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SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 Target 12: Preventing and Improving 2 3 By 2020 the of known has been prevented and their conservation 4 status, particularly of those most in decline, has been improved and sustained. 5 6 7 Preface 8 9 The report on modelling and scenarios for GBO3 summarized predicted loss under 10 future scenarios based on four key measures: (i) species extinctions, (ii) changes in species 11 , (iii) loss, and (iv) changes in the distribution of species, functional species 12 groups or biomes (Leadley et al. 2010, Pereira et al. 2010). In this report, habitat loss is 13 considered under the targets that comprise Strategic Goal B (‘Reduce the direct pressures on 14 biodiversity’). Here, we consider extinction risk and conservation status. For extinction risk, we 15 use measures based on the threat status (measured using the IUCN Red List) of species, such as 16 the (Butchart et al., 2004). We also consider changes in species population sizes 17 and distributions, and changes in the and species composition of ecological 18 communities. Change in the diversity and composition of communities are considered despite 19 the focus of this target on the status of known threatened species, because changes in local 20 diversity accumulate to cause global loss of species, including of known threatened species. We 21 do not consider genetic diversity here because of the focus of the target on conserving species. 22 Genetic diversity is considered under Chapter 13, although only for cultivated plants, 23 domesticated animals and their wild relatives. The long-term conservation of species and of 24 biodiversity more broadly will depend on conserving genetic diversity (e.g. Forest et al., 2007), 25 and thus genetic diversity should be considered in future reports and target-setting. Freshwater 26 environments are lacking much of the information required to present an equivalent 27 assessment to those for the terrestrial and marine environments, necessitating a more 28 qualitative treatment. 29 30 31 1. Are we on track to achieve the 2020 target? 32 33 1.a Status and trends to date 34 35 Observed extinctions have generally increased over the last 200 years (Barnosky et al. 2011). For 36 birds and , there has been a slowing in the apparent rate of extinction in the last 50 37 years (Figure 12.1A), although uncertainty about whether and when a species became extinct is 38 large (see ‘Uncertainties’ below), and there is generally a long lag time between a species 39 becoming extinct and being recorded as such. For freshwater fish species on the other hand, 40 observed numbers of extinctions have increased unabated over the last 100 years (Figure 41 12.1B). Consistent data on extinctions for other taxonomic groups are not available, but the

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 number of extinctions since 1500 is very high. For example, at least 34 amphibians became 2 extinct during this period, 2 and 165 possibly extinct (Stuart et al., 2008). At 3 least 310 of the approximately 6800 species of molluscs assessed by IUCN have become extinct 4 since 1500, nearly 5% of the total assessed (www.iucnredlist.org). In order to prevent 5 extinctions of known threatened species in the near future (the main aim of Target 12) will 6 require the protection of the sites containing the last populations of 7 species (Alliance for Zero Extinction sites): Coverage of these by protected areas has increased 8 steadily over the past 25 years (Figure 12.2 D; Butchart et al., 2012). Protection of Important 9 Bird Areas has increased rapidly in the same time period, although from a much lower starting 10 point (Figure 12.2 E). All measures to protect known threatened species will require significant 11 investments; there have been no clear trends in funding for the protection of species in the last 12 15 years (Figure 12.2 F). 13

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SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

Figure 12.1. Median and 95% confidence intervals of the number of extinctions in 25-year intervals from 1800 to the present of (A) and bird (data source: BirdLife International, 2014) species and (B) freshwater fish (in total, 47 mammal species, 90 bird species and 32 fish species were declared extinct, and 27 mammals and 13 birds presumed extinct since 1800). When an exact extinction date was not given, an interval during which a declared extinction is thought to have occurred was used; otherwise, the last sighting of the species was considered as the earliest date and the latest date was assumed to be 30 years after last sighting. For the 43 species presumed extinct, we considered the last sighting as the earliest date of extinction and added the average time between last sighting and the declaration of extinction of other species to derive the latest date; C) Red List Index (RLI) for the world’s birds (red, 9869 species), mammals (purple, 4556), amphibians (green, 4355) and corals (blue, 704); and an aggregate estimate (black; Butchart et al., 2010); declines correspond to increases in extinction risk (Butchart, S. H. M. et al., unpublished data). The RLI ranges from 0 (all species are extinct) to 1 (all species are considered “Least Concerned”). Confidence intervals around the aggregate RLI trend represent 95% confidence intervals, and were based on multiple sources of underlying uncertainty – see Butchart et al., 2010; D) reconstructed trend in extinction risk for (284 species) and ungulates (262 species) in the last 40 years. The Red List status of all species was retrospectively assessed applying the current IUCN criteria to information on past population and geographic range size, structure, and trend, as well as habitat loss and other threats, available from historical IUCN Red Data Books and Action Plans (Di Marco et al. in press; doi: 10.1111/cobi.12249). 1 2 The average extinction risk of assessed species – measured as the Red List Index – increased 3 steadily over the past 40 years with no signs of slowing (Figure 12.1C, D), although increased 4 attention and investment towards threatened species has prevented some critically endangered 5 species from going extinct (Butchart et al., 2006; Hoffmann et al. 2010). Among terrestrial 6 species, amphibians have a high level of threat and are declining in conservation status strongly 7 (Figure 12.1C), with 32% of species threatened and 40% declining according to the IUCN 8 (www.iucnredlist.org; Stuart et al., 2008). For plants, comprehensive assessments of extinction 9 risk are only available for gymnosperms, for which 41% of species are considered threatened 10 (www.iucnredlist.org); there are no reported trends in extinction risk of plants at present. For 11 flowering plants, only 6% of the approximately 270,000 known species have been assessed 12 (including all cacti); however, of these 56% (31% of cacti) are considered threatened. The 13 conservation status of terrestrial species and fungi is poorly known at a global 14 scale, but assessments are available for certain regions suggesting that significant proportions of 15 species are threatened with extinction: 9% of European (van Swaay et al., 2010), 15% 16 of European dragonflies (Kalkman et al., 2010), 11% of European saproxylic beetles (Nieto & 17 Alexander, 2009) and 16% of British fungi (Evans et al., 2006). Freshwater species are also 18 showing strong declines, with 32% of freshwater vertebrates and 32% of decapods at risk of 19 extinction (Collen et al. 2014). In the marine realm, over 550 species of marine fishes and 20 are listed on the IUCN Red List as Critically Endangered, Endangered, and 21 Vulnerable (www.iucnredlist.org). This is an underestimate, owing to insufficient data with 22 which to assess the extinction risk of many marine organisms. As with trends in the extinction 23 risk of species, population trends – as measured by the (Figure 12.2C), the

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 Wild Bird Index of habitat specialist bird species (cross-reference to Target 5) and the Wildlife 2 Picture Index (O’Brien et al. 2010) – continue to decline. 3 4 For all terrestrial vertebrate groups, habitat loss because of agriculture, aquaculture and logging 5 is a stress responsible for the decline of the greatest number of species (Hoffmann et al., 2010). 6 Reptiles and amphibians are particularly sensitive to habitat degradation because of their 7 comparatively low dispersal ability, relatively small home ranges and thermoregulatory 8 constraints (Kearney et al., 2009). For mammals and birds, is the next greatest threat 9 (Hoffman et al., 2010). For amphibians, and disease (in particular the chytrid 10 fungal pathogen Batrachochytrium dendrobatidis; Cheng et al. 2011) are the main drivers of 11 decline after habitat loss, although the interaction of these threats with is likely 12 to exacerbate amphibian decline in the near future (Hof et al. 2011; Pounds et al. 2006). 13 Invasive alien species are also a major threat to birds, particularly those on oceanic islands 14 (BirdLife International 2014). Disease is also an important threat for certain other taxonomic 15 groups (for example, white nose syndrome in bats). The relative threat posed to other animal 16 taxonomic groups by different human activities is less well known. For invertebrates – bees in 17 particular – pesticides appear to be a serious threat (e.g. Gill et al., 2012). 18 19 Plant species are mainly affected by loss, degradation and increased fragmentation of , 20 and alien invasive species (Bilz et al., 2011). In the future, the threat from climate change is 21 predicted to grow (Bilz et al., 2011; Giam et al., 2010). and extinction have been 22 identified as important threats to the crop wild relatives and to plant populations that occur on 23 islands (Bilz et al., 2011). Aquatic plants are affected by modification and loss caused 24 by the transformation of wetland habitats, and the intensification of agricultural activities 25 accompanied by eutrophication and (Bilz et al., 2011). In some countries the collection 26 of wild plant species (as medicinal plants, for food, or for their beauty or value for collectors) is 27 causing a loss of species and a reduction of their reproductive success (Bilz et al., 2011). 28 29 While the global assessment of marine species is still ongoing, data are available on the threats 30 driving species loss for several well studied groups. The chondrichthyans (sharks and rays) are 31 overexploited through targeted fisheries as well as incidental by-catch (Dulvy et al. 2014). In 32 addition, half of the 69 high-value sharks and rays in the global fin trade are threatened (53.6%, 33 n = 37), while low-value fins often enter trade as well, even if meat demand is the main fishery 34 driver (Dulvy et al. 2014). Similarly, for parrotfishes and surgeonfishes, species that play critical 35 roles in coral reef , 40% (73 species) of known species are impacted by small and 36 large scale fisheries and 6% are recorded to be affected by habitat modification, 3% by pollution 37 and 1% by by-catch (Comeros-Raynal et al. 2012). For groupers and wrasses, 12% of the 163 38 species assessed are considered to be at risk of extinction if current trends continue, with 13% 39 considered near-threatened, under the IUCN Red List criteria. However, 30% of species could 40 not be assessed owing to insufficient data. The major driver of extinction risk in this group is 41 overfishing, with poor or no fishery management (Sadovy de Mitcheson et al. 2012). For

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 seabirds, particularly albatrosses and large petrels, longline and gillnet fisheries present a severe 2 threat (Croxall et al., 2012). 3 4 At the global scale, limited data prevent comparable reporting for freshwater species, especially 5 freshwater fishes and invertebrates. However, based on current data, the main threat to 6 freshwater vertebrates and decapods is habitat loss and degradation, affecting 80% of species. 7 This is followed by pollution (50% of threatened species) and exploitation (40% of threatened 8 species) (Collen et al. 2014). The combined effects of and habitat degradation 9 are acute for freshwater-dependent chondrichthyans, with over one-third (36.0%) of the 90 10 obligate and euryhaline freshwater chondrichthyans considered threatened (Dulvy et al. 2014). 11 The degradation of coastal, estuarine and riverine habitats threatens 14% of sharks and rays: 12 through residential and commercial development (22 species, including river 13 sharks Glyphis spp.); mangrove destruction for shrimp farming in Southeast Asia (4 species, 14 including Bleeker’s variegated stingray Himantura undulata); dam construction and water 15 control (8 species, including the Mekong freshwater stingray Dasyatis laosensis), and pollution 16 (20 species) are noted as driving species declines (Dulvy et al. 2014). 17 18 Importantly, within broad groups of species, the effect of threats will not fall evenly on different 19 species. In terrestrial environments, large-bodied, slow-breeding species with strict habitat and 20 dietary requirements have been shown to be more adversely impacted by habitat loss (e.g. 21 Vetter et al., 2011; Newbold et al., 2013), and to be at greater risk of extinction (Cardillo et al., 22 2005; Davidson et al., 2009) than other species. Similarly, among marine fishes, turtles and 23 mammals, large-bodied, late maturing species have been shown to be more sensitive to fishing 24 and pollution than other species (Reynolds et al. 2005; Cheung et al. 2005; 2007; Davidson et 25 al., 2012; Norse et al. 2012; Maxwell et al. 2013), while marine mammals are also sensitive to 26 coastal stressors, such as habitat loss (Davidson et al., 2012; Maxwell et al. 2013). 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 1.b Projecting forward to 2020 A B

C D

E F

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SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 Figure 12.2.Statistical extrapolation to 2020 of 6 key measures of the extinction, extinction risk and 2 conservation status of species: observed extinction rates of birds and mammals (A), the aggregate Red 3 List Index of birds, mammals and amphibians (B), the Living Planet Index (C), the representation by 4 protected areas of sites whose protection could avert the extinction of known threatened species: 5 Alliance for Zero Extinction sites (AZEs; D) and Important Bird Areas (IBAs; E) and funds for the protection 6 of species (F). Long dashes represent extrapolation period. Short dashes represent 95% confidence 7 bounds. Horizontal dashed grey line represents model-estimated 2010 value for indicator. Extrapolation 8 assumes underlying processes remain constant. Visconti et al. (unpublished data) (A); S. H. M. Butchart 9 et al. (unpublished data); B. Collen et al. (unpublished data) and described in Collen et al. (2009) (C); S. H. 10 M. Butchart et al. (unpublished data) and described in Butchart et al. (2012) (D-E) and AidData 11 (http://aiddata.org/) (F). Extrapolations are based on the assumption that underlying mechanisms 12 continue to follow trends. Methods for model fitting are described in the introductory chapter. 13 14 Concerted conservation action has been shown to be effective in reducing the extinction risk of 15 vertebrate species (Butchart et al., 2006; Hoffmann et al., 2010), and further action might 16 prevent some extinctions that would otherwise occur by 2020. However, extrapolations suggest 17 that it is very unlikely that all extinctions of known threatened (bird and mammal) species will 18 be prevented by 2020 (Figure 12.2 A). Indeed, many species are at high risk of imminent 19 extinction (e.g. Wake, 2012) and the level of resourcing required to prevent extinctions of 20 known threatened species is an order of magnitude greater than current investment (McCarthy 21 et al., 2012). Furthermore, many undescribed species have already, or will by 2020, become 22 extinct without our knowledge (Mora et al. 2011). The global rate of extinctions might be 23 slowing (Figure 12.2 A); however, at least for birds the rate of extinctions in continental areas 24 may be accelerating (Szabo et al., 2012) and lags in reporting might lead to an underestimate of 25 recent extinctions. On the other hand, the rate of extinction of freshwater fish species is likely to 26 continue increasing (Figure 12.1 B); however, as noted elsewhere, data for freshwater species 27 are very limited. Furthermore, extinction risk – as measured by the Red List Index for birds, 28 mammals and amphibians – is predicted to continue to increase (Figure 12.2 B), as are 29 population trends, as measured by the Living Planet Index (Figure 12.2 C; Collen et al. 2009) and 30 Wild Bird Index (cross-reference to Target 5). On the other hand, coverage of Alliance for Zero 31 Extinction sites by protected areas is predicted to increase, although based on the current rate 32 of increase it is unlikely that 25% of sites will be protected before 2020 (Figure 12.2 D; Butchart 33 et al. 2012). Coverage of Important Bird Areas is predicted to increase rapidly, exceeding 25% 34 coverage of sites by 2020 (Figure 12.2 E). The incomplete coverage of assessments of marine 35 species and the short time series of existing data preclude a numerical extrapolation of marine 36 species’ trends to 2020. Future trends in funding for species protection are difficult to predict 37 (Figure 12.2 F). 38 39 In terrestrial, marine and freshwater environments, , fragmentation and 40 degradation (hereafter “habitat loss”) are likely to remain major stresses on biodiversity until 41 2020 and beyond (Alkemade et al., 2009; Green et al., 2005; Jetz et al., 2007; Martinuzzi et al. 42 2013a,b). In addition, for both marine and freshwater species, over-exploitation is and will 43 remain a major threat (Pitcher and Cheung 2013, see Target 6). Many studies have predicted the

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 impact that habitat loss will have in the future on the ranges (e.g., Jetz et al., 2007; Cheung et 2 al., 2009), population trends (e.g., WWF, 2012) and extinction risk (Bird et al., 2011) of species, 3 and on the diversity of ecological communities (Gibson et al., 2011; Allan 2004; Cheung et al., 4 2009; Newbold et al., in prep.). Moreover, emerging threats such as deep-sea mining may 5 further increase the extinction risk associated with habitat changes (Boschen et al., 2013). 6 7 Short-term future projections of the extinction risk of species as a result of projected habitat 8 loss generally predict a worsening situation. However, improvements can be seen under some 9 scenarios. Under business-as-usual scenarios, species within ecological communities are 10 projected to continue declining in abundance on average (Fig. 12.3A; Alkemade et al., 2009), 11 and the number of species within communities is also projected to decrease (Fig. 12.3B). The 12 projections suggest that global populations of and ungulate species will continue 13 decreasing steeply (Fig. 12.3C), and that these species will lose substantial proportions of their 14 ranges (Visconti et al., 2011). This leads to a predicted increase in species’ extinction risk (Fig. 15 12.3D; Di Marco et al. in press; Visconti et al., submitted; see also Millennium Ecosystem 16 Assessment, 2005). Regional model predictions under business-as-usual scenarios mirror these 17 results: for example, in the Brazilian Amazon approximately 2%, on average, of vertebrate 18 species are predicted to become locally extinct as a result of habitat loss, with a further 12% 19 committed to extinction (Wearn et al., 2012), while the percentage of threatened bird species in 20 the same region is predicted to increase from 3% to between 8 and 11% (Bird et al., 2011). 21 22 Under the Rio+20 scenarios ( Environmental Assessment Agency, 2010), designed to 23 mitigate biodiversity losses, losses of within- diversity (abundances and numbers of 24 species) are slowed to some extent, but not prevented (Fig. 12.3A, B). and 25 extinction risk trends are reversed under these mitigation scenarios in the short term, caused by 26 a net gain in natural habitat in and South-East Asia, which are hotspots of carnivore and 27 ungulate richness (Fig. 12.3C, D). The scenarios assume that the natural habitat gained is 28 biotically equivalent to primary natural habitat; relaxing this assumption would lessen the 29 modelled effectiveness of mitigation. In the Brazilian Amazon, the of vertebrate 30 species is predicted to decrease by one- to two-thirds under scenarios that assume a reduced 31 rate of (Wearn et al., 2012). 32

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 2 Figure 12.3. Predicted changes in the global average of local abundance and of 3 ecological communities, and of average population trends of carnivores and ungulates (calculated as a 4 geometric mean of the ratio between population size at a given time and population size in 1970, 5 following the Living Planet Index methods; Collen et al., 2009) and extinction risk (Red List Index – RLI) 6 from 2000 to 2050, under three of the Rio+20 scenarios (Netherlands Environmental Assessment 7 Agency, 2010; see also chapter 0). Values are scaled to equal 100% in 2000. The population trends and

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 extinction risk projections under the Rio+20 scenarios are the ‘maximum physiological dispersal’ 2 projections of terrestrial carnivore and ungulate species from Visconti et al. (in review). The modelled 3 indicators measure slightly different aspects of conservation status, hence the differences in projected 4 trends. GLOBIO projects mean species abundance (MSA) across all taxonomic groups relative to pristine 5 conditions as a response to multiple pressures including habitat loss, climate change and human 6 . MSA does not allow for increases in species abundance and measures “naturalness”. Local 7 total abundance (PREDICTS model), global population trends of species and extinction risk (RLI) do not 8 have this constraint. PREDICTS and GLOBIO measure local losses, which are aggregated spatially across 9 grid cells, while RLI and LPI trends are measures of global species decline, which are aggregated across 10 species. The extrapolated trend in extinction risk (RLI) for carnivores and ungulates was done by fitting a 11 natural spline interpolation to the data in Fig 12.1B. Vertical bars show uncertainty in 2050 (shown only 12 for 2050 for clarity); uncertainty estimates were not available for the GLOBIO or Visconti LPI projections. 13 14 While positive changes to land-use policies (e.g. investing in forest restoration or modifying 15 investments in crop production) can affect trends, there are limits to what can be achieved. In 16 the , for example, the basic economic and demographic factors shaping land-use 17 change are powerful and even fairly dramatic policy changes have been shown to lead to only 18 moderate deviations from a business-as-usual scenario (Radeloff et al. 2012). However, some 19 policy tools will be easier to enact, highlighting that opportunities exist for exploring different 20 policy options that can have more substantial impacts on the reduction of habitat loss. 21 22 23 2. What needs to be done to reach the Aichi Target? 24 25 2.a. Actions 26 27 Human actions have greatly increased current extinction rates. Reducing the threat of human- 28 induced extinction requires action to address the direct and indirect drivers of change. As such, 29 actions taken to attain the targets under Strategic Goals A and B also have the potential to 30 contribute to the attainment of this target. Despite individual success stories, there is no sign of 31 an overall reduced risk of extinction across groups of species; however there are very large 32 regional differences. Against this background, possible key actions to accelerate progress 33 towards this target include: 34 35 (a) Identifying and prioritizing species for conservation activities based on 36 assessments of species conservation status (Target 19); 37 38 (b) Filling gaps in existing national, regional and global species conservation status 39 assessments (Target 19) ; 40 41 (c) Developing and implementing species action plans that include specific 42 conservation actions aimed directly at particular threatened species, for example through 43 restrictions on hunting and trade, captive breeding and reintroductions;

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 (d) Developing more representative and better-managed systems, 2 prioritizing sites of special importance to biodiversity such as Alliance for Zero Extinction Sites 3 and Key Biodiversity Areas (Target 11); 4 5 (e) Reducing the loss, degradation and fragmentation of habitats (Target 5), and 6 actively restoring degraded habitats (Target 15); 7 8 (f) Promoting fishing practices that take account of the impact of fisheries on 9 marine ecosystems and non-targeted species (Target 6); 10 11 (g) Controlling or eradicating invasive alien species and pathogens (Target 9); 12 13 (h) Reducing pressures on land use through sustainable land-use practices (Target 14 7); and 15 16 (i) Reducing pressures from trade, by increasing awareness among potential 17 consumers of products from threatened species (Target 1), and through actions agreed under 18 the Convention on International Trade in of Wild Fauna and Flora (Target 19 4). 20 21 Most of the Convention’s programmes of work as well as the Global Strategy for Plant 22 Conservation and the Global Taxonomy Initiative provide guidance that is relevant to this 23 target. 24 25 To prevent further extinctions of known threatened species, substantial conservation 26 investment is needed across terrestrial, freshwater and marine ecosystems: it is estimated that 27 investment needs to increase by an order of magnitude in order to reduce the extinction risk of 28 known threatened species (McCarthy et al., 2012). It is essential to continue monitoring the 29 status of species that have already been assessed, and to obtain information on the distribution 30 and extinction risk of less well-studied species to make assessments and future projections of 31 the status of these species. Assessments for species in all environments, but especially for 32 freshwater and marine species, are a work in progress (see Carrizzo et al. 2013 and 33 http://sci.odu.edu/gmsa/index.html), and many critical regions have not been evaluated. 34 Investments in completing these assessments are crucial for conservation decision-makers to be 35 able to adequately represent, evaluate and conserve lesser-known taxa. 36 37 Actions aimed at the conservation of threatened species can be broadly categorized as species- 38 level, which are aimed directly at threatened populations (e.g. legislation on hunting and trade, 39 vaccinations, captive breeding and reintroductions) and site, ecosystem, or landscape-level, 40 which are directed at species' habitat (e.g. protected areas, invasive species control, forest 41 management) (Boyd et al., 2008). Species-level actions are generally targeted at the protection 42 of a single species, although protection of habitat thus achieved might also protect other

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 species (Skaala et al., 2014), while broader site, ecosystem, and landscape-level actions are 2 likely to benefit multiple species (Boyd et al. 2008). In the last 3 decades, species-level 3 conservation actions reduced the extinction risk of nearly 30 species of vertebrates (Hoffmann 4 et al., 2010). Among habitat-level actions, management and protection of sites had a positive 5 effect on 36 species; invasive species control on 16, legislation and education on 14, and 6 hunting and trade management on 8 species of terrestrial vertebrates (Hoffmann et al. 2010). 7 Further such actions will help to avoid extinction and improve the conservation status of species 8 in the future. 9 10 Among threatened terrestrial vertebrates, 20% can be protected in single sites, i.e. the entire 11 global population is restricted to, and thus assumed able to be conserved at, sites managed for 12 conservation as a single unit (Boyd et al. 2008). Approximately 60% can be protected through a 13 network of sites, which suggests that effectively managed protected areas aimed at protecting 14 the remaining populations of these species, coupled with site-level management to address the 15 causes of their decline is the most important action to achieve target 12 (Boyd et al. 2008). It is 16 also essential to increase knowledge about the status of other taxonomic groups (Stuart et al., 17 2010). In order to effectively protect freshwater biodiversity, it will be necessary to target 18 protected areas towards freshwater habitats (see Target 11). Similarly, effectively managed 19 Marine Protected Areas have been shown to allow recovery of fish , particularly of 20 predatory species (Edgar et al. 2014), although the contribution of marine protected areas to 21 reduction in extinction risk has not been quantified. Protection of Alliance for Zero Extinction 22 sites (AZEs) and Important Bird and Biodiversity Areas has increased over time, although 23 progress has slowed recently (Figure 11.2F; Butchart et al 2012). Increasing efforts to protect 24 these sites will help to avert extinctions in the near future. 25 26 Species-level conservation needs to be complemented by landscape- or ecosystem-scale policy 27 measures aimed at reducing habitat loss, over-exploitation, pollution, and impact of invasive 28 species and pathogens. In terrestrial and inland water environments, habitat loss is by far the 29 greatest threat to animal and plant species (Hoffman et al. 2010). Therefore, actions aimed at 30 stopping habitat loss and mitigating fragmentation (see chapter 5), and actively restoring 31 degraded habitat (see chapter 15) will be critical for the persistence of many terrestrial and 32 inland water species. The highest density of endangered terrestrial species is in Southeast Asia, 33 owing to deforestation and consequent conversion to cropland and wood plantations, and to 34 direct exploitation of plant and animal species (Orme et al., 2005; Sodhi et al., 2010). For 35 terrestrial species, this region, together with other regions of high endemicity, such as global 36 plant biodiversity hotspots (Myers et al. 2000) and tropical islands, require immediate attention. 37 38 Effectively managed Marine Protected Areas are shown to result in significant recovery of fish 39 biomass, particularly for predatory species (Edgar et al. 2014), although the contribution of 40 marine protected areas to reduction in extinction risk has not been quantified. Increased 41 biomass in marine protected areas is also shown to increase ecosystem resilience to climate 42 change effect (Bates et al. 2013). In addition, ecosystem-based that

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 consider the fisheries management in the context of global and local environmental changes 2 and other human impacts should be implemented. 3 4 Invasive species are also a major threat: for example, for declining terrestrial invertebrates, 5 invasive species are listed as a major threat for 15% of species (Hoffmann et al., 2010). 6 Therefore, targeted efforts at eradicating invasive species, especially cats and rats on islands, are 7 urgently required to prevent imminent extinctions (see also Target 9). Although the contribution 8 of marine invasive species to extinction has not been quantified, marine invasion should be 9 prevented through a number of measures. These measures include effective control of ballast 10 water discharge, improved public education, monitoring and removal actions to eliminate or 11 suppress invasive species. 12 13 For more than 300 amphibian species affected by the chytrid fungus Batrachochytrium 14 dendrobatidis (Vredenburg et al. 2010), and several other critically endangered species with 15 very small and declining populations, captive breeding will be required until the causes of 16 decline are removed or mitigated sufficiently to permit reintroduction (Boyd et al. 2008; Stuart 17 et al., 2008). 18 19 Given the stress placed on native freshwater and marine fishes and invertebrates by 20 unsustainable harvesting, there is an urgent need to reduce such harvesting and to develop 21 more sustainable methods and approaches that would improve the status of many threatened 22 species and improve livelihoods for humans (see also targets 6, 7 and 14). Use of destructive 23 fishing methods, particularly on vulnerable habitats, should be prevented. By-catch of 24 vulnerable and endangered species such as some sharks, seabirds, sea turtles needs to be 25 substantially reduced. To improve current population trends it will be critical to complement 26 actions towards sustainable harvests with effective placement and management of protected 27 areas, some of which would be beneficially established through locally managed areas (see also 28 Target 11), to protect critical habitats and to restore abundance and increase resilience of 29 populations. 30 31 Habitats and species are rarely affected by single pressures, and therefore multiple coordinated 32 actions are required. Species-level management is therefore best coordinated through action 33 plans. These have been produced and updated for several taxonomic groups by the 34 International Union for Conservation of Nature 35 (https://www.iucn.org/about/work/programmes/species/publications/species_actions_plans/), 36 other NGOs and regional and local government authorities worldwide. A notable example is the 37 Global Strategy for Plant Conservation (GSPC), established by the Convention on Biological 38 Diversity and updated for the period 2011-2020 http://www.cbd.int/gspc/. The incorporation of 39 GSPC targets and species actions plans into NBSAPs (National Biodiversity Strategies And Action 40 Plans; cross-reference to Target 17) and their timely implementation will be critical to prevent 41 the extinction of many known threatened species. 42

SBSTTA Review Draft GBO4 – Technical Document – Target 12 DO NOT CITE

1 2.b. Costs and Cost-benefit analysis 2 3 Global estimates of the costs of meeting Target 12 suggest that US$3.4 to 4.8 billion will be 4 required per year (McCarthy et al., 2012; High Level Panel, 2014). This estimate was based on 5 extrapolation of the estimated cost of actions needed to improve the conservation status (Red 6 List status) of a sample of 211 threatened bird species combined with data on the relative costs 7 of conservation actions for birds and a wide range of other taxa (McCarthy et al., 2012). 8 Assuming that conservation actions undertaken for each species are entirely independent of 9 one another, it is estimated that improving the status of all bird species will cost $1.23 billion 10 per year (McCarthy et al., 2012). Recognizing that some conservation actions will benefit 11 species other than the target species, total costs are estimated at $0.88billion per year 12 (McCarthy et al., 2012). Extrapolating these costs from the 1,115 globally threatened bird 13 species to the 13,452 other known threatened species, it is estimated that improving the status 14 of all known threatened species will cost between $3.41 billion and $4.76 billion per year 15 (McCarthy et al., 2012). Current funding is only 12% of that required (McCarthy et al., 2012). 16 17 Quantifying the total value of the benefits provided by biodiversity to human society, and thus 18 the economic benefits of preventing extinctions and meeting Target 12, is impossible. However, 19 almost all analyses that have been carried out have suggested that the benefits of conservation 20 actions outweigh the costs. For example, pollination services provided by species have 21 been estimated to be worth $19 to 21 billion per year in the alone (High Level 22 Panel, 2014). Furthermore, it has been estimated that 2.5% to 16% of all jobs in the European 23 Union depend on the environment to some degree and that 5.8% of jobs in sub-Saharan Africa 24 depend on tourism, much of which is nature-based (High Level Panel, 2014). It has been 25 estimated that a network of protected areas that adequately conserved biodiversity would 26 achieve a benefit-to-cost ration of 100:1 (Balmford et al., 2002). 27 28 29 3. What are the implications for biodiversity in 2020? 30 31 Extinction of species, both local and global, will have profound effects on ecological 32 communities more broadly and on the functioning of ecosystems. The non-random loss of 33 species from ecological communities leads to those communities becoming homogenized and 34 dominated by certain functional types of species (Newbold et al., in press). The loss of key 35 species from communities can lead to altered interactions among species and ultimately to 36 trophic cascades (Estes et al., 2011). Finally, the local extinction of species from ecological 37 communities will impair the functioning of ecosystems: recent meta-analyses have shown that 38 more diverse communities function more resiliently over space and time, in the face of 39 environmental changes (Isbell et al., 2011). 40 41

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1 4. What do scenarios suggest for 2050? 2 3 Land-use change and over-exploitation will remain the major drivers of terrestrial species loss 4 until 2050, but with climate change increasing in importance over time (Alkemade et al., 2009; 5 Collen et al., 2014). Most of the Rio+20 scenarios (Netherlands Environmental Assessment 6 Agency, 2010) predict further declines in population trends of species and in the average local 7 diversity of ecological communities, and further increases in species’ extinction risk, although 8 these changes are slowed or in some cases reversed under scenarios that assume some sort of 9 mitigation efforts (consumption or technology changes) (Figure 12.3). 10 11 Climate change may affect species directly, through their physiological tolerance, or indirectly 12 through changes in vegetation (Powell & Lenton, 2013). Marine species are also threatened by 13 ocean acidification and hypoxia (Vaquer-Sunyer & Duarte, 2008; Godbold & Calosi, 2012). The 14 combined effects of these stressors may further exacerbate the effects of climate change on 15 marine biodiversity (Mora et al. 2013). The frequency and intensity of extreme climate events is 16 also likely to have a major impact on future fisheries production in both inland and marine 17 systems. Shifts in the migration phenology of many species important for commercial and 18 recreational fisheries have been attributed to climate change, including: Pacific salmon (Quinn 19 and Adams 1996), (Juanes et al. 2004) and smelt (Ahas and Aasa 2006). There 20 are strong interactions between the effects of fishing and the effects of climate because fishing 21 reduces the age, size, and geographic diversity of populations and the biodiversity of marine 22 ecosystems (Brander 2007), which makes species more vulnerable to the potential effects of 23 climate change. Inland (freshwater) fisheries are additionally threatened by changes in 24 precipitation and water management (Palmer et al. 2008; Strayer and Dudgeon 2010). 25 26 In all environments, synergistic effects of multiple drivers could further increase biodiversity 27 loss. For example, the impact of habitat loss on species has been shown to be worsened by 28 climate change (Mantyka‐Pringle et al. 2012), the invasion and spread of exotic plants has been 29 shown to be more likely given higher rates of land-use change (Chytrý et al. 2012). These results 30 suggest that future biodiversity assessments should consider the interacting effects of multiple 31 threats to biodiversity loss, rather than treating the effects of drivers as being additive. 32 Distribution shifts driven by climate change will alter biodiversity patterns (Lawler et al., 2009) 33 and may affect trophic interactions, although the implications of the latter for extinction risk are 34 not yet clear. 35 36 Biodiversity in some , such as coral reefs (cross-reference to Target 10), is 37 particularly sensitive to projected climate change and ocean acidification. At a global scale, the 38 potential impact of climate change on freshwater biodiversity remains poorly understood, but is 39 projected to present a growing challenge to the integrity and function of freshwater systems 40 (Dudgeon et al. 2006). 41

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1 In the technical report on modelling and scenarios for the Global Biodiversity Outlook 3 (Leadley 2 et al., 2010), models predicting future changes (to 2050) in extinction rates, average abundance 3 of species within ecological communities, and species distributions were reviewed. In summary: 4 projected extinction rates ranged from values similar to current ones (for models of projected 5 species-specific habitat loss) to two orders of magnitude larger (for models based on the 6 species-area relationship); models of projected species abundance (all based on the GLOBIO 7 model, Alkemade et al. 2009) predicted a mean decline of 9-17% in abundance by 2050; for 8 both species loss and decrease in abundance, the socio-economic scenarios reviewed only 9 made small differences in the predicted outcomes; all studies of changes in species distributions 10 (mostly based on niche models or global vegetation models) predict distributional shifts that 11 result in changes of biotic communities and potentially the creation of new communities, yet 12 there is great uncertainty on the rate and extent of change. 13 14 Since the publication of the Global Biodiversity Outlook 3, several studies have advanced our 15 understanding of biodiversity scenarios for 2050. 16 17 There is a consensus that there will be widespread local extinctions of species in both marine 18 and terrestrial environments, driven by climate change (Fig. 12.4; 12.5; Cheung et al. 2009; 19 Bellard et al. 2012), which are also likely to trigger cascade effects through co-extinctions of 20 dependent species (Brook et al. 2008), which could result in loss of ecosystem services (Hooper 21 et al. 2012; Tilman et al. 2012). 22

23 24 Figure 12.4. Projections biodiversity loss owing to climate change (and other drivers). The width of the 25 box indicates the generality of the predictions with respect to spatial scale and taxonomic breadth. The 26 box is delimited by the upper and lower boundaries of the intermediate scenario, while the whiskers 27 indicate the highest and lowest biodiversity losses across all scenarios. The highest estimates of local 28 losses are obtained when considering direct effects of climate on species by projecting their bioclimatic 29 envelope (e.g. Thomas et al. 2004; Thuiller et al. 2005) and at the lowest end when considering only

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1 indirect effects through changes in land cover (Jetz et al., 2007). Reproduced from Bellard et al. (2013). 2 Note, this figure needs to be replaced with a high-resolution version during copyediting. 3

4 5 Figure 12.5. Proportion of exploited marine fishes and invertebrates (1066 spp.) predicted to become 6 locally extinct given predicted climate change under the SRES A2 emissions scenario by 2050, relative to 7 2000. Adapted from Cheung et al. (2009). Note: updated versions of these models are still being run but 8 will be ready in time for the final version. 9 10 Species can survive climate change by shifting their ranges or by adapting, either through 11 evolutionary change (i.e. changes in behavioural, physiological or ecological traits) or through 12 phenotypic plasticity (i.e., the species already possess the required traits to survive under new 13 climatic conditions and these traits are selected for within the existing pool). 14 15 For terrestrial species, the velocity of climate change (Loarie et al. 2009) is expected to outpace 16 the dispersal ability of most species, across several studied taxa (Bertrand et al. 2011; Devictor 17 et al. 2012; Schloss et al. 2012). Species with narrow altitudinal ranges and low thermal 18 tolerance, especially those inhabiting high mountains, are predicted to incur local extinctions in 19 several regions of the world (Laurance et al., 2011; Dullinger et al., 2012). Furthermore, for 20 terrestrial species to adapt evolutionarily to climate change would require rates of niche 21 evolution that are more than 10,000 times faster than those typically observed (Quintero & 22 Wiens 2013). However, a recent study revised upwards many previous estimates of species 23 ability to shift their range (Chen et al. 2011), and several marine and freshwater groups appear 24 able to keep pace with climate change (Kappes & Haase 2012; Kinlan & Gaines 2003). 25 26 Projected changes vary substantially in different parts of the world owing to variation in the 27 different drivers of biodiversity change. Under business-as-usual scenarios, particularly strong 28 declines are predicted in Africa, because of expanding agriculture, livestock production and 29 forestry (Jetz et al. 2007; Visconti et al. 2011; Fig. 12.6). Large declines of terrestrial species are 30 also predicted in the Amazon, a region with very low spatial climatic gradients that is predicted 31 to experience no-analog future climates (Williams et al. 2007; Fig. 12.6), and which is rich in 32 vertebrate species with high intrinsic vulnerability to climate change (Foden et al. 2013). Finally, 33 large declines and turnover rates are predicted in areas rich in elevational specialists (Laurance

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1 et al. 2011) such as the Andes for mammals (Lawler et al. 2009; Schloss et al. 2012) and the 2 Himalaya for birds (Jetz et al. 2007). For marine fish and invertebrate species the areas with 3 highest expected local extinctions by 2050 are sub-polar regions, the tropics and semi-enclosed 4 seas (e.g. the Mediterranean and the Red Sea; Fig. 12.5); while the areas with highest number 5 of expected invasions are the Arctic and Southern Ocean (Cheung et al. 2009). Inland waters 6 remain one of the most highly threatened ecosystems (Vörösmarty et al. 2010), and regardless 7 of the land use change scenario considered the biodiverse catchments of the southeast United 8 States are expected to see dramatic urban expansion (Martinuzzi et al. 2013b). Under some 9 scenarios the southeast United States is also expected to see crop expansion that would further 10 fragment and pollute critical freshwater habitats (Martinuzzi et al. 2013b). 11

12 Figure 12.6. Modelled change in several measures of biodiversity (average population trends of carnivore and ungulate species, calculated following the methods used by the Living Planet Index – LPI; Visconti et al., in review; average local species richness; Newbold et al., in prep.; and average local abundance of species; Alkemade et al., 2009) between 2000 and 2050 under a baseline scenario (left panels) and the ‘technology change’ Rio+20 scenario (right panels) (scenarios presented in Netherlands Environmental

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Assessment Agency, 2010). Local abundance and LPI measures included both direct effects of climate change and indirect effects (through land cover change). Local species richness change accounted for indirect effects. For these maps, LPI was calculated for each grid cell by aggregating population trends in projected population size within the cell for all carnivore and ungulate species. This contrasts with the LPI calculations in figure 12.3 where the trend in population size for each species were calculated globally and aggregated across all species. In LPI calculations, the local extinctions where replaced with 1% of the maximum population size to avoid calculating a geometric mean with a zero. Because changes in LPI are sensitive to species richness, grid cells with <10 species of carnivore and ungulate species where removed from the LPI analyses. 1 2 A number of studies have focused on particular regions. Range shifts and contractions are 3 predicted by 2050 for two-thirds of European breeding birds (Barbet-Massin et al. 2012), for 4 species in France (Cheaib et al. 2012) and for Alpine plants (with an almost 50% reduction 5 in range size by 2100; Dullinger et al. 2012). Contractions and shifts in the distributions of 6 European plants, birds and mammals are expected to be similar across taxonomic groups, 7 because sensitivity to climate change is not strongly correlated with phylogeny (Thuiller et al. 8 2011). In Australia, 67% of Australian savanna bird species ranges are projected to decrease. 9 However, migratory and tropical-endemic birds are predicted to benefit from climate change 10 with increasing distributional area. Richness hotspots of tropical savanna birds are also expected 11 to move, increasing in southern savannas and southward along the east coast of Australia, but 12 decreasing in the arid zone (Reside et al. 2012). 13 14 Long-term projections of land use change under the Rio+20 scenarios indicate that habitat loss 15 will continue to pose a threat to biodiversity under the business-as-usual scenario (Fig. 12.3 A- 16 D), particularly in Africa and Central Asia (Figure 12.6; Visconti et al., submitted). Regional 17 models that predict the impacts of land-use change on species extinction similarly predict a 18 worsening situation under business-as-usual scenarios: in the Brazilian Amazon 10% of species, 19 on average, are predicted to become locally extinct as a result of forest loss, with a further 27% 20 committed to extinction (Wearn et al., 2012). In the mitigation scenarios, short-term trends in 21 the diversity of ecological communities (see previous section) are continued (Fig. 12.3 A, D; 22 Newbold et al., in prep.), driven by continued land-use change, which is captured better than 23 climate change in the GLOBIO and PREDICTS model frameworks. For population trends and 24 extinction risk of carnivores and ungulates, the short-term gains begin to be reversed by 2050 as 25 climate change overcomes the beneficial effects of reduced land-use change (Figure 12.3 C, D; 26 Visconti et al., 2011). Similarly, scenarios for the Brazilian Amazon that predict reduced rates of 27 deforestation lead to reduced local extinctions of species (by 37-57% for actual extinctions and 28 61-82% for , depending on the scenario adopted; Wearn et al., 2012). 29 30 31 32

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1 5. Uncertainties 2 3 There are, unavoidably, many uncertainties in the various methods used to make predictions 4 about the future of biodiversity. However, all of the extrapolations and models reviewed here 5 confer a high degree of confidence in the assertion that current trends in extinction risk of 6 species, and in the conservation status of species and ecological communities, are strongly 7 negative. Furthermore, all of the models employing business-as-usual scenarios predict further 8 strong declines throughout this century. 9 10 Status and trends 11 12 Estimates of past extinction rates are uncertain for several reasons. First, the number of field 13 biologists is small relative to the number of species, and therefore extinction rates can be 14 estimated only for a few well-studied and possibly atypical groups (mainly vertebrates), while 15 extinctions can go undetected in species-rich but poorly studied groups (Balmford et al. 2003). 16 Second, being confident that a species is actually extinct requires levels of survey effort that 17 very often exceed available resources even for very well-studied groups (Butchart et al., 2006; 18 Scott et al., 2008). Finally, species do not immediately respond to human pressures, and 19 extinction can be delayed for centuries (Tilman et al., 1994). Even for species that are almost 20 certainly extinct, knowing exactly when extinction occurred is difficult, and most known 21 extinctions are accompanied by a range of likely dates. 22 23 All of the measures used to assess status and trends were biased toward vertebrate species in 24 terrestrial environments, and therefore our knowledge of recent changes in the status of 25 invertebrate species, and all species in freshwater and marine environments, is much more 26 limited. 27 28 Projections 29 30 There are fundamental differences between extrapolating the past trend of an indicator into the 31 future, and modelling future trends based on scenarios of the underlying pressures, which leads 32 to large differences in projected outcomes. The statistical extrapolations used to project trends 33 to 2020 assume that the extent to which targets will be achieved is only a function of the inertia 34 in the underlying mechanisms that underpin the trends, while the models based on scenarios of 35 how the pressures will change explicitly project the underlying mechanisms underpinning the 36 trends which therefore can take different trajectories respect to the past. For example in the 37 case of the Red List Index, the extrapolations assumed a constant trend in the indicator, and 38 therefore a further increase in extinction risk, while the more process-driven models assumed a 39 constant trend in the pressures, a slower short-term decline in population size and therefore a 40 reduction in extinction risk. 41

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1 For scenario-based modelling, there is great variation in projected future extinction rates both 2 within and between studies, with three factors explaining much of this variation. First, the 3 degree of land use and climate change predicted by different scenarios explains much of the 4 variation in projected extinctions within studies. For example, Thomas et al. (2004) projected 5 vertebrate extinctions are 11 to 34% for 0.8° to 1.7°C global warming versus 33 to 58% for 6 >2.0°C warming (the magnitude of these predicted losses has been disputed since, and they are 7 based on models, which are subject to numerous sources of uncertainty – 8 see e.g. Thuiller et al., 2004; Araújo & Guisan, 2006). Second, an important contribution to the 9 broad range of projections within studies is different assumptions about species life-history 10 traits, especially displacement rates (e.g., the highest projected extinction rates are 38% with 11 unlimited migrations rates versus 58% with no migration in Thomas et al. 2004) and habitat 12 specificity (e.g. in Malcolm et al. 2006 the highest extinction rates are 7% for broad habitat 13 specificity versus 43% for narrow habitat specificity), emphasizing the need for research on 14 these fundamental aspects of species and their incorporation into global models (Foden 15 et al. 2013; Thuiller et al. 2008). Third, there is a substantial degree of uncertainty in the climate 16 and land-use change models themselves, which contributes to uncertainty in projected rates of 17 extinction or biodiversity loss. 18 19 Species response models 20 21 A large fraction of the variation in predicted outcomes for biodiversity among studies arises 22 from differences between modelling approaches. For example, Sekercioglu et al. (2008), using a 23 logistic model of extinction risk as a function of range size, predicted ten times more birds 24 extinction than Jetz et al. (2007), using a linear, mechanistic model of extinction as a function of 25 habitat suitability. The assumed linear relationships between habitat and population decline, 26 which underlie many predictions of global extinctions (e.g. Jetz et al., 2007; Visconti et al., in 27 review), may lead to underestimates of species global extinction risk (Di Fonzo et al. 2013). 28 29 Studies using bioclimatic envelope models tend to project larger range contractions and 30 increase in extinction risk under future climate change than other approaches. This is likely to 31 be in part due to the largely untested assumption that species will not survive climatic 32 conditions never experienced before, whereas species might adapt to climate change through 33 phenotypic plasticity or micro-evolution (Charmantier et al. 2008; Boutin & Lane 2014). 34 However, there are a number of other known limitations of species distribution models, which 35 could contribute to their predicting relatively large changes (Araújo & Guisan, 2006). 36 37 Species-area relationship models tend to give larger measures of extinction risk (Pimm & Raven 38 2000; Thomas et al. 2004) because they are based on the accumulation of species with 39 expanding sampling area, which may not accurately reflect the scaling of species extinction with 40 reduced area (Lewis, 2006; He & Hubbell 2011; but see e.g. Pereira et al., 2012; Pimm & Brooks, 41 2013), and have in at least one case (Thomas et al., 2004) been criticized for misapplying the 42 Red List criteria (Akçakaya et al., 2006). Species-area relationships also measure species

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1 committed to extinction. However, the lag time between being committed to extinction and 2 actually going extinct may range from decades to centuries (Stork, 2010; Wearn et al., 2012). 3 4 Spatially-explicit models probably make more conservative and robust 5 estimates of extinction risk by avoiding several of the assumptions described above (Pearson et 6 al. 2014), but are computationally intensive and require data available for only a fraction of 7 species. 8 9 Global change models 10 11 Additional uncertainty in model projections arises from their coverage of threats affecting 12 species. The LPI and RLI projections for large mammals (Figure 12.3; 12.6) only accounted for 13 land use and climate change despite direct persecution being an important threat for these 14 species. The PREDICTS model projections (Figure 12.3; 12.6) were based on only land-use 15 change and indirect impacts of climate change through biome shifts. None of the terrestrial 16 models reviewed here accounted for direct harvesting of species, and the Rio+20 scenarios did 17 not include future projections of human population density, which could act as a proxy for 18 pressure from direct harvesting in terrestrial environments. The qualitative differences between 19 the Rio+20 scenarios used here are unlikely to be affected by the inclusion of direct harvest, 20 because several factors (low food security, poor access to food markets and a high proportion of 21 people living in rural areas) mean that direct harvest of species is likely to be greatest in the 22 business-as-usual scenario. 23 24 For marine species, the projections (Figure 12.5) focused on climate change as a driver. Addition 25 of other threats, particularly fishing and habitat loss might modify the rate of local extinction. 26 27 Finally, there is uncertainty in the outputs from climate or Earth System models used to drive 28 the projections, particularly at the finer spatial scale often used in biodiversity modelling (Stock 29 et al., 2011). Models often do not consider trophic interactions in detail, or the scope for 30 evolutionary adaptation. Overall, based on fundamental biological and ecology theory, 31 observations and model projections, the large-scale direction of local extinction indicated by 32 model projections is more robust, while the projected magnitude and finer-scale patterns more 33 uncertain. 34 35 36 37 38

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1 6. Dashboard – Progress towards Target1 2 3 Target Elements Status Comment Confidence Target Extinction of known Further extinctions likely by Low 12 threatened species has 2020, e.g. for amphibians and been prevented fish. For bird and mammal species some evidence

measures have prevented extinctions The conservation status of Red List Index still declining, no High those species most in sign overall of reduced risk of decline has been extinction across groups of improved and sustained species. Very large regional differences 4 5 6 Complied by: Tim Newbold, Piero Visconti, Carlo Rondinini, William Cheung and Stephanie 7 Januchowski-Hartley, with contributions from Andy Purvis and Stuart Butchart. 8 Extrapolations: Derek Tittensor 9 NBSAPs and National Reports: Kieran Mooney / CBD Secretariat 10 Dashboard: Tim Hirsch 11 12 6. References 13 14 Akçakaya, H. R., Butchart, S. H. M., Mace, G. M., Stuart, S. N. & Hilton-Taylor, C. (2006) Use and misuse of the IUCN 15 Red List criteria in projecting climate change impacts on biodiversity. Global Change Biology, 12, 2037-2043. 16 Ahas, R. & A. Aasa. 2006. The effects of climate change on the phenology of selected Estonian plant, bird and fish 17 populations. International Journal of Biometeorology 51:17-26. 18 Alkemade et al. (2009). GLOBIO3: A framework to investigate options for reducing global terrestrial biodiversity 19 loss. Ecosystems 12: 374-390. 20 Allan, J.D. 2004. Landscapes and riverscapes: the influence of land use on stream ecosystems. Annual Review of 21 Ecology Evolution & Systematics 35: 257-284. 22 Araújo, M. B. & Guisan, A. 2006. Five (or so) challenges for species distribution modelling. Journal of 23 33: 1677-1688. 24 Balmford, A., R. E. Green, and Jenkins, M.. 2003. Measuring the changing state of nature. Trends in Ecology and 25 Evolution 13: 326-330. 26 Barbet-Massin, M., Thuiller, W. & Jiguet, F. 2012. The fate of European breeding birds under climate, land-use and 27 dispersal scenarios. Global Change Biology 18: 881-890.

1 This provides a current assessment of progress towards the Aichi Biodiversity Target" based on the material presented in this chapter and the expert judgement of the authors of the GBO-4 Technical Report. It is subject to change as additional material becomes available, including information from national reports, NBSAPs and the BIP partnership.

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