LiDAR as a rapid tool to predict forest habitat types in Natura 2000 networks

Management strategies for the conservation of biodiversity can be developed only with precise information on the spatial distribution of organisms on relevant, mostly regional, spatial scales. Current surrogates for approximating the distribution of biodiversity are habitats mapped within a number of national and international frameworks (e.g., Natura 2000), even though conventional habitat mapping is time consuming and requires well-trained personnel. Here we evaluated the use of light detection and ranging (LiDAR) to map forest habitat types to simplify the process. We used available data of habitat types for the Bavarian Forest National Park as a basis to predict habitat types with LiDAR-derived variables. Furthermore, we compared these results with predictions based on extensive ground-based climate, soil and vegetation data. Using linear and flexible discriminant analyses, we found that LiDAR is able to predict forest habitat types with the same overall accuracy as the extensive ground data for climate, soil and vegetation composition. Subtle differences in the vegetation structure between habitat types, particularly in the vertical and horizontal vegetation profiles, were captured by LiDAR. These differences in the physiognomy were in part caused by changes in altitude, which also influence tree species composition. We propose that the most-efficient way to identify forest habitat types according Natura 2000 is to combine remote-sensing LiDAR data with well-directed field surveys.     

High-resolution satellite remote sensing of littoral vegetation of Lake Sevan (Armenia) as a basis for monitoring and assessment

Physics-based remote sensing in littoral environments for ecological monitoring and assessment is a challenging task that depends on adequate atmospheric conditions during data acquisition, sensor capabilities and correction of signal disturbances associated with water surface and water column. Airborne hyper-spectral scanners offer higher potential than satellite sensors for wetland monitoring and assessment. However, application in remote areas is often limited by national restrictions, time and high costs compared to satellite data. In this study, we tested the potential of the commercial, high-resolution multi-spectral satellite QuickBird for monitoring littoral zones of Lake Sevan (Armenia). We present a classification procedure that uses a physics-based image processing system (MIP) and GIS tools for calculating spatial metrics. We focused on classification of littoral sediment coverage over three consecutive years (2006–2008) to document changes in vegetation structure associated with a rise in water levels. We describe a spectral unmixing algorithm for basic classification and a supervised algorithm for mapping vegetation types. Atmospheric aerosol retrieval, lake-specific parameterisation and validation of classifications were supported by underwater spectral measurements in the respective seasons. Results revealed accurate classification of submersed aquatic vegetation and sediment structures in the littoral zone, documenting spatial vegetation dynamics induced by water level fluctuations and inter-annual variations in phytoplankton blooms. The data prove the cost-effective applicability of satellite remote-sensing approaches for high-resolution mapping in space and time of lake littoral zones playing a major role in lake ecosystem functioning. Such approaches could be used for monitoring wetlands anywhere in the world.     

Developing flow–ecology relationships: Implications of nonlinear biological responses for water management

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Tackling unresolved questions in forest ecology: The past and future role of simulation models

1. Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations.
2. We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.
3. Using three widely applied but contrasting approaches – species distribution models, individual‐based forest models, and dynamic global vegetation models – as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
4. Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Forest models can help understanding the processes that shape forest functioning, structure and diversity, since they can can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations. Here we describe the development of three widely applied but contrasting forest mo−delling approaches — species distribution models, individual‐based models and dynamic global vegetation models. We provide an overview of recent model applications and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.     

西北干旱区河西走廊荒漠绿洲土地覆盖类型与蒸散的关系研究——基于Landsat 8和ZY3数据融合

蒸散是地表水热平衡的重要分量,也是陆地生态过程与水文过程之间的重要纽带,尤其在干旱区地-气相互作用、碳循环、水循环等过程所包含的物质与能量交换中占有极其重要的地位。基于Landsat 8遥感影像和资源三号影像(ZY3)的高分辨率植被信息,利用SEBS模型对西北干旱区河西走廊中段临泽绿洲北部区域地表蒸散量进行了估算,并用绿洲内部和绿洲-荒漠过渡带两个通量塔涡动相关数据对模型进行评估,分析了不同土地覆盖类型对蒸散量空间分布的影响。结果表明:(1)SEBS模型模拟值与实测日蒸散值之间拟合效果较好,且在均一地表时(绿洲农田区)估算精度更高(R~2=0.96,P0.001),RMSE、MAE分别为0.84 mm/d、0.56 mm/d;(2)从季节变化来看蒸散量与作物生长密切相关,夏季灌溉和降雨使得研究区水分充足,植被覆盖度高,蒸散量相应增加,在绿洲地区可达5.95 mm/d,而冬季最小仅为0.52 mm/d;(3)从蒸散量的空间变化来看,水体蒸散值最大,其余依次为农田、防护林、裸地和灌木丛,说明除水体外,随着植被覆盖的增大,蒸散量也逐渐增加。通过ZY3影像的高分辨率植被信息与Landsat 8影像热红外数据融合,提高了SEBS模型对该区域蒸散量的模拟效果,增进了我们对绿洲下垫面与大气间水热交换规律、水文过程、生态-水文相互作用的深入理解。     

Similarity between contemporary vegetation and plant remains in the surface sediment in Mediterranean lakes

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Diet composition of the Eurasian otter Lutra lutra in different freshwater habitats of temperate Europe: a review and meta‐analysis

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Are the landscape‐level drivers of water column and surface sediment diatoms different?

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Functional classifications and their application in phytoplankton ecology

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Classification of vegetation in the Western Australian wheatbelt using Landsat MSS data

We examined the use of Landsat multispectral scanner (MSS) data to provide preliminary information on broad vegetation types present within nature reserves in the wheatbelt region of Western Australia. We analysed Landsat data for an area of natural vegetation for which ground survey and aerial photographic data are available. We used canonical variate analysis to examine the degree of spectral separation between training sites selected in the main structural vegetation types. The training classes were then grouped into spectral classes and an allocation procedure used to map the pixels in the reserve into these classes. The analysis provided a good correspondence between spectral classes and broad vegetation types recognised from aerial photography, but did not discriminate between differences in dominant species (e.g. between different types of Eucalypt woodland). The classification derived from the study reserve was then applied successfully to two nearby reserves, indicating that the data can be used to provide initial information on the broad vegetation types present in wheatbelt reserves, although it is not suitable for finer resolution studies.Abbreviation MSS = Multi-spectral scanner     

How good are Bayesian belief networks for environmental management? A test with data from an agricultural river catchment

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Heterogeneous flows foster heterogeneous assemblages: relationships between functional diversity and hydrological heterogeneity in riparian plant communities

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A critical analysis of regulated river ecosystem responses to managed environmental flows from reservoirs

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Successional changes in the soft-water macrophyte vegetation of (sub)atlantic, sandy, lowland regions during this century

SUMMARY.

• 1 Considerable changes in macrophyte vegetation can be noticed in 146 originally soft waters, when data on the recent aquatic vegetation are compared with historical information from the period 1900–60. Changes in nutrient status (N, P and C) and accumulation of organic material can be regarded as the operative factors.
• 2 The processes observed in soft waters are acidification, eutrophication and water hardening. Which process dominates depends on the type of soft water.
• 3 Acidification as well as eutrophication of water bodies may ultimately result in the total disappearance of all aquatic macrophytes, with the exception of the floating-leaved nymphaeids Nymphaea alba L. and Nuphar lutea (L.) Sm. Observed successional stages are described and summarized.

     

Inferring species interactions from ecological survey data: A mechanistic approach to predict quantitative food webs of seed feeding by carabid beetles

1. Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, for example, predation, are short‐lived and difficult to observe or detect. While there are different methods for inferring the presence of interactions, they have rarely been used to predict the interaction strengths that are required to construct weighted, or quantitative, ecological networks.
2. Here, we develop a trait‐based approach suitable for inferring weighted networks, that is, with varying interaction strengths. We developed the method for seed‐feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other species and types of interaction.
3. Using existing literature data from experimental seed‐feeding trials, we predicted a per‐individual interaction cost index based on carabid and seed size. This was scaled up to the population level to create inferred weighted networks using the abundance of carabids and seeds from empirical samples and energetic intake rates of carabids from the literature. From these weighted networks, we also derived a novel measure of expected predation pressure per seed type per network.
4. This method was applied to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how network structure and predation pressure varied among fields.
5. Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This permits ecological network analysis even at times and in places when interactions were not directly assessed.

     

Large‐scale environmental flow results in mixed outcomes with short‐term benefits for a semi‐arid floodplain plant community

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Habitat preferences of ungulates in closed savanna of central Africa

Habitat preferences of fifteen species of ungulate were studied between July and September 1975 in dry savanna woodland of Mwabvi Game Reserve, Southern Malawi, Central Africa. Thirteen vegetation types were recognized using vegetation transects and plotless sampling techniques (but three of these are omitted from further analysis here either because of the difficulty of sampling in a representative manner or because of their infrequency). A combination of six methods was used to study habitat preferences since each had particular advantages or disadvantages, although quadrat sampling of fresh pellets/spoor counts was the most satisfactory and so used predominantly. The most common and widely distributed species was the Greater kudu, although abundance estimates in different habitats varied according to the method used. Pellet/spoor counts showed heavy use of open grassland by kudu which was not detected by daytime drives. Temporal patterns of activity indicated that the species was moving into more closed woodland during the day and only coming out into open grassland at night. Relative abundance estimates of a species may also be affected by changing group size. The mean group size of kudu increased in more open vegetation, although group size in warthog did not show this relationship. Some species, e.g. impala, reedbuck, and klipspringer showed narrow habitat preferences, occurring in only one or a few vegetation types, whilst others, e.g. kudu, sable, duiker, suni, and grysbok showed much broader preferences. Mixed Colophospermum mopane /Acacia woodland had the highest species diversity but rather low abundance. Open grassland and Acacia/Albizia woodland had high species diversity together with the greatest abundance of ungulates. Open Julbernardia/Diplorynchus, Brachystegia/Julber-nardia woodland, and particularly Pterocarpus/Diplorynchus/Combretum hill woodland had the lowest species diversity and abundance of ungulates. Ready access to cover and availability of suitable food plants probably account for the preferences of certain vegetation types over others, whilst the different behavioural ecology and food preferences of each species account for individual species differences. Access to water probably also determines habitat preferences in particular species, and studies during the wet season may show different distributions.     

Numeric classification as an aid to spectral mapping of vegetation communities

This study demonstrates a vegetation mapping methodology that relates the reflectance information contained in multispectral imagery to traditionally accepted ecological classifications. Key elements of the approach used are (a) the use of cover rather than density or presence/absence to quantify the vegetation, (b) the inclusion of physical components as well as vegetation cover to describe and classify field sites, (c) development of an objective land cover classification from this quantitative data, (d) use of the field sample sites as training areas for the spectral classification, and (e) the use of a discriminant function to effectively tie the two classifications together. Land cover over 39000 ha of Australian chenopod shrubland was classified into nine groups using agglomerative hierarchical clustering, a discriminant function developed to relate cover and spectral classes, and the vegetation mapped using a maximum likelihood classification of multi-date Landsat TM imagery. The accuracy of the mapping was assessed with an independent set of field samples and by comparison with a map of land systems previously interpreted from aerial photography. Overall agreement between the digital classification and the land system map was good. The units that have been mapped are those derived from numeric vegetation classification, demonstrating that accepted ecological methods and sound image analysis can be successfully combined.     

Floodplain ecosystem dynamics under extreme dry and wet phases in semi‐arid Australia

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