Relationship of fish and macroinvertebrate communities in the mid-Atlantic uplands: Implications for integrated assessments

Indices developed for stream bioassessment are typically based on either fish or macroinvertebrate assemblages. These indices consist of metrics which subsume attributes of various species into aggregate measures reflecting community-level ecological responses to disturbance. However, little is known about the relationship between fish and macroinvertebrate metrics, or about how ecological health assessments are affected by assemblage-specific responses to disturbance. We used principal component analysis (PCA) and regression analysis of existing fish (n = 371) and macroinvertebrate (n = 442) stream bioassessment data from a multi-source dataset to determine broad scale, within-assemblage metric patterns, and to examine the intercorrelation of fish and macroinvertebrate metrics (n = 246) and their response to watershed area and land use/land cover gradients. Fish and macroinvertebrate metrics expressed as principal components (PCs) accounted for 72.4 and 85.4% of dataset variance, respectively, with PC-metric patterns reflecting aspects of stream impairment including water and habitat quality. Model components predicting fish metric response differed among fish PCs, with watershed area and macroinvertebrate metric response strongly correlated with the first fish PC, and remaining fish PC models consisting of watershed area, land use, and macroinvertebrate PCs. Correlation between fish and macroinvertebrate PCs, and models relating fish and macroinvertebrate PCs generally explained less variation (13–27%) than metric response models of fish (25–34%) and macroinvertebrates (8–38%) to watershed area and land use/land cover variables. Best-response models integrating fish and macroinvertebrate PCs, watershed area, and land use/land cover variables accounted for the greatest variation in fish PCs (32–50%) across sites. Because fish and macroinvertebrate metrics provide different information on ecological condition, integrated use of information from multiple groups may be appropriate when developing monitoring programs.     

Effects of urban and non-urban land cover on nitrogen and phosphorus runoff to Chesapeake Bay

The aim of this study was to determine the effects of catchment and riparian stream buffer-wide urban and non-urban land cover/land use (LC/LU) on total nitrogen (TN) and total phosphorus (TP) runoff to the Chesapeake Bay. The effects of the composition and configuration of LC/LU patches were explored in particular. A hybrid-statistical-process model, the SPAtially Referenced Regression On Watershed attributes (SPARROW), was calibrated with year 1997 watershed-wide, average annual TN and TP discharges to Chesapeake Bay. Two variables were predicted: (1) yield per unit watershed area and (2) mass delivered to the upper estuary. The 166,534 km² watershed was divided into 2339 catchments averaging 71 km². LC/LU was described using 16 classes applied to both the catchments and also to riparian stream buffers alone. Seven distinct landscape metrics were evaluated. In all, 167 (TN) and 168 (TP) LC/LU class metric combinations were tested in each model calibration run. Runs were made with LC/LU in six fixed riparian buffer widths (31, 62, 125, 250, 500, and 1000 meters (m)) and entire catchments. The significance of the non-point source type (land cover, manure and fertilizer application, and atmospheric deposition) and factors affecting land-to-water delivery (physiographic province and natural or artificial land surfaces) was assessed. The model with a 31 m riparian stream buffer width accounted for the highest variance of mean annual TN (r² = 0.9366) and TP (r² = 0.7503) yield (mass for a specified time normalized by drainage area). TN and TP loadings (mass for a specified time) entering the Chesapeake Bay were estimated to be 1.449 × 10⁸ and 5.367 × 10⁶ kg/yr, respectively. Five of the 167 TN and three of the 168 TP landscape metrics were shown to be significant (p-value ≤ 0.05) either for non-point sources or land-to-water delivery variables. This is the first demonstration of the significance of riparian LC/LU and landscape metrics on water quality simulation in a watershed as large as the Chesapeake Bay. Land cover metrics can therefore be expected to improve the precision of estimated TN and TP annual loadings to the Chesapeake Bay and may also suggest changes in land management that may be beneficial in control of nutrient runoff to the Chesapeake Bay and similar watersheds elsewhere.     

A multivariate analysis integrating ecological,socioeconomic and physical characteristics to investigate urban forest cover and plant diversity in Beijing,China

Understanding the factors driving the variation in urban green space and plant communities in heterogeneous urban landscapes is crucial for maintaining biodiversity and important ecosystem services. In this study, we used a combination of field surveys, remote sensing, census data and spatial analysis to investigate the interrelationships among geographical and social-economic variables across 328 different urban structural units (USUs) and how they may influence the distributions of urban forest cover, plant diversity and abundance, within the central urban area of Beijing, China. We found that the urban green space coverage varied substantially across different types of USUs, with higher in agricultural lands (N = 15), parks (N = 46) and lowest in utility zones (N = 36). The amount of urban green space within USUs declines exponentially with the distance to urban center. Our study suggested that geographical, social and economic factors were closely related with each other in urban ecological systems, and have important impacts on urban forest coverage and abundance. The percentage of forest as well as high and low density urban areas were mainly responsible for variations in the data across all USUs and all land use/land cover types, and thus are important constituents and ecological indicators for understanding and modeling urban environment. Herb richness is more strongly correlated with tree and shrub density than with tree and shrub richness (r = −0.472, p < 0.05). However, other geographic and socioeconomic factors showed no significant relationships with urban plant diversity or abundance.     

Bio-thermal effects of open dumps on surroundings detected by remote sensing—Influence of geographical conditions

This study has used remotely sensed data of Landsat-8 for monitoring open dumps of Municipal Solid Waste (MSW) using vegetation health as a bio-indicator and thermal emissions from it. Open dump of Mahmood Booti has been found to affect the surrounding vegetation up to 800 m in dry summers and reducing to 400 m in winters, while averaging to a distance of about 650 m. Average thermal influence zone has been observed to have same radial extent of about 650 m varying between the minimum of 350 m in dry summer and maximum of 1000 m in winter. All the corresponding details of bio-indicators and temperature variations have also been discussed. In addition to this, the results and methodology of spatial analysis for Mahmood Booti dump of Lahore, Pakistan, surrounded by a heterogeneous land cover, have been compared with the main dumping facility of Faisalabad, Pakistan, which is surrounded by a homogeneous vegetation cover all around. This comparison yielded two main conclusions, first, the surrounding geography of an open MSW dump affects the severity of bio-thermal effects, in addition to waste age, characterization, pile etc. Second, GIS analysis for studying bio-thermal effects requires modification that varies for prevailing neighborhood land cover conditions of MSW open dumps. Use of remotely sensed data for monitoring dumped MSW is a good alternative but selection of proper GIS methodology, representing natural setting of phenomena is equally important as that of the accuracy of the remotely sensed data.     

Impact of landscape pattern at multiple spatial scales on water quality: A case study in a typical urbanised watershed in China

Buffer zones along rivers and streams can provide water quality services by filtering nutrients, sediment and other contaminants from the surface. Redundancy analysis was used to determine the influence of the landscape pattern at the entire catchment scale and at multiple buffer zone scales (100 m, 300 m, 500 m, 1000 m and 1500 m) on the water quality in a highly urbanised watershed. Change-point analysis was further applied to estimate the specific locations along a gradient of landscape metric that result in a sudden change in the water quality variable. The landscape characteristics for 100 m buffer zones appeared to have a slightly greater influence on the water quality than the entire catchment. The patch density of urban land and the large patch index of water were recognised as the dominant variables influencing the water quality for a 100 m buffer zone. The result of change-point analysis indicated key interval values of the two landscape metrics within the 100 m buffer zone. When the patch density of urban land was >30–40 n/100 ha and the largest patch index of water was >2.5–3.5%, the watershed water quality appeared to be better protected.     

Vegetation mapping and multivariate approach to indicator species of a forest ecosystem: A case study from the Thandiani sub Forests Division (TsFD) in the Western Himalayas

QuestionsDoes the plant species composition of Thandiani sub Forests Division (TsFD) correlate with edaphic, topographic and climatic variables? Is it possible to identify different plant communities in relation to environmental gradients with special emphasis on indicator species? Can this approach to vegetation classification support conservation planning?LocationThandiani sub Forests Division, Western Himalayas.MethodsQuantitative and qualitative characteristics of species along with environmental variables were measured using a randomly stratified design to identify the major plant communities and indicator species of the Thandiani sub Forests Division. Species composition was recorded in 10 × 2.5 × 2 and 0.5 × 0.5 m square plots for trees, shrubs and herbs, respectively. GPS, edaphic and topographic data were also recorded for each sample plot. A total of 1500 quadrats were established in 50 sampling stations along eight altitudinal transects encompassing eastern, western, northern and southern aspects (slopes). The altitudinal range of the study area was 1290 m to 2626 m above sea level using. The relationships between species composition and environmental variables were analyzed using Two Way Cluster Analysis (TWCA) and Indicator Species Analysis (ISA) via PCORD version 5.ResultsA total of 252 plant species belonging to 97 families were identified. TWCA and ISA recognized five plant communities. ISA additionally revealed that mountain slope aspect, soil pH and soil electrical conductivity were the strongest environmental factors (p ≤ 0.05) determining plant community composition and indicator species in each habitat. The results also show the strength of the environment-species relationship using Monte Carlo procedures.ConclusionsAn analysis of vegetation along an environmental gradient in the Thandiani sub Forests Division using the Braun-Blanquet approach confirmed by robust tools of multivariate statistics identified indicators of each sort of microclimatic zones/vegetation communities which could further be used in conservation planning and management not only in the area studied but in the adjacent regions exhibit similar sort of environmental conditions.     

Analysis of a volumetric-modulated arc therapy (VMAT) single phase prostate template as a class solution

AimTo assess a class solution template for volumetric-modulated arc therapy (VMAT) for prostate cancer using plan analysis software.BackgroundVMAT is a development of intensity-modulated radiotherapy (IMRT) with potential advantages for the delivery of radiotherapy (RT) in prostate cancer. Class solutions are increasingly used for facilitating RT planning. Plan analysis software provides an objective tool for evaluating class solutions.Materials and methodsThe class solution for VMAT was based on the current static field IMRT template. The plans of 77 prostate cancer patients were evaluated using a set of in-house plan quality metrics (scores) (PlanIQ™, Sun Nuclear Corporation). The metrics compared the class solution for VMAT planning with the IMRT template and the delivered clinical plan (CP). Eight metrics were associated with target coverage and ten with organs-at-risk (OAR). Individual metrics were summed and the combined scores were subjected to non-parametric analysis. The low-dose wash for both static IMRT and VMAT plans were evaluated using 40 Gy and 25 Gy isodose volumes.ResultsVMAT plans were of equal or better quality than the IMRT template and CP for target coverage (combined score) and OAR combined score. The 40 Gy isodose volume was marginally higher with VMAT than IMRT (4.9%) but lower than CP (−6.6%)(P = 0.0074). The 25 Gy volume was significantly lower with VMAT than both IMRT (−32.7%) and CP (−34.4%)(P < 0.00001).ConclusionsAutomated VMAT planning for prostate cancer is feasible and the plans are equal to or better than the current IMRT class solution and the delivered clinical plan.     

Evaluation of automatic image quality assessment in chest CT – A human cadaver study

PurposeThe evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers.MethodsChest CT’s of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized.ResultsGood correlations were found between IQs and the measured physical-technical image quality: noise (ρ = −1.00), contrast-to-noise (ρ = 1.00) and contrast-detail (ρ = 0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively.ConclusionsThe automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs.     

Using algal metrics and biomass to evaluate multiple ways of defining concentration-based nutrient criteria in streams and their ecological relevance

We examined the utility of nutrient criteria derived solely from total phosphorus (TP) concentrations in streams (regression models and percentile distributions) and evaluated their ecological relevance to diatom and algal biomass responses. We used a variety of statistics to characterize ecological responses and to develop concentration-based nutrient criteria (derived from ecological effects) for streams in Connecticut, USA, where urbanization is the primary cause of watershed alteration. Mean background TP concentration in the absence of anthropogenic land cover was predicted to be 0.017 mg/l, which was similar to the 25th percentile of all study sites. Increased TP concentrations were significantly correlated with altered diatom community structure, decreased percent low P diatoms and diatoms sensitive to impervious cover, and increased percent high P diatoms, diatoms that increase with greater impervious cover, and chlorophyll a (P < 0.01). Variance partitioning models showed that shared effects of anthropogenic land cover and chemistry (i.e., chemistry affected by land cover) represented the majority of explained variation in diatom metrics and chlorophyll a. Bootstrapped regression trees, threshold indicator taxa analysis, and boosted regression trees identified TP concentrations at which strong responses of diatom metrics and communities occurred, but these values varied among analyses. When considering ecological responses, scientifically defensible and ecologically relevant TP criteria were identified at (1) 0.020 mg/l for designating highest quality streams and restoration targets, above which sensitive taxa steeply declined, tolerant taxa increased, and community structure changed, (2) 0.040 mg/l, at which community level change points began to occur and sensitive diatoms were greatly reduced, (3) 0.065 mg/l, above which most sensitive diatoms were lost and tolerant diatoms steeply increased to their maxima, and (4) 0.082 mg/l, which appeared to be a saturated threshold, beyond which substantially altered community structure was sustained. These criteria can inform anti-degradation policies for high quality streams, discharge permit decisions, and future strategies for watershed development and managment. Our results indicated that management practices and decisions at the watershed scale will likely be important for improving degraded streams and conserving high quality streams. Results also emphasized the importance of incorporating ecological responses and considering the body of evidence from multiple conceptual approaches and statistical analyses for developing nutrient criteria, because solely relying on one approach could lead to misdirected decisions and resources.     

Extent estimates and land cover relationships for functional indicators in non-wadeable rivers

Functional indicators are being increasingly used to assess waterway health but their responses to pressure in non-wadeable rivers have not been widely documented or applied in modern survey designs that provide unbiased estimates of extent. This study tests the response of river metabolism and loss in cotton strip tensile strength across a land use pressure gradient in non-wadeable rivers of northern New Zealand, and reports extent estimates for river metabolism and decomposition rates. Following adjustment for probability of selection, ecosystem respiration (ER) and gross primary production (GPP) for the target population of order 5–7 non-wadeable rivers averaged −7.3 and 4.8 g O₂ m⁻² d⁻¹, respectively, with average P/R < 1 indicating dominance by heterotrophic processes. Ecosystem respiration was <−3.3 g O₂ m⁻² d⁻¹ for 75% of non-wadeable river length with around 20% of length between −10 and −20 g O₂ m⁻² d⁻¹. Cumulative distribution functions of cotton strength loss estimates indicated a more-or-less linear relationship with river km reflecting an even spread of decay rates (range in k 0.0007–0.2875 d⁻¹) across non-wadeable rivers regionally. A non-linear relationship with land cover was detected for GPP which was typically <5 g O₂ m⁻² d⁻¹ where natural vegetation cover was below 20% and greater than 80% of upstream catchment area. For cotton strength loss, the relationship with land cover was wedge-shaped such that sites with >60% natural cover had low decay rates (<0.02 d⁻¹) with variability below this increasing as natural cover declined. Using published criteria for assessing waterway health based on ER and GPP, 232–298 km (20–29%) of non-wadeable river length was considered to have severely impaired ecosystem functioning, and 436–530 km (42–50%) had no evidence of impact on river metabolism.     

Light thresholds derived from seagrass loss in the coastal zone of the northern Great Barrier Reef,Australia

There is a world-wide trend for deteriorating water quality and light levels in the coastal zone, and this has been linked to declines in seagrass abundance. Localized management of seagrass meadow health requires that water quality guidelines for meeting seagrass growth requirements are available. Tropical seagrass meadows are diverse and can be highly dynamic and we have used this dynamism to identify light thresholds in multi-specific meadows dominated by Halodule uninervis in the northern Great Barrier Reef, Australia. Seagrass cover was measured at ∼3 month intervals from 2008 to 2011 at three sites: Magnetic Island (MI) Dunk Island (DI) and Green Island (GI). Photosynthetically active radiation was continuously measured within the seagrass canopy, and three light metrics were derived. Complete seagrass loss occurred at MI and DI and at these sites changes in seagrass cover were correlated with the three light metrics. Mean daily irradiance (I_d) above 5 and 8.4 mol m⁻² d⁻¹ was associated with gains in seagrass at MI and DI, however a significant correlation (R = 0.649, p < 0.05) only occurred at MI. The second metric, percent of days below 3 mol m⁻² d⁻¹, correlated the most strongly (MI, R = −0.714, p < 0.01 and DI, R = −0.859, p = <0.001) with change in seagrass cover with 16–18% of days below 3 mol m⁻² d⁻¹ being associated with more than 50% seagrass loss. The third metric, the number of hours of light saturated irradiance (H_sat) was calculated using literature-derived data on saturating irradiance (E_k). H_sat correlated well (R = 0.686, p < 0.01; and DI, R = 0.704, p < 0.05) with change in seagrass abundance, and was very consistent between the two sites as 4 H_sat was associated with increases in seagrass abundance at both sites, and less than 4 H_sat with more than 50% loss. At the third site (GI), small seasonal losses of seagrass quickly recovered during the growth season and the light metrics did not correlate (p > 0.05) with change in percent cover, except for I_d which was always high, but correlated with change in seagrass cover. Although distinct light thresholds were observed, the departure from threshold values was also important. For example, light levels that are well below the thresholds resulted in more severe loss of seagrass than those just below the threshold. Environmental managers aiming to achieve optimal seagrass growth conditions can use these threshold light metrics as guidelines; however, other environmental conditions, including seasonally varying temperature and nutrient availability, will influence seagrass responses above and below these thresholds.     

Effect of time on consistent and repeatable macrophyte index for wetland condition

The vegetation portion of the Florida Wetland Condition Index (FWCI), an index of biological integrity, provided consistent and repeatable measures of condition at eighteen wetlands sampled in two consecutive growing seasons. The sample wetlands reflected a gradient of adjacent land use from non-impacted reference areas to wetlands imbedded within silviculture, cattle pasture and residential areas. Wetlands were described as herbaceous depression (n = 6), forested depression (n = 5) and forested strand or floodplain wetlands (n = 7), and represented different states of succession. Even though the wetlands were unique from one another and occurred across a large geographic area in Florida, the FWCI results calculated for all the wetlands were representative of adjacent land use impacts and not sensitive to natural variation. During the duration of this study, changes in weather from drought to tropical storm conditions, as well as management activities such as fire and herbivory, impacted wetlands. These effects were apparent in the change of species composition between sampling periods; 23–56% of species were different when resampled. Even though composition changed, the proportion of indicators remained consistent. The resulting condition scores suggested a one-to-one relationship between sampling periods.     

Anthropometric features and cutaneous melanoma risk: A prospective cohort study in French women

BackgroundEpidemiological studies on anthropometric features and cutaneous melanoma risk in women yielded inconsistent results, with few analyses involving prospective cohort data. Our objective was to explore several anthropometric characteristics in relation to the risk of melanoma in women.MethodsWe prospectively analysed data from E3N, a French cohort involving 98,995 women born in 1925–1950. Participants completed self-administered questionnaires sent biennially over 1990–2008. Relative risks (RRs) and 95% confidence intervals (CIs) were computed using Cox proportional hazards regression models, adjusted for age, number of naevi, freckling, skin and hair colour, skin sensitivity to sun exposure, residential sun exposure, and physical activity.ResultsHeight was positively associated with melanoma in age-adjusted models only (RR = 1.27, 95% CI = 1.05–1.55 for ≥164 cm vs. <160 cm; P for trend = 0.02). After full adjustment, there was a significantly positive relationship between sitting-to-standing height ratio and melanoma risk (RR = 1.40, 95% CI = 1.06–1.86 for ≥0.533 vs. <0.518; P for trend = 0.02). A large body shape at menarche was inversely associated with the risk of melanoma (RR = 0.78, 95% CI = 0.62–0.98; compared with lean). However, weight, body mass index, body surface area, waist or hip circumference, sitting height or leg length were not significantly associated with risk.ConclusionThese results suggest that height, sitting-to-standing height ratio and body shape at menarche may be associated with melanoma risk. Further research is required to confirm these relationships and better understand the underlying mechanisms.     

Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data

Reliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling.We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data.Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS- or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS- and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed.     

Landscape heterogeneity metrics as indicators of bird diversity: Determining the optimal spatial scales in different landscapes

Species distribution models are often used to study the biodiversity of ecosystems. The modelling process uses a number of parameters to predict others, such as the occurrence of determinate species, population size, habitat suitability or biodiversity. It is well known that the heterogeneity of landscapes can lead to changes in species’ abundance and biodiversity. However, landscape metrics depend on maps and spatial scales when it comes to undertaking a GIS analysis.We explored the goodness of fit of several models using the metrics of landscape heterogeneity and altitude as predictors of bird diversity in different landscapes and spatial scales. Two variables were used to describe biodiversity: bird richness and trophic level diversity, both of which were obtained from a breeding bird survey by means of point counts. The relationships between biodiversity and landscape metrics were compared using multiple linear regressions. All of the analyses were repeated for 14 different spatial scales and for cultivated, forest and grassland environments to determine the optimal spatial scale for each landscape typology.Our results revealed that the relationships between species’ richness and landscape heterogeneity using 1:10,000 land cover maps were strongest when working on a spatial scale up to a radius of 125–250 m around the sampled point (circa 4.9–19.6 ha). Furthermore, the correlation between measures of landscape heterogeneity and bird diversity was greater in grasslands than in cultivated or forested areas. The multi-spatial scale approach is useful for (a) assessing the accuracy of surrogates of bird diversity in different landscapes and (b) optimizing spatial model procedures for biodiversity mapping, mainly over extensive areas.     

Temporal stability of vegetation indicators of wetland condition

Vegetation indices are widely employed to evaluate wetland ecological condition, and are expected to provide sensitive and specific detection of environmental change. Most studies evaluate the performance of condition assessment metrics in the context of the data used to calibrate them. Here we examined the temporal stability of the Florida Wetland Condition Index (FWCI) for vegetation of depressional forested wetlands by resampling sites in 2008 that were previously sampled to develop the FWCI in 2001. Our objective was to determine if FWCI, a composite of six vegetation-based metrics, provides a robust measure of condition given inter-annual variation in environmental conditions (i.e., rainfall) between sampling periods. To that end, we sampled 22 geographically isolated wetlands in north Florida that spanned a wide land use/land cover intensity gradient. Our results suggested the FWCI is robust. We observed no significant paired difference in FWCI across or within land use categories, and the relationship between FWCI in 2001 and 2008 was strong (r² = 0.88, p < 0.001). This was despite surprisingly high composition change. Mean Jaccard community similarity within sites between years was 0.30, suggesting that most of the herbaceous taxa were replaced, possibly because of different antecedent rainfall conditions or sampling during different phenological periods; both are contingencies to which condition indices must be robust. We did observe some evidence of convergence toward the mean in 2008, with the fitted slope relating 2001 and 2008 FWCI scores significantly below one (0.63, 95% CI = 0.53–0.73). The most variable FWCI component metric was the proportional representation of obligate wetland taxa, suggesting that systematic changes may have been induced by different hydrologic conditions prior to sampling; notably, however, FWCI computed without this component still exhibited a slope significantly less than 1 (0.72, 95% CI = 0.61–0.88). Moreover, there was evidence that species lost from reference sites (higher condition) were replaced by taxa of lower floristic quality, while species lost from agricultural sites (consistently the lowest condition land use category) were replaced by species of higher quality. A significant positive association between FWCI and the ratio of coefficients of conservatism (CC) of species lost to those gained suggests some overfitting in FWCI development. However, despite modest evidence of overfitting, FWCI provides temporally consistent estimates of wetland condition, even under conditions of substantial taxonomic turnover.     

Measurement of stray neutron doses inside the treatment room from a proton pencil beam scanning system

PurposeTo measure the environmental doses from stray neutrons in the vicinity of a solid slab phantom as a function of beam energy, field size and modulation width, using the proton pencil beam scanning (PBS) technique.MethodMeasurements were carried out using two extended range WENDI-II rem-counters and three tissue equivalent proportional counters. Detectors were suitably placed at different distances around the RW3 slab phantom. Beam irradiation parameters were varied to cover the clinical ranges of proton beam energies (100–220 MeV), field sizes ((2 × 2)–(20 × 20) cm²) and modulation widths (0–15 cm).ResultsFor pristine proton peak irradiations, large variations of neutron H¹(10)/D were observed with changes in beam energy and field size, while these were less dependent on modulation widths. H¹(10)/D for pristine proton pencil beams varied between 0.04 μSv Gy⁻¹ at beam energy 100 MeV and a (2 × 2) cm² field at 2.25 m distance and 90° angle with respect to the beam axis, and 72.3 μSv Gy⁻¹ at beam energy 200 MeV and a (20 × 20) cm² field at 1 m distance along the beam axis.ConclusionsThe obtained results will be useful in benchmarking Monte Carlo calculations of proton radiotherapy in PBS mode and in estimating the exposure to stray radiation of the patient. Such estimates may be facilitated by the obtained best-fitted simple analytical formulae relating the stray neutron doses at points of interest with beam irradiation parameters.     

Performance of the Phytoplankton Index for Lakes (IPLAC): A multimetric phytoplankton index to assess the ecological status of water bodies in France

A new phytoplankton-based index was designed to respond to the Water Framework Directive (WFD) requirements concerning the assessment of lake ecological status. The “Indice Phytoplancton Lacustre” (IPLAC) is a multimetric index, taking into account biomass, abundance and species composition of communities. The first metric is based on the total phytoplankton biomass (MBA), the second on the abundance and taxonomic composition (MCS) of 165 indicator taxa. The IPLAC was developed on 2 independent databases, one for the calibration and the second for the validation of the metrics. The calibration dataset was composed of 255 “lake-years” from 214 distinct lakes sampled between 2005 and 2012. The validation dataset included 173 lake-years in order to confirm the response of the index to the trophic gradient and anthropogenic pressure.The results show that the IPLAC correctly highlights chemical pressure (eutrophication). Especially high Pearson correlations are shown with total phosphorus (r = −0.71, p-value <0.001), chlorophyll-a (r = −0.83, p-value <0.001) and water transparency (r = 0.73, p-value <0.001) which are the main proxies for the trophic level. Corine land cover was used as an indication of the anthropogenic pressure and good correlations are also found with the watershed land use, negatively correlated with agricultural area (r = −0.60, p-value <0.001), population density (r = −0.36, p-value <0.001) and positively with forest area (r = 0.57, p-value <0.001).The index is WFD-compliant and is dedicated to natural lakes and artificial water bodies in metropolitan France, and will be routinely used by the French Ministry of the Environment to assess lake ecological status through the phytoplankton community. However, the results must be carefully interpreted in two cases: reservoirs with large water level fluctuations, and samples that include less than 5 indicator species.     

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Riparian zones are central landscape features providing several ecosystem services and are exceptionally rich in biodiversity. Despite their relatively low area coverage, riparian zones consequently represent a major concern for land and water resource managers confirmed within several European directives. These directives involve effective multi-scale monitoring to assess their conditions and their ability to carry out their functions. The objective of this research was to develop automated tools to provide from a single aerial LiDAR dataset new mapping tools and keystone riparian zone attributes assessing the ecological integrity of the riparian zone at a network scale (24 km).Different metrics were extracted from the original LiDAR point cloud, notably the Digital Terrain Model and Canopy Height Model rasters, allowing the extraction of riparian zones attributes such as the wetted channel (0.89 m; mean residual) and floodplain extents (6.02 m; mean residual). Different riparian forest characteristics were directly extracted from these layers (patch extent, overhanging character, longitudinal continuity, relative water level, mean and relative standard deviation of tree height). Within the riparian forest, the coniferous stands were distinguished from deciduous and isolated trees, with high accuracy (87.3%, Kappa index).Going further the mapping of the indicators, our study proposed an original approach to study the riparian zone attributes within different buffer width, from local scale (50 m long channel axis reach) to a network scale (ca. 2 km long reaches), using a disaggregation/re-agraggation process. This novel approach, combined to graphical presentations of the results allow natural resource managers to visualise the variation of upstream–downstream attributes and to identify priority action areas.In the case study, results showed a general decrease of the riparian forests when the river crosses built-up areas. They also highlighted the lower flooding frequency of riparian forest patches in habitats areas.Those results showed that LiDAR data can be used to extract indicators of ecological integrity of riparian zones in temperate climate zone. They will enable the assessment of the ecological integrity of riparian zones to be undertaken at the regional scale (13,000 km, completely covered by an aerial LIDAR survey in 2014).     

Mapping riparian condition indicators in a sub-tropical savanna environment from discrete return LiDAR data using object-based image analysis

Mapping, monitoring and managing the environmental condition of riparian zones are major focus areas for local and state governments in Australia. New remotely sensed data techniques that can provide the required mapping accuracies, complete spatial coverage and processing and mapping transferability are currently being developed for use over large spatial extents. The research objective was to develop and apply an approach for mapping riparian condition indicators using object-based image analysis of airborne Light Detection and Ranging (LiDAR) data. The indicators assessed were: streambed width; riparian zone width; plant projective cover (PPC); longitudinal continuity; coverage of large trees; vegetation overhang; and stream bank stability. LiDAR data were captured on 15 July 2007 for two 5 km stretches along Mimosa Creek in Central Queensland, Australia. Field measurements of riparian vegetation structural and landform parameters were obtained between 28 May and 5 June 2007. Object-based approaches were developed for mapping each riparian condition indicator from the LiDAR data. The validation and empirical modelling results showed that the object-based approach could be used to accurately map the riparian condition indicators (R² = 0.99 for streambed width, R² = 0.82 for riparian zone width, R² = 0.89 for PPC, R² = 0.40 for bank stability). These research findings will be used in a 26,000 km mapping project assessing riparian vegetation and physical form indicators from LiDAR data in Victoria, Australia.