Predict Ecosystem Functioning Research Articles

Functional diversity is a passenger but not driver of drought‐related plant diversity losses in annual grasslands

Abstract Effects of climate change on plant community functional diversity are of interest since experiments have found functional diversity to predict ecosystem function. Functional diversity has been hypothesized to confer resilience to plant communities (as a “driver” of community change), but in unmanipulated natural communities, it might alternatively (or additionally) act as a “passenger” by responding to changes in plant diversity caused by extrinsic factors such as climate. We examined trends in plant functional diversity in annual grasslands in Northern California over a 19‐year period, during which a trend towards drier winters had previously been associated with the losses of drought‐intolerant species. We tested whether functional diversity decreased over the period of the study (acting as a passenger), and also whether initial site functional diversity influenced the degree of community change over the study period (acting as a driver). Initial community functional diversity was not related to species richness loss or community variability. We found that functional diversity declined as plant species richness and community mean specific leaf area declined over the course of the study, and all of these trends were associated with declining precipitation, indicating that functional diversity acted as a passenger of community change. Synthesis. This study is among the first to demonstrate that recent climatic trends may drive loss of functional diversity. Our findings highlight that functional diversity does not necessarily confer community resilience when its variation is shaped by the environment rather than by experimental treatments.

Decreased community litter decomposition associated with nitrogen-induced convergence in leaf traits in an alpine meadow

Anthropogenic activities introduce nitrogen (N) into terrestrial ecosystems, inducing changes in quantity and quality of plants. However, little is known about how do nitrogen (N)-mediated such changes alter functional diversity of green leaf traits? How does N-mediated changes in leaf quality contribute to the rate of litter decomposition at intra- or inter-species level? How can such N-mediated changes in quantity and quality be scaled up to explain and predict community-level litter decomposition? A common garden litter decomposition was conducted in an alpine meadow on the Tibetan Plateau, where six litter species and litter mixtures from the communities that had experienced eight-year N addition treatment, were subjected to decomposition for 641 days, with three harvests. For litter mixtures, littles were selected randomly from aboveground shoots collected from 0.5 × 0.5 m2 quadrats. We found that N enrichment increased green leaf and litter N concentrations, and caused small and idiosyncratic variations in phosphorus and carbon concentrations. Plasticity in leaf nutrient concentrations induced little variation in litter decomposition in the six species. Meanwhile, N enrichment induced a reduction in leaf trait diversity and community-level litter decomposition. Correspondingly, positive relationship between decomposition rate (k) and leaf trait diversity were observed. N enrichment reduced dissimilarity of leaf traits, which could relate a reduction of litter decomposition at community level. By integrating intra- and interspecific trait variation with the abundances of coexisting species, these findings can help predict ecosystem function with N enrichment.

Relationships between plant traits, soil properties and carbon fluxes differ between monocultures and mixed communities in temperate grassland.

The use of plant traits to predict ecosystem functions has been gaining growing attention. Above‐ground plant traits, such as leaf nitrogen (N) content and specific leaf area (SLA), have been shown to strongly relate to ecosystem productivity, respiration and nutrient cycling. Furthermore, increasing plant functional trait diversity has been suggested as a possible mechanism to increase ecosystem carbon (C) storage. However, it is uncertain whether below‐ground plant traits can be predicted by above‐ground traits, and if both above‐ and below‐ground traits can be used to predict soil properties and ecosystem‐level functions.Here, we used two adjacent field experiments in temperate grassland to investigate if above‐ and below‐ground plant traits are related, and whether relationships between plant traits, soil properties and ecosystem C fluxes (i.e. ecosystem respiration and net ecosystem exchange) measured in potted monocultures could be detected in mixed field communities.We found that certain shoot traits (e.g. shoot N and C, and leaf dry matter content) were related to root traits (e.g. root N, root C:N and root dry matter content) in monocultures, but such relationships were either weak or not detected in mixed communities. Some relationships between plant traits (i.e. shoot N, root N and/or shoot C:N) and soil properties (i.e. inorganic N availability and microbial community structure) were similar in monocultures and mixed communities, but they were more strongly linked to shoot traits in monocultures and root traits in mixed communities. Structural equation modelling showed that above‐ and below‐ground traits and soil properties improved predictions of ecosystem C fluxes in monocultures, but not in mixed communities on the basis of community‐weighted mean traits. Synthesis. Our results from a single grassland habitat detected relationships in monocultures between above‐ and below‐ground plant traits, and between plant traits, soil properties and ecosystem C fluxes. However, these relationships were generally weaker or different in mixed communities. Our results demonstrate that while plant traits can be used to predict certain soil properties and ecosystem functions in monocultures, they are less effective for predicting how changes in plant species composition influence ecosystem functions in mixed communities.

Plant evolutionary history mainly explains the variance in biomass responses to climate warming at a global scale.

Evolutionary history shapes the interspecific relatedness and intraspecific variation, which has a profound influence on plant functional traits and productivity. However, it is far from clear how the phylogenetic relatedness among species and intraspecific variation could contribute to the observed variance in plant biomass responses to climate warming. We compiled a dataset with 284 species from warming experiments to explore the relative importance of phylogenetic, intraspecific, experimental and ecological factors to warming effects on plant biomass, using phylogenetic eigenvector regression and variance decomposition. Our results showed that phylogenetic relatedness could account for about half the total variance in biomass responses to warming, which were correlated with leaf economic traits at the family level but not at species level. The intraspecific variation contributed to approximately one-third of the variance, whereas the experimental design and ecological characteristics only explained 7-17%. These results suggest that intrinsic factors (evolutionary history) play more important roles than extrinsic factors (experimental treatment and environment) in determining the responses of plant biomass to warming at the global scale. This highlights the urgent need for land surface models to include evolutionary aspects in predicting ecosystem functions under climate change.

Community-weighted mean traits play crucial roles in driving ecosystem functioning along long-term grassland restoration gradient on the Loess Plateau of China

The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in ecology. Recent empirical and theoretical studies have shown that ecosystem functioning is strongly affected by the community-weighted mean (CWM) traits and functional traits diversity (FTD). However, little is known about the relative roles of CWM traits and FTD in explaining ecosystem functioning along a grassland restoration gradient on the Loess Plateau of China. We set up a grassland restoration gradient on the Loess Plateau of China applying the chronosequence approach. Using community biomass and soil carbon stock (SCS) as proxies for ecosystem functioning, we measured 13 functional traits on 28 common plant species and identified the dominant functional traits through principal component analysis (PCA). Our results showed that: (1) Specific leaf area (SLA), mature plant height (MPH) and leaf dry matter content (LDMC) loaded on separate principle components, which could be regarded as dominant functional traits to assess ecosystem functioning. (2) The variation of species diversity was not obvious, but FTD changed significantly along the restoration gradient. Following initial increases, FTD, CWM-SLA and SCS then declined, with the threshold occurring at the 18-year restoration. (3) Community biomass increased significantly through more biomass allocation to the below-ground in the latter stage of restoration. Community biomass was significantly correlated with CWM-MPH while SCS was positively correlated with CWM-SLA. We conclude that community-level functional traits are better than species diversity and FTD in predicting ecosystem functioning, and specifically restoration for 18 years could be the turning point for the degraded grassland ecosystem on the Loess Plateau of China.

Plant traits inform predictions of tundra responses to global change.

Contents Summary 1742 I. Introduction 1742 II. The global context of tundra trait variation 1743 III. The current state of knowledge on trait change in the tundra biome 1744 IV. The links between traits and ecosystem functions 1744 V. Future priorities for tundra trait research 1746 VI. Conclusions 1746 References 1747 SUMMARY: In the rapidly warming tundra biome, plant traits provide an essential link between ongoing vegetation change and feedbacks to key ecosystem functions. However, only recently have comprehensive trait data been compiled for tundra species and sites, allowing us to assess key elements of functional responses to global change. In this review, we summarize trait-based research in tundra ecosystems, with a focus on three components: plant trait variation and how it compares with global patterns; shifts in community-level traits in response to environmental change; and the use of traits to understand and predict ecosystem function. Quantifying patterns and trends in plant traits will allow us to better project the consequences of environmental change for the ecology and functioning of tundra ecosystems.

Linking Landsat to terrestrial LiDAR: Vegetation metrics of forest greenness are correlated with canopy structural complexity

Vegetation metrics derived from satellite imagery provide continuous and large spatial-scale measurements that are critical for interpreting and predicting ecosystem function. However, uncertainty still remains as to the precise structural information that could be estimated from these metrics. Landsat-derived metrics provide pixel measurements of vegetation across the landscape, whereas Light Detection and Ranging (LiDAR) provides multidimensional data on the vertical arrangement of forests. Terrestrial LiDAR metrics of structural complexity describe the arrangement of vegetation in the canopy, and could be coupled with Landsat-derived metrics through their influence on energy and light. Linking Landsat to terrestrial LiDAR estimates of canopy structure could expand the interpretation of Landsat-derived metrics and broaden the spatial scale at which structural complexity can be evaluated. Here, we examined associations between Landsat-derived metrics and terrestrial LiDAR measurements of structural complexity. Structural complexity measurements were obtained with terrestrial LiDAR from plots within eight forested NEON sites across eastern North America. Vegetation metrics (NDVI, EVI, tasseled cap metrics) were calculated for corresponding locations from Landsat 8 satellite imagery. Results showed that canopy reflectance, greenness and brightness, were linked with several measures of canopy structure. Higher levels of greenness were associated with stands having a taller canopy, greater leaf area density and variability, and a less open and porous canopy. Among greenness metrics, NDVI was most strongly correlated with structural complexity metrics (adj. R2 = 0.52 – 0.62 for six metrics). Additionally, we found that a brighter canopy was associated with greater leaf area density and variability, canopy cover, porosity, and lower leaf clumping. Our results demonstrated the potential for large-spatial extent estimates of structural complexity using satellite imagery, and may lead to improved predictions of forest ecosystem functioning such as those predicted in “big leaf” ecosystem models.

Physical Processes Dictate Early Biogeochemical Dynamics of Soil Pyrogenic Organic Matter in a Subtropical Forest Ecosystem

Quantifying links between pyOM dynamics, environmental factors and processes is central to predicting ecosystem function and response to future perturbations. In this study, changes in carbon (TC), nitrogen (TN) , pH and relative recalcitrance (R50) for pine- and cordgrass-derived pyOM were measured at 3-6 weeks intervals throughout the first year of burial in the soil. Objectives were to 1) identify key environmental factors and processes driving early-stage pyOM dynamics, and 2) develop quantitative relationships between environmental factors and changes in pyOM properties. The study was conducted in sandy soils of a forested ecosystem in the Longleaf pine range, US with a focus on links between changes in pyOM properties, fire history (FH), cumulative precipitation (Pcum), average temperature (Tavg) and soil residence time (SRT). Pcum, SRT and Tavg were the main factors controlling TC and TN accounting for 77-91% and 64-96% of their respective variability. Fire history, along with Pcum, SRT and Tavg, exhibited significant controlling effects on pyOM, pH and R50 - accounting for 48-91% and 88-93% of respective variability. Volatilization of volatiles and leaching of water-soluble components (in summer) and the sorption of exogenous organic matter (fall through spring) were most plausibly controlling pyOM dynamics in this study. Overall, our results point to climatic and land management factors and physicochemical process as the main drivers of pyOM dynamics in the pine ecosystems of the Southeastern US.

Disturbance Impacts on Thermal Hot Spots and Hot Moments at the Peatland‐Atmosphere Interface

AbstractSoil‐surface temperature acts as a master variable driving nonlinear terrestrial ecohydrological, biogeochemical, and micrometeorological processes, inducing short‐lived or spatially isolated extremes across heterogeneous landscape surfaces. However, subcanopy soil‐surface temperatures have been, to date, characterized through isolated, spatially discrete measurements. Using spatially complex forested northern peatlands as an exemplar ecosystem, we explore the high‐resolution spatiotemporal thermal behavior of this critical interface and its response to disturbances by using Fiber‐Optic Distributed Temperature Sensing. Soil‐surface thermal patterning was identified from 1.9 million temperature measurements under undisturbed, trees removed and vascular subcanopy removed conditions. Removing layers of the structurally diverse vegetation canopy not only increased mean temperatures but it shifted the spatial and temporal distribution, range, and longevity of thermal hot spots and hot moments. We argue that linking hot spots and/or hot moments with spatially variable ecosystem processes and feedbacks is key for predicting ecosystem function and resilience.

A comparison of the ability of PLFA and 16S rRNA gene metabarcoding to resolve soil community change and predict ecosystem functions

Soil bacterial community structure has traditionally been measured using phospholipid fatty acid (PLFA) profiling. However, with the development of high-throughput sequencing technologies and metabarcoding techniques, more studies are now using 16S rRNA gene metabarcoding to measure bacterial community structure. Metabarcoding provides a much greater level of detail than PLFA profiling does, but it remains unclear whether or not the two techniques have a similar ability to answer many of the common questions asked by ecologists. We test the relative ability of the two techniques to quantify differences in bacterial community structure among five land uses (natural and planted forest, unimproved and improved grasslands, and vineyards), and to predict ecosystem functions. We also test whether PLFA- and metabarcoding-based metrics indicative of microbial growth strategies are correlated to each other. We show that both techniques showed broadly similar patterns of bacterial community composition change with land use and a remarkably similar ability to predict a wide range of ecosystem functions (carbon and nutrient cycling, and responses to drought). However, they were also complementary, as each showed different strengths in discriminating land uses and predicting ecosystem functions. PLFA metrics (i.e. the gram-positive:gram-negative ratio and fungal:bacterial ratio) were strongly correlated with the equivalent 16S rRNA gene metabarcoding metrics (i.e. the gram-positive:gram-negative and oligotrophic:copiotrophic ratios), although PLFA metrics were less well correlated with the Proteobacteria:Acidobacteria ratio. For many ecological questions the two techniques thus give broadly comparable results, providing confidence in the ability of both techniques to quantify meaningful changes in bacterial communities.

Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

Abstract Recent studies clearly support a positive biodiversity–ecosystem functioning (BEF) relationship in phytoplankton. As taxon richness does not quantify functional diversity, functional approaches have been developed to link community functioning to diversity. Compared to terrestrial plant communities, only a few studies have validated phytoplankton functional approaches in BEF relationships. Furthermore, the ability of functional and taxonomic richness measures in predicting ecosystem functioning of natural phytoplankton communities has not been compared yet. Here, we analysed the BEF relationship using taxonomic and functional (trait categories and response groups sensu Reynolds) approaches in a broad‐scale phytoplankton dataset from Fennoscandia. First, we analysed how taxonomic and functional compositions were related to local environmental predictors. We then compared how taxonomic and functional richness performed in predicting resource‐use efficiency (the yield in phytoplankton biomass standardised by total phosphorus) as an ecosystem functioning measure. Finally, we tested whether the relationship between ecosystem functioning and taxonomic richness is further enhanced once each of the functional richness measure is also considered. Among the approaches, phytoplankton functional trait categories as community matrix showed the best correspondence with the local environment. The richness of phytoplankton response groups predicted ecosystem functioning significantly better than the taxonomic and the functional trait category richness—both in the full dataset and in almost all Fennoscandian countries. On top of taxonomic richness, only the residual variation in response group richness predicted ecosystem functioning positively in the entire dataset and in all individual countries. Applying functional approaches, reduced complexity of data should come along with reduced ecological information. We showed, however, that both functional approaches represented some functional redundancy among taxa in a meaningful way, and enhanced our ability in predicting community composition from environmental predictors. Moreover, phytoplankton response group richness sensu Reynolds summarises information on ecosystem functioning contained in the taxonomic data in a way that represents functional diversity better than the richness of functional trait categories. Interestingly, the response group approach, which is exclusively derived from field observations rather than from quantified phytoplankton traits, outperforms taxonomic richness and trait category richness in predicting ecosystem functioning in our dataset. This may highlight that our ability to quantify phytoplankton traits is still limited. Existing phytoplankton functional approaches, however, can translate the taxonomic information into a reduced but reliable functional matrix already and predict ecosystem functioning better than taxonomic data.

Phylogenetic conservation of substrate use specialization in leaf litter bacteria.

Environmental change will influence the ecosystem processes regulated by microbial communities, including leaf litter decomposition. To assess how microbial communities and their functioning might respond to increases in temperature, we quantified the distribution of traits related to carbon substrate utilization and temperature sensitivity in leaf litter bacteria isolated from a natural grassland ecosystem in Southern California. The isolates varied substantially in their carbon substrate use, as well as their response to temperature change. To better predict the functioning and responses in natural communities, we also examined if the functional and response traits were phylogenetically patterned or correlated with one another. We found that the distribution of functional traits displayed a phylogenetic pattern, but the sensitivity of the traits to changes in temperature did not. We also did not detect any correlations between carbon substrate use and sensitivity to changes in temperature. Together, these results suggest that information about microbial composition may provide insights to predicting ecosystem function under one temperature, but that these relationships may not hold under new temperature conditions.

Different clades and traits yield similar grassland functional responses

Plant functional traits are viewed as key to predicting important ecosystem and community properties across resource gradients within and among biogeographic regions. Vegetation dynamics and ecosystem processes, such as aboveground net primary productivity (ANPP), are increasingly being modeled as a function of the quantitative traits of species, which are used as proxies for photosynthetic rates and nutrient and water-use efficiency. These approaches rely on an assumption that a certain trait value consistently confers a specific function or response under given environmental conditions. Here, we provide a critical test of this idea and evaluate whether the functional traits that drive the well-known relationship between precipitation and ANPP differ between systems with distinct biogeographic histories and species assemblages. Specifically, we compared grasslands spanning a broad precipitation gradient (∼200-1,000 mm/y) in North America and South Africa that differ in the relative representation and abundance of grass phylogenetic lineages. We found no significant difference between the regions in the positive relationship between annual precipitation and ANPP, yet the trait values underlying this relationship differed dramatically. Our results challenge the trait-based approach to predicting ecosystem function by demonstrating that different combinations of functional traits can act to maximize ANPP in a given environmental setting. Further, we show the importance of incorporating biogeographic and phylogenetic history in predicting community and ecosystem properties using traits.

利用结构方程解析杉木林生产力与环境因子及林分因子的关系

PDF HTML阅读 XML下载 导出引用 引用提醒 利用结构方程解析杉木林生产力与环境因子及林分因子的关系 DOI: 10.5846/stxb201512132482 作者: 作者单位: 安徽农业大学林学与园林学院,安徽农业大学林学与园林学院,安徽农业大学林学与园林学院,安徽农业大学林学与园林学院,安徽农业大学林学与园林学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家"973"计划项目（2012CB416905），中国科学院战略先导性科技专项（2011XDA05050204）；安徽农业大学青年项目（2014zr013） Structural equation model analysis of the relationship between environmental and stand factors and net primary productivity in Cunninghamia lanceolata forests Author: Affiliation: School of Forestry Landscape of Architecture,Anhui Agricultural University,School of Forestry Landscape of Architecture,Anhui Agricultural University,School of Forestry Landscape of Architecture,Anhui Agricultural University,School of Forestry Landscape of Architecture,Anhui Agricultural University,School of Forestry Landscape of Architecture,Anhui Agricultural University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:通过收集155篇644条杉木林生产力数据，利用结构方程模型，分析杉木林净初级生产力与年均降雨量、年均温度、林分密度和林龄之间的关系。结果表明：杉木林净生产力与年均降水量和年均温度呈显著正相关，相关系数分别为0.63和0.378。杉木林净生产力与林龄和林分密度呈显著负相关，相关系数分别为-0.332和-0.408。结构方程模型较好的解析了杉木净初级生产力与环境因子和林分因子之间的关系。杉木林净生产力与年均降水量、年均温度、林龄、林分密度都有影响，其总通径系数分别为0.398（P < 0.01）、0.746（P < 0.01）、-0.321（P < 0.01）和-0.738（P < 0.01）。年均温度和林龄不仅直接影响杉木林净生产力，还通过影响年均降水量和林分密度间接影响林分净生产力。年均温度和林龄的直接通径系数分别为0.494（P < 0.01）和-0.700（P < 0.01）；年均温度和林龄的间接通径系数分别为0.252（P < 0.05）和0.379（P < 0.05）。结构方程作为大尺度分析净初级生产力的方法，杉木林净初级生产力影响因素的62%来自年均降水量、年均温度、林龄和林分密度。 Abstract:We used a structural equation model to analyze the relationship between environmental and forest stand factors and net primary productivity in Cunninghamia lanceolata forests. We collected 644 data points from 155 published studies on net primary productivity (NPP) measurements of Cunninghamia lanceolata forests. The environmental factors included mean annual precipitation (MAP) and mean annual temperature (MAT). The stand factors included age and density of trees. The correlations between NPP and environmental and stand factors were different. NPP was significantly positively correlated with both MAP and MAT, with correlation coefficients of 0.630 and 0.378 respectively. Conversely, NPP was significantly negatively correlated with both age and density, with correlation coefficients of -0.332 and -0.408 respectively. Each variable fitted a normal distribution after natural logarithmic transformation. We used a structural equation model to explore the relationship between NPP and MAP, MAT, age, and density. The results showed that the structural equation model was an excellent method to explain the relationship between environmental and stand factors, and NPP. MAP, MAT, age and density, all had an effect on NPP, with total path coefficients of 0.398 (P < 0.01), 0.746 (P < 0.01), -0.321 (P < 0.01) and -0.738 (P < 0.01), respectively. MAT and age had both direct and indirect effects on NPP, as MAT had a direct effect on MAP, and age had a direct effect on density. MAT and age directly affected NPP as well, and were therefore included as direct and indirect path coefficients in the structural equation model. The direct path coefficients of MAT and age were 0.494 (P < 0.01) and -0.700 (P < 0.01) respectively. The indirect path coefficients of MAT and age were 0.252 (P < 0.05) and 0.379 (P < 0.05) respectively. The structural equation model analysis indicated that MAP and MAT were the strongest positive drivers of NPP, whereas age and density were the strongest negative drivers of NPP. The structural equation model analysis also indicated that MAP, MAT, age, and density explained 62% of the variation in NPP of Cunninghamia lanceolata forests. We conclude that the structural equation model is the most appropriate approach to understand and predict ecosystem functioning, as understanding NPP requires an accurate assessment of large-scale patterns in NPP distribution and partitioning in relation to environmental and stand factors. 参考文献 相似文献 引证文献

Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands.

Functional diversity, the extent of functional differences among species in a community, drives biodiversity–ecosystem function (BEF) relationships. Here, four species traits and aboveground biomass production (ABP) were considered. We used two community-wide measures of plant functional composition, (1) community weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FDQ) to evaluate the effects of functional diversity on the ABP in the Northern Tibetan alpine grasslands. Both species and functional diversity were positively related to the ABP. Functional trait composition had a larger predictive power for the ABP than species diversity and FDQ, indicating a primary dependence of ecosystem property on the identity of dominant species in our study system. Multivariate functional diversity was ineffective in predicting ecosystem function due to the trade-offs among different traits or traits selection criterions. Our study contributes to a better understanding of the mechanisms driving the BEF relationships in stressed ecosystems, and especially emphasizes that abiotic and biotic factors affect the BEF relationships in alpine grasslands.

The Evolutionary Legacy of Diversification Predicts Ecosystem Function.

Theory suggests that the structure of evolutionary history represented in a species community may affect its functioning, but phylogenetic diversity metrics do not allow for the identification of major differences in this structure. Here we propose a new metric, ELDERness (for Evolutionary Legacy of DivERsity) to estimate evolutionary branching patterns within communities by fitting a polynomial function to lineage-through-time (LTT) plots. We illustrate how real and simulated community branching patterns can be more correctly described by ELDERness and can successfully predict ecosystem functioning. In particular, the evolutionary history of branching patterns can be encapsulated by the parameters of third-order polynomial functions and further measured through only two parameters, the "ELDERness surfaces." These parameters captured variation in productivity of a grassland community better than existing phylogenetic diversity or diversification metrics and independent of species richness or presence of nitrogen fixers. Specifically, communities with small ELDERness surfaces (constant accumulation of lineages through time in LTT plots) were more productive, consistent with increased productivity resulting from complementary lineages combined with niche filling within lineages. Overall, while existing phylogenetic diversity metrics remain useful in many contexts, we suggest that our ELDERness approach better enables testing hypotheses that relate complex patterns of macroevolutionary history represented in local communities to ecosystem functioning.

Unifying ecological stoichiometry and metabolic theory to predict production and trophic transfer in a marine planktonic food web.

Two ecological frameworks have been used to explain multitrophic interactions, but rarely in combination: (i) ecological stoichiometry (ES), explaining consumption rates in response to consumers' demand and prey's nutrient content; and (ii) metabolic theory of ecology (MTE), proposing that temperature and body mass affect metabolic rates, growth and consumption rates. Here we combined both, ES and MTE to investigate interactive effects of phytoplankton prey stoichiometry, temperature and zooplankton consumer body mass on consumer grazing rates and production in a microcosm experiment. A simple model integrating parameters from both frameworks was used to predict interactive effects of temperature and nutrient conditions on consumer performance. Overall, model predictions reflected experimental patterns well: consumer grazing rates and production increased with temperature, as could be expected based on MTE. With decreasing algal food quality, grazing rates increased due to compensatory feeding, while consumer growth rates and final biovolume decreased. Nutrient effects on consumer biovolume increased with increasing temperature, while nutrient effects on grazing rates decreased. Highly interactive effects of temperature and nutrient supply indicate that combining the frameworks of ES and MTE is highly important to enhance our ability to predict ecosystem functioning in the context of global change.

Density dependence of herbivorous central stoneroller Campostoma anomalum in stream mesocosms

AbstractHerbivorous fish can have strong effects on stream ecosystem function by consuming primary producers and excreting limiting nutrients, but it is unclear whether they are resource limited. Thus, understanding factors regulating abundance of these fish might help predict ecosystem function. We used stream mesocosms to test whether populations of central stoneroller Campostoma anomalum exhibit density dependence across a range of typical densities and resource abundance found in Great Plains streams. We predicted that incrementally increasing stocking biomass from 3·7 to 24·9 g·m−2 would reduce standing stocks of resources resulting in lower growth of stocked fish. Fish growth (over 41 days) was compared to initial stocking biomass and primary production as well as standing stocks of algae and invertebrates using regression analysis. Mean growth of individuals was negatively associated with stocking biomass ( = 0·55; P = 0·02), as predicted. Contrary to our prediction, increases in fish biomass led to increased primary productivity ( = 0·31, P = 0·07), but resulted in no relationship among algal filament lengths ( = 0·00; P = 0·34), algal biomass ( = 0·12; P = 0·19) or invertebrate biomass ( = 0·03; P = 0·30). Thus, density dependence occurred without an apparent reduction in food resources. We hypothesised that stoneroller growth was possibly limited by competition for high‐quality algae or invertebrates, or behavioural interactions causing interference competition.

High-Order Interactions between Species Strongly Influence the Activity of Microbial Communities

We are surrounded by complex communities of microbes, many that play a fundamental role in our everyday lives. The activity of a biological community is the outcome of complex interactions between community members, and it is often unclear how those interactions work. Developing a quantitative understanding of how ecosystems of microbes interact will be essential to predicting how microbial networks respond to environmental or biological changes and aid in designing synthetic communities with tailored functionality. Here we combine modeling and experimental data to analyze the interaction networks within a multispecies community of microbes.The community consists of four species isolated from fresh water. We measured the overall metabolic rate of all subsets of this community to quantify interactions between community members, including high-order interactions between three or four species. For two-species interactions, we found a range of interactions, from no interaction to strongly positive. Accounting for interactions between species greatly improved the ability to predict ecosystem function. When not taking any interactions into account, the predictions of the overall metabolic rate were off by more than 30%. Further measurements to include 3 and 4 species interactions revealed a complex set of interactions between these four species. The 3 and 4 species interactions coefficients on average resulted in 20-40% changes in metabolic rate of individual species. We compare how model predictions of the overall metabolic rate improve when incorporating pairwise and higher-order interactions between species.We incorporated these findings into a theoretical model which examined how the overall metabolic rate of a community depended on the distribution of interaction strengths and the distribution of cells in space. We found that the distribution of cells in space was particularly important for networks containing strong high-order interactions.

坡向因子对黄土高原草地群落功能多样性的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 坡向因子对黄土高原草地群落功能多样性的影响 DOI: 10.5846/stxb201505010900 作者: 作者单位: 陕西师范大学生命科学学院,陕西师范大学生命科学学院 作者简介: 通讯作者: 中图分类号: 基金项目: 陕西师范大学中央高校基本科研业务费（GK201503044） Effect of slope aspect on the functional diversity of grass communities in the Loess Plateau Author: Affiliation: Shaanxi Normal University, College of Life Sciences,Shaanxi Normal University, College of Life Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:研究群落水平上的植物功能性状特征及功能多样性随坡向的变化规律，对认识不同坡向上的植物群落形成过程具有重要意义。以黄土高原不同坡向上的自然草地群落为研究对象，比较研究了植物功能性状（株高和比叶面积）和功能多样性测度指标（功能丰富度、功能均匀度和功能离散度）随坡向的变化规律。研究结果显示：（1）阴坡的株高和比叶面积显著高于其他坡向；（2）一元性状的功能丰富度在不同坡向间均无显著差异；阴坡和半阴坡的多元性状功能丰富度显著高于阳坡；（3）阴坡的株高功能均匀度显著高于半阳坡，而比叶面积功能均匀度在各坡向的差异并不显著；多元性状功能均匀度在不同坡向差异显著，阴坡最高，半阳坡最低；（4）阴坡和半阴坡的株高功能离散度显著高于阳坡和半阳坡，而半阴坡的比叶面积功能离散度显著高于阳坡；半阴坡的多元性状功能离散度Rao指数显著高于阳坡。研究结果暗示了，在阴坡和半阴坡上，植物对群落内的生态位空间和资源利用更充分，种间竞争强度较低，不同物种之间生态位高度分化；而在阳坡和半阳坡上，由于水分等条件的限制植物可占据的生态位空间有限，导致其对占据的生态位空间使用不足，物种间资源竞争较强烈。在群落水平上，研究地区的植物功能性状及功能多样性随坡向的规律性变化，反映了黄土高原植被群落构建过程中坡向因子对功能性状的筛选效应。该研究结果对该区的植被恢复重建的物种选择及植被布局规划具有重要实践意义。 Abstract:Functional diversity of a plant community, which is based on plant traits, has been proposed as a key component predicting ecosystem function. Knowledge about how plant functional traits and functional diversity change along with the different slope aspects at the community level is important for understanding the formation of plant communities under distinct slope aspects. However, to date, previous studies on plant communities in sunny and cloudy slope environments have mainly been descriptive. To our knowledge, no research has dealt with the relationship between the slope aspect and community assembly based on plant functional diversity (i.e., functional richness, evenness and divergence). In this study, we aimed to uncover the relationship between slope aspects and plant functional traits. Three sampling transects (1 m × 5 m) were established on each of four sites facing north, south, east, or west, in Malan Mountain, Loess Plateau. Each of the sampling transects were evenly divided into fifteen 1 m × 1 m plots, and a plot survey was conducted. We measured plant height (H) and specific leaf area (SLA), and then calculated three types of functional diversity indices (i.e., functional richness, evenness, and divergence), which included three one-dimensional indices based on single traits (i.e., FRci, FRO, FDvar) and three multi-dimensional indices based on two traits (i.e., FRci, FEve, FDQ). A comparison of the changing pattern of plant functional traits and the three types of functional diversity was conducted among the four slope aspects (the cloudy, sunny, semi-cloudy, and semi-sunny slope). Our results indicated that: (1) the value of H and SLA on the cloudy slope was greater than the others; (2) there was no significant difference among the four slope aspects in one-dimensional functional richness indices of H and SLA, while the multi- dimensional functional richness indices of plants on the cloudy slope and the semi-cloudy slope were greater than those of the plants on the sunny slope; (3) on the cloudy slope, the one-dimensional functional evenness of H was significantly greater compared to those on the semi-sunny slope, while that of SLA was not significantly influenced by the slope aspect; the multi-dimensional functional evenness indices of plants on the cloudy slope was greater than those of the plants on semi-sunny slope; (4) the one-dimensional functional divergence of H on the cloudy and semi-cloudy slope were significantly greater than those on the semi-sunny and sunny slope, while that of SLA on the semi-cloudy slope was significantly greater than those on the sunny slope; the multi-dimensional functional divergence index and Rao's quadratic entropy of plants was significantly greater on the semi-cloudy slope compared with those on the sunny slope. Our results indicated that for plant traits, more niche space was occupied, more resources were sufficiently exploited, lower competition intensity occured, and a high level of niche differentiation existed on the cloudy and semi-cloudy slopes. By contrast, because of the limitation of all kinds of soil conditions and environmental factors, plant traits occupied less niche space on the sunny and semi-sunny slope, resources were exploited less sufficiently, and competition for resources tended to be stronger. At the community-level, the changing pattern of plant functional traits and functional diversity along the four different slope aspects suggests the existence of an environmental fitter effect on functional traits under the process of community assembly in the Loess region. These findings would have significant practical implications for species selection and vegetation rehabilitation layout planning in the hilly area of the Loess Plateau. 参考文献 相似文献 引证文献