Phytosociological synrelevés and plant landscape mapping: From theory to practice

Abstract

A mapping methodology is presented here that allows the practical implementation of synphytosociological and geosynphytosociological surveys. The proposed methodology consists in carrying out synrelevés from vegetation maps produced through the use of geographic information system (GIS). Such mapping has the great advantage of allowing the overlaying of the study area map with many thematic maps that are particularly useful in the definition of the areas of potential vegetation. In the present case, the use of solar radiation maps is proposed, as these are more representative than aspect maps (exposure) of the actual conditions of the mapped areas. Indeed, the main ecological factors that delimit the ecological niche of plant communities, the vegetation series and the geosigmeta are defined qualitatively and quantitatively. The methodology is here applied to an area of the Italian Adriatic coast that has a great diversity of environmental conditions. The conclusions confirm that the proposed methodology allows predictive models of the plant landscape units (geosigmeta) to be obtained with great precision; they can be mapped and quantified in concrete terms insofar as they are defined through multidimensional correlations.     

Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time

Tidal salt marshes in the San Francisco Estuary region display heterogeneous vegetation patterns that influence wetland function and provide adequate habitat for native or endangered wildlife. In addition to analyzing the extent of vegetation, monitoring the dynamics of vegetation pattern within restoring wetlands can offer valuable information about the restoration process. Pattern metrics, derived from classified remotely sensed imagery, have been used to measure composition and configuration of patches and landscapes, but they can be unpredictable across scales, and inconsistent across time. We sought to identify pattern metrics that are consistent across spatial scale and time – and thus robust measures of vegetation and habitat configuration – for a restored tidal marsh in the San Francisco Bay, CA, USA. We used high-resolution (20 cm) remotely sensed color infrared imagery to map vegetation pattern over 2 years, and performed a multi-scale analysis of derived vegetation pattern metrics. We looked at the influence on metrics of changes in grain size through resampling and changes in minimum mapping unit (MMU) through smoothing. We examined composition, complexity, connectivity and heterogeneity metrics, focusing on perennial pickleweed (Sarcocornia pacifica), a dominant marsh plant. At our site, pickleweed patches grew larger, more irregularly shaped, and closely spaced over time, while the overall landscape became more diverse. Of the two scale factors examined, grain size was more consistent than MMU in terms of identifying relative change in composition and configuration of wetland marsh vegetation over time. Most metrics exhibited unstable behavior with larger MMUs. With small MMUs, most metrics were consistent across grain sizes, from fine (e.g. 0.16 m²) to relatively large (e.g. 16 m²) pixel sizes. Scale relationships were more variable at the landcover class level than at the landscape level (across all classes). This information may be useful to applied restoration practitioners, and adds to our general understanding of vegetation change in a restoring marsh.     

Spatiotemporal Patterns of Production Can Be Used to Detect State Change Across an Arid Landscape

Methods to detect and quantify shifts in the state of ecosystems are increasingly important as global change drivers push more systems toward thresholds of change. Temporal relationships between precipitation and aboveground net primary production (ANPP) have been studied extensively in arid and semiarid ecosystems, but rarely has spatial variation in these relationships been investigated at a landscape scale, and rarely has such information been viewed as a resource for mapping the distribution of different ecological states. We examined the broad-scale effects of a shift from grassland to shrubland states on spatiotemporal patterns of remotely sensed ANPP proxies in the northern Chihuahuan Desert. We found that the normalized difference vegetation index (NDVI), when averaged across an eight-year period, did not vary significantly between these states, despite changes in ecosystem attributes likely to influence water availability to plants. In contrast, temporal relationships between precipitation and time-integrated NDVI (NDVI-I) modeled on a per-pixel basis were sensitive to spatial variation in shrub canopy cover, a key attribute differentiating ecological states in the region. The slope of the relationship between annual NDVI-I and 2-year cumulative precipitation was negatively related to, and accounted for 71% of variation in, shrub canopy cover estimated at validation sites using high spatial resolution satellite imagery. These results suggest that remote sensing studies of temporal precipitation–NDVI relationships may be useful for deriving shrub canopy cover estimates in the region, as well as for mapping other ecological state changes characterized by shifts in long-term ANPP, plant functional type dominance, or both.     

Mapping changes in tidal wetland vegetation composition and pattern across a salinity gradient using high spatial resolution imagery

Detailed vegetation mapping of wetlands, both natural and restored, can offer valuable information about vegetation diversity and community structure and provides the means for examining vegetation change over time. We mapped vegetation at six tidal marshes (two natural, four restored) in the San Francisco Estuary, CA, USA, between 2003 and 2004 using detailed vegetation field surveys and high spatial-resolution color-infrared aerial photography. Vegetation classes were determined by performing hierarchical agglomerative clustering on the field data collected from each tidal marsh. Supervised classification of the CIR photography resulted in vegetation class mapping accuracies ranging from 70 to 92%; 10 out of 12 classification accuracies were above 80%, demonstrating the potential to map emergent wetland vegetation. The number of vegetation classes decreased with salinity, and increased with size and age. In general, landscape diversity, as measured by the Shannon’s diversity index, also decreased with salinity, with an exception for the most saline site, a newly restored marsh. Vegetation change between years is evident, but the differences across sites in composition and pattern were larger than change within sites over two growing seasons.     

Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover

Aim Woody plants affect vegetation–environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broad‐scale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape‐scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island. Location The Santa Rita Mountains, Arizona, USA. Methods Using a satellite‐measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time‐series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation–environment feedbacks at the local scale. Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation‐ and community‐specific patterns of vegetation dynamics across the gradient. Main conclusions In addition to the environmental factors usually considered – climate, reflecting resources and constraints, and vegetation community, reflecting species composition and relative dominance – woody plant cover, a broad‐scale proxy of many vegetation–environment interactions, represents an ecological dimension that provides additional process‐related understanding of landscape‐scale patterns of vegetation function.     

Phenological description of natural vegetation in southern Africa using remotely‐sensed vegetation data

Abstract. Various attempts have been made to describe and map the vegetation of southern Africa with recent efforts having an increasingly ecologi cal context. Vegetation classification is usually based on vegetation physiognomy and floristic composition, but phenology is useful source of information which is rarely used, although it can contribute functional information on ecosystems. The objectives of this study were to identify a suite of variables derived from time‐series NDVI data that best describe the phenological phenomena of vegetation in southern Africa and, secondly, to assess a classification of pixels of the study area based on NDVI variables using a preexisting map of the biomes that was delimited on the basis of life forms and climate. A number of variables were derived from the satellite data for describing phenological phenomena, which were analysed by multivariate techniques to determine which variables best explained the variation in the satellite data. This set of variables was used to produce a phenological classification of the vegetation of southern Africa, the results of which are discussed in relation to their concordance with the existing biome boundaries.     

The development of a Canadian dynamic habitat index using multi-temporal satellite estimates of canopy light absorbance

Monitoring patterns of fauna diversity across the landscape, both spatially and temporally, presents special challenges due to the dynamic nature of populations and complex interactions with the local and regional environment. One area where progress is being made is the development of relationships between regional biodiversity with indirect indicators or surrogates, such as vegetative production. In this paper we discuss implementation of a dynamic habitat index, originally developed in Australia, to Canadian conditions. The index, based on the fraction of photosynthetically active radiation (fPAR) absorbed by vegetation, a variable which is analogous to green vegetation cover, is derived solely from satellite data. The index utilizes time series of satellite observations of greenness to derive three indicators of the underlying vegetation dynamics; the cumulative annual greenness, the minimum level of perennial cover, and the degree of vegetation seasonality. We apply the index across Canada and compare the three components by ecozones, demonstrating that Canada's terrestrial environment can effectively be clustered into five major dynamic habitat regimes. These range from those with low cumulative greenness and highly seasonal variation in cover, to regimes which have high canopy light absorbance with limited seasonality and continuous annual green cover. By comparing data from multiple years, our analysis indicates that a number of these ecozones have experienced changes in their composition over the past 6 years. We believe this methodology can provide an initial stratification of large areas for biodiversity monitoring and can be used to focus finer scale approaches to specific regions of interest or monitor regions too remote for comprehensive field surveys.     

Mapping and monitoring of coastal wetlands of Çukurova Delta in the Eastern Mediterranean region

The aim of this research was to link vegetation characteristics, such as spatial and temporal distribution, and environmental variables, with land cover information derived from remotely sensed satellite images of the Eastern Mediterranean coastal wetlands of Turkey. The research method was based on (i) recording land cover characteristics by means of a vegetation indicator, and (ii) classifying and mapping coastal wetlands utilizing a Landsat Thematic Mapper (TM) image of Çukurova Deltas in Turkey. Vegetation characteristics of various habitats, such as sand dunes, salt marshes, salty plains and afforestation areas, were identified by field surveys. A Landsat TM image of 4 July 1993 was pre-processed and then classified using the Maximum Likelihood (ML) algorithm and Artificial Neural Networks (ANN). As a result of this supervised classification, the land cover types were classified with a largest accuracy of 90.2% by ANN. The classified satellite sensor imagery was linked to vegetation and bird census data, which were available through literature in a Geographical Information System (GIS) environment to determine the spatial distribution of plant and bird biodiversity in this coastal wetland. The resulting data provide an important baseline for further investigations such as monitoring, change detections and designing conservation policies in this coastal ecosystem.     

Remote sensing of upland vegetation: the potential of high spatial resolution satellite sensors

Aim Traditional methodologies of mapping vegetation, as carried out by ecologists, consist primarily of field surveying or mapping from aerial photography. Previous applications of satellite imagery for this task (e.g. Landsat TM and SPOT HRV) have been unsuccessful, as such imagery proved to have insufficient spatial resolution for mapping vegetation. This paper reports on a study to assess the capabilities of the recently launched remote sensing satellite sensor Ikonos, with improved capabilities, for mapping and monitoring upland vegetation using traditional image classification methods. Location The location is Northumberland National Park, UK. Methods Traditional remote sensing classification methodologies were applied to the Ikonos data and the outputs compared to ground data sets. This enabled an assessment of the value of the improved spatial resolution of satellite imagery for mapping upland vegetation. Post‐classification methods were applied to remove noise and misclassified pixels and to create maps that were more in keeping with the information requirements of the NNPA for current management processes. Results The approach adopted herein for quick and inexpensive land cover mapping was found to be capable of higher accuracy than achieved with previous approaches, highlighting the benefits of remote sensing for providing land cover maps. Main conclusions Ikonos imagery proved to be a useful tool for mapping upland vegetation across large areas and at fine spatial resolution, providing accuracies comparable to traditional mapping methods of ground surveys and aerial photography.     

Plant species richness and shrub cover attenuate drought effects on ecosystem functioning across Patagonian rangelands

Drought is an increasingly common phenomenon in drylands as a consequence of climate change. We used 311 sites across a broad range of environmental conditions in Patagonian rangelands to evaluate how drought severity and temperature (abiotic factors) and vegetation structure (biotic factors) modulate the impact of a drought event on the annual integral of normalized difference vegetation index (NDVI-I), our surrogate of ecosystem functioning. We found that NDVI-I decreases were larger with both increasing drought severity and temperature. Plant species richness (SR) and shrub cover (SC) attenuated the effects of drought on NDVI-I. Grass cover did not affect the impacts of drought on NDVI-I. Our results suggest that warming and species loss, two important imprints of global environmental change, could increase the vulnerability of Patagonian ecosystems to drought. Therefore, maintaining SR through appropriate grazing management can attenuate the adverse effects of climate change on ecosystem functioning.     

Long-term response of fishes and other fauna to restoration of former salt hay farms: multiple measures of restoration success

This synthesis brings together published and unpublished data in an evaluation of restoration of former salt hay farms to functioning salt marshes. We compared nine years of field measurements between three restored marshes (Dennis, Commercial, and Maurice River Townships) and a reference marsh (Moores Beach) in the mesohaline portion of Delaware Bay. In the process, we compared channel morphology, geomorphology, vegetation, sediment organic matter, fish assemblages, blue crabs, horseshoe crabs, benthic infauna, and diamondback terrapins. For fishes we compared structural (distribution, abundance) and functional (feeding, growth, survival, reproduction, production) aspects to evaluate the restored marshes in an Essential Fish Habitat context. Marsh vegetation and drainage density responded gradually and positively with restored marshes approximating the state of the reference marsh within the nine-year study period. The fauna responded more quickly and dramatically with most measures equal or greater in the restored marshes within the first one or two years after restoration. Differences in response time between the vegetation and the fauna imply that the faunal response was more dependent on access to the shallow intertidal marsh surface and intertidal and subtidal creeks than on characteristics of the vegetated marsh. The fishes in created subtidal creeks in restored marshes responded immediately and maintained fish assemblages similar to the reference marsh over the study period. The intertidal creek fish assemblages tended to become more like the reference marsh in the last years of the comparison. Overall, these results document the success of the restoration and how marshes function for both resident and transient fauna, especially fishes.     

Mapping landscape corridors

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and demonstrate the approach with a forest map derived from satellite imagery of northern Slovakia. We show how the approach can be used to differentiate between relatively narrow (‘line’) and wide (‘strip’) structural corridors by mapping corridors at multiple scales of observation, and indicate how to map functional corridors with maps of observed or simulated organism movement. An application to environmental reporting is demonstrated by assessing structural forest corridors in relation to forest types in northern Slovakia.     

Mapping functional connectivity

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible, and automated approach for the definition of indicators based on the classification and mapping of spatial patterns of connectivity from observed or simulated movement and dispersal events. The approach is illustrated with data derived from simulated movement on a map produced from satellite imagery of a structurally complex, multi-habitat landscape. The analysis reveals critical areas that facilitate the movement of dispersers among habitat patches. Mathematical morphology can be applied to any movement map providing new insights into pattern-process linkages in multi-habitat landscapes.     

Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series

Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000–2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies.     

Spatial and temporal modelling for parasite transmission studies and risk assessment

Spatial and temporal modelling of parasite transmission and risk assessment require relevant spatial information at appropriate spatial and temporal scales. There is now a large literature that demonstrates the utility of satellite remote sensing and spatial modelling within geographical information systems (GIS) and firmly establishes these technologies as the key tools for spatial epidemiology. This review outlines the strength of satellite remotely sensed data for spatial mapping of landscape characteristics in relation to disease reservoirs, host distributions and human disease. It is suggested that current satellite technology can fulfill the spatial mapping needs of disease transmission and risk modelling, but that temporal resolution, which is a function of the satellite data acquisition characteristics, may be a limitating factor for applications requiring information about landscape or ecosystem dynamics. The potential of the Modis sensor for spatial epidemiology is illustrated with reference to mapping spatial and temporal vegetation dynamics and small mammal parasite hosts on the Tibetan plateau. Future research directions and priorities for landscape epidemiology are considered.     

Ecological structure of vegetation cover of taiga and alpine territory: Detection and representation of basic peculiarities by the mapping method

The geobotanical mapping of territory in the upper reaches of the Bureya River was carried out. Zonality, general diversity, and territorial ratio of vegetation classes, as well as location on relief (landscape) and dynamic vegetation series, are represented on the map of actual vegetation cover. Mapping as a research method, as a rule, leads to a higher level of understanding of basic peculiarities of an object. The map as a result of research reflects clearly basic peculiarities of an object in accordance with the map scale or demonstrably shows the shortcomings of the conducted study.     

Interactions between a salt marsh native perennial (Salicornia virginica) and an exotic annual (Polypogon monspeliensis) under varied salinity and hydroperiod

An exotic grass invades salt marshes of southern California in very wet years and where there are sewage spills or urban runoff. A series of growth-chamber, mesocosm, and greenhouse experiments explored whether soil salinity and/or waterlogging could explain invasion patterns. In all experiments, salinity significantly affected the growth and distribution of Polypogon monspeliensis (rabbit-foot grass, an exotic annual grass) and Salicornia virginica (pickleweed, a native perennial succulent). High salinities caused a greater reduction in seed germination rates for P. monspeliensis than for S. virginica, indicating that high salinity limits establishment and the spread of this exotic grass. At Tijuana Estuary, fresh water inputs to tidal mesocosms lowered soil salinities, increased cover of P. monspeliensis, and decreased cover of S. virginica. Polypogon monspeliensis outcompeted S. virginica under all salinity and hydrology treatments in the greenhouse experiment. Seasonally-low soil salinities caused by winter runoff and anthropogenic fresh water inputs are the likely factors controlling annual variations in the distribution of P. monspeliensis in southern California salt marshes. Our understanding of the causes of invasion is readily applicable to management: local invasions may be reversed by adding salt, and larger scale problems could be avoided by reinstating more natural hydrologic regimes.     

Drainage and Elevation as Factors in the Restoration of Salt Marsh in Britain

Intertidal restoration through realignment of flood defenses has become an important component of the U.K. coastal and estuarine management strategy. Although experimentation with recent deliberate breaches is in progress, the long‐term prognosis for salt marsh restoration can be investigated at a number of sites around Essex, southeast England where salt marshes have been reactivated (unmanaged restoration) by storm events over past centuries. These historically reactivated marshes possess higher creek densities than their natural marsh counterparts. Both geomorphology and sedimentology determine the hydrology of natural and restored salt marshes. Elevation relative to the tidal frame is known to be the primary determinant of vegetation colonization and succession. Yet vegetation surveys and geotechnical analysis at a natural marsh, where areas with good drainage exist in close proximity to areas of locally hindered drainage at the same elevation, revealed a significant inverse relationship between water saturation in the root zone and the abundance of Atriplex portulacoides, normally the physiognomic dominant on upper salt marsh in the region. Elsewhere in Essex natural and restored marshes are typified by very high sediment water contents, and this is reflected in low abundance of A. portulacoides. After a century of reestablishment no significant difference could be discerned between the vegetation composition of the storm‐reactivated marshes and their natural marsh counterparts. We conclude that vegetation composition may be restored within a century of dike breaching, but this vegetation does not provide a reliable indicator of ecological functions related to creek structure.     

面向土系调查制图的小尺度区域景观分类——以宁镇丘陵区中一小区域为例

土系是中国土壤系统分类的基层分类单元,与所处微域景观联系密切,对小尺度样区进行景观分类研究有助于对研究区景观建立系统的认识。以宁镇丘陵区一小尺度样区为例,结合景观生态分类理论及土系特点,探讨了面向土系调查制图的景观分类的原则与方法,建立了包括景观区、景观类、景观亚类和景观相的四级景观分类系统,并借助3S技术进行了景观制图,并以此为基础对样区开展土系调查,对景观分类体系进行了验证。结果表明,景观相与土系有较好相关性,对土系分布具有指示作用,此景观分类体系有助于对土壤所处景观条件形成深入系统认识,可为土系调查制图工作提供参考。