Seed dispersal function of the brown bear Ursus arctos on Hokkaido Island in northern Japan: gut passage time, dispersal distance, germination, and effects of remaining pulp

Megafauna are important seed dispersers because they can disperse large quantities of seeds over long distances. In Hokkaido, Japan, the largest terrestrial animal is the brown bear (Ursus arctos) and other megafauna seed dispersers are lacking. Thus, brown bears are expected to have an important function as seed dispersers in Hokkaido. In this study, we, for the first time, evaluated the seed dispersal function of brown bears in Hokkaido using three fleshy-fruited trees and studied: (1) gut passage time (GPT) in feeding experiments, (2) seed dispersal distance using tracking data of wild bears, and (3) the effect of gut passage and pulp removal on germination rate. Most seeds were defecated intact, and less than 6% were broken. The average GPT without pulp was 3 h and 56 min to 6 h and 13 min, depending on the plant and trial. Each plant's average simulated seed dispersal distance was 202-512 m. The dispersal distance of Actinidia arguta seeds with pulp was significantly longer than those without pulp because of their longer GPT. The germination rate of defecated seeds without pulp was 19-51%, depending on the plant, and was significantly higher or not different comparing with that of seeds with pulp. We concluded that brown bears in Hokkaido are effective seed dispersers. In managing brown bears in Hokkaido, such ecological functions should be considered along with conserving the bear population and reducing human-bear conflicts.

Is Ecotourism an Opportunity for Large Wild Animals to Thrive?

The development of ecotourism involving wild animals in Russia is overlooked despite the fact that the country’s territory is significant not only in terms of area but also in terms of the diversity of its flora and fauna. A significant part of Russia’s territory has a low population density, especially beyond the Ural ridge. It retains its natural primeval nature, which can contribute to the development of ecotourism. Initial attempts have been made to develop this, mainly in the European part (Tatarstan, Murmansk Region, the Baltic Sea, Baikal, Altai), but the commercial use of wild animals within ecotourism programs, including the ones in Siberia and the Far East, has not been discussed. This work focuses on the basics of launching ecotourism in the industrial region of Siberia (Kuzbass, Russia) as part of the Alcesalces conservation program.

Living With Elephants: Evidence-Based Planning to Conserve Wild Elephants in a Megadiverse South East Asian Country

Theory of Change (ToC) and Social Return of Investment (SROI) are planning tools that help projects craft strategic approaches in order to create the most impact. In 2018, the Management & Ecology of Malaysian Elephants (MEME) carried out planning exercises using these tools to develop an Asian elephant conservation project with agriculture communities. First, a problem tree was constructed together with stakeholders, with issues arranged along a cause-and-effect continuum. There were 17 main issues identified, ranging from habitat connectivity and fragmentation, to the lack of tolerance toward wild elephants. All issues ultimately stemmed from a human mindset that favors human-centric development. The stakeholders recognize the need to extend conservation efforts beyond protected areas and move toward coexistence with agriculture communities for the survival of the wild elephants. We mapped previous Human-Elephant Conflict (HEC) management methods and other governmental policies in Malaysia against the problem tree, and provided an overview of the different groups of stakeholders. The ToC was developed and adapted for each entity, while including Asian elephants as a stakeholder in the project. From the SROI estimation, we extrapolated the intrinsic value of the wild Asian elephant population in Johor, Malaysia, to be conservatively worth at least MYR 7.3 million (USD 1.8 million) per year. From the overall calculations, the potential SROI value of the project is 18.96 within 5 years, meaning for every ringgit invested in the project, it generates MYR 18.96 (USD 4.74) worth of social return value. There are caveats with using these value estimations outside of the SROI context, which was thoroughly discussed. The SROI provides projects with the ability to justify to funders the social return values of its activities, which we have adapted to include the intrinsic value of an endangered megafauna. Moreover, SROI encourages projects to consider unintended impacts (i.e., replacement, displacement, and deadweight), and acknowledge contributions from stakeholders. The development of the problem tree and ToC via SROI approach, can help in clarifying priorities and encourage thinking out of the box. For this case study, we presented the thinking process, full framework and provided evidences to support the Theory of Change.

Spatial variation in population-density of snow leopards in a multiple use landscape in Spiti Valley, Trans-Himalaya

The endangered snow leopard Panthera uncia occurs in human use landscapes in the mountains of South and Central Asia. Conservationists generally agree that snow leopards must be conserved through a land-sharing approach, rather than land-sparing in the form of strictly protected areas. Effective conservation through land-sharing requires a good understanding of how snow leopards respond to human use of the landscape. Snow leopard density is expected to show spatial variation within a landscape because of variation in the intensity of human use and the quality of habitat. However, snow leopards have been difficult to enumerate and monitor. Variation in the density of snow leopards remains undocumented, and the impact of human use on their populations is poorly understood. We examined spatial variation in snow leopard density in Spiti Valley, an important snow leopard landscape in India, via spatially explicit capture-recapture analysis of camera trap data. We camera trapped an area encompassing a minimum convex polygon of 953 km2. Our best model estimated an overall density of 0.5 (95% CI: 0.31–0.82) mature snow leopards per 100 km2. Using AIC, our best model showed the density of snow leopards to depend on estimated wild prey density, movement about activity centres to depend on altitude, and the expected number of encounters at the activity centre to depend on topography. Models that also used livestock biomass as a density covariate ranked second, but the effect of livestock was weak. Our results highlight the importance of maintaining high density pockets of wild prey populations in multiple-use landscapes to enhance snow leopard conservation.