Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.     

Deriving state-and-transition models from an image series of grassland pattern dynamics

We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1 m quadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological ‘phases’ and ‘transitions’ of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands.     

Effects of Exploitation and Park Boundaries on Legume Trees in the Sonoran Desert

Abstract: Legume trees have been harvested in the Sonoyta Valley since 1975. We estimated the effects of this woodcutting along the border between Organ Pipe Cactus National Monument (U.S.A.) and Sonora, Mexico. We placed 10 × 100 m transects in ephemeral watercourses and uplands on both sides of the international boundary at different distances from the border. Mesquite and ironwood trees exhibited significantly higher damage in the Mexican sites than in the protected uplands in the United States. Damage for all the species significantly decreased 500 m from the border, with the exception of ironwood, for which damage remained high within ephemeral watercourses.     

Molecular Evidence for a Unique Evolutionary Lineage of Endangered Sonoran Desert Fish (Genus Poeciliopsis)

Efforts to restore an endangered species in its former range should be based on a sound understanding of evolutionary relationships among remaining natural populations. In this study mitochondrial (mt) DNA diversity within and among Gila River drainage populations of the endangered Sonoran topminnow ( Poeciliopsis occidentalis ) in Arizona was compared to that from neighboring populations in Sonora, Mexico, where the species remains locally abundant. No mtDNA diversity was detected within or among samples from the Gila River basin in Arizona. But considerable variation was found within and among populations from several river systems in Sonora. Examination of mtDNA from a population that inhabits the upper reaches of the Río Yaqui in southeastern Arizona revealed substantial divergence between it and all other populations examined. We comment on the implications of this divergent population for topminnow management in Arizona and argue for more-detailed genetic and morphological studies to determine the distributional limits and specific status of this highly divergent form.     

Hierarchical analysis of vegetation dynamics over 71 years: soil-rainfall interactions in a Chihuahuan Desert ecosystem

Proliferation of woody plants in grasslands and savannas is a persistent problem globally. This widely observed shift from grass to shrub dominance in rangelands worldwide has been heterogeneous in space and time largely due to cross-scale interactions among soils, climate, and land-use history. Our objective was to use a hierarchical framework to evaluate the relationship between spatial patterns in soil properties and long-term shrub dynamics in the northern Chihuahuan Desert of New Mexico, USA. To meet this objective, shrub patch dynamics from 1937 to 2008 were characterized at patch and landscape scales using historical imagery and a recent digital soils map. Effects of annual precipitation on patch dynamics on two soils revealed strong correlations between shrub growth on deep sandy soils and above-average rainfall years (r = 0.671, P = 0.034) and shrub colonization and below-average rainfall years on shallow sandy soils (r = 0.705, P = 0.023). Patch-level analysis of demographic patterns revealed significant differences between shrub patches on deep and shallow sandy soils during periods of above- and below-average rainfall. Both deep and shallow sandy soils exhibited low shrub cover in 1937 (1.0% +/- 2.3% and 0.3% +/- 1.3%, respectively [mean +/- SD]) and were characterized by colonization or appearance of new patches until 1960. However, different demographic responses to the cessation of severe drought on the two soils and increased frequency of wet years after 1960 have resulted in very different endpoints. In 2008 a shrubland occupied the deep sandy soils with cover at 19.8% +/- 9.1%, while a shrub-dominated grassland occurred on the shallow sandy soils with cover at 9.3% +/- 7.2%. Present-day shrub vegetation constitutes a shifting mosaic marked by the coexistence of patches at different stages of development. Management implications of this long-term multi-scale assessment of vegetation dynamics support the notion that soil properties may constrain grassland remediation. Such efforts on sandy soils should be focused on sites characterized by near-surface water-holding capacity, as those lacking available water-holding capacity in the shallow root zone pose challenges to grass recovery and survival.     

Comparison of six correlative models in predictive vegetation mapping on a local scale

A variety of statistical techniques has been used in predictive vegetation modelling (PVM) that attempt to predict occurrence of a given community or species in respect to environmental conditions. We compared the performance of three profile models, BIOCLIM, GARP and MAXENT with three nonparametric models of group discrimination techniques, MARS, NPMR and LRT. The two latter models are relatively new statistical techniques that have just entered the field of PVM. We ran all models on a local scale for a given grassland community (Teucrio-Seslerietum) using the same input data to examine their performance. Model accuracy was evaluated both by Cohen’s kappa statistics (κ) and by area under receiver operating characteristics curve based both on resubstitution of training data and on an independent test data set. MAXENT of profile models and MARS of group discrimination techniques achieved the best prediction.     

Empirical study of GARCH models with leverage effect in an environmental application

Atmospheric carbon dioxide concentration (ACDC) level is an important factor for predicting temperature and climate changes. We analyze the conditional variance of a function of ACDC level known as ACDC level growth rate (ACDCGR) using the generalised autoregressive conditional heteroskedasticity (GARCH) and GARCH models with leverage effect. The data are a subset of the well known Mauna Loa atmosphere carbon dioxide record. We test for the presence of stylized facts in the ACDCGR time series. The performance of GARCH models are compared to EGARCH, TGARCH and PGARCH models. Model fit measures AIC, BIC and likelihood is calculated for each fitted model. The results do confirm the presence of some of important stylized facts in the ACDCGR time series, but the presence of leverage effect is not significant . The out of sample one step ahead forecasting performances of the models based on RMSE and MAE metrics are evaluated. EGARCH model with student $t$ disturbances showed the best fit and a valid forecasting performance. A bootstrap algorithm is employed to calculate confidence intervals for future values of ACDCGR time series and its volatility. The constructed bootstrap confidence intervals showed a reasonable performance.     

Population level risk assessment: practical considerations for evaluation of population models from a risk assessor's perspective

Population models are increasingly being considered as a tool for pesticide risk assessment in order to evaluate how potential effects act on the population level and population recovery. While the importance and difficulties of such models have been discussed by various authors during the past decade, mainly with a focus on how to describe or develop such models, several biological and methodological aspects have never been addressed so far, which are relevant for the application of models in risk assessment. These include a critical review of our knowledge of a species, the use of field data by taking methodological constraints into account, how to include uncertainty in model validation or how to measure effects. Although these aspects will be critical for the acceptance of population models by authorities, most of them apply not only to population models, but also to standard risk assessment. In the present article, we give practical recommendations for addressing these questions in population level risk assessments.     

An evaluation of procedures for the digestion of soils and vegetation from areas with metalliferous pollution

Various digestion or extraction processes are available for the determination of trace metals in environmental samples using diverse analytical techniques. Our research examines the most efficient and reproducible methods of digestion utilising readily available laboratory equipment, reagents and instrumentation. Extraction procedures reported in over 80 recent research works were considered and the most common methods were critically evaluated. Thus nitric acid, nitric acid/perchloric acid, aqua regia, nitric acid/hydrogen peroxide and microwave-assisted methods were investigated using soil and leaf samples collected adjacent to three old metalliferous workings. Analysis was carried out using Flame Atomic Absorption Spectrometry and the results were evaluated. Differences in efficiency of extraction relative to specific metals and different substrates are highlighted and recommendations made for a digestion procedure suitable for environmental samples. Aqua regia produced the most accurate, efficient and reproducible results; we consider methods of improving both of these factors and sample preparation. Our recommended methodology has applications in environmental surveys, environmental geology, environmental toxicology, geochemistry and provides a means of obtaining meaningful and reliable results for the determination of metals present in soils, minerals and vegetation.     

Historical record of anthropogenic polycyclic aromatic hydrocarbons in a lake sediment from the southern Tibetan Plateau

High-altitude lake sediments can be used as natural archives to reconstruct the history of pollutants. In this work, the temporal distribution of polycyclic aromatic hydrocarbons (PAHs) was determined in a sediment core collected from the southern Tibetan Plateau (TP), which was dated by using the ²¹⁰Pb dating method and validated with the ¹³⁷Cs fallout peak. The concentrations of the anthropogenic PAHs (Σ₈PAH) in the sediment core ranged from 0.83 to 12 ng/g dw, and the fluxes of the Σ₈PAH were in the range of 2.1–27 g/cm²/year. The temporal variations in the concentration and input flux of anthropogenic PAHs were low with little variability before the 1950s, and then gradually increased from the 1950s to the 1980s, and an accelerated increase was observed after the early 1980s. The content of total organic carbon played an insignificant role in affecting the time trends of PAHs in the sediment core. Diagnostic concentration fractions of PAH components indicate PAHs in the lake sediment of the southern TP which are mainly from biomass burning and/or from long-range atmospheric transport.     

Application of Markov-chain model for vegetation restoration assessment at landslide areas caused by a catastrophic earthquake in Central Taiwan

The 921 earthquake caused a catastrophic disaster in Central Taiwan. Ten years have passed since the earthquake occurred. Vegetation succession is the basis for establishing a restoration reference which plays an important role in vegetation restoration at landslide sites. Generally, growth conditions for grass are easier and the growth rate is faster than that for trees. Therefore, grass can be considered a pioneer species or an important reference for the early vegetation succession stage. This is the reason why grass is required to be extracted from other land covers. Integrating remote sensing, geographic information system and image classification into vegetation succession models is very important. In this study, the Markov chain model was applied for vegetation restoration assessment and discussion. Chiufenershan and Ninety-nine peaks were selected as the study areas. Five SPOT satellite images are used for land cover mapping and vegetation restoration simulations. Four categories of land covers were extracted, including forest, grass, bare land and water, respectively. From the transitive probability matrix (derived from any two land covers), the results show that vegetation restoration at the Chiufenershan and Ninety-nine peaks landslide areas is ongoing, but that has been disturbed by natural disasters.     

Indices of Grassland Biodiversity in the Chihuahuan Desert Ecoregion Derived from Remote Sensing

Abstract: We used a relatively simple and direct remote-sensing approach to determine biodiversity values in arid ecosystems and thus identify potential conservation sites. We developed indices based on regression models between grass, shrub, litter, exposed-soil groundcover components, and Landsat thematic mapper satellite imagery reflectance values over a reference site in the northern Chihuahuan Desert in New Mexico. This site supports low-disturbance desert grasslands that have been excluded from livestock grazing for 55 years and moderate-disturbance grasslands that have been under a continuous grazing regime for over 100 years. Greater richness and abundance of noninvasive and nonruderal plant species were associated with the low-disturbance grasslands that had lower shrub abundance, increased litter and grass cover, and lower exposed soil. Using the thematic mapper indices, we computed an additive grassland biodiversity index such that, as exposed soil and shrub values go down, litter and grass values go up, as does the biodiversity index. When the biodiversity index was applied to the reference-site landscape, grasslands previously identified for their high conservation value were detected. As a further test, we applied the indices to a site in Chihuahua, Mexico, that supports similar grasslands but for which there are few other data on condition and conservation values. The soil, grass, and shrub indices were moderately effective in describing the range of variation at the Mexico site, but the litter equation was not. Still, higher biodiversity value in terms of nonruderal plant diversity tended to correspond to higher grass cover and lower soil exposure and a higher overall biodiversity index. Some localized calibration with geologic substrate may be required along with an assessment of the temporal constraints, but generally the index shows promise for quickly and efficiently detecting desert grasslands of high biodiversity conservation value.     

Geochemical transformation of soil cover and vegetation in a drained floodplain lake affected by long-term discharge of effluents from rayon industry plants,lower Don River Basin,Southern Russia

Environmental Geochemistry and Health - Lake Atamanskoye is one of the most polluted aquatic environments in the South of Russia. This water body was affected by long-term pollution by effluent...     

Nitrogen regulation of the climate-carbon feedback: evidence from a long-term global change experiment

Modeling studies have shown that nitrogen (N) strongly regulates ecosystem responses and feedback to climate warming. However, it remains unclear what mechanisms underlie N regulation of ecosystem-climate interactions. To examine N regulation of ecosystem feedback to climate change, we have conducted a warming and clipping experiment since November 1999 in a tallgrass prairie of the Great Plains, USA. Infrared heaters were used to elevate soil temperature by an average of 1.96 degrees C at a depth of 2.5 cm from 2000 to 2008. Yearly biomass clipping mimicked hay or biofuel feedstock harvest. We measured carbon (C) and N concentrations, estimated their content and C:N ratio in plant, root, litter, and soil pools. Warming significantly stimulated C storage in aboveground plant, root, and litter pools by 17%, 38%, and 29%, respectively, averaged over the nine years (all P < 0.05) but did not change soil C content or N content in any pool. Plant C:N ratio and nitrogen use efficiency increased in the warmed plots compared to the control plots, resulting primarily from increased dominance of C4 plants in the community. Clipping significantly decreased C and N storage in plant and litter pools (all P < 0.05) but did not have interactive effects with warming on either C or N pools over the nine years. Our results suggest that increased ecosystem nitrogen use efficiency via a shift in species composition toward C4 dominance rather than plant N uptake is a key mechanism underlying warming stimulation of plant biomass growth.     

Estimation of the longitudinal dispersion coefficient using a two-zone model in a channel partially covered with artificial emergent vegetation

Environmental Fluid Mechanics - Understanding scalar transport in solvents is important in chemical engineering, pollution control, and water remediation, where the longitudinal dispersion...     

浮叶植物重建对富营养化湖泊氮磷营养水平的影响

利用太湖五里湖污染底泥，在不破坏表层沉积物形态和结构的情况下，利用大口径的采样器采集沉积物柱状样，研究浮叶植物荇菜（Limnanthemun nymphoides）在此底泥上适应性生长情况及其对水体以及沉积物中氮磷的影响。结果表明，在培养实验过程中，荇菜生长使上覆水体中的氮、磷营养水平逐渐降低，藻类的生长明显受到克制，水体透明度增加，水质逐渐改善。通过植物根系对沉积物和问隙水中营养盐的直接吸收，使表层（0～5cm）沉积物与问隙水中氮磷营养盐的水平在实验结束后有明皿下降，对于控制沉积物内源营养盐释放有重要的作用。因此，恢复以水生植物为丰的水生生态系统足重建富营养湖泊生态系统和控制湖泊内源负荷的重要措施。     

Modeling the longitudinal profiles of streamwise velocity in an open channel with a model patch of vegetation

This paper proposes a model for predicting the longitudinal profiles of streamwise velocities in an open channel with a model patch of vegetation. The governing equation was derived from the momentum equation and flow continuity equation. The model can estimate the longitudinal profiles of velocities both inside and outside a vegetation patch. Laboratory experiments indicate that the longitudinal profiles of velocities inside a patch and in the adjacent bare channel have the same adjustment distance in the longitudinal direction, but the profiles have different trends because the vegetation drag drives the flow from the patch to the adjacent bare channel. The model considers different dimensionless parameters in two flow adjustment regions upstream of and inside the patch. Sixteen sets of experimental data from different sources are used to verify the model. The model is capable of modeling the longitudinal profiles of velocities inside and outside patches of cylinders or cylinder-like plants. Compared to a previous model, the current model improves the modeling accuracy of longitudinal profiles of velocities.