Modeling outcomes of approaches to sustained human and snow leopard coexistence

The snow leopard (Uncia uncia) is in danger of extinction. Killing to protect livestock is among the primary causes of its decline. Efforts to mitigate this threat have focused on balancing the need to conserve the snow leopard with the needs of local people in snow leopard habitat, many of whom rely on raising livestock for their livelihoods. Conservation of the snow leopard has the characteristics of a public good, and outside funding is required to support conservation efforts. There are 5 commonly discussed approaches to resolving this issue: (1) direct payments for conservation, (2) investments in protection from predation, (3) damage compensation payments, (4) investments in better livestock husbandry, and (5) leases of pastureland for wild prey. After a review of these 5 conservation strategies, an economic–ecologic model, which includes the interactions between the snow leopard, its wild prey, and livestock, is used to evaluate the 2 most promising conservation strategies. The model reveals that investments in protection from predation and leases of pastureland for wild prey are effective but only in delaying the eventual extinction of the snow leopard. To preserve the snow leopard, these approaches must be applied more aggressively and new ones explored.     

A Bayesian mixture model for missing data in marine mammal growth analysis

Much of what is known about bottle nose dolphin (Tursiops truncatus) anatomy and physiology is based on necropsies from stranding events. Measurements of total body length, total body mass, and age are used to estimate growth. It is more feasible to retrieve and transport smaller animals for total body mass measurement than larger animals, introducing a systematic bias in sampling. Adverse weather events, volunteer availability, and other unforeseen circumstances also contribute to incomplete measurement. We have developed a Bayesian mixture model to describe growth in detected stranded animals using data from both those that are fully measured and those not fully measured. Our approach uses a shared random effect to link the missingness mechanism (i.e. full/partial measurement) to distinct growth curves in the fully and partially measured populations, thereby enabling drawing of strength for estimation. We use simulation to compare our model to complete case analysis and two common multiple imputation methods according to model mean square error. Results indicate that our mixture model provides better fit both when the two populations are present and when they are not. The feasibility and utility of our new method is demonstrated by application to South Carolina strandings data.     

Selenium and nano-selenium in plant nutrition

Selenium (Se) is a naturally occurring metalloid element which occurs nearly in all environments. Se is considered as a finite and non-renewable resource on the Earth. The common sources of Se in earth’s crust occur in association with sulfide minerals such as metal selenide, whereas it is rarely found in elemental form (Se⁰). While there is no evidence of Se need for higher plants, several reports show that when Se added at low concentrations, Se exerts beneficial effects on plant growth. Se may act as quasi-essential micronutrient through altering different physiological and biochemical traits. Thus, plants vary considerably in their physiological and biochemical response to Se. This review focusses on the physiological importance of Se forms as well as different Se fertilizers for higher plants, especially plant growth, uptake, transport, and metabolism.     

Protecting biodiversity and economic returns in resource-rich tropical forests

In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. We examined how protection of biodiversity and economic revenues can be balanced in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimized the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon across a range of opportunity costs (i.e., sacrifices of extractive profit). We also applied spatial statistics to remotely sensed, historic deforestation data to focus the optimization on areas most threatened by imminent forest loss. Giving up 5% of a year's oil profits (US$221 million) allowed for a protected area network that retained an average of 65% of the extent of each species and ecosystem. This performance far exceeded that of the network produced by simple optimization for land area (which required a sacrifice of approximately 40% of annual oil profits [US$1.7 billion]) and used only marginally less land to achieve equivalent levels of ecological protection. We identified what we call emergency conservation targets: regions that are essential components of a cost-effective conservation reserve network but at imminent risk of destruction, thus requiring urgent and effective protection. Governments can use our methods when evaluating extractive-led development options to responsibly manage the associated ecological and economic trade-offs and protect natural capital.     

Partners under pressure: humanitarian action for the Syria crisis

Partnerships between organisations in humanitarian crisis situations generally are challenging, but at the apex are those established as part of remote management in a context of extreme insecurity. To date, little systematic research has been conducted on arrangements between local organisations that have access to crisis‐affected populations and international organisations that hold the purse strings. This paper presents the findings of nine months of qualitative research conducted with five Syrian local organisations and their international partners engaging in humanitarian action across the Turkey–Syria border, and presents insights into the components of successful partnerships. It redefines capacity along organisational and operational lines, and unpacks how monitoring and evaluation and donor requirements create tension and, at times, place local organisations at risk. The paper highlights the centrality of trust in successful partnerships, and describes the personalisation of the conflict by local organisations. Based on a historical case study of civil society in northern Iraq, it closes with some suggestions for long‐term sustainability.     

Stakeholder perspectives on the value proposition of enterprise-level natural capital accounting for three primary industries

Environment Systems and Decisions - Globally we are experiencing a decline in aggregate natural capital. Many primary industries and enterprises are highly dependent on renewable and non-renewable...     

In acceptance we trust? Conceptualising acceptance as a viable approach to NGO security management

This paper documents current understanding of acceptance as a security management approach and explores issues and challenges non‐governmental organisations (NGOs) confront when implementing an acceptance approach to security management. It argues that the failure of organisations to systematise and clearly articulate acceptance as a distinct security management approach and a lack of organisational policies and procedures concerning acceptance hinder its efficacy as a security management approach. The paper identifies key and cross‐cutting components of acceptance that are critical to its effective implementation in order to advance a comprehensive and systematic concept of acceptance. The key components of acceptance illustrate how organisational and staff functions affect positively or negatively an organisation's acceptance, and include: an organisation's principles and mission, communications, negotiation, programming, relationships and networks, stakeholder and context analysis, staffing, and image. The paper contends that acceptance is linked not only to good programming, but also to overall organisational management and structures.     

Morphological and chemical characteristics of atmospheric particles in the Metropolitan Zone of Toluca Valley (Mexico)

Scanning electron microscopy with energy-dispersive spectroscopy has been used for both morphological and elemental chemistry analyses of atmospheric particles. This technique allows the in situ observation of individual aerosol particles in the sample chamber. Aerotransported particles were analysed from seven monitoring stations located in the Metropolitan Zone of Toluca Valley (MZTV). Several different morphologies were identified: aggregates, porous spheres, rough and smooth compact material. The elemental composition included C, Na, Mg, Al, Si, S, Cl, K, Mn, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn and Ce. These are semiquantitative analyses considering the bulk sample or individual particles. It was possible to correlate or confirm some chemical associations such as C–S, Ca–S–O and Si–Al–O, probably due to the presence of compounds derived from incomplete combustion, building tailing materials and aluminosilicates of cortical origin. Bioaerosols such as pollen, spores, brochosomes and diatoms were identified in the zone; all these types of particles have a natural origin too. Several types of suspended particles were identified in the MZTV, they were from different sources (natural and anthropogenic) to which the population can be potentially exposed, and may cause harm in the short- and long-term, according to their chemical element composition and size.     

Heteroplasmy in a deep-sea protobranch bivalve suggests an ancient origin of doubly uniparental inheritance of mitochondria in Bivalvia

Most metazoan species have strict maternal inheritance of the mitochondrial genome. In bivalves, a unique inheritance pattern called doubly uniparental inheritance (DUI) occurs in at least seven bivalve families. In this system of mitochondrial inheritance, males inherit and carry mtDNA from both parents, while females only carry mtDNA from the mother. Here, we present evidence of mitochondrial heteroplasmy in deep-sea protobranch bivalves. Divergent 16S rRNA and cytochrome b sequences were obtained within individuals of Ledella ultima. Ledella sublevis also exhibited divergent 16S sequences. Levels of divergence between 16S sequences within individuals were 27 and 15 % for each species, respectively. Ratios of homoplasmic to heteroplasmic individuals were not significantly different from 1:1, in agreement with sex ratios in protobranchs. The results provide the first evidence for mitochondrial heteroplasmy in the protobranchs and suggest DUI might have evolved much earlier in the evolution of the Bivalvia than previously thought.     

Uncertainty in invasive alien species listing

Lists of invasive alien species (IAS) are essential for preventing, controlling, and reporting on the state of biological invasions. However, these lists suffer from a range of errors, with serious consequences for their use in science, policy, and management. Here we (1) collated and classified errors in IAS listing using a taxonomy of uncertainty; and (2) estimated the size of these errors using data from a completed listing exercise, with the purpose of better understanding, communicating, and dealing with them. Ten errors were identified. Most result from a lack of knowledge or measurement error (epistemic uncertainty), although two were a result of context dependence and vagueness (linguistic uncertainty). Estimates of the size of the effects of these errors were substantial in a number of cases and unknown in others. Most errors, and those with the largest estimated effect, result in underestimates of IAS numbers. However, there are a number of errors where the size and direction of the effect remains poorly understood. The effect of differences in opinion between specialists is potentially large, particularly for data-poor taxa and regions, and does not have a clearly directional or consistent effect on the size and composition of IAS lists. Five tactics emerged as important for reducing uncertainty in IAS lists, and while uncertainty will never be removed entirely, these approaches will significantly improve the transparency, repeatability, and comparability of IAS lists. Understanding the errors and uncertainties that occur during the process of listing invasive species, as well as the potential size and nature of their effects on IAS lists, is key to improving the value of these lists for governments, management agencies, and conservationists. Such understanding is increasingly important given positive trends in biological invasion and the associated risks to biodiversity and biosecurity.