and (d) South Africa and surrounding sub-Antarctic islands. Not shown are Galapagos penguins nesting only on the Galapagos Islands. Panel a is
projected using South Pole Lambert Azimuthal Equal Area. Panels b, c, and d are projected using the World Geodetic System 1984. Basemap from
limitation to be addressed for expanding and strengthening such analyses in the future. First, the limited overlap between the METT and the LPD data sets shows a lack of coordi- nation between the collection of data on PA interventions and outcomes. Second, our ﬁnal model accounts for only a relatively small fraction of the variance observed in the data. Managers would be ill-advised to use the patterns we report to guide funding in speciﬁc PAs or to discount the role of plan- ning, enforcement, or the involvement of local stakeholders in speciﬁc PA management. Third, the LPD also has shortcom- ings in its ability to assess PA performance, because positive slopes are not a direct measure of conservation success but only of growing populations. Similarly, the LPD lacks infor- mation on equivalent population trends outside PAs, making it impossible to fully discount the eﬀect of location and history of the PA in trends obtained. Fourth, while the wide appli- cation of the METT makes it a potentially powerful tool for understanding conservation input and outputs, it is not without its limitations. Lack of uniformly applied guidelines for the implementation of METT assessment can lead to individual PAs interpreting similar conditions diﬀerently (Cook & Hock- ings, 2011). Similarly, PA managers and other stakeholder
Additionally, we investigated whether hotspots of endemism are associated with PAs. According to Crisp et al. (2001), a species is endemic if it occurs only in a defined area (i.e., continent, region, or ecoregion). An area has high endemism if it contains many range-restricted species. We first determined which penguin species are endemic to globalterrestrial ecoregions, representative of distinct biotas and likely reflecting species distribution (Olson et al. 2001). By overlaying ecoregion polygons (an ArcGIS layer package) with penguin ranges, we identified all ecoregions within which a species is located. We considered a species endemic to an ecoregion if that species is found only in that ecoregion. To determine global endemism, we first calculated the Corrected Weighted Endemism (CWE) for each grid cell, in order to reduce the strong effect of species richness and emphasize areas that have a high proportion of species with restricted ranges. CWE represents the weighted endemism (for each grid cell, the sum of the reciprocal of the total number of grid cells that each species occurs in) divided by the total number of species in that cell (Crisp et al. 2001). This index ranges from 0.0 to 1.0, corresponding to 0-100% of the species occurring within that cell are range-restricted to that cell (Laffan & Crisp 2003). We performed all analyses using the Analysis and Spatial Statistics tools and SDMToolbox (CWE) of ArcGIS 10.2.2 (Brown 2014; ESRI 2014).
Road construction, improvements, and expansion are bringing frontier regions of the world into the global economic sphere at an accelerated pace. With this comes rapid habitat destruction and fragmentation that negatively impacts bio- diversity, and biodiversity experts have long lamented that species are going ex- tinct before science even has a chance to describe or study them. With time run- ning short, it is essential to target the collection of species data in areas where there are spatial gaps in collections and where we know road development is likely to occur. We also must consider the role protectedareas are playing in protecting biodiversity in relation to road development. The information for all of this exists, and if properly assembled in a GIS (Geographic Information Sys- tem), scientists could more efficiently target collection efforts and the evaluation of the role of protectedareas in species conservation. Unfortunately, species oc- currence information is often not readily available in digital form. Rather, much of that information is contained only on specimen tags in museums. Efforts by organizations such as the GBIF (Global Biodiversity Information Facility) in re- cent years are emblematic in making millions of species occurrence records di- gitally available. GBIF serves >6.4 × 108 occurrence records for >1.6 × 106 spe- cies, but it is an ongoing effort to fill gaps, address biases and make the data more complete  . Among the groups least represented in GBIF are insects (<8% of the total set of records), despite their high diversity and ecological im- portance.
In Botswana, 17% o f the land surface area is designated as National Parks and Game Reserves and a further 21% is designated as Wildlife Management Areas (Government o f Botswana, 1975; IUCN, 1987a). Elsewhere protectedareas play an important role in fisheries management, research, single species conservation and habitat protection (Gardner & Struthers, 2012). There are many examples o f the benefits o f protectedareas in fisheries management, e.g., arresting and possibly reversing the global and local decline in fish populations and productivity by protecting critical breeding, nursery and feeding habitats (Kenchiton et al., 2003) and increased abundance and spawning biomass (Bohnsack, 1998). In South Africa for example, Marine ProtectedAreas (MPAs) typically contain fish o f large size and higher abundance than adjacent fished areas (Cowley et al., 2002), while in Kenya, species’ richness was significantly higher in a Marine Reserve than beyond reserve boundaries (Cote et al., 2001). As a result, no-take Marine ProtectedAreas are recognised as an important strategy for slow growing species with limited distribution as well as for stock rebuilding o f overexploited species (Cowley et al., 2002). The role and potential importance o f protectedareas in fisheries management, in freshwaters is, however, not well researched.
This work was supported by the National Socio- Environmental Synthesis Center (SESYNC) under funding received from the National Science Foun- dation DBI-1052875, as part of the working group “Solving the Mystery of Marine Protected Area (MPA) Performance: Linking Governance, Conser- vation, Ecosystem Services and Human Well Being.” David Gill was supported by the Luc Hoffmann Institute and SESYNC. Alfonso Lombana, Gonzalo Cid, Ruth Gates, Anne Henshaw, Hannah Thomas, and Stephen Woodley also provided valuable contributions. Michael Webster and Carly Strasser provided valuable feedback on the manuscript, and Dawn Pointer McCleskey and Molly Spiegel assisted with references. This manuscript is an output of the IUCN World Commission on ProtectedAreas–Species Survival Commission Joint Task Force on Biodiversity and ProtectedAreas. This manuscript is contribution #10 of the research initiative Solving the Mystery of MPA Performance.
Another connection is the “citizen science” approach (Fig. 2). People engaged in this kind of initiative usually do not directly depend on the biodiversity monitored as a resource, so they do not implement management solutions on the basis of research ﬁndings (Kennett et al., 2015). This kind of monitoring has great poten- tial to engage many people in biodiversity projects in collaboration with scientists. Three cases that can exemplify this potential are the following: (i) the Brazilian Road Ecology Center monitors road mor- tality due to animal–vehicle collisions, including protectedareas, through a system called Urubu Mobile which has more than 16,000 volunteers (Bager et al., 2016); (ii) in a call for volunteers in 2015, Parque Nacional da Serra da Bodoquena (Fig. 1) received more than 200 candidates for participation in the Monitora Program; and (iii) the Wikiaves system (www.wikiaves.com.br) has bird records from almost all Brazilian protect areas collected by birdwatch- ers. Although both participatory monitoring and citizen science approaches have their own practical advantages and disadvantages (Kennett et al., 2015; Dillon et al., 2016), considering the perspec- tives of connection with the Monitora Program, we believe that the Multiple Evidence Base Approach in a pressure–state–response model and multi-layer platform provide a common ground to pro- mote these dialogs. The number of multi-layer platforms with ecological, social and economic data sets is rapidly increasing, rang- ing from initiatives focused on speciﬁc territories (e.g. SOMAI – Sistema de Observac¸ ão e Monitoramento da Amazônia Indígena - SOMAI, 2018) to global datasets such as Google Public Data Explorer (Google, 2018).
Science and planning for marine conservation is a complex, cross-disciplinary task. Marine conservation involves many objectives and there is much uncertainty in how ecosystems and their human populations behave. It is therefore important for environmental managers to access the best available information and expertise and to support research that improves conservation outcomes. This thesis demonstrates through several case studies, how the systematic use of information, decision support tools and consultation can be used to identify sites for marine protectedareas (MPAs) and plan for future research. The studies differ in their immediate goals and the information available. All however, benefit from linking explicit objectives to spatial databases and tools that allow scientists, managers and communities to explore and evaluate management scenarios using realistic data.
These five data sets were ‘unioned’ in GIS overlays to produce physical categories formed by the intersection of the different classes in each data set. However, if more than a few classes within each data set were used, many different categories and spurious overlaps resulted. If a few broad classes in each data set were selected on the basis of their presumed biological importance, this problem was greatly reduced, but the resulting patterns were still difficult to substantiate in terms of species assemblages or ecosystem processes (Figure 3.10). Moreover, geophysical classifications of the region had already been proposed (Hopley 1982, 1983, Hopley et al. 1989) and it was apparent that extensive data sets for many taxa and descriptions of cross shelf and other spatial patterns in biodiversity existed for at least some areas (Done 1982, Dinesen 1982, 1983, Williams 1982, Williams and Hatcher 1983, Riddle 1988). Several institutions in the region also had well developed research programs and scientists with experience in these waters. Some of these scientists (T. Done, D. Williams and A. Ayling) had already provided delphic maps of patterns in the distributions of corals, fishes and benthos for the marine park and there were several regional data sets suitable for numerical modelling. A systematic search for all available broad scale biological and physical data sets of the region was therefore conducted in conjunction with interviews with over 70 marine science and reserve design experts. A questionnaire (Appendix 6) was sent to the scientists prior to the interviews, and the results recorded and transcribed for later reference. The interviews assisted in providing: • access to additional data sets
The PA-TAMCO Analytic Model is technically based on the processing and analysis of Remote Sensing images and land cover mapping for the identification of land cover classes and periodical land cover changes [54, 55, 56, 57]. The Remote Sensing data can be of low, medium or high spatial resolutions; depending on their availability and cost, the size of a specific protected area and the degree of accuracy expected for the assessment. Preferably, the data are acquired at the beginning of the dry season to avoid noisy images and allow maximal differentiation of land cover classes, especially between herbaceous and woody [26-57]. The importance and interest of Remote Sensing data and GIS techniques associated with eco-landscape structure tools for the study and monitoring of natural ecosystems are widely recognized [58, 54, 59] compared to in situ or direct methods which are costly and technically demanding .
Research on the conservation of biodiversity has become increasingly important in the last two decades, particularly in the face of threats such as habitat loss and fragmentation [ 1 – 3 ], climate change [ 3 – 5 ], invasive species [ 6 , 7 ], and many others. Humans are responsible for several threats to wildlife, primarily habitat loss. As the human population continues to grow and human needs increase, many animals will continue to suffer due to habitat loss. Of all the biodiversity “hot- spots” remaining in the world, only one-third of the historic habitat supporting the high biodi- versity in these areas remains [ 1 ]. Although habitat loss and degradation affects all wildlife, it has drastic effects on birds. Nearly 85% of the globally threatened bird species [ 8 ] are significantly threatened by habitat loss. Such effects on birds are also evident at localized scales, for example Iowa has lost 57% of historic forest habitat, 95% of historic wetland habitat, and 99.9% of historic grassland habitat since European settlement [ 9 ]. As a result, nearly 30% of Iowa’s breeding and migratory birds are considered Species of Greatest Conservation Need (SGCN), and a majority of these species are also of heightened conservation status in the Midwest United States [ 10 ]. Funding for the conservation of biodiversity and habitat management is severely lacking [ 11 , 12 ] despite the increasing threats mentioned above. Therefore, identification of priority areas (i.e., areas where the most species can be benefitted with the least amount of cost) is critical to effec- tive conservation planning [ 11 , 13 ].
At the pan-tropical scale, 65% of all PAs reduced forest loss (that is P < 1), with 49% of reserves classed as effective (defined as P<0.75), 33% as highly effective (P<0.5) and 19% as extremely effective (P < 0.25). In the subset of PAs with similar slope and elevation the respective numbers were 60%, 41%, 27% and 14%. This confirms that a fraction of reserves are only effec- tive because of their terrain. A meta-analysis of previous studies found a slightly better perfor- mance than we report here, with 82% of studies reporting lower rates of habitat loss within PAs compared to control areas .  found that 40% of PAs experienced major management issues and were unlikely to deliver effective conservation. At the continental scale, we found that Australasia had the largest fraction of effective PAs (76%, 68% in subset), followed by the Neo- tropics (57%, 52% in subset), with Africa (48%, 43% in subset) and Asia (42%, 31% in subset) having fewer effective reserves (Table 1). In Asia the fraction of effective reserves is much lower in the subset of PAs with similar slope and elevation in inner and outer buffers. This suggests that PAs in Asia are less effective when there is no protection given by steep slopes and elevation.
However, as conservation science continues to evolve, and approaches to conservation planning become more systematic, inadequacies and deficiencies in existing protected area networks are becoming apparent (Shaw et al., 2014; Watson et al., 2014). The Antarctic continent has not escaped scrutiny, and recently the role of Antarctic Specially ProtectedAreas (ASPA’s) in achieving both Antarctic conservation objectives and globalconservation targets has been questioned (Shaw et al. 2014; Hughes et al 2013). With significant inadequacies identified in both placement and management, it is timely that the existing ASPA system be reviewed in accordance with the underlying principles of effective conservation planning, and, that its efficacy in 1) designating areas that adequately represent Antarctic biodiversity, and 2) separating these from threatening processes, be assed.
Both C-Plan and Marxan provided similar maps of irreplaceability that focussed on those habitats found at a limited number of locations. Both tools indicated high irreplaceabilities for the areas between Byron Bay and Julian Rocks, in the Brunswick River estuary and for distinctive rocky shore types at Cape Byron, Broken Head and Lennox Head. Marxan was however, able to effectively aggregate planning units into larger zones and generate a range of different reserve designs that minimised impacts on different commercial fisheries. What was surprising were the major differences between reserve designs produced using cost data for different fisheries, while still meeting conservation targets. This indicates that designs that aim to accommodate different commercial and other activities need give consideration to the individual differences among patterns of use. Unfortunately, because of time constraints, Marxan was only used to a limited degree in the workshops. The results however provided useful insights into the range of zoning options available and the potential impacts for different fisheries.
• Nine significant wetland remnants on the upper Parramatta River (Ermington Bay, Meadowbank Park, Yarralla Bay, Majors Bay, Mason Park, Homebush Bay, Silverwater Saltmarsh, Lower Duck River and Haslem's Creek) are listed on the register of the National Estate. Newington Wetlands is listed in the Directory Of Important Wetlands and includes mangrove and saltmarsh habitats bordering four brackish ponds. These areas were once part of extensive mangrove and saltmarsh wetlands on the Parramatta River. The saltmarsh communities are in good health and display a species composition uncommon in the Sydney area and include Samphire (Sarcocornia quinqueflora), Seablite (Suaeda australis), Sand Couch Grass (Sporobolus virginicus), the restricted saltmarsh species, Lampranthus tegens (small pig face), an important stand of native rush (Juncus kraussi), the Chenopod Halosarcia pergranulata and one of the largest remaining populations of the uncommon Wilsonia backhousei, which is at its northern limit in Sydney (ANCA 1996, Commonwealth of Australia 2003).
The surveys were performed in two reserves of Misiones province, separated by about 40 km: Reserva de Vida Silvestre Urugua-ı´ (RVSU) (25 u 599 S, 54u 059 W) and Campo Anexo Manuel Belgrano (CAMB) (26u 029 S, 53u 479 W), each representing the Paranaense Forest and Moist Forest with A. angustifolia, respectively (Figure 1). The reserves are differentiated by conserved surface, altitude, management degree, and vegeta- tion type. RVSU is a private natural reserve that covers 3,423 ha at ,200 m a.s.l. It was created in 1997 and previously used for selective logging until the 1970s. This reserve, now under strict protection, is part of one of the largest corridors of continuous original rainforest in the southern portion of the Atlantic Forest, a ‘green block’ of almost 6,000 km 2 . It is characterized by diversified forests, although trees of Balfourodendron riedelianum and Nectandra spp. dominate plant formations. CAMB is a governmen- tal forest reserve that covers 2,136 ha at ,600 m a.s.l. It was created in 1948 to protect native and planted populations of A. angustifolia. This rainforest is also characterized by an undergrowth of tree ferns (Alsophyla sp., Dicksonia sp., Trichipteris sp.) . However, in CAMB there are also plantations with exotic conifers (Pinus taeda). Therefore, this reserve is a mosaic of preserved and disturbed areas, isolated from other protectedareas and surrounded mainly by small farms (Figure 1).
national level are correlated with the Human Devel- opment Index 39 gives an indication of how manage- ment effectiveness varies globally, with developing countries showing lower management effectiveness. Studies have linked development to the quality of governance (see Box 2). However, the fact that man- agement effectiveness has been reported to improve with time gives cause for concern. In Madagascar, for example, management effectiveness appears to have increased, while the quality of governance has substantially decreased in connection with a polit- ical crisis. 14 In relation to this, it is important to recognize that time lags might be involved, that the adaptive idea of the PAME actually does work and strengthens the local institutions, even under more challenging national governance periods, or simply that the management effectiveness data are biased. In conclusion, studies are lacking and inference is difficult, and while indicators of good governance exist for most nations (Table 1), assessments of management effectiveness tend to be carried out at the local PA level. Thus, while national governance indicators could allow for global comparisons and an analysis of the role of governance quality in PA management effectiveness, there is a lack of under- standing of how governance quality at such a level is linked to variation in the quality of governance at subnational or local management levels.
Acid sulphate soil risk maps predict the distribution of acid soils based on an assessment of the geomorphic environment using 1:25,000 scale aerial photograph interpretation and extensive field and laboratory soil analysis. These soils occur naturally and only become a threat when oxidised through exposure to the air. This occurs when either the water table is lowered artificially or sediments are excavated. Most estuaries in the Hawkesbury Shelf bioregion have these soils present, but these are no risk while left undisturbed. The threat of acid release is related to the probability of inappropriate land use as well as the occurrence of the sediments themselves.