing author keywords we used Web of Science keywords ( KeyWords Plus ) when available. Articles were separated into terrestrial, marine, freshwater and other systems. System specific words were determined by: 1. Extracting 1000 most frequently used keywords from all articles 2. Words assigned to either terrestrial, marine, or freshwater 3. Titles and keywords searched and articles separated 4. Abstract searched and articles separated Figure S2 contains schematic and numeric flow chart of approach. Articles were separated into five major drivers of biodiversity loss: Climate Change, Habitat Change, Invasive Species, Overexploitation and Pollution. Driver specific search words (Supplementary Table 2) were determined by: 1. Extracting top 100 words from articles containing the explicit driver in title, abstract or keywords. 2. Each set of 100 words was filtered, utilising words in which >50% of the current authors agreed related to specific driver. Code file classification_words.r at contains all words used to classify systems and drivers. 3. Description of methods used in primary research The methods employed by the included studies are those relating to primary research that use descriptive, comparative, experimental, mathematical, statistical and interdisciplinary approaches.

4 4. Criteria for determination of independent findings Validated separation of articles into systems by: 1. Manually inspecting 10% of the articles in each system classification (Supplementary Table 5). 2. Comparing results to Table 1 in Menge et al (Supplementary Table 6). 5. Statistical procedures and conventions 1. Tested whether author agreements for words to separated drivers were statistically different to that expected by chance using Fleiss Kappa test (Supplementary Table 3) in R package irr Conducted sensitivity analysis using explicit driver words to examine bias in our search words towards a particular system (Supplementary Table 7, Supplementary Figure 4). 6. Treatment of qualitative research The articles used have been downloaded from primary research journals in ecology that almost exclusively use quantitative approaches. Any reviews, commentaries, editorials, etc. were excluded (stage 2). However, although highly unlikely, it is possible that some articles we used may include information derived from qualitative methodologies. 7. Potential sources of bias 1. There are more ecology and conservation journals that have not been included that may potentially alter findings. How addressed: A cut off criteria was set at an Impact Factor of and journals were only used when they were generic for systems and drivers. The current sample of journals is 21, with a total of 44,852 articles. This large sample size of generic and high impact journals should be representative of the broad fields of ecology and conservation. 2. The proportion of articles categorised into systems may influence the results. How addressed: A manual validation of 10% of articles was conducted and our results were compared with a previous study 1 to which they closely aligned (Supplementary Table 6). 3. The proportions of articles categorised into drivers may affect comparisons. How addressed: A sensitivity analysis was conducted to ensure proportions of systems within a driver were consistent when altering search words (Supplementary Table 7, Supplementary Figure 4). 4. We have assumed that the presence of certain words in the title, keywords or abstract means an article directly deals with respective drivers or systems. Similarly, papers that were disregarded during the search due to the absence of such words may in fact deal with a given driver or system but only mention relevant terms in the main text of the manuscript. Thus, meta-analysis approaches (e.g. 4 ), which directly quantify effect sizes, could differ to the results generated here from using volume of literature. How addressed: Given the large sample size (>44,000 articles), and as with all text mining analyses, these types of assumptions are necessary. Since the title, keywords and abstract deal with the key components of the research, it is safe to assume that the majority of research captured in the categorisation process would reflect articles that directly deal with the driver or system (as shown in the validation process).

5 5. Search words (both system and driver) were selected by the authors. These words may differ if done with a different sample of people. How addressed: Used a Fleiss Kappa test to compare agreement between authors and whether agreements differed from random (Supplementary Table 3).

6 Explanation of approach to derive values for Figure 2 and Supplementary Figure 1 Impact of drivers Current, predicted and historic impact for each driver was derived from Figure 3 (pg. 9) of the Millennium Ecosystem Assessment (MEA) 5. To enable more quantifiable comparisons to be made, we ranked each driver by its historic impact (impact over the past years) as defined by the cell colour in Figure 3 (light yellow = 1, yellow = 2, orange =3, red = 4). Similarly, we defined the trend in driver impact as per the arrow lines in Figure 3 (diagonal down arrow = 1, horizontal arrow = 2, diagonal up arrow = 3, vertical arrow = 4). Given that terrestrial systems examined in the MEA included seven diverse ecosystems (i.e. Boreal Forest, Temperate Forest, Tropical Forest, Temperate grassland, Mediterranean dryland, Tropical grassland/savanna and Desert), we have depicted the range across these systems in Supplementary Figure 1 with whiskers as well as displaying a mean value across the rankings (Figure 2 only displays the mean value). Rankings were plotted from Least impact (rank of 1) to Most impact (rank of 4). We also note here, that the original figure of the MEA was based on expert opinion and so too does our representation in Figure 2 and Supplementary Figures 1. Aichi Targets To assess progress in achieving Aichi targets related to the 5 major drivers of biodiversity loss we used the Global Biodiversity Outlook Report 6. We identified 15 Aichi targets related to a driver: 5.1: The rate of loss of forest is at least halved (Habitat Change) 5.2: The loss of all habitats is at least halved (Habitat Change) 5.3: Degradation and fragmentation are significantly reduced (Habitat Change) 6.1: Fish, invertebrate stocks and aquatic plants are managed and harvested sustainably (Overexploitation) 6.2: Recovery plans and measures are in place (Overexploitation) 6.3: Fisheries has no adverse effects on threatened species- (Overexploitation) 6.4: The impact of fisheries within safe ecological limits (Overexploitation) 8.1: Pollution levels are not detrimental (Pollution) 8.2: Pollution from excess nutrients is not detrimental (Pollution) 9.1: Invasive species identified and prioritized (Invasive Species) 9.2: Invasive pathways identified and prioritized (Invasive Species) 9.3: Priority invasive species controlled and eradicated (Invasive Species) 9.4: Introduction and establishment prevented (Invasive Species) 10.1: Anthropogenic pressures on coral reefs minimized (Climate Change) 10.2: Anthropogenic pressures on other ecosystems minimized (Climate Change) Two of these targets (8.1 and 10.2) have not had their progress assessed within the Global Biodiversity Outlook Report so were excluded in Figure 2.

7 Supplementary Figure 1. Threats to biodiversity and policy targets. left, Historic (shaded) and predicted (solid) impact of major drivers on biodiversity loss adapted from the MEA 5. Whiskers for terrestrial system represent range. right, Progress in achieving Aichi biodiversity management targets adapted from Global Biodiversity Outlook Report 6 (Supplementary Methods).

8 Supplementary Figure 2. Flow chart of methods of how articles were classified into different systems; terrestrial, marine, freshwater and other (includes papers that deal with multiple systems as well as papers that were unable to be classified according to this method). Blue dotted lines represent summed articles. Refer to R code for search terms.

9 Supplementary Figure 3. Trends of research on drivers per system

10 Supplementary Figure 4. Comparison of resulting driver and system classifications from Scenario 1 (only the specific driver word was used) and Scenario 2 (words which had >50% agreement between authors on this paper). See Supplementary Table 2 for the search words used.

11 Supplementary Table 1. Number of articles extracted the Web of Science (retrieved 3 rd April 2017) from 21 peer-reviewed ecology and conservation journals during Selected journals (boldfaced) had to (1) have a 2016 Impact Factor >4.000, (2) include continuous data from , and (3) be primary research journals for all areas of ecology ( Generic ) to avoid any bias towards any particular driver or system. Specialised journals were excluded (italicised) and include those that focus on (1) reviews, opinions and commentaries, (2) specific systems, or (3) technical applications. Articles tagged in the ISI database as reviews, news, editorials, letters, etc. were excluded. A total of articles including titles, abstract and keywords were used. Publication ISI IF Published Total Excl. reviews, Incl. abstr., Category (2016) extracted editorials, etc. keyword, title Trends in Ecology & Evolution Yes Specialised NA NA NA Annual Review of Ecology Evolution and Systematics Yes Specialised NA NA NA ISME Journal No Specialised NA NA NA Ecology Letters Yes General Ecological Monographs Yes General Global Change Biology Yes General Frontiers in Ecology and the Environment Yes Specialised NA NA NA Molecular Ecology Resources Yes Specialised NA NA NA Conservation Letters No General NA NA NA Molecular Ecology Yes General Global Ecology and Biogeography Yes General Journal of Ecology Yes General Wildlife Monographs Yes Specialised NA NA NA Methods in Ecology and Evolution No Specialised NA NA NA Functional Ecology Yes General Journal of Applied Ecology Yes General Advances in Ecological Research Yes Specialised NA NA NA Proceedings of the Royal Society B - Biological Sciences Yes General Ecography Yes General Conservation Biology Yes General Ecology Yes General Landscape and Urban Planning Yes Specialised NA NA NA Bull American Mus Nat History Yes Specialised NA NA NA Journal of Animal Ecology Yes General Diversity and Distributions Yes General Ecological Applications Yes General Journal of Biogeography Yes General Evolution Yes General Ecosystems Yes General American Naturalist Yes General Agriculture Ecosystems Environment Yes Specialised NA NA NA Ecosystem Services No General NA NA NA Oikos Yes General Biological Conservation Yes General Total

12 Supplementary Table 2. Words used to categorise articles into drivers of biodiversity loss. Scenario 1 used only the specific driver word, whereas Scenario 2 used words selected from the top 100 keywords (resulting from a single driver word search) that had >50% agreement between authors on this paper. Note we included all word derivatives (e.g. change = changed, changes, changing). SCENARIO Climate Change Habitat Change Invasive species Overexploitation Pollution SCENARIO 1 CLIMATE CHANGE HABITAT CHANGE INVASIVE SPECIES OVEREXPLOITATION POLLUTION SCENARIO 2 CLIMATE CHANGE HABITAT CHANGE INVASIVE SPECIES OVERFISHING POLLUTION GLOBAL WARMING HABITAT LOSS BIOLOGICAL INVASION OVEREXPLOITATION EUTROPHICATION CARBON DIOXIDE DEFORESTATION INVASIVE OVERGRAZING AIR POLLUTION OCEAN ACIDIFICATION FRAGMENTATION INVASION OVERHUNTING LIGHT POLLUTION CLIMATE WARMING LAND-USE CHANGE INVASION ECOLOGY OVERHARVESTING NOISE POLLUTION HABITAT QUALITY ALIEN SPECIES EXPLOITATION ECOTOXICOLOGY FOREST FRAGMENTATION INTRODUCED SPECIES OIL POLLUTION HABITAT FRAGMENTATION INVASIVE PLANTS MARINE POLLUTION HABITAT MODIFICATION INVASIONS METAL POLLUTION LANDSCAPE CHANGE NON-NATIVE SPECIES INVASIVENESS INVASIBILITY

13 Supplementary Table 3. Results from the Fleiss Kappa test comparing agreements among authors for the keywords used to classify drivers of biodiversity loss. The null-hypothesis of the Fleiss Kappa test is that agreement is random. Driver Kappa P value Lower bound Upper bound Judgement All 0.72 < Substantial agreement Climate Change 0.70 < Substantial agreement Habitat Change 0.90 < Almost perfect agreement Invasive Species 0.67 < Substantial agreement Overexploitation 0.79 < Substantial agreement Pollution 0.60 < Substantial agreement Kappa scales are: = slight agreement = fair agreement = moderate agreement = substantial agreement = almost perfect agreement

14 Supplementary Table 4. Number of articles categorised into drivers and combinations of drivers. Note that the drivers climate change and invasive species are abbreviated to Climate and Invasive. Number of Articles Driver of Biodiversity Loss Total Terrestrial Marine Freshwater Other No Driver Driver (total = 11549) Climate Invasive Habitat Pollution Overexploitation Drivers (total = 1412) Climate + Habitat Climate + Invasive Invasive + Habitat Climate + Pollution Overexploitation + Habitat Climate + Overexploitation Invasive + Pollution Pollution + Habitat Overexploitation + Invasive Overexploitation + Pollution Drivers (total = 115) Climate + Invasive + Habitat Climate + Overexploitation + Habitat Climate + Pollution + Habitat Climate + Invasive + Pollution Climate + Overexploitation + Pollution Invasive + Pollution + Habitat Overexploitation + Invasive + Habitat Overexploitation + Invasive + Pollution Overexploitation + Pollution + Habitat Climate + Overexploitation + Invasive Drivers (total = 19) Climate + Invasive + Pollution + Habitat Climate + Overexploitation + Invasive + Habitat Climate + Overexploitation + Pollution + Habitat Overexploitation + Invasive + Pollution + Habitat Climate + Overexploitation + Invasive + Pollution Drivers (total = 1) Climate + Overexploitation + Invasive + Pollution + Habitat Number of articles classified into drivers (% articles classified into drivers) (29%) 8475 (30%) 1204 (33%) 832 (35%) 2585 (24%) Total number of articles

15 Supplementary Table 5. Validation results of successfully categorising articles by title, keywords and abstract searches. Ten percent of each category was validated by authors on the manuscript manually reading each paper. System Number articles classified into system Number of articles validated (10%) Successful categorisation (%) Terrestrial % Marine % Freshwater %

16 Supplementary Table 6. Comparing the results of the database categorised into system from this paper with results from Menge et al System This paper: % of 44,852 articles (no. of articles) Menge et al. 2009: % of 5,824 articles (no. of articles) Terrestrial 62.54% (28,051) 60.37% (3,516) Marine 8.18% (3,670) 7.96% (464) Freshwater 5.30% (2,378) 9.3% (542) Other 23.97% (10,753) 22% (1,302)

17 Supplementary Table 7. Results of drivers of biodiversity loss classified into systems comparing two different scenarios of word selection (see Supplementary Table 2 for the search words used). Scenario 1 - explicit driver word % Articles (number of articles) Driver of No. of % of Biodiversity Loss articles articles Freshwater Marine Terrestrial Other Climate Change % 5.52% (291) 11.95% (630) 65.20% (3436) 17.32% (913) Habitat Change % 4.03% (6) 7.38% (11) 65.77% (98) 22.82% (34) Invasive Species % 9.98% (132) 5.367% (71) 57.07% (755) 27.59% (365) Overexploitation % 5.36% (6) 31.25% (35) 36.61% (41) 26.79% (30) Pollution % 14.32% (58) 15.31% (62) 42.27% (172) 27.90% (113) Scenario 2 - >50% agreement % Articles (number of articles) Driver of No. of % of Biodiversity Loss articles articles Freshwater Marine Terrestrial Other Climate Change % 5.53% (321) 12.54% (727) 64.91% (3763) 17% (986) Habitat Change % 3.23% (109) 3.37% (114) 77.95% (2634) 15.45% (522) Invasive Species % 8.10% (314) 5.44% (211) 61.46% (2382) 25% (969) Overexploitation % 4.64% (37) 29.45% (235) 41.85% (334) 24.06% (192) Pollution % 20.76% (197) 14.65% (139) 35.30% (335) 29.29% (278)

18 Supplementary References 1 Menge, B. A., et al. J. Exp. Mar. Biol. Ecol. 377, (2009). 2 The Campbell Collaboration (2017). 3 Gamer, M., Lemon, J., Fellows, I. & Singh, P. (2012). 4 Gurevitch, J., Koricheva, J., Nakagawa, S. & Stewart, G. Nature. 555, 175, (2018). 5 Millennium Ecosystem Assessment (2005). 6 Convention on Biological Diversity (2010).