Airborne hyperspectral data predict Ellenberg indicator values for nutrient and moisture availability in dry grazed grasslands within a local agricultural landscape

Species-based ecological indices, such as Ellenberg indicators, reflect plant habitat preferences and can be used to describe local environment conditions. One disadvantage of using vegetation data as a substitute for environmental data is the fact that extensive floristic sampling can usually only be carried out at a plot scale within limited geographical areas. Remotely sensed data have the potential to provide information on fine-scale vegetation properties over large areas. In the present study, we examine whether airborne hyperspectral remote sensing can be used to predict Ellenberg nutrient (N) and moisture (M) values in plots in dry grazed grasslands within a local agricultural landscape in southern Sweden. We compare the prediction accuracy of three categories of model: (I) models based on predefined vegetation indices (VIs), (II) models based on waveband-selected VIs, and (III) models based on the full set of hyperspectral wavebands. We also identify the optimal combination of wavebands for the prediction of Ellenberg values. The floristic composition of 104 (4 m × 4 m grassland) plots on the Baltic island of Öland was surveyed in the field, and the vascular plant species recorded in the plots were assigned Ellenberg indicator values for N and M. A community-weighted mean value was calculated for N (mN) and M (mM) within each plot. Hyperspectral data were extracted from an 8 m × 8 m pixel window centred on each plot. The relationship between field-observed and predicted mean Ellenberg values was significant for all three categories of prediction models. The performance of the category II and III models was comparable, and they gave lower prediction errors and higher R² values than the category I models for both mN and mM. Visible and near-infrared wavebands were important for the prediction of both mN and mM, and shortwave infrared wavebands were also important for the prediction of mM. We conclude that airborne hyperspectral remote sensing can detect spectral differences in vegetation between grassland plots characterised by different mean Ellenberg N and M values, and that remote sensing technology can potentially be used to survey fine-scale variation in environmental conditions within a local agricultural landscape.     

Reliability of Ellenberg indicator values for moisture,nitrogen and soil reaction: a comparison with field measurements

Abstract. Ellenberg indicator values for moisture, nitrogen and soil reaction were correlated with measured soil and vegetation parameters. Relationships were studied through between‐species and between‐site comparisons, using data from 74 roadside plots in 14 different plant communities in The Netherlands forming a wide range. Ellenberg moisture values correlated best with the average lowest moisture contents in summer. Correlations with the annual average groundwater level and the average spring level were also good. Ellenberg N‐values appeared to be only weakly correlated with soil parameters, including N‐mineralization and available mineral N. Instead, there was a strong relation with biomass production. We therefore endorse Hill & Carey's (1997) suggestion that the term N‐values be replaced by ‘productivity values'. For soil reaction, many species values appeared to need regional adjustment. The relationship with soil pH was unsatisfactory; mean indicator values were similar for all sites at pH > 4.75 because of wide species tolerances for intermediate pH levels. Site mean reaction values correlated best (r up to 0.92) with the total amount of calcium (exchangeable Ca²⁺ plus Ca from carbonates). It is therefore suggested that reaction values are better referred to as ‘calcium values'. Using abundance values as weights when calculating mean indicator values generally improved the results, but, over the wide range of conditions studied, differences were small. Indicator values for bryophytes appeared well in line with those for vascular plants. It was noted that the frequency distributions of indicator values are quite uneven. This creates a tendency for site mean values to converge to the value most common in the regional species pool. Although the effect on overall correlations is small, relationships tended to be less linear. Uneven distributions also cause the site mean indicator values at which species have their optimum to deviate from the actual Ellenberg values of these species. Suggestions for improvements are made. It is concluded that the Ellenberg indicator system provides a very valuable tool for habitat calibration, provided the appropriate parameters are considered.     

Modelling the presence of anchovy Engraulis encrasicolus in the Aegean Sea during early summer, based on satellite environmental data

Acoustic and satellite environmental data as well as bathymetry data were used to model the presence of anchovy, Engraulis encrasicolus during early summer in the northern Aegean Sea (Eastern Mediterranean). Generalized Additive Models (GAMs) were used for modelling and subsequently applied in a predictive mode to identify those areas in the Greek Seas and the entire Mediterranean basin that could support species’ presence. Model results were evaluated with the estimation of Receiver Operating Characteristic (ROC)-plots as well as qualitatively, based on (a) acoustic data from concurrent studies in certain areas of the northern Aegean Sea that were not included in the estimation of the GAM model and (b) historical acoustic data from the central Aegean and Ionian Seas. Mapping the estimated environmental conditions in the Mediterranean basin indicated areas that generally agree with the known distribution grounds of anchovy, such as the straits of Sicily and coastal waters of Tunisia, areas in the Tyrrhenian Sea, the Adriatic Sea, the Gulf of Lions and the Catalan Sea. Guest editor: V. D. Valavanis Essential Fish Habitat Mapping in the Mediterranean     

Nutrient availability and nutrient use efficiency in plants growing in the transition zone between land and water

The transition zone between terrestrial and freshwater habitats is highly dynamic, with large variability in environmental characteristics. Here, we investigate how these characteristics influence the nutritional status and performance of plant life forms inhabiting this zone. Specifically, we hypothesised that: (i) tissue nutrient content differs among submerged, amphibious and terrestrial species, with higher content in submerged species; and (ii) PNUE gradually increases from submerged over amphibious to terrestrial species, reflecting differences in the availability of N and P relative to inorganic C across the land–water ecotone. We found that tissue nutrient content was generally higher in submerged species and C:N and C:P ratios indicated that content was limiting for growth for ca. 20% of plant individuals, particularly those belonging to amphibious and terrestrial species groups. As predicted, the PNUE increased from submerged over amphibious to terrestrial species. We suggest that this pattern reflects that amphibious and terrestrial species allocate proportionally more nutrients into processes of importance for photosynthesis at saturating CO₂ availability, i.e. enzymes involved in substrate regeneration, compared to submerged species that are acclimated to lower availability of CO₂ in the aquatic environment. Our results indicate that enhanced nutrient loading may affect relative abundance of the three species groups in the land–water ecotone of stream ecosystems. Thus, species of amphibious and terrestrial species groups are likely to benefit more from enhanced nutrient availability in terms of faster growth compared to aquatic species, and that this can be detrimental to aquatic species growing in the land–water ecotone, e.g. Ranunculus and Callitriche.     

龙感湖沉积物泥芯硅藻群落和营养状态的反演

The importance of aquatic vegetation to the ecologi-cal restoration has been recognized commonly bylimnolo-gists and lake managements[1—4].As to the ecologicalrestoration in eutrophicated lakes,it is of great signifi-cance to knowthe dynamic process of the ecosystemevo-lution in a macrophyte-dominated lake under the humanimpacts in historical period,to make it clear whether thecommunitystructure and ecological function would be af-fected bythe extension of the vegetation growth,tofind asolutionto remain ste...     

Changes in vegetation types and Ellenberg indicator values after 65 years of fertilizer application in the Rengen Grassland Experiment,Germany

Question: How does semi-natural grassland diversify after 65 years of differential application of Ca, N, P, and K fertilizers? Is fertilizer application adequately reflected by the Ellenberg indicator values (EIVs)? Location: Eifel Mountains, West Germany. Methods: The Rengen Grassland Experiment (RGE) was established in an oligotrophic grassland in 1941. Six fertilizer treatments (Ca, CaN, CaNP, CaNP-KCl, CaNP-K₂SO₄, and unfertilized control) were applied annually in five complete randomized blocks. Species composition of experimental plots was sampled in 2006 and compared with constancy tables representing grassland types in a phytosociological monograph of a wider area. Each plot was matched to the most similar community type using the Associa method. Mean EIVs were calculated for each treatment. Results: The control plots supported oligotrophic Nardus grassland of the Polygalo-Nardetum association (Violion caninae alliance). Vegetation in the Ca and CaN treatments mostly resembled montane meadow of Geranio-Trisetetum (Polygono-Trisetion). Transitional types between Poo-Trisetetum and Arrhenatheretum (both from the Arrhenatherion alliance) developed in the CaNP treatment. In the CaNP-KCl and CaNP-K₂SO₄ treatments, vegetation corresponded to the mesotrophic Arrhenatheretum meadow. Major discontinuity in species composition was found between control, Ca, and CaN treatments, and all treatments with P application. EIVs for both nutrients and soil reaction were considerably higher in P treatments than in Ca and CaN treatments. Surprisingly, the control plots had the lowest EIVs for continentality and moisture, although these factors had not been manipulated in the experiment. Conclusions: Long-term fertilizer application can create different plant communities belonging to different phytosociological alliances and classes, even within a distance of a few meters. Due to their correlated nature, EIVs can erroneously indicate changes in factors that actually did not change, but co-varied with factors that did change. In P-limited ecosystems, EIVs for nutrients may indicate availability of P rather than N.     

Distribution of algae in the San Joaquin River, California, in relation to nutrient supply, salinity and other environmental factors

1. The taxonomic composition and biomass of the phytoplankton and the taxonomic composition of the phytobenthos of the San Joaquin River and its major tributaries were examined in relation to water chemistry, habitat and flow regime. Agricultural drainage and subsurface flow contribute to a complex gradient of salinity and nutrients in this eutrophic, ‘lowland type’ river. 2. Because of light‐limiting conditions for growth, maintenance demands of the algae exceed production during summer and autumn in the San Joaquin River where there is no inflow from tributaries. In contrast to substantial gains in concentration of inorganic nitrogen and soluble reactive phosphorus during the summer of normal‐flow years, net losses of algal biomass (2–4 μg L^?1 day^?1 chlorophyll a) occurred in a mid‐river segment with no significant tributary inflow. However, downstream of a large tributary draining the Sierra Nevada, a substantial net gain in algal biomass (6–11 μg L^?1 day^?1) occurred in the summer, but not in the spring (loss of 1–6 μg L^?1 day^?1) or autumn (loss of 2–5 μg L^?1 day^?1). 3. The phytoplankton was dominated in summer by ‘r‐selected’ centric diatoms (Thalassiosirales), species both tolerant of variable salinity and widely distributed in the San Joaquin River. Pennate diatoms were proportionally more abundant (in biomass) in the winter, spring and autumn. Abundant taxa included the diatoms Cyclotella meneghiniana, Skeletonema cf. potamos, Cyclostephanos invisitatus, Thalassiosira weissflogii, Nitzschia acicularis, N. palea and N. reversa, and the chlorophytes Chlamydomonas sp. and Scenesdesmus quadricauda. Patterns in the abundance of species indicated that assembly of the phytoplankton is limited more by light and flow regime than by nutrient supply. 4. The phytobenthos was dominated by larger, more slowly reproducing pennate diatoms. Few of the abundant species are euryhaline. The diatoms Navicula recens and Nitzschia inconspicua and cyanophytes, Oscillatoria spp., were the principal late‐summer benthic species upstream in the mainstem and in drainages of the San Joaquin Valley. Many of the other abundant diatoms (Amphora veneta, Bacillaria paxillifer, Navicula symmetrica, Nitzschia amphibia, N. fonticola, N. palea, Pleurosigma salinarum) of late‐summer assemblages in these segments also are motile species. While many of these species also were abundant in segments downstream of confluences with rivers draining the Sierra Nevada, the relative abundance of prostrate (Cocconeis placentula var. euglypta, Navicula minima) and erect or stalked (Achnanthidium deflexum, Achnanthes lanceolata, Gomphonema kobayasii, G. parvulum var. lagenula) diatoms and Stigeoclonium sp. was greater in these lower San Joaquin River segments. 5. A weighted‐averaging regression model, based on salinity and benthic‐algal abundance in the San Joaquin River and segments of its major tributaries within the San Joaquin Valley, yielded a highly significant coefficient‐of‐determination (r²=0.84) and low prediction error between salinity inferred from the species and that observed, indicating that salinity tolerance is a primary constraint on growth and assembly of the phytobenthos. The same measures of predictability indicated poor performance of a model based on inorganic nitrogen. However, with a greater representation of tributaries (including segments within the Sierra Nevada foothills) in the sample set, an inorganic nitrogen model also yielded a highly significant coefficient‐of‐determination (r²=0.87) and low prediction error between the species‐inferred and the observed concentration. As with the salinity model (r²=0.94) for the enlarged data set, a systematic difference (increased deviation of residuals) existed at high inorganic nitrogen concentrations. These results indicate substantial interaction between salinity and inorganic nitrogen as constraints on the structure of benthic‐algal communities of the San Joaquin River basin.     

The Use of Geographic Information Systems, Remote Sensing, and Suitability Modeling to Identify Conifer Restoration Sites with High Biological Potential for Anadromous Fish at the Cedar River Municipal Watershed in Western Washington, U.S.A.

We developed a methodology integrating several forms of remotely sensed data into a Geographic Information Systems (GIS) model that identifies suitable sites for riparian conifer restoration at the Cedar River Municipal Watershed in western Washington, U.S.A. The model integrates vegetative and geomorphic variables with information on the habitat preferences of anadromous fishes to identify riparian stands where conifer restoration would have the greatest biological benefit for salmon recovery. The high-resolution raster datasets used in our analysis were capable of characterizing the biophysical attributes of riparian areas at finer spatial scales than was previously possible. This model is intended to serve as a screening tool to identify candidate sites for riparian area restoration. The assessment approach described in this study can be applied not only to model salmonid habitat at the watershed scale but also to assess landscape patterns relevant to a wide range of restoration goals. This methodological framework offers several advantages over other approaches to restoration site selection and planning. First, the fine-scale spatial resolution of the GIS datasets (pixels ≤5 m) used in the model provides a more accurate representation of the habitat conditions than has been possible with coarser-scale data (pixels ≥5 m). Therefore, the accuracy of site identification is greatly improved. Second, the quantitative nature of the model exercises greater objectivity than some other landscape-scale planning approaches. This regional planning tool could be replicated in other watersheds with comparable datasets and could be applied to identify habitat restoration sites for other species or guilds of species by simply altering the model criteria to match the habitat needs of the target organisms.     

Relating postglacial relict plants and Holocene vegetation dynamics in the Balearic Islands through field surveys,pollen analysis and GIS modeling

Abstract

An inventory of the current Balearic plants occurring in mesophyllous environments, with climatic conditions similar to those in the first half of the Holocene, was compiled. The presence of these floristic elements, extending mainly into the postglacial time, has been related to pollen records of different localities in the Balearic Islands. GIS techniques have been applied in order to map the past and the present-day vegetation suitability of some of these mesophyllous species using pollen surface samples, forest inventory data and Digital Climatic Models. We integrated the information provided by field survey, pollen records and suitability mapping in order to discuss the vegetation dynamics of different habitats. We focused on the nature and the possible causes of the vegetation landscape change that occurred approximately 5000 – 6000 uncal. years BP, when Fagus, Corylus and Buxus formations were replaced by xeric-type formations with Olea dominance.     

百花山国家级自然保护区褐马鸡栖息地利用分析

栖息地破坏是生物多样性丧失的主要原因之一,对濒危物种的生存也构成严重威胁。褐马鸡(Crossoptilon mantchuricum)作为我国特有珍稀濒危物种,目前仅分布于山西、陕西、河北和北京地区。2013年10月至2014年6月,在北京百花山国家级自然保护区使用样线法进行野外调查,使用存在点与伪不存在点数据,结合海拔、坡度、坡向、距道路距离、距居民点距离和植被类型作为变量,运用CART、Random Forest、Tree Net三个机器学习模型对褐马鸡的上述6种栖息地因子重要性排序,结果显示,海拔是影响褐马鸡分布的最主要因子,其次是植被类型、距道路距离和距居民点距离。根据AUC值选择Tree Net模型为最适宜模型,划分褐马鸡的适宜栖息地类型,并计算适宜面积。本研究有助于了解重点栖息因子对北京地区褐马鸡的影响状况,利于褐马鸡保护管理对策的制定。     

From quantal counts to mechanisms and systems: the past, present, and future of biometrics in environmental toxicology

As appreciation for human impact on the environment has developed, so have the experimental systems and associated statistical tools that quantify this impact. Toxicological study in particular has grown in its complexity and its need for advanced statistical support. Within this perspective, we describe statistical practice in environmental toxicology and risk assessment. We present two case studies, one from mammalian toxicology and one from aquatic toxicology, that highlight the evolution of statistical practice in environmental toxicology.