Distribution Of Patches Research Articles

Environmental Controls to Soil Heavy Metal Pollution Vary at Multiple Scales in a Highly Urbanizing Region in Southern China.

Natural and anthropogenic activities affect soil heavy metal pollution at different spatial scales. Quantifying the spatial variability of soil pollution and its driving forces at different scales is essential for pollution mitigation opportunities. This study applied a multivariate factorial kriging technique to investigate the spatial variability of soil heavy metal pollution and its relationship with environmental factors at multiple scales in a highly urbanized area of Guangzhou, South China. We collected 318 topsoil samples and used five types of environmental factors for the attribution analysis. By factorial kriging, we decomposed the total variance of soil pollution into a nugget effect, a short-range (3 km) variance and a long-range (12 km) variance. The distribution of patches with a high soil pollution level was scattered in the eastern and northwestern parts of the study domain at a short-range scale, while they were more clustered at a long-range scale. The correlations between the soil pollution and environmental factors were either enhanced or counteracted across the three distinct scales. The predictors of soil heavy metal pollution changed from the soil physiochemical properties to anthropogenic dominated factors with the studied scale increase. Our study results suggest that the soil physiochemical properties were a good proxy to soil pollution across the scales. Improving the soil physiochemical properties such as increasing the soil organic matter is essentially effective across scales while restoring vegetation around pollutant sources as a nature-based solution at a large scale would be beneficial for alleviating local soil pollution.

Interactions Between Fire Refugia and Climate-Environment Conditions Determine Mesic Subalpine Forest Recovery After Large and Severe Wildfires

Infrequent stand-replacing wildfires are characteristic of mesic and/or cool conifer forests in western North America, where forest recovery within high-severity burn patch interiors can be slow, yet successful over long temporal periods (decades to centuries). Increasing fire frequency and high-severity burn patch size, under a warming climate, however, may challenge post-fire forest recovery, promoting landscape-level shifts in forest structure, composition, and distribution of non-forest patches. Crucial to a delay and/or impediment to this shift, fire refugia (i.e., remnant seed sources) may determine forest recovery trajectories and potential forest state-transitions. To examine how fire refugia attributes (i.e. extent, composition, and structure) interact with local climate and environmental conditions to determine post-fire forest recovery responses, we developed fine-grain maps of fire refugia via remote sensing and conducted field-based assessment of post-fire conifer tree establishment largely originating (i.e., dispersed) from fire refugium in the Central Cascade Range of the Pacific Northwest United States. We found that limitations on seed availability, represented by the distance2-weighted density (D2WD) of fine-grain refugia extent, largely explained post-fire tree establishment responses within our relatively mesic and cool subalpine study sites. Interactions between seed availability, climate, and environmental conditions indicated that the structural attributes of refugia (e.g., tree height) and site abiotic/biotic environmental controls (e.g., climate water deficit, canopy cover, and coarse woody debris cover) interplayed to constrain or enhance species-specific tree establishment responses. Importantly, these interactions illustrate that when seed availability is critically low for a given area, climate-environment conditions may strongly determine whether forests recover following fire(s). Toward modelling and predicting tree establishment responses and potential forest state-transitions after large stand-replacing fires(s), our study demonstrates the importance of accurately quantifying seed availability via the fine-grain extent, configuration, and attributes of remnant seed source legacies.

A circularly polarized patch antenna with a slotted parasitic loop

AbstractIn the letter, a circularly polarized (CP) patch antenna is proposed, which consists of a slotted radiation patch, a slotted parasitic loop with a short pin, and a ground plane. The slot with one open and one circular end is etched in the radiation patch, and the current distribution of the radiation patch is disturbed to excite the first CP mode. The currents distributed on the slotted radiation patch and parasitic loop can superimpose or cancel each other to produce the second CP mode. Impedance matching and the performance of the first CP can be improved by the two slots and short pin introduced into the parasitic loop, but without effect on the second CP mode. A prototype is designed, and a −10 dB impedance bandwidth of 21.3% (3.10–3.84 GHz), a 3‐dB axial‐ratio bandwidth of 10.1% (3.29–3.64 GHz), an in‐band radiation efficiency of 75%, and unidirectional left‐hand circular‐polarized radiation pattern with in‐band gain of 8.0 dBi are realized.

Influence of Fluid Distribution on Seismic Dispersion and Attenuation in Partially Saturated Limestone

AbstractQuantitatively assessing attenuation and dispersion of elastic‐wave velocities in partially saturated reservoir is difficult because of its sensitivity to fluid distribution. We conducted experiments on homogeneous Indiana limestone samples, partially saturated by two methods: drying and imbibition which lead to different fluid distribution for a given saturation. Forced oscillations (from 0.004 to 100 Hz) and ultrasonic (1 MHz) measurements were done under confining pressure to measure the change of elastic moduli with frequency and their attenuation. Our measurements show that compressional (P‐)velocities are strongly sensitive to the sample’s saturation method. For high saturations (above 80%), obtained by drainage, compressional velocities are frequency dependent, and clear peaks of attenuation can be observed. However, at the same saturations obtained by imbibition, no dispersion or attenuation is observed. In addition, shear velocities show little variation with frequency, saturations, and fluid distribution. The dispersion and attenuation of P‐velocities are shown to be influenced by the pore fluid distribution, which was investigated using micro‐computer‐assisted tomographic (CT) scans. Furthermore, a numerical model developed within the framework of poroelasticity’s theory predicts well the experimental results, using the fluid distribution obtained from CT as an input. Our results show that the velocity dispersion was related to wave‐induced fluid flow at mesoscopic scale controlled by the geometry and distribution of the gas patches.

Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset

Natural wetlands are intrinsically heterogeneous and typically composed of a mosaic of ecosystem patches with different vegetation types. Hydrological and biogeochemical processes in wetlands vary strongly among these ecosystem patches. To date, most remote sensing classification approaches for wetland vegetation either rely on coarse images that cannot capture the spatial variability of wetland vegetation or rely on very-high-resolution multi-spectral images that are detailed but very sporadic in time (less than once per year). This study aimed to use NDVI time series, generated from NASA’s HLS dataset, to classify vegetation patches. We demonstrate our approach at a temperate, coastal lake, estuarine marsh. To classify vegetation patches, a standard time series library of the four land-cover patch types was built from referencing specific locations that were identified as “pure” pixels. These were identified using a single-time high-resolution image. We calculated the distance between the HLS-NDVI time series at each pixel and the “pure”-pixel standards for each land-cover type. The resulting true-positive classified rate was >73% for all patch types other than water lily. The classification accuracy was higher in pixels of a more uniform composition. A set of vegetation maps was created for the years 2016 to 2020 at our research site to identify the vegetation changes at the site as it is affected by rapid water elevation increases in Lake Erie. Our results reveal how changes in water elevation have changed the patch distribution in significant ways, leading to the local extinction of cattail by 2019 and a continuous increase in the area cover of water lily patches.

Disturbances Brought about by Human Activities in Relation to the Eco-Environment of the Main Stream of the Tarim River, 2000–2020

The main stream of the Tarim River in China is typical of ecologically sensitive areas that have been heavily disturbed by human activities; as such, the monitoring of the quality of its eco-environment constitutes an important task for researchers. By using GlobeLand30 data and applying the disturbance degree model and revised ecosystem service value (ESV) model, the study presented in this paper undertook a quantitative estimation of the effects of the disturbance impacts of human activities on the eco-environment of this area in the period of 2000 to 2020. The main conclusions are as follows: (1) disturbance index values, which reflect disturbance to the local ecosystem by human activities, increased over the study period. Further, cultivated land experienced the largest increase, which, in turn, brought about the most significant disturbance to the eco-environment. High disturbance index values presented a patchy distribution in the west of the main stream of the Tarim River and formed bands and dots in the east; the area of land characterized by high and moderate disturbance index values increased, with growth areas taking on a scattered distribution of patches, bands, and dots without significant spatial continuity. (2) The total ESV increased, indicating the quality of the eco-environment improved. The increase of cultivated land offset the increase in ESV, which counteracted the effects of ecological governance measures. Areas with high ESV values were mainly located in the western and central parts of the study area, while low values were found in the middle east and east. Areas with higher increases in ESV were mainly located in the western and the western part of the middle reaches and took on a zonal distribution, while areas of decrease followed a scattered distribution, presenting as dots or patches. Using the quantitative analysis methods and high-resolution remote sensing data to evaluate the changes in the eco-environment was considered as the innovation of this study, and the findings are useful in exploring the influence of human activities on ecosystems and evaluating the eco-environment in the minor watershed of an arid area. This piece of quantitative research contributes to the task of monitoring eco-environmental changes using remote sensing techniques in ecologically sensitive areas.

A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

The Oriental migratory locust is a destructive agricultural pest in China. Large-scale locust area (the area possessing suitable breeding habitat for locusts and has locust infestation) extraction and its evolution analysis are essential for locust ecological control. Existing methods seldom consider the spatial differences in the locust development and habitat landscape structures in large areas. To analyze these effects, our study proposed a landscape-based habitat suitability model (LHS model) for large-scale locust area extraction based on remote sensing data, taking the middle and lower reaches of the Yellow River (MLYR) as an example. Firstly, the DD model was used to simulate locust development and obtain habitat factors of the corresponding dates; secondly, the patch distribution of different land cover classes and their adjacent landscape characteristics were analyzed to determine the landscape-based factors memberships; finally, the habitat suitability index was calculated by combining the factors memberships and weights to extract the locust area. Compared with the patch-based model using moving windows (patch based-analytic hierarchy process model, R2 = 0.77), the LHS model accuracy improved significantly (R2 = 0.83). Our results showed that the LHS model has a better application prospect in large-scale locust area extraction. By analyzing the locust areas evolution along the MLYR extracted using the LHS model, we found human activities were the main factors affecting the locust areas evolution from 2016 to 2020, including: (1) planting the plants that locusts do not like and urbanization caused the decrease of the locust area; (2) the wetland protection policies may cause the increase of the locust area. The model and research results help locust control and prevention to realize the sustainable development of agriculture.

On a consumer-resource system with asymmetric diffusion and geographic heterogeneity

A recent laboratory experiment on consumer-resource interactions showed that when the consumer moves between patches with homogeneous/heterogeneous distribution of toxicant, a homogeneous distribution leads to the lowest abundance of the consumer. Since diffusion rates in both the experiment and the corresponding model are assumed to be symmetric, an extended model with asymmetric diffusion is considered in this work. Rigorous analysis on the model shows global stability of a positive equilibrium, while further study on the equilibrium demonstrates mechanisms how toxicant distribution, asymmetric diffusion and spatial pattern of patches influence total population abundance of the consumer. Consistent with previous results, we show that when the system is in heterogeneous distribution of toxicant, consumer’s diffusion could make its total abundance higher than if non-diffusing, even higher than that when in homogeneous distribution without diffusion. Spatial pattern of patches is also proven to play a role in the increase. Different from previous results, we show that when the system is in homogeneous distribution of toxicant, asymmetric diffusion would make the consumer’s abundance lower than if non-diffusing. Our conclusion predicts that both toxicant distribution and consumer’s diffusion are important in the efficacy of toxicant, which may be helpful for both controlling pest and protecting desirable populations.

Knowledge-guided land pattern depiction for urban land use mapping: A case study of Chinese cities

Accurate urban land-use maps, which reflect the complicated land-use pattern implied in the function and distribution of land-cover types, play an important role in urban analysis. In recent years, data-driven deep learning-based land-use mapping methods have made great breakthroughs due to their strong feature extraction ability. Meanwhile, multisource geographic data, such as open street map (OSM), has been applied in land-use mapping with high spatial resolution remote sensing (HSR) imagery. Nevertheless, given the intraclass visual inconsistency and interclass label ambiguity, there are enormous challenges in OSM-based land-use pattern depiction: 1) the significant size variability of land-use parcel generated by OSM; 2) the weak interpretability of the data-driven based features; and 3) the neglect of intrinsically hierarchical and nested relationships between land-cover and land-use. In this paper, to bridge the “knowledge gap” for urban land-use mapping, a knowledge-guided land pattern depicting (KGLPD) framework is proposed. The proposed KGLPD framework mainly contains four parts. Land-use parcels with various scales are generated based on OSM. An adaptive gradient perceptive (AGP) mechanism is proposed to provide patch distribution prior knowledge for guiding the data-driven based visual feature extraction. To effectively cognize the layout of different land-cover types as the knowledge-driven information, a land pattern cognitive (LPC) model is designed to capture the inner and outer relationships (i.e., direction, distance and co-frequency) of different land-cover types. The fully sparse topic model (FSTM) is then used to extract the critical land pattern information from the data-driven and knowledge-driven information. Four typical Chinese urban cities are selected to evaluate the proposed framework. Experimental results on three cities with four regions of distinctive characteristics in different years, have achieved high classification accuracies of about 80%, with 10% improvement compared with other methods. This demonstrates the effectiveness and robustness of the proposed knowledge-guided urban land use mapping framework. Experimental results on the whole city of Shenzhen in China imply that the proposed framework perform well with small training samples. The results on different cities validate the generalizability and transferability of KGLPD. The typical land-use maps and the corresponding land-cover maps help understanding the relationship between them.

Deciphering the Origins of Transient Seismic Moment Accelerations by Realistic Dynamic Rupture Simulations

ABSTRACTProperties of earthquake source physics can be inferred from the comparison between seismic observations and results of dynamic rupture models. Although simple self-similar rupture models naturally explain the space and time observations at the scale of the whole earthquake, several observational studies based on the analysis of source time functions (STFs) suggest that they are unable to reproduce the initial accelerating phases of the rupture. We here propose to reproduce the observed transient moment accelerations, without affecting the global self-similarity of the rupture, to constrain their possible physical origins. Simulated STFs are generated from dynamic simulations with heterogeneous slip-weakening distance Dc. Heterogeneity is introduced on the fault plane through a fractal number-size distribution of circular patches, in which Dc takes a value proportional to their radius. As a consequence of the stochastic spatial distribution of the patches, rupture development exhibits a large variability, and delays between initiation and main rupture activation frequently occur. This variability, together with the dynamic correlation between rupture velocity and slip velocity inside each broken patch, successfully perturbs the self-similar properties: rather than growing quadratically with time, STFs have an higher apparent time exponent, close to the observed value of 2.7. In a broader perspective, our simulations show that to respect observed STF shapes, realistic dynamic models should generate bursts of seismic moment, most likely by episodes where slip and rupture velocity are correlated. Such a behavior appears to emerge more naturally when considering heterogeneities in the friction parameters rather than in the initial stress.

First look at the topology of reionisation redshifts in models of the epoch of reionisation

Context. During the epoch of reionisation (EoR), the first stars and galaxies appeared while creating ionised bubbles that eventually percolated near z ∼ 6. These ionised bubbles and percolation process are closely scrutinised today because observations of neutral hydrogen will be carried on in the next decade with the Square Kilometre Array radio telescope, for instance. In the meantime, EoR studies are performed in semi-analytical and fully numerical cosmological simulations to investigate the topology of the process, for instance. Aims. We analyse the topology of EoR models by studying regions that are under the radiative influence of ionisation sources. These regions are associated with peak patches of the reionisation redshift field, for which we measure the general properties such as their number, size, shape, and orientation. We aim to gain insights into the geometry of the reionisation process and its relation to the matter distribution, for example. We also assess how these measurements can be used to quantify the effect of physical parameters on the EoR models or the differences between fully numerical simulations and semi-analytical models. Methods. We used the framework of Morse theory and persistent homology in the context of the EoR, which was investigated via the DisPerSE algorithm on gas density and redshift of reionisation maps. We analysed different EoR scenarios with semi-analytical 21cmFAST and fully numerical EMMA simulations. Results. We can distinguish between EoR models with different sources using simple analyses of the number, shape, and size distributions of the reionisation redshift patches. For every model (of the semi-analytical and fully numerical simulations), we statistically show that these bubbles are rather prolate and aligned with the underlying gas filaments. Moreover, we briefly highlight that the percolation process of HII bubbles during the EoR can be followed by studying the reionisation redshift fields with different persistence thresholds. Finally, we show that fully numerical EMMA simulations can be made consistent with 21cmFAST models in this topological framework as long as the source distribution is diffuse enough.

Systematic Obtaining of Foster’s Equivalent Circuits for Symmetric Frequency Selective Surfaces

This work presents an eigenvalue problem to identify the characteristic resonances of a 2-D periodic distribution of planar metallic symmetric patches (stopband-like frequency selective surface) operating within the nondiffraction frequency regime. The eigenvalues of such problems provide the resonance frequencies in that range, whereas the eigenfunctions are a natural basis to expand a general solution under oblique illumination conditions. These basis functions are advantageously used to implement an efficient method of moment (MoM) computer code that leads to small size impedance matrices. It is also shown how the solution of this MoM problem naturally yields a canonical Foster-like equivalent circuit. A systematic method to determine accurate values of the capacitive and inductive components for such an equivalent circuit is proposed. The accuracy of the results obtained using this methodology is demonstrated by means of a systematic comparison with results computed using an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ad hoc</i> in-house MoM software.

Inter-spatial heat vulnerability assessment of Summer - 2018 over Madhya Pradesh using discomfort (wind and thermal) indices

Due to global warming, increase in air temperature is a growing concern at present. This rise in temperature may cause mild to severe thermal discomfort and heat related hazards mostly for the people who are engaged in outside activities throughout the day. The present study shows the inter-spatial monthly distribution of thermal patches over major stations of Madhya Pradesh, viz., Bhopal, Gwalior, Indore, Jabalpur, Hoshangabad, Rewa, Ratlam, Ujjain, Dhar etc. In this study, various Heat Indices applicable for tropical climate including Wet Bulb Globe Temperature (WBGT) are used to estimate the thermal stress by analyzing the meteorological data of Summer-2018 in Madhya Pradesh. Study was carried out for computing indoor, shady and outdoor heat stress separately and heat transfer rates to identify the places vulnerable to severe heat stroke in the month of March, April and May in 2018.It is observed that declaration of heat wave alone at any station is not sufficient for the administration and health organizations to take precautionary actions; also, discomfort indices should be referred for impact based monitoring and making work schedules. It is found that March and April fall in the partial discomfort category for at least half of the districts in Madhya Pradesh. It is interesting to note that several districts fall in discomfort category in outdoor conditions but not in indoor or shady conditions in May month. Severe stresses are observed mainly in the West and Central Madhya Pradesh during April and May months. Comparison of various Heat Indices is too performed along with computing Tropical Summer Index (TSI) and Apparent Temperature (AT) to indicate real feel-like temperatures in Madhya Pradesh during extreme temperature events.

Weakly Supervised Detection of Marine Animals in High Resolution Aerial Images

Human activities in the sea, such as intensive fishing and exploitation of offshore wind farms, may impact negatively on the marine mega fauna. As an attempt to control such impacts, surveying, and tracking of marine animals are often performed on the sites where those activities take place. Nowadays, thank to high resolution cameras and to the development of machine learning techniques, tracking of wild animals can be performed remotely and the analysis of the acquired images can be automatized using state-of-the-art object detection models. However, most state-of-the-art detection methods require lots of annotated data to provide satisfactory results. Since analyzing thousands of images acquired during a flight survey can be a cumbersome and time consuming task, we focus in this article on the weakly supervised detection of marine animals. We propose a modification of the patch distribution modeling method (PaDiM), which is currently one of the state-of-the-art approaches for anomaly detection and localization for visual industrial inspection. In order to show its effectiveness and suitability for marine animal detection, we conduct a comparative evaluation of the proposed method against the original version, as well as other state-of-the-art approaches on two high-resolution marine animal image datasets. On both tested datasets, the proposed method yielded better F1 and recall scores (75% recall/41% precision, and 57% recall/60% precision, respectively) when trained on images known to contain no object of interest. This shows a great potential of the proposed approach to speed up the marine animal discovery in new flight surveys. Additionally, such a method could be adopted for bounding box proposals to perform faster and cheaper annotation within a fully-supervised detection framework.

Wasserstein Patch Prior for Image Superresolution

Many recent superresolution methods are based on supervised learning. That means, that they require a large database of pairs of high- and low-resolution images as training data. However, for many applications, acquiring registered pairs of high and low resolution data or even imaging a large area with a high resolution is unrealistic. To overcome this problem, we introduce a Wasserstein patch prior for unsupervised superresolution of two- and three-dimensional images. In addition to the low-resolution observation, our method only requires one, possibly small, reference image which has a similar patch distribution as the high resolution ground truth. This assumption can e.g. be fulfilled when working with texture images or images of homogeneous material microstructures. The proposed regularizer penalizes the Wasserstein-2-distance of the patch distributions within the reconstruction and the reference image at different scales. We demonstrate the performance of the proposed method by applying it to two- and three-dimensional images of materials&#x0027; microstructures.

A physical–statistical recipe for representation of small-scale oceanic turbulent mixing in climate models

It is well established that small-scale cross-density (diapycnal) turbulent mixing induced by breaking of overturns in the interior of the ocean plays a significant role in sustaining the deep ocean circulation and in regulating tracer budgets such as those of heat, carbon and nutrients. There has been significant progress in the fluid mechanical understanding of the physics of breaking internal waves. Connection of the microphysics of such turbulence to the larger scale dynamics, however, is significantly underdeveloped. We offer a hybrid theoretical–statistical approach, informed by observations, to make such a link. By doing so, we define a bulk flux coefficient, $\varGamma _B$ , which represents the partitioning of energy available to an ‘ocean box’ (such as a grid cell of a coarse resolution climate model), from winds, tides, and other sources, into mixing and dissipation. Here, $\varGamma _B$ depends on both the statistical distribution of turbulent patches and the flux coefficient associated with individual patches, $\varGamma _i$ . We rely on recent parametrizations of $\varGamma _i$ and the seeming universal characteristics of statistics of turbulent patches to infer $\varGamma _B$ , which is the essential quantity for representation of turbulent diffusivity in climate models. By applying our approach to climatology and global tidal estimates, we show that, on a basin scale, energetic mixing zones exhibit moderately efficient mixing that induces significant vertical density fluxes, while quiet zones (with small background turbulence levels), although highly efficient in mixing, exhibit minimal vertical fluxes. The transition between the less energetic to more energetic zones marks regions of intense upwelling and downwelling of deep waters. We suggest that such upwelling and downwelling may be stronger than previously estimated, which in turn has direct implications for the closure of the deep branch of the ocean meridional overturning circulation as well as for the associated tracer budgets.

A Blind SAR Image Despeckling Method Based on Improved Weighted Nuclear Norm Minimization

Coherent imaging of synthetic aperture radar (SAR) systems generates multiplicative speckle noise, severely impairs SAR images’ interpretability. Although numerous despeckling methods have been proposed over the past three decades, SAR despeckling remains an unsolved problem due to its uniqueness and complexity. To address these issues, we propose a novel SAR image despeckling method based on the framework of weighted nuclear norm minimization (WNNM). First, a Gaussian function is used to approximate the distribution of good similar patches (GSP). Clustering is then used to select the optimal patches for the GSP matrix. WNNM can then estimate the underlying clean component of the GSP matrix. To increase the speed of the WNNM, a modified version of the singular value decomposition (SVD) is introduced. Additionally, we developed a noise variance estimation method that enables blind despeckling with the proposed method. Extensive experimental results demonstrate that the proposed method yields superior objective indices and subjective visual inspection.

Writer identification using VLAD Encoding of the Histogram of Gradient Angle Distribution

The use of computers and automatic systems has enabled scientific researchers to improve the classification rate in the field of writer identification. In our paper, we will propose an identification system based on the use of Histogram of Gradient Angle Distribution (HGAD) in square patches centered around Harris Keypoint locations. A global descriptor per image is calculated subsequently via the VLAD encoding of the local descriptors relating to the histograms of the square patches. The study carried out on two public datasets CVL and BFL made it possible to achieve very interesting identification rates with 99.4% in BFL and 99.7% in CVL.

The temporal distribution of cyclamen mite, Phytonemus pallidus (Acari: Tarsonemidae), in strawberry and comparison of sampling methods

Abstract Cyclamen mite, Phytonemus pallidus (Banks) (Acari: Tarsonemidae), is a pest of strawberry, Fragaria × ananassa Duchesne (Rosaceae), that injures new growth, resulting in damage to leaves and fruit. The primary source of cyclamen mite in strawberry is infested planting material, and damaged plants tend to occur in small, isolated patches in perennial production systems. In the present study, we determined through repeated sampling of strawberry plants in Ontario and Saskatchewan, Canada whether relative cyclamen mite population levels were stable in commercial fields and whether overwintering and field renovation (mowing) affected populations. In Ontario, cyclamen mite counts were significantly correlated for 66% (10 of 15) of the paired comparisons from six sampling dates in more than one year, indicating a relatively stable distribution of cyclamen mite patches in strawberry fields. Winter caused high mortality (100 times fewer mites in spring than fall) and mowing caused some mortality (10 times fewer mites post- than pre-mow). We found that more cyclamen mite motiles were extracted from plant material stored in ethanol and triple-washed than were extracted using Berlese funnels, although counts from leaves were correlated between methods. No cyclamen mites were found in Saskatchewan. Knowing that cyclamen mite patches are local and spread is negligible will facilitate targeted applications of controls.

Exploring the potential of rising plate meter techniques to analyse ecosystem services from multi-species grasslands

Context Continuous grazing in extensive grassland creates grazed and ungrazed patches, which are important for ecosystem service delivery. One possibility for optimising ecosystem services is to target a defined compressed sward height, which can be measured with rising plate meters supplied with internal global navigation satellite system (GNSS) receivers. Aims We assessed the ability of a modern rising plate meter to map long-term patch structure in extensively grazed grassland as a means to improve estimation of phytodiversity at paddock scale as a paramount ecosystem service. Methods The patch class proportions obtained from interpolating the georeferenced compressed sward height values were used to calculate phytodiversity indicators at paddock scale as determined by dry-weight ranking. In addition, a modern rising plate meter with internal GNSS receiver was compared with an established one without GNSS receiver. Key results The mapping of the patch classes revealed decreasing proportions of tall patches with increasing stocking intensity. Phytodiversity at paddock scale depended on the proportions of respective patches, highlighting the importance of accurate mapping of patches for ecosystem service assessment. Conclusions The new rising plate meter extends the utilisation of compressed sward height measurements into a spatial context. Patch size, spatial distribution of patches within a paddock and spatial clustering of patches, as well as repeated mapping over time, can be utilised to detect change and monitor long-term management schemes without the need for sophisticated remote-sensing applications. Implications The combination of the new rising plate meter and dry-weight ranking extends grazing management towards biodiversity monitoring in an easy-to-learn approach.