华西雨屏区植被恢复对紫色土酸化的影响

退耕还林是控制水土流失、恢复森林植被和改善生态环境的重要举措。植被恢复进程中会发生土壤酸化,进而影响植物生长,厘清不同还林树种对土壤酸化的影响程度及作用机制有助于更好地评估退耕还林工程的整体生态效益。以华西雨屏区紫色土坡耕地(玉米)为对照,分析了退耕20a后柳杉纯林、柳杉-光皮桦混交林、慈竹林和茶园土壤pH的变化及其垂直分异。结果表明：玉米地、慈竹林、茶园、混交林和柳杉纯林0—50 cm土壤pH平均值分别为5.66、5.55、5.12、5.03和5.00,相较于玉米地,柳杉纯林、混交林和茶园土壤pH值显著下降(P<0.01),土壤酸化严重。相较于玉米地土壤pH值的均匀分布,植被恢复不同类型人工林pH值随土壤深度的增加而增加,10—50 cm土壤pH值(4.89—5.90)显著高于0—10 cm土壤pH值(4.72—5.21)(P<0.01),表层土壤酸化最明显。土壤pH值与土壤有机质含量呈极显著负相关,而与风化指数Na/K比值呈显著正相关,有机质含量和Na/K比值共同解释了土壤pH值变化的53.9%,表明植被恢复引起的土壤有机质积累与长石类矿物风化是驱动紫色土酸化的重要过程...     

Influence of drought-induced acidification on the mobility of dissolved organic carbon in peat soils

A strong relationship between dissolved organic carbon (DOC) and sulphate (SO₄^2?) dynamics under drought conditions has been revealed from analysis of a 10‐year time series (1993–2002). Soil solution from a blanket peat at 10 cm depth and stream water were collected at biweekly and weekly intervals, respectively, by the Environmental Change Network at Moor House‐Upper Teesdale National Nature Reserve in the North Pennine uplands of Britain. DOC concentrations in soil solution and stream water were closely coupled, displaying a strong seasonal cycle with lowest concentrations in early spring and highest in late summer/early autumn. Soil solution DOC correlated strongly with seasonal variations in soil temperature at the same depth 4‐weeks prior to sampling. Deviation from this relationship was seen, however, in years with significant water table drawdown (>?25 cm), such that DOC concentrations were up to 60% lower than expected. Periods of drought also resulted in the release of SO₄^2?, because of the oxidation of inorganic/organic sulphur stored in the peat, which was accompanied by a decrease in pH and increase in ionic strength. As both pH and ionic strength are known to control the solubility of DOC, inclusion of a function to account for DOC suppression because of drought‐induced acidification accounted for more of the variability of DOC in soil solution (R²=0.81) than temperature alone (R²=0.58). This statistical model of peat soil solution DOC at 10 cm depth was extended to reproduce 74% of the variation in stream DOC over this period. Analysis of annual budgets showed that the soil was the main source of SO₄^2? during droughts, while atmospheric deposition was the main source in other years. Mass balance calculations also showed that most of the DOC originated from the peat. The DOC flux was also lower in the drought years of 1994 and 1995, reflecting low DOC concentrations in soil and stream water. The analysis presented in this paper suggests that lower concentrations of DOC in both soil and stream waters during drought years can be explained in terms of drought‐induced acidification. As future climate change scenarios suggest an increase in the magnitude and frequency of drought events, these results imply potential for a related increase in DOC suppression by episodic acidification.     

β‐Cyclodextrin hydrogels containing naphthaleneacetic acid for pH‐sensitive release

β‐Cyclodextrin (β‐CD) hydrogel was prepared in a strong alkali condition using epichlorohydrin (EPI) as a cross‐linker, where the molar ratios of EPI to β‐CD were 8:1, 10:1, and 15:1. In order to endow a pH sensitivity to the hydrogel, naphthaleneacetic acid (NAA) was loaded in the hydrogel by taking advantage of its hydrophobic interaction with the cavities of β‐CD. The releases of blue dextran (a water‐soluble dye) from the hydrogels were promoted, as the pHs of the media increased. When the molar ratio of EPI to β‐CD was lower, the degrees of release were higher, and the pH dependency of the release became more prominent. In fact, the swelling ratio of the hydrogels having a lower molar ratio of EPI to β‐CD was higher. The higher swelling ratio would account for the higher degree of release and the marked pH sensitivity. Biotechnol. Bioeng. 2010;106: 295–302. © 2010 Wiley Periodicals, Inc.     

Bromeliads provide shelter against fire to mutualistic spiders in a fire‐prone landscape

1. A key challenge in the study of mutualistic interactions is understanding sources of variation that strengthen or weaken these interactions. In spider–plant mutualisms, spiders benefit plants by improving plant nutrition and protecting plants from herbivory. Although the benefits of plants to spider growth and survival are often claimed, they are rarely demonstrated. 2. In this study, empirical evidence is provided that bromeliads (Bromelia balansae, Bromeliaceae) are essential for the resilience of the mutualistic bromeliad‐living jumping spider populations (Psecas chapoda, Salticidae) after a fire event, sheltering spiders from the heat of the flames. 3. Spider populations were compared before and after a natural fire event and it was shown that spiders of different ages survived the fire. The survival of such individuals allowed the population of P. chapoda spiders to recover rapidly, returning to pre‐fire levels in 5 months. 4. Bromeliads reduced the susceptibility of P. chapoda spiders to burning, and this mutualistic relationship contributed to the resilience of the spider population after a fire event. It is suggested that frequent fires in fire‐prone landscapes may have strengthened this spider–plant relationship, contributing to the maintenance and evolution of this association.     

Soil acidification reduces the effects of short‐term nutrient enrichment on plant and soil biota and their interactions in grasslands

Soil nitrogen (N) and phosphorus (P) contents, and soil acidification have greatly increased in grassland ecosystems due to increased industrial and agricultural activities. As major environmental and economic concerns worldwide, nutrient enrichment and soil acidification can lead to substantial changes in the diversity and structure of plant and soil communities. Although the separate effects of N and P enrichment on soil food webs have been assessed across different ecosystems, the combined effects of N and P enrichment on multiple trophic levels in soil food webs have not been studied in semiarid grasslands experiencing soil acidification. Here we conducted a short‐term N and P enrichment experiment in non‐acidified and acidified soil in a semiarid grassland on the Mongolian Plateau. We found that net primary productivity was not affected by N or P enrichment alone in either non‐acidified or acidified soil, but was increased by combined N and P enrichment in both non‐acidified and acidified soil. Nutrient enrichment decreased the biomass of most microbial groups in non‐acidified soil (the decrease tended to be greatest with combined N and P enrichment) but not in acidified soil, and did not affect most soil nematode variables in non‐acidified or acidified soil. Nutrient enrichment also changed plant and microbial community structure in non‐acidified but not in acidified soil, and had no effect on nematode community structure in non‐acidified or acidified soil. These results indicate that the responses to short‐term nutrient enrichment were weaker for higher trophic groups (nematodes) than for lower trophic groups (microorganisms) and primary producers (plants). The findings increase our understanding of the effects of nutrient enrichment on multiple trophic levels of soil food webs, and highlight that soil acidification, as an anthropogenic stressor, reduced the responses of plants and soil food webs to nutrient enrichment and weakened plant–soil interactions.     

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.     

Impact of the leaf miner Cameraria ohridella (Lepidoptera: Gracillariidae) and bleeding canker disease on horse‐chestnut: direct effects and interaction

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nNOS–CAPON interaction mediates amyloid‐β‐induced neurotoxicity,especially in the early stages

In neurons, increased protein–protein interactions between neuronal nitric oxide synthase (nNOS) and its carboxy‐terminal PDZ ligand (CAPON) contribute to excitotoxicity and abnormal dendritic spine development, both of which are involved in the development of Alzheimer's disease. In models of Alzheimer's disease, increased nNOS–CAPON interaction was detected after treatment with amyloid‐β in vitro, and a similar change was found in the hippocampus of APP/PS1 mice (a transgenic mouse model of Alzheimer's disease), compared with age‐matched background mice in vivo. After blocking the nNOS–CAPON interaction, memory was rescued in 4‐month‐old APP/PS1 mice, and dendritic impairments were ameliorated both in vivo and in vitro. Furthermore, we demonstrated that S‐nitrosylation of Dexras1 and inhibition of the ERK–CREB–BDNF pathway might be downstream of the nNOS–CAPON interaction.     

Preparation of pH‐stimuli‐responsive PEG–TGA/TGH‐capped CdTe QDs and their application in cell labeling

A pH‐sensitive and double functional nanoprobe was designed and synthesized in a water‐soluble system using thioglycolic acid (TGA) and mercapto‐acetohydrazide (TGH) as the stabilizers. TGA is biocompatible because the carboxyl group is easily linked to biological macromolecules. At the same time, the hydrazide on TGH reacts with the aldehyde on poly(ethylene glycol) (PEG) and forms a hydrazone bond. The hydrazone bond ruptured at specific pH values and exhibited pH‐stimuli‐responsive characteristics. As an optical imaging probe, the PEG–TGA/TGH‐capped CdTe quantum dots (QDs) had high quality, with a fluorescence efficiency of 25–30%, and remained stable for at least five months. This pH‐responsive factor can be used for the effective release of CdTe QDs under the acidic interstitial extracellular environment of tumor cells. This allows the prepared pH‐stimuli‐responsive nanoprobes to show fluorescence signals for use in cancer cell imaging. Copyright © 2014 John Wiley & Sons, Ltd.     

Restoration success of low‐production plant communities on former agricultural soils after top‐soil removal

Abstract. The success inrestoring seven low‐production vegetation types on former agricultural soil after top‐soil removal was investigated. The colonization and establishment of target species in permanent plots was recorded during the first nine years after restoration measures were taken. For each permanent plot abiotic site conditions were used to determine which of the vegetation types could persist there. A comparison of the actual vegetation in the permanent plots with reference releves of the selected vegetation type revealed a gradually increasing similarity during consecutive years for five vegetation types. This was due to the occurrence of an increasing number of target species and the number of permanent plots they occurred in. However, nine years after top‐soil removal a large number of the target species were still lacking from the vegetation in the permanent plots, although most were present in the local species pool. Seed dispersal therefore seems to be a major limiting factor for restoration of these low‐production vegetation types on formerly agricultural soils.     

MotifAnalyzer‐PDZ: A computational program to investigate the evolution of PDZ‐binding target specificity

Recognition of short linear motifs (SLiMs) or peptides by proteins is an important component of many cellular processes. However, due to limited and degenerate binding motifs, prediction of cellular targets is challenging. In addition, many of these interactions are transient and of relatively low affinity. Here, we focus on one of the largest families of SLiM‐binding domains in the human proteome, the PDZ domain. These domains bind the extreme C‐terminus of target proteins, and are involved in many signaling and trafficking pathways. To predict endogenous targets of PDZ domains, we developed MotifAnalyzer‐PDZ, a program that filters and compares all motif‐satisfying sequences in any publicly available proteome. This approach enables us to determine possible PDZ binding targets in humans and other organisms. Using this program, we predicted and biochemically tested novel human PDZ targets by looking for strong sequence conservation in evolution. We also identified three C‐terminal sequences in choanoflagellates that bind a choanoflagellate PDZ domain, the Monsiga brevicollis SHANK1 PDZ domain (mbSHANK1), with endogenously‐relevant affinities, despite a lack of conservation with the targets of a homologous human PDZ domain, SHANK1. All three are predicted to be signaling proteins, with strong sequence homology to cytosolic and receptor tyrosine kinases. Finally, we analyzed and compared the positional amino acid enrichments in PDZ motif‐satisfying sequences from over a dozen organisms. Overall, MotifAnalyzer‐PDZ is a versatile program to investigate potential PDZ interactions. This proof‐of‐concept work is poised to enable similar types of analyses for other SLiM‐binding domains (e.g., MotifAnalyzer‐Kinase). MotifAnalyzer‐PDZ is available at http://motifAnalyzerPDZ.cs.wwu.edu .     

Virulence of oomycete pathogens from Phragmites australis‐invaded and noninvaded soils to seedlings of wetland plant species

Soil pathogens affect plant community structure and function through negative plant–soil feedbacks that may contribute to the invasiveness of non‐native plant species. Our understanding of these pathogen‐induced soil feedbacks has relied largely on observations of the collective impact of the soil biota on plant populations, with few observations of accompanying changes in populations of specific soil pathogens and their impacts on invasive and noninvasive species. As a result, the roles of specific soil pathogens in plant invasions remain unknown. In this study, we examine the diversity and virulence of soil oomycete pathogens in freshwater wetland soils invaded by non‐native Phragmites australis (European common reed) to better understand the potential for soil pathogen communities to impact a range of native and non‐native species and influence invasiveness. We isolated oomycetes from four sites over a 2‐year period, collecting nearly 500 isolates belonging to 36 different species. These sites were dominated by species of Pythium, many of which decreased seedling survival of a range of native and invasive plants. Despite any clear host specialization, many of the Pythium species were differentially virulent to the native and non‐native plant species tested. Isolates from invaded and noninvaded soils were equally virulent to given individual plant species, and no apparent differences in susceptibility were observed between the collective groups of native and non‐native plant species.     

Combining point‐process and landscape vegetation models to predict large herbivore distributions in space and time—A case study of Rupicapra rupicapra

Aim

When modelling the distribution of animals under current and future conditions, both their response to environmental constraints and their resources’ response to these environmental constraints need to be taken into account. Here, we develop a framework to predict the distribution of large herbivores under global change, while accounting for changes in their main resources. We applied it to Rupicapra rupicapra, the chamois of the European Alps.

Location

The Bauges Regional Park (French Alps).

Methods

We built sixteen plant functional groups (PFGs) that account for the chamois’ diet (estimated from sequenced environmental DNA found in the faeces), climatic requirements, dispersal limitations, successional stage and interaction for light. These PFGs were then simulated using a dynamic vegetation model, under current and future climatic conditions up to 2100. Finally, we modelled the spatial distribution of the chamois under both current and future conditions using a point‐process model applied to either climate‐only variables or climate and simulated vegetation structure variables.

Results

Both the climate‐only and the climate and vegetation models successfully predicted the current distribution of the chamois species. However, when applied into the future, the predictions differed widely. While the climate‐only models predicted an 80% decrease in total species occupancy, including vegetation structure and plant resources for chamois in the model provided more optimistic predictions because they account for the transient dynamics of the vegetation (?20% in species occupancy).

Main conclusions

Applying our framework to the chamois shows that the inclusion of ecological mechanisms (i.e., plant resources) produces more realistic predictions under current conditions and should prove useful for anticipating future impacts. We have shown that discounting the pure effects of vegetation on chamois might lead to overpessimistic predictions under climate change. Our approach paves the way for improved synergies between different fields to produce biodiversity scenarios.

     

Forest responses to simulated elevated CO2 under alternate hypotheses of size‐ and age‐dependent mortality

Elevated atmospheric carbon dioxide (eCO₂) is predicted to increase growth rates of forest trees. The extent to which increased growth translates to changes in biomass is dependent on the turnover time of the carbon, and thus tree mortality rates. Size‐ or age‐dependent mortality combined with increased growth rates could result in either decreased carbon turnover from a speeding up of tree life cycles, or increased biomass from trees reaching larger sizes, respectively. However, most vegetation models currently lack any representation of size‐ or age‐dependent mortality and the effect of eCO₂ on changes in biomass and carbon turnover times is thus a major source of uncertainty in predictions of future vegetation dynamics. Using a reduced‐complexity form of the vegetation demographic model the Functionally Assembled Terrestrial Ecosystem Simulator to simulate an idealised tropical forest, we find increases in biomass despite reductions in carbon turnover time in both size‐ and age‐dependent mortality scenarios in response to a hypothetical eCO₂‐driven 25% increase in woody net primary productivity (wNPP). Carbon turnover times decreased by 9.6% in size‐dependent mortality scenarios due to a speeding up of tree life cycles, but also by 2.0% when mortality was age‐dependent, as larger crowns led to increased light competition. Increases in aboveground biomass (AGB) were much larger when mortality was age‐dependent (24.3%) compared with size‐dependent (13.4%) as trees reached larger sizes before death. In simulations with a constant background mortality rate, carbon turnover time decreased by 2.1% and AGB increased by 24.0%, however, absolute values of AGB and carbon turnover were higher than in either size‐ or age‐dependent mortality scenario. The extent to which AGB increases and carbon turnover decreases will thus depend on the mechanisms of large tree mortality: if increased size itself results in elevated mortality rates, then this could reduce by about half the increase in AGB relative to the increase in wNPP.     

Seasonal soil‐surface carbon fluxes from the root systems of young Pinus radiata trees growing at ambient and elevated CO2 concentration

Elevated atmospheric CO₂ concentration may result in increased below‐ground carbon allocation by trees, thereby altering soil carbon cycling. Seasonal estimates of soil surface carbon flux were made to determine whether carbon losses from Pinus radiata trees growing at elevated CO₂ concentration were higher than those at ambient CO₂ concentration, and whether this was related to increased fine root growth. Monthly soil surface carbon flux density (f) measurements were made on plots with trees growing at ambient (350) and elevated (650 μmol mol^?1) CO₂ concentration in large open‐top chambers. Prior to planting the soil carbon concentration (0.1%) and f (0.28 μmol m^?2 s^?1 at 15 °C) were low. A function describing the radial pattern of f with distance from tree stems was used to estimate the annual carbon flux from tree plots. Seasonal estimates of fine root production were made from minirhizotrons and the radial distribution of roots compared with radial measurements of f. A one‐dimensional gas diffusion model was used to estimate f from soil CO₂ concentrations at four depths. For the second year of growth, the annual carbon flux from the plots was 1671 g y^?1 and 1895 g y^?1 at ambient and elevated CO₂ concentrations, respectively, although this was not a significant difference. Higher f at elevated CO₂ concentration was largely explained by increased fine root biomass. Fine root biomass and stem production were both positively related to f. Both root length density and f declined exponentially with distance from the stem, and had similar length scales. Diurnal changes in f were largely explained by changes in soil temperature at a depth of 0.05 m. Ignoring the change of f with increasing distance from tree stems when scaling to a unit ground area basis from measurements with individual trees could result in under‐ or overestimates of soil‐surface carbon fluxes, especially in young stands when fine roots are unevenly distributed.     

Exploring the protein–protein interaction landscape in plants

Protein–protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.     

Molecular dynamics simulation study on the interaction of collagen‐like peptides with gelatinase‐A (MMP‐2)

Although several models have been proposed for the interaction of collagen with gelatinase‐A (matrix metalloproteinases‐2 (MMP‐2)), the extensive role of each domain of gelatinase A in hydrolyzing the collagens with and without interruptions is still elusive. Molecular docking, molecular dynamics (MD) simulation, normal mode analysis (NMA) and framework rigidity optimized dynamics algorithm (FRODAN) based analysis were carried out to understand the function of various domains of MMP‐2 upon interaction with collagen like peptides. The results reveal that the collagen binding domain (CBD) binds to the C‐terminal of collagen like peptide with interruption. CBD helps in unwinding the loosely packed interrupted region of triple helical structure to a greater extent. It can be possible to speculate that the role of hemopexin (HPX) domain is to prevent further unwinding of collagen like peptide by binding to the other end of the collagen like peptide. The catalytic (CAT) domain then reorients itself to interact with the part of the unwound region of collagen like peptide for further hydrolysis. In conclusion the CBD of MMP‐2 recognizes the collagen and aids in unwinding the collagen like peptide with interruptions, and the HPX domain of MMP‐2 binds to the other end of the collagen allowing CAT domain to access the cleavage site. This study provides a comprehensive understanding of the structural basis of collagenolysis by MMP‐2. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 779–794, 2014.     

A compound‐based computational approach for the accurate determination of hot spots

A plethora of both experimental and computational methods have been proposed in the past 20 years for the identification of hot spots at a protein–protein interface. The experimental determination of a protein–protein complex followed by alanine scanning mutagenesis, though able to determine hot spots with much precision, is expensive and has no guarantee of success while the accuracy of the current computational methods for hot‐spot identification remains low. Here, we present a novel structure‐based computational approach that accurately determines hot spots through docking into a set of proteins homologous to only one of the two interacting partners of a compound capable of disrupting the protein–protein interaction (PPI). This approach has been applied to identify the hot spots of human activin receptor type II (ActRII) critical for its binding toward Cripto‐I. The subsequent experimental confirmation of the computationally identified hot spots portends a potentially accurate method for hot‐spot determination in silico given a compound capable of disrupting the PPI in question. The hot spots of human ActRII first reported here may well become the focal points for the design of small molecule drugs that target the PPI. The determination of their interface may have significant biological implications in that it suggests that Cripto‐I plays an important role in both activin and nodal signal pathways.     

Inhibition of interleukin‐1β production by extracellular acidification through the TDAG8/cAMP pathway in mouse microglia

Interleukin‐1β (IL‐1β) is released from activated microglia and involved in the neurodegeneration of acute and chronic brain disorders, such as stroke and Alzheimer's disease, in which extracellular acidification has been shown to occur. Here, we examined the extracellular acidic pH regulation of IL‐1β production, especially focusing on TDAG8, a major proton‐sensing G‐protein‐coupled receptor, in mouse microglia. Extracellular acidification inhibited lipopolysaccharide ‐induced IL‐1β production, which was associated with the inhibition of IL‐1β cytoplasmic precursor and mRNA expression. The IL‐1β mRNA and protein responses were significantly, though not completely, attenuated in microglia derived from TDAG8‐deficient mice compared with those from wild‐type mice. The acidic pH also stimulated cellular cAMP accumulation, which was completely inhibited by TDAG8 deficiency. Forskolin and a cAMP derivative, which specifically stimulates protein kinase A (PKA), mimicked the proton actions, and PKA inhibitors reversed the acidic pH‐induced IL‐1β mRNA expression. The acidic pH‐induced inhibitory IL‐1β responses were accompanied by the inhibition of extracellular signal‐related kinase and c‐Jun N‐terminal kinase activities. The inhibitory enzyme activities in response to acidic pH were reversed by the PKA inhibitor and TDAG8 deficiency. We conclude that extracellular acidic pH inhibits lipopolysaccharide‐induced IL‐1β production, at least partly, through the TDAG8/cAMP/PKA pathway, by inhibiting extracellular signal‐related kinase and c‐Jun N‐terminal kinase activities, in mouse microglia.

     

The contrasting effects of short‐ and long‐term habitat drainage on the population dynamics of freshwater turtles in a human‐dominated landscape

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