16 February 2018

Borneo, Ravaged by Deforestation, Loses Nearly 150,000 Orangutans in 16 Years

A new study calculates that the island of Borneo lost nearly 150,000 orangutans in the period between 1999 and 2015, largely as a result of deforestation and killing. There were an estimated 104,700 of the critically endangered apes left as of 2012. The study also warns that another 45,000 orangutans are doomed by 2050 under the business-as-usual scenario, where forests are cleared for logging, palm oil, mining and pulpwood leases. Orangutans are also disappearing from intact forests, most likely being killed, the researchers say. The researchers have called for more effective partnerships between governments, industries and local communities to ensure the Bornean orangutan’s survival. Public education and awareness will also be key.

Read More: https://news.mongabay.com/2018/02/borneo-ravaged-by-deforestation-loses-nearly-150000-orangutans-in-16-years-study-finds/

09 February 2018

Deforestation Wanes in Indonesia’s Aceh and Leuser Ecosystem, But Threats Remain

Deforestation in Indonesia’s Aceh province last year fell 18 percent from 2016 — a trend activists attribute to better law enforcement and intensified campaigning about the importance of protecting the unique Leuser Ecosystem. Another factor is a government moratorium on oil palm planters clearing peatlands, but this hasn’t stopped many such operators from acting with impunity. Activists worry that future threats will come from road projects and planned hydropower and geothermal plants.

Read More: https://news.mongabay.com/2018/02/deforestation-wanes-in-indonesias-aceh-and-leuser-ecosystem-but-threats-remain-ngo-says/

08 February 2018

Species co-occurrence analysis predicts management outcomes for multiple threats

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Abstract: "Mitigating the impacts of global anthropogenic change on species is conservation’s greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species’ responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery."

Read More: https://www.nature.com/articles/s41559-017-0457-3

Using Transfer Function Analysis to develop biologically and economically efficient restoration strategies

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Abstract: "Rare species across taxonomic groups and biomes commonly suffer from multiple threats and require intensive restoration, including population reintroduction and threat control. Following reintroduction, it is necessary to identify what level of threat control is needed for species to persist over time. Population reintroduction and threat control are time intensive and costly. Thus, it is pragmatic to develop economically efficient restoration strategies. We combined transfer function analysis and economic cost analysis to evaluate the effects of biologically meaningful increases in demographic processes on the persistence of a reintroduced population of a Hawaii endemic long-lived shrub, Delissea waianaeensis. We show that an increase in fertility by 0.419 following the suppression of non-native rodents or an increase by 0.098 in seedling growth following the suppression of invasive molluscs would stabilize the population (i.e., λ = 1). Though a greater increase in fertility than seedling growth was needed for the reintroduced population to persist over time, increasing fertility by suppressing rodents was the most cost effective restoration strategy. Our study emphasizes the importance of considering the effects of large increases in plant vital rates in population projections and incorporating the economic cost of management actions in demographic models when developing restoration plans for endangered species."

Read More: https://www.nature.com/articles/s41598-018-20178-7

01 February 2018

Toward Reliable Population Estimates of Wolves by Combining Spatial Capture-Recapture Models and Non-Invasive DNA Monitoring

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Abstract: "Decision-makers in wildlife policy require reliable population size estimates to justify interventions, to build acceptance and support in their decisions and, ultimately, to build trust in managing authorities. Traditional capture-recapture approaches present two main shortcomings, namely, the uncertainty in defining the effective sampling area, and the spatially-induced heterogeneity in encounter probabilities. These limitations are overcome using spatially explicit capture-recapture approaches (SCR). Using wolves as case study, and non-invasive DNA monitoring (faeces), we implemented a SCR with a Poisson observation model in a single survey to estimate wolf density and population size, and identify the locations of individual activity centres, in NW Iberia over 4,378 km2. During the breeding period, posterior mean wolf density was 2.55 wolves/100 km2 (95% BCI=1.87–3.51), and the posterior mean population size was 111.6 ± 18.8 wolves (95% BCI=81.8–153.6). From simulation studies, addressing different scenarios of non-independence and spatial aggregation of individuals, we only found a slight underestimation in population size estimates, supporting the reliability of SCR for social species. The strategy used here (DNA monitoring combined with SCR) may be a cost-effective way to generate reliable population estimates for large carnivores at regional scales, especially for endangered species or populations under game management."

Read More: "https://www.nature.com/articles/s41598-018-20675-9"

Pervasive Rise of Small-scale Deforestation in Amazonia

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Abstract: "Understanding forest loss patterns in Amazonia, the Earth’s largest rainforest region, is critical for effective forest conservation and management. Following the most detailed analysis to date, spanning the entire Amazon and extending over a 14-year period (2001–2014), we reveal significant shifts in deforestation dynamics of Amazonian forests. Firstly, hotspots of Amazonian forest loss are moving away from the southern Brazilian Amazon to Peru and Bolivia. Secondly, while the number of new large forest clearings (>50 ha) has declined significantly over time (46%), the number of new small clearings (<1 ha) increased by 34% between 2001–2007 and 2008–2014. Thirdly, we find that small-scale low-density forest loss expanded markedly in geographical extent during 2008–2014. This shift presents an important and alarming new challenge for forest conservation, despite reductions in overall deforestation rates."

Read More: https://www.nature.com/articles/s41598-018-19358-2

Warning Signals of Biodiversity Collapse Across Gradients of Tropical Forest Loss

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Abstract: "We evaluate potential warning signals that may aid in identifying the proximity of ecological communities to biodiversity thresholds from habitat loss—often termed “tipping points”—in tropical forests. We used datasets from studies of Neotropical mammal, frog, bird, and insect communities. Our findings provide only limited evidence that an increase in the variance (heteroskedasticity) of biodiversity-related parameters can provide a general warning signal of impending threshold changes in communities, as forest loss increases. However, such an apparent effect was evident for amphibians in the Brazilian Atlantic Forest and Amazonian mammal and bird communities, suggesting that impending changes in some species assemblages might be predictable. We consider the potential of such warning signs to help forecast drastic changes in biodiversity."

Read More: https://www.nature.com/articles/s41598-018-19985-9