Foreword

Mitigation and Adaptation Strategies for Global Change -     

台风灾害气象指数保险相关技术方法初探

气象指数灾害保险是目前全球范围内广泛研究的一种风险转移工具,它可以克服传统的自然灾害保险的局限性,在农业保险领域应用前景广阔。以福建省连江县为例,依据连江县台风灾害及台风活动特征,将能够对连江县造成一定损失的台风分成分别以大风、大雨和大风雨为主导的3类。结合连江站相关气象数据及概率分布建立了广义的台风灾害气象指数,最后构建了保险赔付路线图,以供有关部门参考。     

Probability distributions of arsenic in soil from brownfield sites in Beijing (China): statistical characterization of the background populations and implications for site assessment studies

A probabilistic analysis was performed on soil arsenic concentration data from 4 brownfield sites at Beijing (Chaoyang and Haidian Districts), involved in environmental assessment studies. The available data sets were processed to provide a statistical characterization of the background populations and differentiate “anomalous data” from the natural range of variation of arsenic concentrations in soil. The site-specific background distributions and the existing wide-scale background values defined for the Beijing area were compared, discussing related implications for the definition of metal contamination soil screening levels (SSLs) in site assessment studies. The statistical analysis of As data sets discriminated site-specific background populations, encompassing 88% to 94% of the sample data, from outliers values, associated with either subsoil natural enrichments or possible anthropogenic releases. Upper Baseline Concentration (UBC) limits (+ 2σ level), including most of the site-specific metal background variability, were derived based on the statistical characterization of the background populations. Sites in the Chaoyang South District area had UBC values in the range 10.4–12.6 mg·kg^-1. These ranges provide meaningful SSL values to be adopted for As in local site assessment studies. Using the wide-scale background value for the Beijing area would have erroneously classified most of the areas in the subject sites as potentially contaminated.     

A simple linear model for estimating ozone AOT40 at forest sites from raw passive sampling data

A rapid, empirical method is described for estimating weekly AOT40 from ozone concentrations measured with passive samplers at forest sites. The method is based on linear regression and was developed after three years of measurements in Trentino (northern Italy). It was tested against an independent set of data from passive sampler sites across Italy. It provides good weekly estimates compared with those measured by conventional monitors (0.85 ≤R(2)≤ 0.970; 97 ≤ RMSE ≤ 302). Estimates obtained using passive sampling at forest sites are comparable to those obtained by another estimation method based on modelling hourly concentrations (R(2) = 0.94; 131 ≤ RMSE ≤ 351). Regression coefficients of passive sampling are similar to those obtained with conventional monitors at forest sites. Testing against an independent dataset generated by passive sampling provided similar results (0.86 ≤R(2)≤ 0.99; 65 ≤ RMSE ≤ 478). Errors tend to accumulate when weekly AOT40 estimates are summed to obtain the total AOT40 over the May-July period, and the median deviation between the two estimation methods based on passive sampling is 11%. The method proposed does not require any assumptions, complex calculation or modelling technique, and can be useful when other estimation methods are not feasible, either in principle or in practice. However, the method is not useful when estimates of hourly concentrations are of interest.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Correlation of six anthropogenic markers in wastewater, surface water, bank filtrate, and soil aquifer treatment

Six trace contaminants (acesulfame (ACE), sucralose (SUC), carbamazepine (CBZ), diatrizoic acid (DTA), 1H-benzotriazole (BTZ) and its 4-methyl analogue (4-TTri)) were traced from wastewater treatment plants (WWTPs) to receiving waters and further to riverbank filtration (RBF) wells to evaluate their prediction power as potential wastewater markers. Furthermore, the persistence of some compounds was investigated in advanced wastewater treatment by soil aquifer treatment (SAT). During wastewater treatment in four conventional activated sludge WWTPs ACE, SUC, and CBZ showed a pronounced stability expressed by stable concentration ratios in influent (in) and effluent (out) (ACE/CBZ: in45, out40; SUC/CBZ: in1.8, out1.7; and ACE/SUC: in24, out24). In a fifth WWTP, additional treatment with powdered activated carbon led to a strong elimination of CBZ, BTZ, and 4-TTri of about 80% and consequently to a distinctive shift of their ratios with unaffected compounds. Data from a seven month monitoring program at seven sampling locations at the rivers Rhine and Main in Germany revealed the best concentration correlation for ACE and CBZ (r(2) = 0.94) and also a good correlation of ACE and CBZ concentrations to BTZ and 4-TTri levels (r(2) = 0.66 to 0.82). The comparison of ratios at different sampling sites allowed for the identification of a CBZ point source. Furthermore, in Switzerland a higher consumption of SUC compared to Germany can be assumed, as a steadily increasing ACE/SUC ratio along the river Rhine was observed. In RBF wells a good correlation (r(2) = 0.85) was again observed for ACE and CBZ. Both also showed the highest stability at a prolonged residence time in the subsurface of a SAT field. In the most peripheral wells ACE and CBZ were still detected with mean values higher than 36 μg L(-1) and 1.3 μg L(-1), respectively. Although SUC concentrations in wastewater used for SAT decreased by more than 80% from about 18 μg L(-1) to 2.1 μg L(-1) and 3.5 μg L(-1) in these outlying wells, the compound was still adequate to indicate a wastewater impact in a qualitative way.     

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.     

Benefits of protected areas for nonbreeding waterbirds adjusting their distributions under climate warming

Climate warming is driving changes in species distributions and community composition. Many species have a so-called climatic debt, that is, shifts in range lag behind shifts in temperature isoclines. Inside protected areas (PAs), community changes in response to climate warming can be facilitated by greater colonization rates by warm-dwelling species, but also mitigated by lowering extirpation rates of cold-dwelling species. An evaluation of the relative importance of colonization-extirpation processes is important to inform conservation strategies that aim for both climate debt reduction and species conservation. We assessed the colonization-extirpation dynamics involved in community changes in response to climate inside and outside PAs. To do so, we used 25 years of occurrence data of nonbreeding waterbirds in the western Palearctic (97 species, 7071 sites, 39 countries, 1993–2017). We used a community temperature index (CTI) framework based on species thermal affinities to investigate species turnover induced by temperature increase. We determined whether thermal community adjustment was associated with colonization by warm-dwelling species or extirpation of cold-dwelling species by modeling change in standard deviation of the CTI (CTI_SD). Using linear mixed-effects models, we investigated whether communities in PAs had lower climatic debt and different patterns of community change than communities outside PAs. For CTI and CTI_SD combined, communities inside PAs had more species, higher colonization, lower extirpation, and lower climatic debt (16%) than communities outside PAs. Thus, our results suggest that PAs facilitate 2 independent processes that shape community dynamics and maintain biodiversity. The community adjustment was, however, not sufficiently fast to keep pace with the large temperature increases in the central and northeastern western Palearctic. Our results underline the potential of combining CTI and CTI_SD metrics to improve understanding of the colonization-extirpation patterns driven by climate warming.     

Convergence or divergence in desertification risk? Scale-based assessment and policy implications in a Mediterranean country

This paper explores changes (1990–2000) in two environmental indexes with the aim of providing empirical evidence on regional and local convergence in an increasing-impact phenomenon such as Land Degradation (LD) in Italy. Convergence analysis for ESAI (Environmental Sensitive Area Index) and LVI (Land Vulnerability Index) was developed at five different geographical scales. Results indicate that territorial disparities in land vulnerability tend to increase during the investigated period following a defined spatial pattern that depends on land quality, the environmental context and the economic performance of regional systems. Finally, the implications this process has on policy strategies aimed at mitigating desertification risk are discussed.