Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

A study on the factor market distortion and the carbon emission scale effect of two-way FDI

Based on the data of 30 Chinese provinces for the period from 2004 to 2015, this paper expounds the carbon emissions effect of two-way foreign direct investment (FDI) from the perspective of scale effect and factor market distortions. This study uses Kaya identity to decompose carbon emission and construct simultaneous equations model to empirically examine the factor market distortion and the carbon emission scale effect of two-way FDI. The results show that the inward foreign direct investment (IFDI) increase regional carbon emission through scale effect and also exacerbates factor market distortion in China, whereas the outward FDI trends reduce carbon emission and reduces factor market distortions in China. The study also shows that human capital, research and development (R&D), trade openness, and capital accumulation are important determinants of two-way FDI. Therefore, the study proposes that IFDI policies should focus on acquiring green technologies. In addition, the domestic enterprises should be encouraged to participate in global business.     

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base‐flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite‐nitrate (NO₂‐NO₃), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO₂‐NO₃ concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed‐use and heavily impacted watersheds.     

A review of vulnerability indicators for deltaic social–ecological systems

The sustainability of deltas worldwide is under threat due to the consequences of global environmental change (including climate change) and human interventions in deltaic landscapes. Understanding these systems is becoming increasingly important to assess threats to and opportunities for long-term sustainable development. Here, we propose a simplified, yet inclusive social–ecological system (SES)-centered risk and vulnerability framework and a list of indicators proven to be useful in past delta assessments. In total, 236 indicators were identified through a structured review of peer-reviewed literature performed for three globally relevant deltas—the Mekong, the Ganges–Brahmaputra–Meghna and the Amazon. These are meant to serve as a preliminary “library” of potential indicators to be used for future vulnerability assessments. Based on the reviewed studies, we identified disparities in the availability of indicators to populate some of the vulnerability domains of the proposed framework, as comprehensive social–ecological assessments were seldom implemented in the past. Even in assessments explicitly aiming to capture both the social and the ecological system, there were many more indicators for social susceptibility and coping/adaptive capacities as compared to those relevant for characterizing ecosystem susceptibility or robustness. Moreover, there is a lack of multi-hazard approaches accounting for the specific vulnerability profile of sub-delta areas. We advocate for more comprehensive, truly social–ecological assessments which respond to multi-hazard settings and recognize within-delta differences in vulnerability and risk. Such assessments could make use of the proposed framework and list of indicators as a starting point and amend it with new indicators that would allow capturing the complexity as well as the multi-hazard exposure in a typical delta SES.     

Population Structure of Sable in the Baikal Mountain Land: Analysis of Genetic and Phenotypic Traits

Russian Journal of Ecology - The genetic and phenotypic structure (according to the fur color) of 14 sable samples from the Baikal mountain land (BML) has been studied by analyzing 257 animals for...     

Research on the experiment of the enhancement removal of fine sand by hydrocyclone in sewage treatment plant

The content of fine sand (< 200 μm) in primary sludge is relatively high in Chongqing sewage treatment plant owing to the part of rainwater will be mixed with sand and discharged into the municipal pipe network. Due to the insufficient separation of the sand, different obstacles to subsequent treatment processes may increase equipment wear, reduce effective volume of the tank, or shorten the cleaning cycle. There is a common use of grit chamber for the separation. Nevertheless, the use of hydrocyclone shows an outstanding performance in cost effectiveness and ease operation. The primary sludge in a sewage plant in Chongqing was monitored, and the average concentration of total suspend solids (TSS), total sand content, and volatile suspended solid (VSS) were 40.25 g/L, 17.51 g/L, and 13.41 g/L, respectively. The size of sand in the sludge was small, and the sand below 30 μm accounted for about 70% of the total sand. It formed flocs with organic matter and was removed in subsequent process units. While the size between 30–200 μm, called fine sand, was the main separation object, accounted for about 28.5%. According to XRF and XRD analysis, the sludge composition was mainly composed of quartz (SiO₂), plagioclase (Na(AlSi₃O₈)), and calcite (CaCO₃), which were similar to the main mineral composition of surface sediments and mountain rocks in the main urban area of Chongqing. A single-factor experiment on two types (FX100 and FX50) of hydrocylones was conducted to determine their abilities concerning the separation of fine sand and enrichment of organic matters from primary sludge. FX100 and FX50 showed best performance in the case of P = 0.17 Mpa, underflow diameter (Du) = 18 mm and P = 0.20 Mpa, Du = 6 mm, respectively. The removal efficiency of fine sand by hydrocyclone FX50 was 71.39%. While, it had poor performance on organic matter enrichment and the removal efficiency of which was 17.38%. By contrast, the removal rate by FX100 reached 61.89% for fine sand and only 6.89% for organic matters detached. The superimposition effect did not appear in the serial experiments on hydrocylone FX100 and FX50, but the power is 3.5 times of that of single-stage hydrocylone FX100. Comprehensive consideration of the processing capacity per unit time and operating power, the hydrocylone FX100 was more suitable for actual operation.