Influence of woody vegetation on pollinator densities in oilseed Brassica fields in an Australian temperate landscape

Wild pollinators may benefit Brassica oilseed production in temperate Australia, yet it is not known how the density of potential pollinators varies in these landscapes. In this study we assessed whether the density of feral honeybees, hoverflies (probably 2 species) and native bees (multiple species) in temperate Australian Brassica oilseed crops was related to the composition of the landscape. The density of pollinators was measured at multiple points in six different Brassica oilseed paddocks (20–80 ha) at least 1.75 km apart. Landscape composition at multiple scales (radii 100–2000 m) was determined from GIS layers of Brassica paddocks, woody vegetation and non-woody vegetation, and a derived layer expected to reflect the condition of woody vegetation remnants (the ‘Link’ score). Densities of feral honeybees were higher near the edges of Brassica fields than towards the middle. Densities of feral honeybees were strongly positively associated with the summed ‘Link’ score within 300 m and with the amount of woody vegetation. Densities of native bees and hoverflies were not strongly associated with woody vegetation or with woody vegetation with a high ‘Link’ score. Our results suggest that maximising feral honeybee abundance within paddocks in these landscapes may require smaller paddocks than those typically used, interspersed with habitat beneficial to feral honeybees such as woody vegetation in good condition.     

A review of indicators of estuarine tidal wetland condition

This review critically evaluates indicators of tidal wetland condition based on 36 indicator development studies and indicators developed as part of U.S. state tidal wetland monitoring programs. Individual metrics were evaluated based on relative scores on two sets of evaluation factors. A rigor score evaluated metric development based on conceptual relevance, indicator development method, degree of independent validation, and temporal and spatial extent tested. An applicability score evaluated metrics based on cost of data collection, probable spatial extent of applicability, technical complexity, and indicator responsiveness. The majority of indicators could be classified as biotic condition indicators (81%), with vegetation (37%) and macroinvertebrate (28%) metrics composing the largest proportion. Most metrics provided a conceptual model or scientific justification (97%), were developed by correlation to environmental gradients (46%), were tested over multiple seasons or years (49%) and at multiple sites (88%). Few were independently validated (18%). Average rigor score was 10 (on a scale of 0–25) and ranged between 1 and 21. Highest rigor scores were for trematode community metrics (community similarity index, species richness) and metrics of grass shrimp (Palaemonetes pugio) individuals (gene expression, relative fecundity, embryo hatching success, larval survival). Most metrics had a high cost of data collection (63%), required field and laboratory processing (84%), would be applicable across the U.S. (72%), and were responsive to the variable of interest (44%). Mean applicability score was 4.9 (range: 2–8). Highest scores were found for metrics that only required field collection of data using simple or no instrumentation. Lowest scoring metrics required expensive equipment, specialized taxonomic knowledge, complex laboratory analysis, and/or culturing of organisms. Scores for individual metrics were grouped by indicator, then averaged and rescaled between 0 and 100 to provide a composite evaluation of the indicator they measured. Among major indicator types, biotic indicators had the highest rigor scores (mean = 44, range 20–79), followed by indicators of chemical/physical characteristics (mean = 36, range 16–56), landscape condition (mean = 31, range 24–37), and hydrology/geomorphology indicators (mean = 21, range 4–52). In contrast, biotic indicators scored lowest for applicability (mean = 58, range 25–100) and indicators of landscape condition scored highest. The results of this review suggest that the development and selection of tidal wetland indicators could be vastly improved by employing a standardized development methodology that provides uniform information about each indicator. In addition, tidal wetland indicator research should focus on the development of indicators of ecological processes and disturbance regimes.     

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.     

Development,calibration, and validation of a littoral zone plant index of biotic integrity (PIBI) for lacustrine wetlands

We examine lacustrine wetland plant assemblages in the Central Corn Belt Plain portion of the Lake Michigan basin and developed a multimetric plant index of biotic integrity (PIBI). Our objectives were to determine the structural and functional attributes of littoral zone plant assemblages of least-impacted lacustrine wetlands, establish and test candidate metrics, statistically test and calibrate metrics, and finally validate a PIBI along a disturbance gradient. Of 35 candidate metrics, we chose 11 metrics that were grouped into four categories: species richness and composition, species tolerance, guild structure, and vegetation abundance. Based on Spearman correlations, we identified a suite of metrics, particularly those related to species richness and tolerance that had a strong response to human-induced habitat change. The overall PIBI correlated strongly with independent measures of habitat quality (p < 0.001) using a qualitative habitat index developed for lacustrine habitats. We validated the lacustrine PIBI by comparing index response to various landuse, landcover, and management types. Least impacted lakes and lakes classified as recreational or undergoing ecological restoration were not statistically separable and received the highest index scores, while the lowest scores were associated with industrial and residential land use. Least-impacted sites differ significantly (p < 0.001) from both industrial and residential lakes.     

Assessment of biotic condition of Atlantic Rain Forest streams: A fish-based multimetric approach

We developed a preliminary fish-based multimetric index (MMI) to assess biotic condition of Atlantic Rain Forest streams in Southeastern Brazil. We used least-disturbed sites as proxies of reference conditions for metric development. To determine the disturbance gradient we used an Integrated Disturbance Index (IDI) that summarized the multiple disturbances measured at local/regional catchment scales in a single index, describing the totality of exposure of the streams to human pressures. For our 48 sites, nine were least-disturbed (IDI < 0.25), five were most-disturbed (IDI > 1.35) and 34 were intermediate. Initially, we considered 41 candidate metrics selected primarily from previous studies. We screened this pool of candidate metrics using a series of tests: range test, signal-to-noise test, correlation with natural gradients, responsiveness test, and redundancy test. After screening, we selected six metrics for the MMI: % Characiform individuals, % water column native individuals, % benthic invertivorous individuals, % tolerant species, % intolerant species, and % detritivorous individuals. Metrics such as diversity, dominance, species richness and biomass that have been historically used for assessing ecosystem condition failed one or more screening tests. We conclude that an IDI and rigorous metric screening are critical to the MMI development process and for meaningful assessments of stream condition.     

Effect of fire on soil nutrients and under storey vegetation in Chir pine forest in Garhwal Himalaya,India

The study was carried out in the Pinus roxburghii Sargent (Chir pine) forest in the sub-tropical region of Garhwal Himalaya to assess the effect of fire on soil nutrient status at different altitudes (700 m, 800 m and 1000 m), soil depths (0–20 cm, 20–40 cm and 40–60 cm) and on under storey vegetation. The soil nutrients and under storey vegetation were assessed before fire (pre-fire) and after fire (post-fire). The results of the study indicate that fire plays an important role in soil nutrient status and under storey vegetation. The nutrients (soil organic carbon, nitrogen, phosphorus and potassium), decreased in post-fire assessment and with increasing altitudes, and soil depths, compared to pre-fire assessment. The under storey vegetation diminished after fire in all forest sites. The study concludes that in Chir pine forest, fire plays a role in reducing soil nutrients along the altitudinal gradient, soil depths and under storey vegetation. Thus, these nutrients can be saved through some management practices e.g. by early controlled burning and by educating local villagers about the negative impacts of severe wild fires on soil and vegetation.     

Exploring effective conservation networks based on multi-scale planning unit analysis. A case study of the Balsas sub-basin,Maranhão State,Brazil

Nature conservation and restoration activities require delineation of effective conservation networks. This paper presents a methodology which allows a quick evaluation of different planning options for extensive areas. We analyzed the spatial structure of remaining patches of the natural Cerrado vegetation in the Balsás sub-basin, South of Maranhão State of Brazil (about 25,590 km²) in order to understand how the remaining habitats are distributed and spatially configured. Conservation area network scenarios are based on hexagonal cells, referred to as analysis unit (AU) cells. A multi-scale analysis of 10,000 ha and 50,000 ha AU cells was set up to represent local and regional scales, respectively. For each AU at both local and regional scales we computed landscape metrics of native vegetation: NATIVE VEGETATION COVER: percentage of native vegetation cover; (NV-NP): number of patches; (NV-MSI): mean shape index. Subsequently, five different conservation and restoration strategies were defined: (a) only enforce nature conservation within legally established units; (b) target nature conservation only within the local AU landscape; (c) target regional management by combining neighboring AU; (d) management of both local landscape and region; (e) protect the legal conservation areas and promote local and regional conservation. We also generated scenarios of habitat capacity for mammals and matched these results with the different vegetation conservation scenarios. Results indicate that only 12% of the study area is well conserved and that 43% of the region is in a very critical condition. The percentage of AU cells where native vegetation conservation actions are required differ for the five conservation strategies: These results allow policy makers and other stakeholders to target the locations and extent of conservation units required. We suggest that about 45% of the sub-basin could be managed at local, regional or both scales. Regarding a mammal species diversity scenario an even higher percentage of the average habitat capacity of the selected species occurs in open cerrado and valleys areas that coincide with critical areas. The proposed multi-scale analysis unit cell approach can support the planning process of extensive areas as necessary in Brazil.     

Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa

Texture information from passive remote sensing images provides surrogates for habitat structure, which is relevant for modeling biodiversity across space and time and for developing effective ecological indicators. However, the applicability of this information might differ among taxa and diversity measures. We compared the ability of indicators developed from texture analysis of remotely sensed images to predict species richness and species turnover of six taxa (trees, pyraloid moths, geometrid moths, arctiinae moths, ants, and birds) in a megadiverse Andean mountain rainforest ecosystem. Partial least-squares regression models were fitted using 12 predictors that characterize the habitat and included three topographical metrics derived from a high-resolution digital elevation model and nine texture metrics derived from very high-resolution multi-spectral orthophotos. We calculated image textures derived from mean, correlation, and entropy statistics within a relatively broad moving window (102 m × 102 m) of the near infra-red band and two vegetation indices. The model performances of species richness were taxon dependent, with the lowest predictive power for arctiinae moths (4%) and the highest for ants (78%). Topographical metrics sufficiently modeled species richness of pyraloid moths and ants, while models for species richness of trees, geometrid moths, and birds benefited from texture metrics. When more complexity was added to the model such as additional texture statistics calculated from a smaller moving window (18 m × 18 m), the predictive power for trees and birds increased significantly from 12% to 22% and 13% to 27%, respectively. Gradients of species turnover, assessed by non-metric two-dimensional scaling (NMDS) of Bray-Curtis dissimilarities, allowed the construction of models with far higher predictability than species richness across all taxonomic groups, with predictability for the first response variable of species turnover ranging from 64% (birds) to 98% (trees) of the explained change in species composition, and predictability for the second response variable of species turnover ranging from 33% (trees) to 74% (pyraloid moths). The two NMDS axes effectively separated compositional change along the elevational gradient, explained by a combination of elevation and texture metrics, from more subtle, local changes in habitat structure surrogated by varying combinations of texture metrics. The application of indicators arising from texture analysis of remote sensing images differed among taxa and diversity measures. However, these habitat indicators improved predictions of species diversity measures of most taxa, and therefore, we highly recommend their use in biodiversity research.     

Acoustic patterns at the Samford Ecological Research Facility in South East Queensland,Australia: The Peri-Urban SuperSite of the Terrestrial Ecosystem Research Network

Acoustic signals that emanate from ecosystems are an important ecological variable which can provide evidence of current ecological condition as well as ecological change over time. The Terrestrial Ecosystem Research Network (TERN) established protocols to record sounds in ten SuperSites distributed throughout Australia with the objective of characterizing the soundscape in a representative landscape in different regions of Australia. This acoustic monitoring system enables a comparison of the soundscapes within and between Australian regions to determine similarities and differences in these landscapes and regions.This research quantifies the soundscape patterns in one of these SuperSites, Samford Ecological Research Facility (TERN-SERF), which is part of the South-East Queensland Peri-Urban SuperSite. An analysis and visualization of patterns in the soundscape was conducted using a continuous acoustic recording collected at TERN-SERF. The recording was made using a Song Meter (SM2) in a representative wooded habitat at TERN-SERF from 1 August to 30 September 2013. The recording was made in 16-bit stereo at 44 kHz and stored in wav file format. The recording was split into 1-minute-long recordings comprising 86,196 records and then sub-sampled at a 30-minute interval, providing 2878 one-minute-long recordings every 1/2 h. Soundscape metrics were computed for each of the two recording intervals. Soundscape power values were computed for each of ten frequency intervals (1–11 kHz) for both the 1-minute and the 30-minute interval recordings. In addition, six acoustic indices were computed from each recording.The acoustics metrics derived from the two sets of recordings (1-minute and 30-minute recording intervals) were examined to determine if they revealed different patterns. Several soundscape metrics were calculated for each recording including ten soundscape power values at 1 kHz frequency intervals and six acoustics indices. The soundscape shows a dynamic but consistent pattern over time of day during the monitoring period, depending on the metric examined. The metrics revealed different soundscape patterns. All soundscape power values at 1 kHz frequency intervals defined the dawn and dusk chorus, some more distinctly than others. Three of six acoustic indices also changed abruptly at the dawn chorus. No significant difference was found when soundscape metrics were compared between the 1-minute (high resolution) and 30-minute (lower resolution) recording intervals. A t-test was used to compare the mean values of ten soundscape power frequency intervals (p = 0.44) and the mean values of six acoustics indices (p = 0.41).Sounds were identified in 180 recordings made at 0530 h, 0600 h and 0630 h in the 1-minute long 30-minute interval recordings each day during the recording period (August and September). Sixty-seven species of birds were identified. Soundscape metrics were correlated with avian species counts and calls by all species using a correlation threshold of r > 0.7. This analysis revealed that soundscape power at the frequency interval 3–4 kHz was correlated with both the number of species (r = − 0.927) and total calls (r = − 0.996) over the three time periods. Three indices, the ADI (r = 0.953, r = 0.709), the AEI (r = 0.978, r = 0.774) and (H) (r = 0.795, r = 0.985) were similarly correlated as was an index derived soundscape power, the Shannon-Weaver Index (r = − 0.997, r = − 0.849). Other indices were correlated (r > 0.7) with only the number of avian species or only the number of calls.This methodology establishes an analysis protocol for analyzing large acoustic data sets, and demonstrates the effectiveness of using acoustic metrics for summarizing and interpreting long-term recordings.     

Development of a diatom index of biotic integrity for acid mine drainage impacted streams

Acid mine drainage (AMD) resulting from extensive coal mining throughout Appalachia since the 1800s has caused a legacy of severe acid and dissolved metal loads to thousands of stream miles, which has critically impacted aquatic life and ecological attributes. Relationships of diatoms and macroinvertebrates with AMD have been established, but no index specifically designed to quantify AMD impacts using diatoms has been created, nor have the response of multiple organism groups been compared for their utility as indices assessing AMD severity.For the purpose of developing an effective assessment and management strategy for AMD impacted streams, this study created and tested a multi-metric AMD-diatom index of biotic integrity (AMD-DIBI) and compared its response to AMD severity with an already established multi-metric macroinvertebrate community index (ICI). In 2006, 41 sites in southeast Ohio were sampled that represented an AMD impact gradient and non-AMD impacted reference sites. Metrics comprising the AMD-DIBI were selected based on their responsiveness to AMD and nutrient impacts. In the following year, the AMD-DIBI and its metrics were tested on a validation dataset consisting of 18 sites in an AMD impacted watershed. Results indicated a significant correlation between AMD-DIBI and ICI scores, and both indices and all metrics were strongly correlated with water chemistry variables indicative of AMD pollution (P < 0.05). Stepwise multiple regression selected alkalinity and conductivity as most influential to AMD-DIBI (adjusted r² = 0.70) and ICI scores (adjusted r² = 0.66). Narrative classes (e.g., Poor, Fair, Good, and Excellent) defined by index scores provided effective classifications of AMD severity. When tested on the watershed scale, AMD-DIBI and its metrics very successfully quantified AMD gradients and coal mining impacts as indicated by canonical correspondence analysis. This newly developed AMD-DIBI will be very useful for assessing impairment, sensitivity, and recovery of diatom communities in streams damaged or threatened by coal mining activities. In addition, because the AMD-DIBI was very responsive to a gradient of AMD pollution, it could be used in future studies measuring the long-term status of streams and effectiveness of various remediation methods. This study highlights the responsive power of diatom-based metrics.     

Appropriate vegetation indices for measuring the impacts of deer on forest ecosystems

Increasing deer density can cause serious degradation of forests in the Americas, Europe, and Asia. To manage deer impacts, evaluating their current impacts on forest ecosystems is necessary, usually via vegetation indices. However, the relationship between vegetation indices and absolute deer density, while taking into account tree size, snow depth, light condition, and the type of understory vegetation, has never been investigated. We examined the relationship between various vegetation indices and absolute deer density in 344 study plots in the deciduous broad-leaved forest of Yamanashi Prefecture, central Japan. In each plot, debarking and browsing, along with the coverage and maximum height of understory vegetation, were surveyed. Estimated deer densities for 82 5 × 5-km mesh units ranged from 0.8 deer/km² to 32.7 deer/km². The percentages of debarked trees within a plot ranged from 0 to 84%. Debarking was promoted by high deer density, small tree size, and thick snow. The effect of tree size on debarking was stronger than that of deer density. Occurrence of browsing on understory vegetation was higher at higher deer densities, and where understory vegetation was dominated by evergreen dwarf bamboo. Coverage and maximum height of understory vegetation were unaffected by deer density but increased with canopy openness and the dominance of dwarf bamboo in the understory. Overall, we predict that debarking of small trees living in heavy snow areas should occur even at low deer densities (<10 deer/km²). Browsing on dwarf bamboo should occur at intermediate deer densities (10–30 deer/km²), while debarking of thick trees living in low snow areas should occur only at high deer densities (≥30 deer/km²). Our study shows that debarking and browsing on understory vegetation are appropriate indices for evaluating deer impacts on forest ecosystems, but that tree size, snow depth, and the type of understory vegetation should also be considered.     

Spatial metrics for detecting ecosystem degradation in the ridge-slough patterned landscape

Indicators of landscape condition should be selected based on their sensitivity to environmental changes and their capacity to provide early warning detection of those changes. We assessed the performance of a suite of spatial-pattern metrics selected to quantify the condition of the ridge-slough landscape in the Everglades (South Florida, USA). Spatial pattern metrics (n = 14) that describe landscape composition, geometry and hydrologic connectivity were enumerated from vegetation maps of twenty-five 2 × 2 km primary sampling units (PSUs) that span a gradient of hydrologic and ecological condition across the greater Everglades ecosystem. Metrics were assessed in comparison with field measurements from each PSU of landscape condition obtained from regional surveys of soil elevation, which have previously been shown to capture dramatic differences between conserved and degraded locations. Elevation-based measures of landscape condition included soil elevation bi-modality (BI_SE), a binary measure of landscape condition, and also the standard deviation of soil elevation (SD_SE), a continuous measure of condition. Metric performance was assessed based on the strength (sensitivity) and shape (leading vs. lagging) of the relationship between spatial pattern metrics and these elevation-based measures. We observed significant logistic regression slopes with BI_SE for only 4 metrics (slough width, ridge density, directional connectivity index – DCI, and least flow cost – LFC). More significant relationships (n = 8 metrics) were observed with SD_SE, with the strongest associations for slough density, mean ridge width, and the average length of straight flow, as well as for a suite of hydrologic connectivity metrics (DCI, LFC and landscape discharge competence – LDC). Leading vs. lagging performance, inferred from the curvature of the association obtained from the exponent of fitted power functions, suggest that only DCI was a leading metric of the loss of soil elevation variation; most metrics were indeterminate, though some were clearly lagging. Our findings support the contention that soil elevation changes from altered peat accretion dynamics precede changes in landscape pattern, and offer insights that will enable efficient monitoring of the ridge-slough landscape as part of the ongoing Everglades restoration effort.     

Variable angle stereo imaging for rapid patient position correction in an in-house real-time position monitoring system

PurposeTo develop and validate a variable angle stereo image based position correction methodology in an X-ray based in-house online position monitoring system.Materials and methodsA stereo imaging module that enables 3D position determination and couch correction of the patient based on images acquired at any arbitrary angle and arbitrary angular separation was developed and incorporated to the in-house SeedTracker real-time position monitoring system. The accuracy of the developed system was studied by imaging an anthropomorphic phantom implanted with radiopaque markers set to known offset positions from its reference position in an Elekta linear accelerator (LA) and associated XVI imaging system. The accuracy of the system was further validated using CBCT data set from 10 prostate SBRT patients. The time gains achieved with the stereo image based position correction was compared with the manual matching of seed positions in Digitally Reconstructed Radiographs (DRRs) and kV images in the Mosaiq record and verify system.ResultsBased on phantom and patient CBCT dataset study stereo imaging module implemented in the SeedTracker shown to have an accuracy of 0.1(σ = 0.5) mm in detecting the 3D position offset. The time comparison study showed that stereo image based methodology implemented in SeedTracker was a minimum of 80(4) s faster than the manual method implemented in Mosaiq R&V system with a maximum time saving of 146(6) s.ConclusionThe variable angle stereo image based position correction method was shown to be accurate and faster than the standard manual DRR–kV image based correction approach, leading to more efficient treatment.     

Developing indices of temporal dispersion and continuity to map natural vegetation

An accurate and updated natural vegetation map is imperative for sustainable environmental management. This paper proposed a novel natural vegetation mapping algorithm based on time series images. Several indices of temporal dispersion and continuity were established for this purpose: low density (LD), medium density (MD), high density (HD) and medium continuity (MC). These indices were developed based on the particular percentiles-determined section of the EVI2 temporal profiles obtained through continuous wavelet transform. The natural vegetation was generally characterized as with lower temporal dispersion and greater temporal continuity compared with agricultural crops. The proposed methodology incorporated the indices of temporal dispersion and continuity and was applied to 13 provinces in central East China based on 500 m 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index with two bands (EVI2) in 2013. An overall accuracy of 92.97% was obtained when compared with 2715 ground truth sites. There was also a good agreement (kappa index = 0.8049) on the distribution and areas of different vegetation types between the MODIS-estimated image and the Landsat 8 OLI interpreted data on two test regions. This study demonstrated the efficiency of the transform and metric integrated time series classification approaches in the fields of land and vegetation cover mapping.     

Quantifying ‘normal’ shoulder muscle activity during abduction

The purpose of this experiment was to obtain electromyographic (EMG) activity from a sample of healthy shoulders to allow a reference database to be developed and used for comparison with pathological shoulders. Temporal and intensity shoulder muscle activation characteristics during a coronal plane abduction/adduction movement were evaluated in the dominant healthy shoulder of 24 subjects. Surface and intramuscular fine wire electrodes recorded EMG activity from 15 shoulder muscles (deltoid × 3, trapezius × 3, subscapularis × 2, latissimus dorsi, pectoralis major, pectoralis minor, supraspinatus, infraspinatus, serratus anterior and rhomboids) at 2000 Hz for 10 s whilst each subject performed 10 dynamic coronal plane abduction/adduction movements from 0° to 166° to 0° with a light dumbbell. Results revealed that supraspinatus (?.102 s before movement onset) initiated the movement with middle trapezius (?.019 s) and middle deltoid (?.014 s) also activated before the movement onset. Similar patterns were also found in the time of peak amplitude and %MVC with a pattern emerging where the prime movers (supraspinatus and middle deltoid) were among the first to reach peak amplitude or display the highest %MVC values. In conclusion, the most reproducible patterns of activation arose from the more prime mover muscle sites in all EMG variables analysed and although variability was present, there emerged ‘invariant characteristics’ that were considered ‘normal’ for this group of non pathological shoulders. The authors believe that the methodology and certain parts of the analysis in this study can be duplicated and used by future researchers who require a reference database of muscle activity for use as a control group in comparisons to their respective pathological shoulder group.     

Experimental evidence for a delayed response of the above-ground vegetation and the seed bank to the invasion of an annual exotic plant in deciduous forests

Invasions by alien plants significantly affect native biodiversity and ecosystem functioning. We conducted a 5-year field experiment to investigate potential effects of the annual invasive plant Impatiens glandulifera on both the native above-ground vegetation and the soil seed bank in a deciduous forest in Switzerland. Eight years after the establishment of I. glandulifera, we set up plots in patches invaded by the alien plant, in plots from which the invasive plant had been manually removed and in plots which were not yet colonized by the invasive plant. We examined plant species richness, diversity and plant species composition in the above-ground vegetation and soil seed bank in all plots one year and five years after the initiation of the experiment. The 36 plots (3 plot types × 6 replicates × 2 sites) were equally distributed over two forest sites. Neither the native above-ground vegetation nor the soil seed bank was influenced by the presence of I. glandulifera one year after the start of the field experiment. After five years, however, plant species richness of both the above-ground vegetation and the soil seed bank was reduced by 25% and 30%, respectively, in plots invaded by the alien plant compared to plots from which I. glandulifera had been removed or uninvaded plots. Furthermore, plots invaded by the alien plant had a lower total seedling density (reduction by 60%) and an altered plant species composition in the soil seed bank compared to control plots. Our field experiment indicates that negative effects of the annual invasive plant on the native above-ground vegetation and soil seed bank of deciduous forests become visible with a delay of several years.     

Estimating root zone soil moisture at distant sites using MODIS NDVI and EVI in a semi-arid region of southwestern USA

This study investigates the potential of using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to estimate root zone soil moisture at native in-situ measured sites, and at distant sites under the same climatic setting. We obtained in-situ data from Soil Climate Analysis Network (SCAN) sites near the Texas-New Mexico border area, and NDVI and EVI products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Terra satellite. Results show that soil moisture values of the same depth are highly correlated (r = 0.53 to 0.85) among sites as far as 150 km apart, and that NDVI and EVI are highly correlated at the same site (r = 0.87 to 0.91). Correlation based on raw time series of NDVI and soil moisture is in general higher than that based on deseasonalized time series at every depth. The correlation reaches maximum value when vegetation index (VI) lags soil moisture by 5 to 10 days. NDVI shows a slightly higher correlation with soil moisture than EVI does by using the deseasonalized time series of NDVI and soil moisture. It is found that deseasonalized time series of NDVI and soil moisture are correlated at native sites (r = 0.33 to 0.77), but not at sites where soil moisture is very low. Regression analysis was conducted using deseasonalized time series soil moisture and deseasonalized time series NDVI with a 5-day time lag. Regression models developed at one site and applied to a similar distant site can estimate soil moistures, accounting for 50–88% of the variation in observed soil moistures.     

The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures

Retrieving leaf chlorophyll content at a range of spatio-temporal scales is central to monitoring vegetation productivity, identifying physiological stress and managing biological resources. However, estimating leaf chlorophyll over broad spatial extents using ground-based traditional methods is time and resource heavy. Satellite-derived spectral vegetation indices (VIs) are commonly used to estimate leaf chlorophyll content, however they are often developed and tested on broadleaf species. Relatively little research has assessed VIs for different leaf structures, particularly needle leaves which represent a large component of boreal forest and significant global ecosystems. This study tested the performance of 47 published VIs for estimating foliar chlorophyll content from different leaf and canopy structures (broadleaf and needle). Coniferous and deciduous sites were selected in Ontario, Canada, representing different dominant vegetation species (Picea mariana and Acer saccharum) and a variety of canopy structures. Leaf reflectance data was collected using an ASD Fieldspec Pro spectroradiometer (400–2500 nm) for over 300 leaf samples. Canopy reflectance data was acquired from the medium resolution imaging spectrometer (MERIS). At the canopy level, with both leaf types combined, the DD-index showed the strongest relationship with leaf chlorophyll (R² = 0.78; RMSE = 3.56 μg/cm²), despite differences in leaf structure. For needleleaf trees alone the relationship with the top VI was weaker (D_[red], R² = 0.71; RMSE = 2.32 μg/cm²). A sensitivity study using simulated VIs from physically-modelled leaf (PROSPECT) and canopy (4-Scale) reflectance was performed in order to further investigate these results and assess the impacts of different background types and leaf area index on the VIs’ performance. At the leaf level, the MNDVI8 index showed a strong linearity to changing chlorophyll and negligible difference to leaf structure/type. At canopy level, the best performing VIs were relatively consistent where LAI ≥ 4, but responded strongly to differences in background at low canopy coverage (LAI = 2). This research provides comprehensive assessments for the use of spectral indices in retrieval of spatially-continuous leaf chlorophyll content at the leaf (MTCI: R² = 0.72; p < 0.001) and canopy (DD: R² = 0.78; p < 0.001) level for resource management over different spatial and temporal scales.     

Estimation of wetland vegetation height and leaf area index using airborne laser scanning data

Wetland vegetation is a core component of wetland ecosystems. Wetland vegetation structural parameters, such as height and leaf area index (LAI) are important variables required by earth-system and ecosystem models. Therefore, rapid, accurate, objective and quantitative estimations of wetland vegetation structural parameters are essential. The airborne laser scanning (also called LiDAR) is an active remote sensing technology and can provide accurate vertical vegetation structural parameters, but its accuracy is limited by short, dense vegetation canopies that are typical of wetland environments. The objective of this research is to explore the potential of estimating height and LAI for short wetland vegetation using airborne discrete-return LiDAR data.The accuracies of raw laser points and LiDAR-derived digital elevation models (DEM) data were assessed using field GPS measured ground elevations. The results demonstrated very high accuracy of 0.09 m in raw laser points and the root mean squared error (RMSE) of the LiDAR-derived DEM was 0.15 m.Vegetation canopy height was estimated from LiDAR data using a canopy height model (CHM) and regression analysis between field-measured vegetation heights and the standard deviation (σ) of detrended LiDAR heights. The results showed that the actual height of short wetland vegetation could not be accurately estimated using the raster CHM vegetation height. However, a strong relationship was observed between the σ and the field-measured height of short wetland vegetation and the highest correlation occurred (R² = 0.85, RMSE = 0.14 m) when sample radius was 1.50 m. The accuracy assessment of the best-constructed vegetation height prediction model was conducted using 25 samples that were not used in the regression analysis and the results indicated that the model was reliable and accurate (R² = 0.84, RMSE = 0.14 m).Wetland vegetation LAI was estimated using laser penetration index (LPI) and LiDAR-predicted vegetation height. The results showed that the vegetation height-based predictive model (R² = 0.79) was more accurate than the LPI-based model (the highest R² was 0.70). Moreover, the LAI predictive model based on vegetation height was validated using the leave-one-out cross-validation method and the results showed that the LAI predictive model had a good generalization capability. Overall, the results from this study indicate that LiDAR has a great potential to estimate plant height and LAI for short wetland vegetation.     

Evaluation of tomato cultivars to Helicoverpa armigera using two-sex life table parameters in laboratory

Helicoverpa armigera (Hübner) is one of the most important pests of a wide range of agricultural crops worldwide. Resistance of 10 tomato cultivars (‘Primoearly,’ ‘Riogrand,’ ‘CaljN3,’ ‘Kingstone,’ ‘Earlyurbana,’ ‘Petomech,’ ‘EarlyurbanaY,’ ‘Mobil,’ ‘Imprial’ and ‘Petoearly’) to H. armigera was evaluated under laboratory conditions at 25 ± 1 °C, 60 ± 5% RH and a photoperiod of 16:8 (L:D) hours using age-stage, two-sex life table parameters. The larval period ranged from 19.96 on ‘Riogrand’ to 24.58 days on ‘Imprial.’ The insects reared on ‘Imprial’ had the longest total preoviposition period (44.80 days) and those reared on ‘Riogrand’ had the shortest one (35.44 days). The longest adult longevity for female and male was observed on ‘EarlyurbanaY’ (14.40 days) and ‘Kingstone’ (15.00 days), respectively. Using age-stage, two-sex life table, the value of the net reproductive rate (R₀) varied from 7.8 on ‘Imprial’ to 186.9 offspring per individual on ‘Petomech.’ The lowest value of the intrinsic rate of increase (r) and finite rate of increase (λ) was on ‘Imprial’ (0.0410 and 1.0423 day^− 1, respectively) and the highest was on ‘Petomech’ (0.1274 and 1.1359 day^− 1, respectively). The mean generation time (T) on different cultivars varied from 39.9 to 48.2 days. The results revealed that ‘Petomech’ was the most susceptible (suitable) and ‘Imprial’ was the most resistant (unsuitable) cultivar to this pest among the tomato cultivars tested.