红壤丘陵区LAI与土壤侵蚀分布特征的关系

叶面积指数(LAI)是常用的一个用于描述植被覆盖的方面指数,土壤侵蚀的分布又与植被的覆盖状况息息相关,这就意味着LAI与土壤侵蚀有一定的相关性,目前有关这二者的相关性研究还鲜有文献报道。基于这此,本研究首先利用2000年的遥感影像(TM)解释出该年度的土壤侵蚀强度图,再利用该遥感影像通过图像的代数运算得出该地区的NDVI栅格图,通过实测该县不同典型植被条件的LAI值,得出实测的LAI与图像NDVI值之间的函数关系式,由图像的代数运算把NDVI图转换成LAI图,即实现了遥感图像的实测LAI纠正。在GIS软件的帮助下,通过将LAI栅格图与土壤侵蚀强度图的空间叠加分析,得到不同LAI条件下的土壤侵蚀分布。结果表明,LAI与土壤侵蚀的分布表现为:大致以LAI=2为分界线,当LAI<2时,土壤侵蚀并未随LAI的增加而迅速减少,LAI>2时,土壤侵蚀的分布随植被指数的增加而减少,当LAI=2左右时,土壤侵蚀的面积最大。这种情况对于轻度、中度及强度土壤侵蚀的影响是类似的,都呈类正态分布的曲线形式,但在曲线的两侧土壤侵蚀类型是有本质区别的,在曲线的左侧土壤侵蚀类型的分布是中度和强度为主,而在曲线右侧则以轻度为主。表明LAI这个指标与土壤侵蚀有很好的相关性,可以用于土壤侵蚀方面的相关研究工作。     

京津冀地区近20年NDVI时空变化特征

健康稳定的自然生态系统是保障城市发展的重要基础.了解京津冀城镇快速发展过程中自然生态系统的变化,有助于该区域城镇绿色协调可持续发展.植被指数NDVI时空变化特征可反映地区自然生态系统状况及其演变规律.基于MOD13Q1和Landsat遥感影像数据,利用一元线性回归趋势分析法分析近20年(2000—2019年)京津冀地区...     

Is catchment productivity a useful predictor of taxa richness in lake plankton communities?

The influence of catchment variables on lake organisms is understudied. The terrestrial zone in the vicinity of lakes is, however, probably highly important for biota due to the effects on water chemistry and to various processes operating across ecosystem boundaries. We examined the relative importance of lake and catchment variables, as well as large-scale geographical factors, on the taxa richness of phyto- and zooplankton in 100 small lakes in Finland. In variation partitioning, the variability of phytoplankton richness was most strongly related to the effects of lake variables, the joint effects of lake and catchment variables, and the joint effects of all three groups of variables. Zooplankton richness, in turn, was most strongly related to the effects of lake and catchment variables and the joint effect of lake and catchment variables. The exact results of the variation partitioning depended on the catchment sizes considered in the regression models. Among lake variables, planktonic richness was strongly related to variables indicating productivity. Among catchment variables, the normalized difference vegetation index (NDVI), indicating catchment productivity, showed a relatively strong association with planktonic richness. These results provide evidence that catchment variables such as the NDVI may be efficient predictors of planktonic richness in small lakes. It is possible that individual lakes embedded in a highly productive landscape have higher taxa richness than solitary, potentially productive lakes because of the high influx of dispersing propagules from the regional pool. We also suggest that catchment variables may respond to environmental changes at different scales than the lake variables, and explicit consideration of catchment productivity would therefore be useful when planning research and monitoring programs for freshwater organisms.     

Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data

This paper introduces an innovative modelling strategy aimed at simulating the main terms of net forest carbon budget (net primary production, NPP and net ecosystem exchange, NEE) in Tuscany (Central Italy). The strategy is based on the preliminary calibration and application of parametric and bio-geochemical models (C-Fix and BIOME-BGC, respectively), which simulate the behaviour of forest ecosystems close to equilibrium condition (climax). Next, the ratio of actual over-potential tree volume is computed as an indicator of ecosystem distance from climax and is combined with the model outputs to estimate the NPP and NEE of real forests. The per-pixel application of the new modelling strategy was made possible by the collection of several data layers (maps of forest type and volume, daily meteorological data and monthly normalized difference vegetation index (NDVI) images for the years 1999–2003) which served to characterize the eco-climatic and forest features of the region. The obtained estimates of forest NPP and NEE were evaluated against ground measurements of accumulated woody biomass and net carbon exchange. The results of these experiments testify the good potential of the proposed strategy and indicate some problem areas which should be the subject of future research.     

Woody plant richness and NDVI response to drought events in Catalonian (northeastern Spain) forests

The role of species diversity on ecosystem resistance in the face of strong environmental fluctuations has been addressed from both theoretical and experimental viewpoints to reveal a variety of positive and negative relationships. Here we explore empirically the relationship between the richness of forest woody species and canopy resistance to extreme drought episodes. We compare richness data from an extensive forest inventory to a temporal series of satellite imagery that estimated drought impact on forest canopy as NDVI (normalized difference vegetation index) anomalies of the dry summer in 2003 in relation to records of previous years. We considered five different types of forests that are representative of the main climatic and altitudinal gradients of the region, ranging from lowland Mediterranean to mountain boreal-temperate climates. The observed relationship differed among forest types and interacted with the climate, summarised by the Thorntwaite index. In Mediterranean Pinus halepensis forests, NDVI decreased during the drought. This decrease was stronger in forests with lower richness. In Mediterranean evergreen forests of Quercus ilex, drought did not result in an overall NDVI loss, but lower NDVI values were observed in drier localities with lower richness, and in more moist localities with higher number of species. In mountain Pinus sylvestris forests NDVI decreased, mostly due to the drought impact on drier localities, while no relation to species richness was observed. In moist Fagus sylvatica forests, NDVI only decreased in plots with high richness. No effect of drought was observed in the high mountain Pinus uncinata forests. Our results show that a shift on the diversity-stability relationship appears across the regional, climatic gradient. A positive relationship appears in drier localities, supporting a null model where the probability of finding a species able to cope with drier conditions increases with the number of species. However, in more moist localities we hypothesize that the proportion of drought-sensitive species would increase in richer localities, due to a higher likelihood of co-occurrence of species that share moist climatic requirements. The study points to the convenience of considering the causes of disturbance in relation to current environmental gradients and historical environmental constraints on the community.     

Influences of canopy structure and physiological traits on flux partitioning between understory and overstory in an eastern Siberian boreal larch forest

Boreal forests play an important role in the global balance of energy and CO₂. Our previous study of elaborate eddy covariance observations in a Siberian boreal larch forest, conducted both above the forest canopy and at the forest floor, revealed a significant contribution of latent heat flux (LE) from the cowberry understory to the whole ecosystem LE. Thus, in the present study, we examined what factors control the partitioning of whole ecosystem LE and CO₂ flux into the understory and overstory vegetation, using detailed leaf-level physiology (for both understory and overstory vegetation) and soil respiration property measurements as well as a multilayer soil-vegetation-atmosphere transfer (SVAT) model. The modeling results showed that the larch overstory's leaf area index (LAI) and vertical profile of leaf photosynthetic capacity were major factors determining the flux partitioning in this boreal forest ecosystem. This is unlike other forest ecosystems that tend to have dense LAI. We concluded that control of the larch overstory's LAI had a relationship with both the coexistence of the larch with the cowberry understory and with the water resources available to the total forest ecosystem.     

Predicting Bird Species Distributions in Reconstructed Landscapes

Abstract:  Landscape optimization for biodiversity requires prediction of species distributions under alternative revegetation scenarios. We used Bayesian model averaging with logistic regression to predict probabilities of occurrence for 61 species of birds within highly fragmented box–ironbark forests of central Victoria, Australia. We used topographic, edaphic, and climatic variables as predictors so that the models could be applied to areas where vegetation has been cleared but may be replanted. Models were evaluated with newly acquired, independent data collected in large blocks of remnant native vegetation. Successful predictions were obtained for 18 of 45 woodland species (40%). Model averaging produced more accurate predictions than "single best" models. Models were most successful for smaller-bodied species that probably depend on particular vegetation types. Predictions for larger, generalist species, and seasonal migrants were less successful, partly because of changes in species distributions between model building (1995–1997) and validation (2004–2005) surveys. We used validated models to project occurrence probabilities for individual species across a 12,000-km² region, assuming native vegetation was present. These predictions are intended to be used as inputs, along with landscape context and temporal dynamics, into optimization algorithms to prioritize revegetation. Longer-term data sets to accommodate temporal dynamics are needed to improve the predictive accuracy of models.     

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.     

Linking marine resources to ecotonal shifts of water uptake by terrestrial dune vegetation

As evidence mounts that sea levels are rising, it becomes increasingly important to understand the role of ocean water within terrestrial ecosystem dynamics. Coastal sand dunes are ecosystems that occur on the interface of land and sea. They are classic ecotones characterized by zonal distribution of vegetation in response to strong gradients of environmental factors from the ocean to the inland. Despite the proximity of the dune ecosystem to the ocean, it is generally assumed that all vegetation utilizes only freshwater and that water sources do not change across the ecotone. Evidence of ocean water uptake by vegetation would redefine the traditional interpretation of plant-water relations in the dune ecosystem and offer new ideas for assessing maritime influences on function and spatial distribution of plants across the dune. The purpose of this study was to identify sources of water (ocean, ground, and rain) taken up by vegetation using isotopic analysis of stem water and to evaluate water uptake patterns at the community level based on the distribution and assemblage of species. Three coastal dune systems located in southern Florida, USA, and the Bahamian bank/platform system were investigated. Plant distributions across the dune were zonal for 61-94% of the 18 most abundant species at each site. Species with their highest frequency on the fore dune (nearest the ocean) indicate ocean water uptake as evidenced by delta 18O values of stem water. In contrast, species most frequent in the back dune show no evidence of ocean water uptake. Analysis of species not grouped by frequency, but instead sampled along a transect from the ocean toward the inland, indicates that individuals from the vegetation assemblage closest to the ocean had a mixed water-harvesting strategy characterized by plants that may utilize ocean, ground-, and/or rainwater. In contrast, the inland vegetation relies mostly on rainwater. Our results show evidence supporting ocean water use by dune vegetation and demonstrate an exciting relationship between seawater and ecotonal shifts in plant function of a terrestrial ecosystem.     

The importance of spatial autocorrelation,extent and resolution in predicting forest bird occurrence

Concerns about declines in forest biodiversity underscore the need for accurate estimates of the distribution and abundance of organisms at large scales and at resolutions that are fine enough to be appropriate for management. This paper addresses three major objectives: (i) to determine whether the resolution of typical air photo-derived forest inventory is sufficient for the accurate prediction of site occupancy by forest birds. We compared prediction success of habitat models using air photo variables to models with variables derived from finer resolution, ground-sampled vegetation plots. (ii) To test whether incorporating spatial autocorrelation into habitat models via autologistic regression increases prediction success. (iii) To determine whether landscape structure is an important factor in predicting bird distribution in forest-dominated landscapes. Models were tested locally (Greater Fundy Ecosystem [GFE]) using cross-validation, and regionally using an independent data set from an area located ca. 250 km to the northwest (Riley Brook [RB]). We found significant positive spatial autocorrelation in the residuals of at least one habitat model for 76% (16/21) of species examined. In these cases, the logistic regression assumption of spatially independent errors was violated. Logistic models that ignored spatial autocorrelation tended to overestimate habitat effects. Though overall prediction success was higher for autologistic models than logistic models in the GFE, the difference was only significantly improved for one species. Further, the inclusion of spatial covariates did little to improve model performance in the geographically discrete study area. For 62% (13/21) of species examined, landscape variables were significant predictors of forest bird occurrence even after statistically controlling for stand-level variability. However, broad spatial extents explained less variation than local factors. In the GFE, 76% (16/21) of air photo and 81% (17/21) of ground plot models were accurate enough to be of practical utility (AUC > 0.7). When applied to RB, both model types performed effectively for 55% (11/20) of the species examined. We did not detect an overall difference in prediction success between air photo and ground plot models in either study area. We conclude that air photo data are as effective as fine resolution vegetation data for predicting site occupancy for the majority of species in this study. These models will be of use to forest managers who are interested in mapping species distributions under various timber harvest scenarios, and to protected areas planners attempting to optimize reserve function.     

基于GIS的祁连山植被NDVI对气温降水的旬响应分析

利用祁连山地区SPOTVGT-NDVI数据和气象站点旬平均气温、降水资料,运用最大化合成、趋势线分析和相关分析方法分析了祁连山植被的时空变化趋势,并从旬时间尺度上分析了祁连山植被对气温和降水的响应特征。结果表明:近10年来,祁连山年最大化植被NDVI增加了3.1%,植被改善、无变化和退化的面积分别占总面积的70.21%、21.44%和8.35%。祁连山植被NDVI对气温变化的响应大于降水,对气温和降水变化的最大响应滞后都为2旬左右。秋季植被NDVI对气温和降水变化响应最大,夏季植被NDVI对气温和降水响应的滞后期长于春季和秋季。祁连山植被NDVI对气温和降水变化的旬最大响应表现为中段大于东段和西段,NDVI对气温和降水变化的最大响应滞后期呈现出西段中段东段的空间分布特征。     

Indicators of ecosystem function identify alternate states in the sagebrush steppe

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.     

Ecosystem services and urban heat riskscape moderation: water, green spaces, and social inequality in Phoenix, USA

Urban ecosystems are subjected to high temperatures--extreme heat events, chronically hot weather, or both-through interactions between local and global climate processes. Urban vegetation may provide a cooling ecosystem service, although many knowledge gaps exist in the biophysical and social dynamics of using this service to reduce climate extremes. To better understand patterns of urban vegetated cooling, the potential water requirements to supply these services, and differential access to these services between residential neighborhoods, we evaluated three decades (1970-2000) of land surface characteristics and residential segregation by income in the Phoenix, Arizona, USA metropolitan region. We developed an ecosystem service trade-offs approach to assess the urban heat riskscape, defined as the spatial variation in risk exposure and potential human vulnerability to extreme heat. In this region, vegetation provided nearly a 25 degrees C surface cooling compared to bare soil on low-humidity summer days; the magnitude of this service was strongly coupled to air temperature and vapor pressure deficits. To estimate the water loss associated with land-surface cooling, we applied a surface energy balance model. Our initial estimates suggest 2.7 mm/d of water may be used in supplying cooling ecosystem services in the Phoenix region on a summer day. The availability and corresponding resource use requirements of these ecosystem services had a strongly positive relationship with neighborhood income in the year 2000. However, economic stratification in access to services is a recent development: no vegetation-income relationship was observed in 1970, and a clear trend of increasing correlation was evident through 2000. To alleviate neighborhood inequality in risks from extreme heat through increased vegetation and evaporative cooling, large increases in regional water use would be required. Together, these results suggest the need for a systems evaluation of the benefits, costs, spatial structure, and temporal trajectory for the use of ecosystem services to moderate climate extremes. Increasing vegetation is one strategy for moderating regional climate changes in urban areas and simultaneously providing multiple ecosystem services. However, vegetation has economic, water, and social equity implications that vary dramatically across neighborhoods and need to be managed through informed environmental policies.     

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.     

Quantifying relationships between bird and butterfly community shifts and environmental change.

Quantifying the manner in which ecological communities respond during a time of decreasing precipitation is a first step in understanding how they will respond to longer-term climate change. Here we coupled analysis of interannual variability in remotely sensed data with analyses of bird and butterfly community changes in montane meadow communities of the Greater Yellowstone Ecosystem. Landsat satellite imagery was used to classify these meadows into six types along a hydrological gradient. The northern portion of the ecosystem, or Gallatin region, has smaller mean patch sizes separated by ridges of mountains, whereas the southern portion of the ecosystem, or Teton region, has much larger patches within the Jackson Hole valley. Both support a similar suite of butterfly and bird species. The Gallatin region showed more overall among-year variation in the normalized difference vegetation index (NDVI) when meadow types were pooled within regions, perhaps because the patch sizes are smaller on average. Bird and butterfly communities showed significant relationships relative to meadow type and NDVI. We identified several key species that are tightly associated with specific meadow types along the hydrological gradient. Comparing taxonomic groups, fewer birds showed specific habitat affinities than butterflies, perhaps because birds are responding to differences in habitat structure among meadow types and using the landscape at a coarser scale than the butterflies. Comparing regions, the Teton region showed higher predictability of community assemblages as compared to the Gallatin region. The Gallatin region exhibited more significant temporal trends with respect to butterflies. Butterfly communities in wet meadows showed a distinctive shift along the hydrological gradient during a drought period (1997-2000). These results imply that the larger Teton meadows will show more predictable (i.e., static) species-habitat associations over the long term, but that the smaller Gallatin meadows may be an area that will exhibit the effects of global climate change faster.     

Integrated models to support multiobjective ecological restoration decisions

Many objectives motivate ecological restoration, including improving vegetation condition, increasing the range and abundance of threatened species, and improving species richness and diversity. Although models have been used to examine the outcomes of ecological restoration, few researchers have attempted to develop models to account for multiple, potentially competing objectives. We developed a combined state‐and‐transition, species‐distribution model to predict the effects of restoration actions on vegetation condition and extent, bird diversity, and the distribution of several bird species in southeastern Australian woodlands. The actions reflected several management objectives. We then validated the models against an independent data set and investigated how the best management decision might change when objectives were valued differently. We also used model results to identify effective restoration options for vegetation and bird species under a constrained budget. In the examples we evaluated, no one action (improving vegetation condition and extent, increasing bird diversity, or increasing the probability of occurrence for threatened species) provided the best outcome across all objectives. In agricultural lands, the optimal management actions for promoting the occurrence of the Brown Treecreeper (Climacteris picumnus), an iconic threatened species, resulted in little improvement in the extent of the vegetation and a high probability of decreased vegetation condition. This result highlights that the best management action in any situation depends on how much the different objectives are valued. In our example scenario, no management or weed control were most likely to be the best management options to satisfy multiple restoration objectives. Our approach to exploring trade‐offs in management outcomes through integrated modeling and structured decision‐support approaches has wide application for situations in which trade‐offs exist between competing conservation objectives.     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用.以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特...     

Recovery of forest structure and spectral properties after selective logging in lowland Bolivia.

Effective monitoring of selective logging from remotely sensed data requires an understanding of the spatial and temporal thresholds that constrain the utility of those data, as well as the structural and ecological characteristics of forest disturbances that are responsible for those constraints. Here we assess those thresholds and characteristics within the context of selective logging in the Bolivian Amazon. Our study combined field measurements of the spatial and temporal dynamics of felling gaps and skid trails ranging from <1 to 19 months following reduced-impact logging in a forest in lowland Bolivia with remote-sensing measurements from simultaneous monthly ASTER satellite overpasses. A probabilistic spectral mixture model (AutoMCU) was used to derive per-pixel fractional cover estimates of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil. Results were compared with the normalized difference in vegetation index (NDVI). The forest studied had considerably lower basal area and harvest volumes than logged sites in the Brazilian Amazon where similar remote-sensing analyses have been performed. Nonetheless, individual felling-gap area was positively correlated with canopy openness, percentage liana coverage, rates of vegetation regrowth, and height of remnant NPV. Both liana growth and NPV occurred primarily in the crown zone of the felling gap, whereas exposed soil was limited to the trunk zone of the gap. In felling gaps >400 m2, NDVI, and the PV and NPV fractions, were distinguishable from unlogged forest values for up to six months after logging; felling gaps <400 m2 were distinguishable for up to three months after harvest, but we were entirely unable to distinguish skid trails from our analysis of the spectral data.     

Estimating non-native plant richness with a species-accumulation model along roads

Monitoring non-native plant richness is important for biodiversity conservation and scientific research. The species-area model (SA model) has been used frequently to estimate the total species richness within a region. However, the conventional SA model may not provide robust estimations of non-native plant richness because the ecological processes associated with the accumulation of exotic and native plants may differ. Because roads strongly dictate the distributions of exotic plants, we propose a species-accumulation model along roads (SR model), rather than an SA model, to estimate the non-native plant richness within a region. Using 270 simulated data sets, we compared the differences in performance between the SR and SA models. A decision tree based on prediction accuracy was created to guide model application, which was validated using field data from 3 national nature reserves in 3 different provinces in China. The SR model significantly outperformed the SA model when non-native species were restricted to the roadsides and the proportion of uncommon exotic species was small. More importantly, the SR model accurately estimated the non-native plant richness in all field sites with an error of <1 species per site. We believe our new model meets the practical need to efficiently and robustly estimate non-native plant richness, which may facilitate effective biodiversity conservations and promote research on non-native plant invasion and vegetation dynamics.     

Leaf-area index and light attenuation in rapidly expanding shrub thickets

There is increasing interest in the changes in ecosystem services that accompany the conversion of grasslands to shrub-dominated communities. Shrub structure and associated effects on the light environment may be especially important in affecting productivity and diversity. Leaf-area index (LAI) and understory light levels of Morella cerifera shrub thickets were assessed on Hog Island, Virginia, USA, at four sites along a soil chronosequence. LAI was estimated from annual leaf litter, with allometric models relating stem diameter to leaf area, with a portable integrating radiometer (LI-COR LAI-2000), and from photosynthetically active radiation (PAR) using the Beer-Lambert law. For the two youngest thickets, LAI estimates from leaf litter (approximately 10.0) approached levels often associated with tropical rain forest. Allometric models estimated LAI values at 9.8 and 12.5 for the same thickets. High LAI in thickets also results in high light attenuation. Light levels within thickets were as low as 0.7% of above-canopy PAR in the youngest thicket. These data suggest that M. cerifera shrub thickets have a very high potential for annual net primary production. Furthermore, extreme modification of the light environment, coupled with heavy shrub litter fall, may exclude potential competitors during thicket establishment and rapidly alter community structure and ecosystem function.