The importance of building/maintaining soil carbon, for soil health and CO 2 mitigation, is of increasing interest to a wide audience, including policymakers, NGOs and land managers. Integral to any approaches to promote carbon sequestering practices in managed soils are reliable, accurate and cost-effective means to quantify soil C stock changes and forecast soil C responses to different management, climate and edaphic conditions. While technology to accurately measure soil C concentrations and stocks has been in use for decades, many challenges to routine, cost-effective soil C quantification remain, including large spatial variability, low signal-to-noise and often high cost and standardization issues for direct measurement with destructive sampling. Models, empirical and process-based, may provide a cost-effective and practical means for soil C quantification to support C sequestration policies. Examples are described of how soil science and soil C quantification methods are being used to support domestic climate change policies to promote soil C sequestration on agricultural lands (cropland and grazing land) at national and provincial levels in Australia and Canada. Finally, a quantification system is outlinedconsisting of well-integrated datamodel frameworks, supported by expanded measurement and monitoring networks, remote sensing and crowd-sourcing of management activity datathat could comprise the core of a new global soil information system. Take Home messages:Increasing soil organic carbon (SOC) stocks would improve the performance of working (managed) soils especially under drought or other stressors, increase agricultural resilience and fertility, and reduce net GHG emissions from soils.There are many improved management practices that can be and are currently being applied to cropland and grazing lands to increase SOC.Land managers are decision makers who operate in larger contexts that bound their agricultural and financial decisions (e.g. market forces, crop insurance, input subsidies, conservation mandates, etc.).Any effort to value improvements in the performance of agricultural soils through enhanced levels of SOC will require feasible, credible and creditable assessment of SOC stocks, which are governed by dynamic and complex soil processes and properties. This paper evaluates currently accepted methods of quantifying and forecasting SOC that, when augmented and pulled together, could provide the basis for a new global soil information system.
Papillomaviruses are epitheliotropic viruses that have circular dsDNA genomes encapsidated in non-enveloped virions. They have been found to infect a variety of mammals, reptiles and birds, but so far they have not been found in amphibians. Using a next-generation sequencing de novo assembly contig-informed recovery, we cloned and Sanger sequenced the complete genome of a novel papillomavirus from the faecal matter of Adé lie penguins (Pygoscelis adeliae) nesting on Ross Island, Antarctica. The genome had all the usual features of a papillomavirus and an E9 ORF encoding a protein of unknown function that is found in all avian papillomaviruses to date. This novel papillomavirus genome shared~60 % pairwise identity with the genomes of the other three known avian papillomaviruses: Fringilla coelebs papillomavirus 1 (FcPV1), Francolinus leucoscepus papillomavirus 1 (FlPV1) and Psittacus erithacus papillomavirus 1. Pairwise identity analysis and phylogenetic analysis of the major capsid protein gene clearly indicated that it represents a novel species, which we named Pygoscelis adeliae papillomavirus 1 (PaCV1). No evidence of recombination was detected in the genome of PaCV1, but we did detect a recombinant region (119 nt) in the E6 gene of FlPV1 with the recombinant region being derived from ancestral FcPV1-like sequences. Previously only paramyxoviruses, orthomyxoviruses and avian pox viruses have been genetically identified in penguins; however, the majority of penguin viral identifications have been based on serology or histology. This is the first report, to our knowledge, of a papillomavirus associated with a penguin species.
Evaluating the fitness of organisms is an essential step towards understanding their responses to environmental change. Connections between energy expenditure and fitness have been postulated for nearly a century. However, testing this premise among wild animals is constrained by difficulties in measuring energy expenditure while simultaneously monitoring conventional fitness metrics such as survival and reproductive output. We addressed this issue by exploring the functional links between field metabolic rate (FMR), body condition, sex, age and reproductive performance in a wild population. We deployed 3D accelerometers on 115 Adélie penguins Pygoscelis adeliae during four breeding seasons at one of the largest colonies of this species, Cape Crozier, on Ross Island, Antarctica. The demography of this population has been studied for the past 18 years. From accelerometry recordings, collected for birds of known age and breeding history, we determined the vector of the dynamic body acceleration (VeDBA) and used it as a proxy for FMR. This allowed us to demonstrate relationships among FMR, a breeding quality index (BQI) and body condition. Notably, we found a significant quadratic relationship between mean VeDBA during foraging and BQI for experienced breeders, and individuals in better body condition showed lower rates of energy expenditure. We conclude that using FMR as a fitness component complementary to more conventional fitness metrics will yield greater understanding of evolutionary and conservation physiology. A http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.13074/suppinfo is available for this article.
Abstract. Confronted with a rapidly changing world and limited resources for conservation, ecologists are increasingly challenged with predicting the impact of climate and land-use change on wildlife. A common approach is to use habitat-suitability models (HSMs) to explain aspects of species' occurrence, such as presence, abundance, and distribution, utilizing physical habitat characteristics. Although HSMs are useful, they are limited because they are typically created using spatial rather than temporal data, which omits temporal dynamics. We explored the value of combining spatial and temporal approaches by comparing HSMs with autoregressive population models. We investigated a 28-year period of bird community dynamics at a field site in northern California during which time the plant community has been transitioning from scrub to conifer forest. We used the two model frameworks to quantify the contribution of vegetation change, weather, and population processes (autoregressive models only) to variation in density of seven bird species over the first 23 years. Model predictive ability was then tested using the subsequent five years of population density data. HSMs explained 58% to 90% of the deviance in species' density. However, models that included density dependence in addition to vegetation covariates provided a better fit to the data for three of the seven species, Song Sparrow (Melospiza melodia), White-crowned Sparrow (Zonotrichia leucophrys), and Wrentit (Chamaea fasciata). These three species have more localized dispersal compared to the other four species, suggesting that dispersal tendency may be an important life-history trait to consider when predicting the impact of climate and land-use change on population levels. Our results suggest that HSMs can effectively explain and predict variation in species' densities through time, however for species with localized dispersal, it may be especially informative to include population processes.
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