Estimating Sonoran pronghorn abundance and survival with fecal DNA and capture–recapture methods

Population abundance estimates are important for management but can be challenging to determine in low‐density, wide‐ranging, and endangered species, such as Sonoran pronghorn (Antilocapra americana sonoriensis). The Sonoran pronghorn population has been increasing; however, population estimates are currently derived from a biennial aerial count that does not provide survival or recruitment estimates. We identified individuals through noninvasively collected fecal DNA and used robust‐design capture–recapture to estimate abundance and survival for Sonoran pronghorn in the United States from 2013 to 2014. In 2014 we generated separate population estimates for pronghorn gathered near 13 different artificial water holes and for pronghorn not near water holes. The population using artificial water holes had 116 (95% CI 102–131) and 121 individuals (95% CI 112–132) in 2013 and 2014, respectively. For all locations, we estimated there were 144 individuals (95% CI 132–157). Adults had higher annual survival probabilities (0.83, 95% CI 0.69–0.92) than fawns (0.41, 95% CI 0.21–0.65). Our use of targeted noninvasive genetic sampling and capture–recapture with Sonoran pronghorn fecal DNA was an effective method for monitoring a large proportion of the population. Our results provided the first survival estimates for this population in over 2 decades and precise estimates of the population using artificial water holes. Our method could be used for targeted sampling of broadly distributed species in other systems, such as in African savanna ecosystems, where many species congregate at watering sites.     

Risk of Local Extinction of Odonata Freshwater Habitat Generalists and Specialists

Understanding the risk of a local extinction in a single population relative to the habitat requirements of a species is important in both theoretical and applied ecology. Local extinction risk depends on several factors, such as habitat requirements, range size of species, and habitat quality. We studied the local extinctions among 31 dragonfly and damselfly species from 1930 to 1975 and from 1995 to 2003 in Central Finland. We tested whether habitat specialists had a higher local extinction rate than generalist species. Approximately 30% of the local dragonfly and damselfly populations were extirpated during the 2 study periods. The size of the geographical range of the species was negatively related to extinction rate of the local populations. In contrast to our prediction, the specialist species had lower local extinction rates than the generalist species, probably because generalist species occurred in both low‐ and high‐quality habitat. Our results are consistent with source–sink theory. Riesgo de Extinción Local de Odonatos de Agua Dulce Generalistas y Especialistas de Hábitat     

Particle size and surface area effects on explosibility using a 20-L chamber

The Mine Safety and Health Administration (MSHA) specification for rock dust used in underground coal mines, as defined by 30 CFR 75.2, requires 70% of the material to pass through a 200 mesh sieve (<75 μm). However, in a collection of rock dusts, 47% were found to not meet the criteria. Upon further investigation, it was determined that some of the samples did meet the specification, but were inadequate to render pulverized Pittsburgh coal inert in the National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) 20-L chamber. This paper will examine the particle size distributions, specific surface areas (SSA), and the explosion suppression effectiveness of these rock dusts. It will also discuss related findings from other studies, including full-scale results from work performed at the Lake Lynn Experimental Mine. Further, a minimum SSA for effective rock dust will be suggested.     

上海市郊春节期间大气颗粒物及其组分的粒径分布

利用电称低压冲击仪(ELPI)在线监测上海市嘉定区2009年春节前后不同粒径(50%切割粒径分别为:0.03、0.06、0.11、0.17、0.26、0.40、0.65、1.00、1.60、2.50、4.40、6.80μm)大气颗粒物的粒子数浓度变化.对比春节与非节日期间该地区大气颗粒物(<0.49、0.49—0.95、0.95—1.50、1.50—3.00、3.00—7.20、>7.20μm)中Na、Mg、Al、K、Ca、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Se、Pb 17种元素,F-、Cl-、NO 2-、SO24-、NO 3-、Na+、NH 4+、K+、Mg2+、Ca2+10种离子与有机碳(OC)、元素碳(EC)质量浓度的粒径分布.结果表明,春节对于大气颗粒物粒子数浓度的影响主要集中在0.11—1.60μm.如果以3.00μm为界将大气颗粒物划分成细(≤3.00μm)和粗(>3.00μm)颗粒物时,春节影响体现在细颗粒的元素为:Na、As、Pb,且主要集中于<0.49μm颗粒中;春节影响集中于大颗粒(>7.20μm)的元素为:Ni、Co;没有受到显著影响的为:Ca、V、Mn、Fe、Z...     

Towards a 3D National Ecological Footprint Geography

In the last decades several indicators have been proposed to guide decision makers and help manage natural capital. Among such indicators is the Ecological Footprint, a resource accounting tool with a biophysical and thermodynamic basis. In our recent paper (Niccolucci et al., 2009), a three dimensional Ecological Footprint (^3DEF) model was proposed to better explain the difference between human demand for natural capital stocks and resource flows. Such ^3DEF model has two relevant dimensions: the surface area (or Footprint size - EF_size) and the height (or Footprint depth - EF_depth). EF_size accounts for the human appropriation of the annual income from natural capital while EF_depth accounts for the depletion of stocks of natural capital and/or the accumulation of stocks of wastes. Building on the 2009 Edition of the National Footprint Accounts (NFA), global trends (from 1961 to 2006) for both EF_size and EF_depth were analyzed. EF_size doubled from 1961 to 1986; after 1986 it reached an asymptotic value equal to the Earth's biocapacity (BC) and remained constant. Conversely, EF_depth remained constant at the “natural depth” value until 1986, the year in which global EF first exceeded Earth's BC. A growing trend was observed after that. Trends in each Footprint land type were also analyzed to better appraise the land type under the higher human induced stress. The usefulness of adopting such ^3DEF model in the National Footprint Accounts was also discussed. In comparing any nation's demand for ecological assets with its own biocapacity in a given year, four hypothetical cases were identified which could serve as the basis for a new Footprint geography based on both size and depth concepts. This ^3DEF model could help distinguish between the use of natural capital flows and the depletion of natural capital stocks while maintaining the structure and advantages of the classical Ecological Footprint formulation.     

Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent

Various methods exist to model a species’ niche and geographic distribution using environmental data for the study region and occurrence localities documenting the species’ presence (typically from museums and herbaria). In presence-only modelling, geographic sampling bias and small sample sizes represent challenges for many species. Overfitting to the bias and/or noise characteristic of such datasets can seriously compromise model generality and transferability, which are critical to many current applications - including studies of invasive species, the effects of climatic change, and niche evolution. Even when transferability is not necessary, applications to many areas, including conservation biology, macroecology, and zoonotic diseases, require models that are not overfit. We evaluated these issues using a maximum entropy approach (Maxent) for the shrew Cryptotis meridensis, which is endemic to the Cordillera de Mérida in Venezuela. To simulate strong sampling bias, we divided localities into two datasets: those from a portion of the species’ range that has seen high sampling effort (for model calibration) and those from other areas of the species’ range, where less sampling has occurred (for model evaluation). Before modelling, we assessed the climatic values of localities in the two datasets to determine whether any environmental bias accompanies the geographic bias. Then, to identify optimal levels of model complexity (and minimize overfitting), we made models and tuned model settings, comparing performance with that achieved using default settings. We randomly selected localities for model calibration (sets of 5, 10, 15, and 20 localities) and varied the level of model complexity considered (linear versus both linear and quadratic features) and two aspects of the strength of protection against overfitting (regularization). Environmental bias indeed corresponded to the geographic bias between datasets, with differences in median and observed range (minima and/or maxima) for some variables. Model performance varied greatly according to the level of regularization. Intermediate regularization consistently led to the best models, with decreased performance at low and generally at high regularization. Optimal levels of regularization differed between sample-size-dependent and sample-size-independent approaches, but both reached similar levels of maximal performance. In several cases, the optimal regularization value was different from (usually higher than) the default one. Models calibrated with both linear and quadratic features outperformed those made with just linear features. Results were remarkably consistent across the examined sample sizes. Models made with few and biased localities achieved high predictive ability when appropriate regularization was employed and optimal model complexity was identified. Species-specific tuning of model settings can have great benefits over the use of default settings.     

Predictors of occupancy trend across spatial scale

Many explorations of extinction probability have had a global focus, yet it is unclear whether variables that explain the probability of extinction at large spatial extents are the same as those at small spatial extents. Thus, we used nearly annual presence-absence records for the most recent 40 years of a 110-year data set from Palenque, Mexico, an area with ongoing deforestation, to explore which of >200 species of birds have probabilities of extirpation that are likely to increase. We assessed associations between long-term trends in species presence (i.e., detection in a given year) and body size, geographic range size, diet, dependence on forest cover, taxonomy, and ecological specialization. Our response variable was the estimated slope of a weighted logistic regression for each species. We assessed the relative strength of each predictor by means of a model ranking scheme. Several variables associated with high extinction probability at global extents, such as large body size or small geographic range size, were not associated with occurrence of birds over time at our site. Body size was associated with species loss at Palenque, but occurrence trends of both very large and very small species, particularly the latter, have declined, or the species have been extirpated. We found no association between declining occurrence trend and geographic range size, yet decline correlated with whether a species depends on forest (mean occupancy trend =-0.0380, 0.0263, and 0.0186 for, respectively, species with high, intermediate, or low dependence on forest) and with complex combinations of diet and foraging strata (e.g., occurrence of canopy insectivores and terrestrial omnivores has increased, whereas occurrence of mid-level frugivores and terrestrial granivores has decreased). Our findings emphasize that analyses of local areas are necessary to explicate extirpation risk at various spatial extents.     

不同粒径土壤中重金属的分布规律

本文选择提钒炼钢厂内部分土壤为研究对象,测定了重金属元素（镉、铜、铬、铅、锌）的含量,并与样品粒度大小的关系进行了探讨,结果表明金属（铜、铬、铅、锌、镉）的浓度最大值出现在粒径较小（100目或160目）的样品中,同时将测定结果与土壤环境质量标准比较,结果表明镉、锌存在污染,其余元素均未超标。     

基于颗粒物化学组分粒径分布特征的源解析方法构建与评估

大气颗粒物污染来源解析可以为大气污染防控提供科学支撑.大部分颗粒物源解析研究是以化学组分为基础,此外,粒径特征也是颗粒物的重要属性之一,通过分析化学组分的粒径特征,有助于提高解析结果准确性.针对目前组分粒径分布信息利用不充分的问题,在三维多粒径因子分析模型(ABB)基础上,将已知源类标识组分粒径分布信息作为约束限制,构建基于组分粒径分布特征的多粒径源解析模型(SDABB).通过模拟数据集对模型进行了评估,探究了SDABB模型对源谱共线性和源贡献粒径分布相似性的敏感程度.结果表明,ABB模型对源谱共线性和源贡献粒径分布相似性较敏感,将粒径分布规律纳入后的SDABB模型,两种情景效果均明显变优,即SDABB模型可以较好解析共线性源类,并且对贡献粒径分布相似性不敏感.     

不同环境条件下水铁矿和针铁矿纳米颗粒稳定性

纳米颗粒的团聚和分散是控制许多重要环境过程的关键因素.本研究通过测定水铁矿纳米颗粒(FHNPs)和针铁矿纳米颗粒(GTNPs)的粒径和Zeta电位,计算DLVO相互作用能,探究了不同pH、离子和有机质条件下两种纳米颗粒的稳定性.结果表明Na~+和Ca~(2+)通过离子强度的作用促进FHNPs和GTNPs团聚;低浓度PO_4~(3-)(2mmol·L~(-1))、HA和FA(2 mg·L~(-1)和10 mg·L~(-1))吸附在铁矿物纳米颗粒上,改变其表面电荷,提高FHNPs和GTNPs在中高pH条件下的稳定性.高浓度的PO_4~(3-)(10mmol·L~(-1))虽然也可改变铁矿物纳米颗粒的电性,但由于离子强度的作用,对GTNPs的稳定性贡献不大.FHNPs或GTNPs的Zeta电位接近于0时,其相互作用的一级势垒和次级势阱常常同时不存在,两种纳米颗粒主要以不可逆的方式在一级势阱中团聚;当一级势垒和次级势阱同时存在时,次级势阱造成的可逆FHNPs和GTNPs团聚比例会增大.本研究结果为进一步考察FHNPs和GTNPs的环境行为和它们在负载污染物迁移中的作用提供数据支撑.