施用农药人员的安全与防护——ASTMF2669《旋用农药人员用防护服性能标准》介绍

本文主要介绍了ASTMF2669-2009《施用农药人员用防护服性能标准》的分级和检测要求、防护服材料性能要求、材料的抗渗透性指标等,并就施药人员的安全与防护以及完善防护服标准体系提出建议．以为我国广大相关领域人员了解标准和应用标准提供帮助．     

Spatiotemporal variations of ambient air pollutants and meteorological influences over typical urban agglomerations in China during the COVID-19 lockdown

To investigate the air quality change during the COVID-19 pandemic, we analyzed spatiotemporal variations of six criteria pollutants in nine typical urban agglomerations in China using ground-based data and examined meteorological influences through correlation analysis and backward trajectory analysis under different responses. Concentrations of PM_2.5, PM₁₀, NO₂, SO₂ and CO in urban agglomerations respectively decreased by 18%–45% (30%–62%), 17%–53% (22%–39%), 47%-64% (14%–41%), 9%–34% (0%–53%) and 16%-52% (23%–56%) during Lockdown (Post-lockdown) period relative to Pre-lockdown period. PM_2.5 pollution events occurred during Lockdown in Beijing-Tianjin-Hebe (BTH) and Middle and South Liaoning (MSL), and daily O₃ concentration rose to grade Ⅱ standard in Post-lockdown period. Distinct from the nationwide slump of NO₂ during Lockdown period, a rebound (～40%) in Post-lockdown period was observed in Cheng-Yu (CY), Yangtze River Middle-Reach (YRMR), Yangtze River Delta (YRD) and Pearl River Delta (PRD). With slightly higher wind speed compared with 2019, the reduction of PM_2.5 (51%–62%) in Post-lockdown period is more than 2019 (15%–46%) in HC (Harbin-Changchun), MSL, BTH, CP (Central Plain) and SP (Shandong-Peninsula), suggesting lockdown measures are effective to PM_2.5 alleviation. Although O₃ concentrations generally increased during the lockdown, its increment rate declined compared with 2019 under similar sunlight duration and temperature. Additionally, unlike HC, MSL and BTH, which suffered from additional (> 30%) air masses from surrounding areas after the lockdown, the polluted air masses reaching YRD and PRD mostly originated from the long-distance transport, highlighting the importance of joint regional governance.     

Temporal limits to simulating the future spread pattern of invasive species: Buddleja davidii in Europe and New Zealand

The spread of invasive species is a major ecological and economic problem. Dynamic spread modelling is a potentially valuable tool to assist regional and central government authorities to monitor and control invasive species. To date a lack of suitable data has meant that most broad scale dispersal models have not been validated with independent datasets, and so their predictive ability and reliability has remained unscrutinised. A dynamic, stochastic dispersal model of the widely invasive plant Buddleja davidii was calibrated on European spread data and then used to project the temporal progression of B. davidii's distribution in New Zealand, starting from several different historical distributions. To assess the model's performance, we constructed an occupancy map based on the average number of simulation realisations that have a population present. The application of Receiver Operating Characteristic (ROC) curves to occupancy maps is introduced, but with specificity substituted by the proportion of available area used in a realisation. A derivative measure, the partial area under these curves when assessed through time (pAUC), is introduced and used to assess overall performance of the spread model. The model was able to attain a high level of model sensitivity, encompassing all of the known locations within the occupancy envelope. However, attempting to simulate the spread of this invasive species beyond a decade had very low model specificity. This is due to several factors, including the exponential process of spread (the further a population spreads the more sites exist from which it can spread stochastically), and the Markovian chain property of the stochastic system whereby differences between realisations compound through time. These features are seen in many reports of spread models, without being explicitly acknowledged. Our measure of pAUC through time allows a model's temporal performance and its specificity to be simultaneously assessed. While the rapid deterioration in model performance limits the utility of this type of modelling for forecasting long-term broad-scale strategic management of biological invasions, it does not necessarily limit its attractiveness for informing smaller scale and shorter term invasion management activities such as surveillance, containment and local eradication.     

我国旱涝空间型的马尔科夫概型分析

旱涝灾害在我国是影响最大、也最为频繁的气候灾害。本文利用马尔科夫概型分析的原理和方法，在验证了我国旱涝空间型序列具有马尔科夫性质的基础上，计算出各状态的转移概率，进而分析了旱涝空间型序列的静态和动态结构，并揭示出旱涝空间型各状态演化的优势倾向。     

Spatial-econometric analysis of attraction and repulsion of private conservation by public reserves

It is difficult for public agencies to make optimal reserve-site selections without knowing how new public reserves might influence the configuration of private conservation. Private land trusts protect much land in the USA, but little is known about how private groups respond to conservation decisions made by other conservation agents. To fill that gap, we analyze township-level spatial data on conservation in California, Illinois, and Massachusetts to explore relationships between the location of private and public conservation land. Using linear spatial-econometric models and Bayesian spatial probit models, we find evidence that private-protected acres are clustered together in space. In California, it appears that private land conservation is attracted towards places where the government has reserves. In Illinois and Massachusetts, however, it appears that private conservation shifts away from townships with government reserves due to a mixture of spatial repulsion and simple acreage displacement.     

Modelling semi-aquatic vertebrates’ distribution at the drainage basin scale: The case of the otter Lutra lutra in Italy

Modelling habitat suitability of semi-aquatic vertebrates for large scale conservation purposes is a particularly challenging task, due to the fine-scale linearity of riverine habitats, and to the ecological continuum represented by the riparian and the aquatic ecosystems, on one side, and by a river and its tributaries, on the other.     

Rarefaction and nonrandom spatial dispersion patterns

Rarefaction estimates how many species are expected in a random sample of individuals from a larger collection and allows meaningful comparisons among collections of different sizes. It assumes random spatial dispersion. However, two common dispersion patterns, within-species clumping and segregation among species, can cause rarefaction to overestimate the species richness of a smaller continuous area. We use field studies and computer simulations to determine (1) how robust rarefaction is to nonrandom spatial dispersion and (2) whether simple measures of spatial autocorrelation can predict the bias in rarefaction estimates. Rarefaction does not estimate species richness accurately for many communities, especially at small sample sizes. Measures of spatial autocorrelation of the more abundant species do not reliably predict amount of bias. Survey sites should be standardized to equal-sized areas before sampling. When sites are of equal area but differ in number of individuals sampled, rarefaction can standardize collections. When communities are sampled from different-sized areas, the mean and confidence intervals of species accumulation curves allow more meaningful comparisons among sites. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

Predictability of marine nematode biodiversity

In this paper, we investigated: (1) the predictability of different aspects of biodiversity, (2) the effect of spatial autocorrelation on the predictability and (3) the environmental variables affecting the biodiversity of free-living marine nematodes on the Belgian Continental Shelf. An extensive historical database of free-living marine nematodes was employed to model different aspects of biodiversity: species richness, evenness, and taxonomic diversity. Artificial neural networks (ANNs), often considered as “black boxes”, were applied as a modeling tool. Three methods were used to reveal these “black boxes” and to identify the contributions of each environmental variable to the diversity indices. Since spatial autocorrelation is known to introduce bias in spatial analyses, Moran's I was used to test the spatial dependency of the diversity indices and the residuals of the model. The best predictions were made for evenness. Although species richness was quite accurately predicted as well, the residuals indicated a lack of performance of the model. Pure taxonomic diversity shows high spatial variability and is difficult to model. The biodiversity indices show a strong spatial dependency, opposed to the residuals of the models, indicating that the environmental variables explain the spatial variability of the diversity indices adequately. The most important environmental variables structuring evenness are clay and sand fraction, and the minimum annual total suspended matter. Species richness is also affected by the intensity of sand extraction and the amount of gravel of the sea bed.     

Genetic relatedness and space use in a behaviorally flexible species of marmot, the woodchuck (Marmota monax)

Solitary species show several patterns of space use and relatedness. Individuals may associate randomly or may live near female or male kin, often as a result of natal philopatry or dispersal patterns. Although usually described as solitary or asocial, woodchucks (Marmota monax) are behaviorally flexible marmots that exhibit greater sociality in some populations than others. I examined relationships between kinship, geographic distance, and home range overlap, as well as dispersal and philopatry, to determine the extent to which kin associated spatially. I used a combination of microsatellite DNA analysis, long-term behavioral observations, and radiotelemetry to test predictions that females, but not males, would associate with kin. Indeed, woodchucks lived closer and shared a greater proportion of their home range with more closely related animals. Overlap of females' and males' home ranges was positively correlated with kinship, and male–female dyads shared more area with closer kin. Most juveniles delayed dispersal beyond their first summer. Females often remained philopatric and settled near their natal range. Although males often dispersed as yearlings, some males also established territories within or immediately adjacent to their natal home ranges. A combination of factors can explain these spatial patterns, including high population density associated with the study site's location within a suburban environment, high dispersal costs, and abundant food. Thus, despite their asocial and solitary reputation, woodchucks displayed spatial patterns seen in other, more social species of ground-dwelling sciurids.