Comparison of boosted regression tree and random forest models for mapping topsoil organic carbon concentration in an alpine ecosystem

Soil organic carbon (SOC) plays an important role in soil fertility and carbon sequestration, and a better understanding of the spatial patterns of SOC is essential for soil resource management. In this study, we used boosted regression tree (BRT) and random forest (RF) models to map the distribution of topsoil organic carbon content at the northeastern edge of the Tibetan Plateau in China. A set of 105 soil samples and 12 environmental variables (including topography, climate and vegetation) were analyzed. The performance of the models was evaluated using a 10-fold cross-validation procedure. Maps of the mean values and standard deviations of SOC were generated to illustrate model variability and uncertainty. The results indicate that the BRT and RF models exhibited very similar performance and yielded similar predicted distributions of SOC. The two models explained approximately 70% of the total SOC variability. The BRT and RF models robustly predicted the SOC at low observed SOC values, whereas they underestimated high observed SOC values. This underestimation may have been caused by biased distributions of soil samples in the SOC space. Vegetation-related variables were assigned the highest importance in both models, followed by climate and topography. Both models produced spatial distribution maps of SOC that were closely related to vegetation cover. The SOC content predicted by the BRT model was clearly higher than that of the RF model in areas with greater vegetation cover because the contributions of vegetation-related variables in the two models (65% and 43%, respectively) differed significantly. The predicted SOC content increased from the northwestern to the southeastern part of the study area, average values produced by the BRT and RF models were 27.3 g kg⁻¹ and 26.6 g kg⁻¹, respectively. We conclude that the BRT and RF methods should be calibrated and compared to obtain the best prediction of SOC spatial distribution in similar regions. In addition, vegetation variables, including those obtained from remote sensing imagery, should be taken as the main environmental indicators and explicitly included when generating SOC maps in Alpine environments.     

Climatic effects on the distribution of ant- and bat fly-associated fungal ectoparasites (Ascomycota,Laboulbeniales)

Laboulbeniales (Ascomycota: Laboulbeniomycetes) are obligate ectoparasitic fungi of arthropods with a worldwide distribution. Their effects on host physiology and behaviour as well as their ecology have recently gained wider attention. One aspect that is virtually unknown regarding Laboulbeniales and arthropod-associated fungi in general, is how abiotic factors shape the distribution of these parasites. We used ant- and bat fly-associated Laboulbeniales to study whether climatic elements play a role in the distribution of fungal species. We collected uninfected and Laboulbeniales-infected insects belonging to three species: bat flies Nycteribia schmidlii and Penicillidia conspicua (Diptera: Nycteribiidae) and the ant Myrmica scabrinodis (Hymenoptera: Formicidae). We used climatic variables and performed statistical analyses to explain the distribution of Laboulbeniales infection. Our results show a higher likelihood of Laboulbeniales presence in habitats with low annual mean temperature and humidity, suggesting that climatic elements can considerably shape the distribution of Laboulbeniales species.     

Spatial variation in the ongoing and widespread decline of a keystone plant species

Extensive dieback in dominant plant species in response to climate change is increasingly common. Climatic conditions and related variables, such as evapotranspiration, vary in response to topographical complexity. This complexity plays an important role in the provision of climate refugia. In 2008/2009, an island‐wide dieback event of the keystone cushion plant Azorella macquariensis Orchard (Apiaceae) occurred on sub‐Antarctic Macquarie Island. This signalled the start of a potential regime shift, suggested to be driven by increasing vapour pressure deficit. Eight years later, we quantified cover and dieback across the range of putative microclimates to which the species is exposed, with the aim of explaining dieback patterns. We test for the influence of evapotranspiration using a suite of topographic proxies and other variables as proposed drivers of change. We found higher cover and lower dieback towards the south of the island. The high spatial variation in A. macquariensis populations was best explained by latitude, likely a proxy for macroscale climate gradients and geology. Dieback was best explained by A. macquariensis cover and latitude, increasing with cover and towards the north of the island. The effect sizes of terrain variables that influence evapotranspiration rates were small. Island‐wide dieback remains conspicuous. Comparison between a subset of sites and historical data revealed a reduction of cover in the north and central regions of the island, and a shift south in the most active areas of dieback. Dieback remained comparatively low in the south. The presence of seedlings was independent of dieback. This study provides an empirical baseline for spatial variation in the cover and condition of A. macquariensis, both key variables for monitoring condition and ‘cover‐debt’ in this critically endangered endemic plant species. These findings have broader implications for understanding the responses of fellfield ecosystems and other Azorella species across the sub‐Antarctic under future climates.     

Red panda fine‐scale habitat selection along a Central Himalayan longitudinal gradient

Red panda Ailurus fulgens, an endangered habitat specialist, inhabits a narrow distribution range in bamboo abundance forests along mountain slopes in the Himalaya and Hengduan Mountains. However, their habitat use may be different in places with different longitudinal environmental gradients, climatic regimes, and microclimate. This study aimed to determine the habitat variables affecting red panda distribution across different longitudinal gradients through a multivariate analysis. We studied habitat selection patterns along the longitudinal gradient in Nepal's Himalaya which is grouped into the eastern, central, and western complexes. We collected data on red panda presence and habitat variables (e.g., tree richness, canopy cover, bamboo abundance, water availability, tree diameter, tree height) by surveys along transects throughout the species’ potential range. We used a multimodal inference approach with a generalized linear model to test the relative importance of environmental variables. Although the study showed that bamboo abundance had a major influence, habitat selection was different across longitudinal zones. Both canopy cover and species richness were unimportant in eastern Nepal, but their influence increased progressively toward the west. Conversely, tree height showed a decreasing influence on habitat selection from Eastern to Western Nepal. Red panda's habitat selection revealed in this study corresponds to the uneven distribution of vegetation assemblages and the dry climatic gradient along the eastern‐western Himalayas which could be related to a need to conserve energy and thermoregulate. This study has further highlighted the need of importance of bamboo conservation and site‐specific conservation planning to ensure long‐term red panda conservation.     

The N-acylethanolamine-mediated regulatory pathway in plants

While cannabinoids are secondary metabolites synthesized by just a few plant species, N-acylethanolamines (NAEs) are distributed widely in the plant kingdom, and are recovered in measurable, bioactive quantities in many plant-derived products. NAEs in higher plants are ethanolamides of fatty acids with acyl-chain lenghts of C12-C(18) and zero to three C=C bonds. Generally, the most-abundant NAEs found in plants and vertebrates are similar, including NAE 16 : 0, 18 : 1, 18 : 2, and 18 : 3. Like in animal systems, NAEs are formed in plants from N-acylphosphatidylethanolamines (NAPEs), and they are hydrolyzed by an amidase to yield ethanolamine and free fatty acids (FFA). Recently, a homologue of the mammalian fatty acid amide hydrolase (FAAH-1) was identified in Arabidopsis thaliana and several other plant species. Overexpression of Arabidopsis FAAH (AtFAAH) resulted in plants that grew faster, but were more sensitive to biotic and abiotic insults, suggesting that the metabolism of NAEs in plants resides at the balance between growth and responses to environmental stresses. Similar to animal systems, exogenously applied NAEs have potent and varied effects on plant cells. Recent pharmacological approaches combined with molecular-genetic experiments revealed that NAEs may act in certain plant tissues via specific membrane-associated proteins or by interacting with phospholipase D-alpha, although other, direct targets for NAE action in plants are likely to be discovered. Polyunsaturated NAEs can be oxidized via the lipoxygenase pathway in plants, producing an array of oxylipin products that have received little attention so far. Overall, the conservation of NAE occurrence and metabolic machinery in plants, coupled with the profound physiological effects of elevating NAE content or perturbing endogenous NAE metabolism, suggest that an NAE-mediated regulatory pathway, sharing similarities with the mammalian endocannabinoid pathway, indeed exists.     

Mendelian randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

We analyze how measures of adiposity – body mass index (BMI) and waist hip ratio (WHR) – causally influence rates of hospital admission. Conventional analyses of this relationship are susceptible to omitted variable bias from variables that jointly influence both hospital admission and adipose status. We implement a novel quasi-Poisson instrumental variable model in a Mendelian randomization framework, identifying causal effects from random perturbations to germline genetic variation. We estimate the individual and joint effects of BMI, WHR, and WHR adjusted for BMI. We also implement multivariable instrumental variable methods in which the causal effect of one exposure is estimated conditionally on the causal effect of another exposure. Data on 310,471 participants and over 550,000 inpatient admissions in the UK Biobank were used to perform one-sample and two-sample Mendelian randomization analyses. The results supported a causal role of adiposity on hospital admissions, with consistency across all estimates and sensitivity analyses. Point estimates were generally larger than estimates from comparable observational specifications. We observed an attenuation of the BMI effect when adjusting for WHR in the multivariable Mendelian randomization analyses, suggesting that an adverse fat distribution, rather than a higher BMI itself, may drive the relationship between adiposity and risk of hospital admission.     

萱草响应非生物胁迫的研究进展

萱草是萱草属(Hemerocallis)多年生宿根花卉,被誉为中华母亲花,具有重要的观赏和药用价值。非生物胁迫导致光合效率降低,渗透调节物质浓度改变,活性氧(ROS)含量上升,膜系统持续受损,诱导AP2/ERF (APETALA2/ethylene-responsive element binding factors)、WRKY等家族基因的表达。该文综述了干旱、涝渍、盐碱、极端温度和重金属胁迫非生物胁迫因子对萱草形态学、生理生化及分子水平的影响,统计了各胁迫下的萱草抗性品种资源,认为地域与胁迫对萱草药用成分代谢变化的影响、抗逆相关基因调控网络与多种胁迫复合分子育种为未来的重点研究方向,为萱草资源开发利用与抗逆品种育种提供理论参考。     

Forecasting the potential distribution of Spodoptera exigua and S. littoralis (Lepidoptera,Noctuidae) in Iran

The beet armyworm, Spodoptera exigua (Hübner, 1808) and the Egyptian cotton leafworm, S. littoralis (Boisduval, 1833), are amongst the most notorious agricultural pest species in Iran. Spodoptera exigua is considered a serious pest of different crops, whereas S. littoralis is known as an important pest of cotton.In this paper, the potential distribution areas of these species in Iran and the important climatic factors affecting their distribution were predicted using the MaxEnt model and the ArcGIS. The results indicate that the main environmental variables contributing to S. exigua’s distribution were precipitation of the coldest quarter (bio19), average wind speed in April (wind4), and annual precipitation (bio12). Also, minimum temperature of the coldest month (bio6), mean temperature of coldest quarter (bio11), altitude and average wind speed in May (wind5) were dominant climatic factors that affected the potential distribution of S. littoralis. These species overlapped in most parts of coastal areas in the southern and northern parts of Iran, with an average overlapping range of 33.2%. Considering their preferred host plants in Iran, it is necessary to strengthen biosurveillance programes and management of these two species in their suitable areas to prevent further invasion, which endangers agricultural security.