Threats from urban expansion, agricultural transformation and forest loss on global conservation priority areas

Including threats in spatial conservation prioritization helps identify areas for conservation actions where biodiversity is at imminent risk of extinction. At the global level, an important limitation when identifying spatial priorities for conservation actions is the lack of information on the spatial distribution of threats. Here, we identify spatial conservation priorities under three prominent threats to biodiversity (residential and commercial development, agricultural expansion, and forest loss), which are primary drivers of habitat loss and threaten the persistence of the highest number of species in the International Union for the Conservation of Nature (IUCN) Red List, and for which spatial data is available. We first explore how global priority areas for the conservation of vertebrate (mammals, birds, and amphibians) species coded in the Red List as vulnerable to each threat differ spatially. We then identify spatial conservation priorities for all species vulnerable to all threats. Finally, we identify the potentially most threatened areas by overlapping the identified priority areas for conservation with maps for each threat. We repeat the same with four other well-known global conservation priority area schemes, namely Key Biodiversity Areas, Biodiversity Hotspots, the global Protected Area Network, and Wilderness Areas. We find that residential and commercial development directly threatens only about 4% of the global top 17% priority areas for species vulnerable under this threat. However, 50% of the high priority areas for species vulnerable to forest loss overlap with areas that have already experienced some forest loss. Agricultural expansion overlapped with similar to 20% of high priority areas. Biodiversity Hotspots had the greatest proportion of their total area under direct threat from all threats, while expansion of low intensity agriculture was found to pose an imminent threat to Wilderness Areas under future agricultural expansion. Our results identify areas where limited resources should be allocated to mitigate risks to vertebrate species from habitat loss.Peer reviewe

User-Generated Geographic Information for Visitor Monitoring in a National Park : A Comparison of Social Media Data and Visitor Survey

Protected area management and marketing require real-time information on visitors’ behavior and preferences. Thus far, visitor information has been collected mostly with repeated visitor surveys. A wealth of content-rich geographic data is produced by users of different social media platforms. These data could potentially provide continuous information about people’s activities and interactions with the environment at different spatial and temporal scales. In this paper, we compare social media data with traditional survey data in order to map people’s activities and preferences using the most popular national park in Finland, Pallas-Yllästunturi National Park, as a case study. We compare systematically collected survey data and the content of geotagged social media data and analyze: (i) where do people go within the park; (ii) what are their activities; (iii) when do people visit the park and if there are temporal patterns in their activities; (iv) who the visitors are; (v) why people visit the national park; and (vi) what complementary information from social media can provide in addition to the results from traditional surveys. The comparison of survey and social media data demonstrated that geotagged social media content provides relevant information about visitors’ use of the national park. As social media platforms are a dynamic source of data, they could complement and enrich traditional forms of visitor monitoring by providing more insight on emerging activities, temporal patterns of shared content, and mobility patterns of visitors. Potentially, geotagged social media data could also provide an overview of the spatio-temporal activity patterns in other areas where systematic visitor monitoring is not taking place.Peer reviewe

Towards automatic detection of wildlife trade using machine vision models

Unsustainable trade in wildlife is one of the major threats affecting the global biodiversity crisis. An important part of the trade now occurs on digital marketplaces and social media. Automated methods to identify trade posts are needed as resources for conservation are limited. Here, we developed machine vision models based on Deep Neural Networks with the aim to automatically identify images of exotic pet animals for sale. We trained 24 neural-net models on a newly created dataset, spanning a combination of five different architectures, three methods of training and two types of datasets. Model generalisation improved after setting a portion of the training images to represent negative features. Models were evaluated on both within and out-of-distribution data to test wider model applicability. The top performing models achieved an f-score of over 0.95 on withindistribution evaluation and between 0.75 and 0.87 on the two out-of-distribution datasets (i.e., data acquired from a source unrelated to training data), therefore, showcasing the potential application of the model to help identify content related to the sale of threatened species on digital platforms. Notably, feature-visualisation indicated that models performed well in detecting the surrounding context in which an animal was located, therefore helping to automatically detect images of animals in non-natural environments. The proposed methods are an important step towards automatic detection of online wildlife trade using machine vision models and can also be adapted to study more broadly other types of online people-nature interactions. Future studies can use these findings to build robust machine-learning models.Peer reviewe

Social media reveal that charismatic species are not the main attractor of ecotourists to sub-Saharan protected areas

Charismatic megafauna are arguably considered the primary attractor of ecotourists to sub-Saharan African protected areas. However, the lack of visitation data across the whole continent has thus far prevented the investigation of whether charismatic species are indeed a key attractor of ecotourists to protected areas. Social media data can now be used for this purpose. We mined data from Instagram, and used generalized linear models with site- and country-level deviations to explore which socio-economic, geographical and biological factors explain social media use in sub-Saharan African protected areas. We found that charismatic species richness did not explain social media usage. On the other hand, protected areas that were more accessible, had sparser vegetation, where human population density was higher, and that were located in wealthier countries, had higher social media use. Interestingly, protected areas with lower richness in non-charismatic species had more users. Overall, our results suggest that more factors than simply charismatic species might explain attractiveness of protected areas, and call for more in-depth content analysis of the posts. With African countries projected to develop further in the near-future, more social media data will become available, and could be used to inform protected area management and marketing.Peer reviewe

Instagram, Flickr, or Twitter : Assessing the usability of social media data for visitor monitoring in protected areas

Social media data is increasingly used as a proxy for human activity in diferent environments, including protected areas, where collecting visitor information is often laborious and expensive, but important for management and marketing. Here, we compared data from Instagram, Twitter and Flickr, and assessed systematically how park popularity and temporal visitor counts derived from social media data perform against high-precision visitor statistics in 56 national parks in Finland and South Africa in 2014. We show that social media activity is highly associated with park popularity, and social media based monthly visitation patterns match relatively well with the ofcial visitor counts. However, there were considerable diferences between platforms as Instagram clearly outperformed Twitter and Flickr. Furthermore, we show that social media data tend to perform better in more visited parks, and should always be used with caution. Based on stakeholder discussions we identifed potential reasons why social media data and visitor statistics might not match: the geography and profle of the park, the visitor profle, and sudden events. Overall the results are encouraging in broader terms: Over 60% of the national parks globally have Twitter or Instagram activity, which could potentially inform global nature conservation.Peer reviewe

Identification of policies for a sustainable legal trade in rhinoceros horn based on population projection and socioeconomic models

Between 1990 and 2007, 15 southern white (Ceratotherium simum simum) and black (Diceros bicornis) rhinoceroses on average were killed illegally every year in South Africa. Since 2007 illegal killing of southern white rhinoceros for their horn has escalated to >950 individuals/year in 2013. We conducted an ecological-economic analysis to determine whether a legal trade in southern white rhinoceros horn could facilitate rhinoceros protection. Generalized linear models were used to examine the socioeconomic drivers of poaching, based on data collected from 1990 to 2013, and to project the total number of rhinoceroses likely to be illegally killed from 2014 to 2023. Rhinoceros population dynamics were then modeled under 8 different policy scenarios that could be implemented to control poaching. We also estimated the economic costs and benefits of each scenario under enhanced enforcement only and a legal trade in rhinoceros horn and used a decision support framework to rank the scenarios with the objective of maintaining the rhinoceros population above its current size while generating profit for local stakeholders. The southern white rhinoceros population was predicted to go extinct in the wild <20 years under present management. The optimal scenario to maintain the rhinoceros population above its current size was to provide a medium increase in antipoaching effort and to increase the monetary fine on conviction. Without legalizing the trade, implementing such a scenario would require covering costs equal to approximately $147,000,000/year. With a legal trade in rhinoceros horn, the conservation enterprise could potentially make a profit of$717,000,000/year. We believe the 35-year-old ban on rhinoceros horn products should not be lifted unless the money generated from trade is reinvested in improved protection of the rhinoceros population. Because current protection efforts seem to be failing, it is time to evaluate, discuss, and test alternatives to the present policy.Peer reviewe

Green environment and incident depression in South Africa : a geospatial analysis and mental health implications in a resource-limited setting

Our results imply the importance of green environments for mental wellbeing in sub-Saharan African settings experiencing rapid urbanisation, economic and epidemiological transition, reaffirming the need to incorporate environmental services and benefits for sustainable socioeconomic development.Peer reviewe

Online sentiment towards iconic species

Studies assessing online public sentiment towards biodiversity conservation are almost non-existent. The use of social media data and other online data sources is increasing in conservation science. We collected social media and online news data pertaining to rhinoceros, which are iconic species especially threatened by illegal wildlife trade, and assessed online sentiment towards these species using natural language processing methods. We also used an outlier detection technique to identify the most prominent conservation-related events imprinted into this data. We found that tragic events, such as the death of the last male northern white rhinoceros, Sudan, in March 2018, triggered the strongest reactions, which appeared to be concentrated in western countries, outside rhinoceros range states. We also found a strong temporal cross-correlation between social media data volume and online news volume in relation to tragic events, while other events only appeared in either social media or online news. Our results highlight that the public is concerned about biodiversity loss and this, in turn, can be used to increase pressure on decision makers to develop adequate conservation actions that can help reverse the biodiversity crisis. The proposed methods and analyses can be used to infer sentiment towards any biodiversity topic from digital media data, and to detect which events are perceived most important to the public.Peer reviewe

Quantitative conservation geography

Ongoing biodiversity loss represents the erosion of intrinsic value of living nature, reduces the contributions nature provides to people, and undermines efforts to move towards sustainability. We propose the recognition of quantitative conservation geography as a subfield of conservation science that studies where, when, and what conservation actions could be implemented in order to mitigate threats and promote sustainable people-nature interactions. We outline relevant methods and data needed in quantitative conservation geography. We also discuss the importance of filling information gaps, for example by using emerging technologies and digital data sources, for the further advancement of this subfield. Quantitative conservation geography can help inform the implementation of national and international conservation actions and policy to help stem the global biodiversity crisis.Peer reviewe

Importance of private and communal lands to sustainable conservation of Africa's rhinoceroses

A new path for rhinoceros (rhino) conservation is needed. Recent data signal the alarming impact of poaching on populations in Africa's rhino stronghold, the state-run Kruger National Park (South Africa), which today supports one quarter the rhinos than a decade ago. We aggregated African rhino population data, highlighting the growing role of private and community rhino custodians, who likely now conserve >50% of Africa's rhinos. Their contribution has been enabled by a supportive policy and economic environment, but this arrangement is becoming more difficult to sustain as costs associated with protecting rhinos skyrocket and revenue-generating options become insufficient. Some privately held rhino populations are small or intensively managed, raising questions about their conservation value. As the role of private and community custodianship becomes increasingly central to the protection of Africa's remaining rhinos, its resilience must be strengthened through implementation of adaptive policies that incentivize rhino conservation. We outline policy pathways to provide an enabling environment for rhino conservation beyond state parks.Peer reviewe