Quantification Of Heterogeneity Research Articles

Photoacoustic spectral analysis at ultraviolet wavelengths for characterizing the Gleason grades of prostate cancer.

The diagnosis of aggressive prostate cancer (PCa) has relied on microscopic architectures, namely Gleason patterns, of tissues extracted through core biopsies. Technology capable of assessing the tissue architecture without tissue extraction will reduce the invasiveness of PCa diagnosis and improve diagnostic accuracy by allowing for more sampling locations. Our recently developed photoacoustic spectral analysis (PASA) has achieved quantification of tissue architectural heterogeneity interstitially. Taking advantage of the unique optical absorption of cell nuclei at ultraviolet (UV) wavelengths, this study investigated PASA at 266 nm for quantifying the tissue architecture heterogeneity in prostates. The results have shown significant differences among the normal, early cancer, and late cancer stages in mouse prostates ex vivo and in vivo (n=20, p<0.05). The study with human samples ex vivo has shown a correlation of 0.80 (n=11, p<0.05) between PASA quantification and pathologic diagnosis.

Genomic Instability in Circulating Tumor Cells.

Simple SummaryIn this review, we focus on recent advances in the detection and quantification of tumor cell heterogeneity and genomic instability of CTCs and the contribution of chromosome instability studies to genetic heterogeneity in CTCs at the single-CTC level.Circulating tumor cells (CTCs) can promote distant metastases and can be obtained through minimally invasive liquid biopsy for clinical assessment in cancer patients. Having both genomic heterogeneity and instability as common features, the genetic characterization of CTCs can serve as a powerful tool for a better understanding of the molecular changes occurring at tumor initiation and during tumor progression/metastasis. In this review, we will highlight recent advances in the detection and quantification of tumor cell heterogeneity and genomic instability in CTCs. We will focus on the contribution of chromosome instability studies to genetic heterogeneity in CTCs at the single-CTC level by discussing data from different cancer subtypes and their impact on diagnosis and precision medicine.

Quantification of groundwater storage heterogeneity in weathered/fractured basement rock aquifers using electrical resistivity tomography: Sensitivity and uncertainty associated with petrophysical modelling

Quantifying groundwater storage in weathered/fractured basement rock aquifers can be challenging owing to both their high degree of heterogeneity and their overall low storage capacity. Therefore, in these aquifers, the use of direct borehole hydraulic data is usually insufficient. Here we assessed the popular method of electrical resistivity tomography (ERT), combined with borehole data and including associated uncertainties, to resolve the spatial variability of groundwater storage properties at high resolution within a fractured mica schist aquifer in Ireland. Porosity distributions across both the saturated and unsaturated zones were calculated from two-dimensional (2D) ERT resistivities using two standard petrophysical models, Archie and Waxman & Smits (WS), the latter accounting for the influence of clay minerals on resistivity data. Our results demonstrated the importance of the hydrogeological conceptual constraints provided by ERT when parametrizing the 2D petrophysical models from borehole point data. They also confirmed the importance of accounting for clay minerals (the products of bedrock weathering processes) in the WS model, whereas predictions from Archie’s model produced unrealistically high porosity values of over an order of magnitude higher than the WS model. The WS model predicted porosities decreasing exponentially with depth, with values ranging from a few % in the shallowest, most-weathered part of the bedrock (upper 5 m on average) and deep fractured zones (to about 20 m deep), to <1% in the underlying fissured aquifer, and possibly down another order of magnitude in the deep massive bedrock. WS-derived porosities were in agreement with independent vertical water content profiles derived from magnetic resonance sounding (MRS), as well as point storativity values estimated from borehole hydraulic testing at the study site, with particularly good matches in the upper weathered/fractured bedrock and deeply weathered/fractured zones associated with regional faults. Detailed comparison suggested that WS provides an upper-bound estimate of groundwater storage in this environment. In the deep massive, un-weathered, and poorly fractured bedrock, however, discrepancies between groundwater storage estimate obtained from the three methods (ERT, MRS, and hydraulic) prevented reliable storage quantification, owing to the methods’ inherent technical limitations in such low porosity rocks. Our results demonstrated the suitability of resistivity tomography to quantify groundwater storage heterogeneity in weathered/fractured basement rock aquifers at high resolution and with reasonable overall uncertainty given the relative high uncertainties in petrophysical parameters at the kilometric scale. The results are promising for better characterization of groundwater storage variations in these hydrogeological systems, which are crucial to predict their response to climate variability and human exploitation.

Methodological Study to Investigate the Potential of Ultrasound-Based Elastography and Texture as Biomarkers to Monitor Liver Tumors.

Aims and objectives: In order to evaluate the responses of hepatic lesions to treatment in terms of tissue stiffness and heterogeneity, this work investigated the robustness of 2D shear-wave elastography (2D SWE) stiffness measurements and texture analyses in vitro and in vivo in terms of repeatability and variability. Methods and materials: A multioperator (n = 5) study was performed with an ultrasonic elastography device on two sets of phantoms. For the first set of phantoms, 10 measurements for each of the eight inclusions were performed by each observer, whereas the second set of phantoms was used to evaluate the influence of depth on the stiffness measurements. Variability of the stiffness measurements was evaluated in vivo on 10 healthy livers, with 10 measurements for each hepatic segment. Texture analyses were performed in B-mode, obtaining elastography images for every hepatic segment. Results: Stiffness measurements were influenced by depth, particularly when exceeding 7 cm. In vivo measurements demonstrated that measurements of segments I, VII, and VIII were less reliable, mainly due to their deeper locations. The protocols used were more flexible in terms of acquisition setup and probe placement than those currently used with Fibroscan®. For texture analysis on the B-mode images, 12 features showed low variability regardless of the evaluated hepatic segment. On elastogram, only two features showed low variability, but not in every segment. Conclusion: We demonstrated the robustness of two methodologies for the quantification of liver stiffness and heterogeneity. Further clinical studies should evaluate whether these techniques can assess tumor responses to treatment and, therefore, have the potential to be used as imaging biomarkers.

Deformation heterogeneity in laser-welded Eurofer

Abstract The suitability of a post-weld heat treatment is often measured in terms of reducing residual stress and/or ensuring hardness homogeneity. Here we use digital image correlation to quantify the localised deformation behaviour of laser-welded Eurofer-97 both with and without a normalising and tempering heat treatment. This is coupled with detailed microscopic analysis to investigate the mechanisms for the localised plasticity measured. We show that although the heat treatment ensures hardness homogeneity, there remains variation in grain size, texture, carbide morphology/density and tensile behaviour across the weld. Accordingly, deformation is heterogeneous under tension, even in the ‘uniform elongation’ regime. To capture this behaviour, a quantification of strain heterogeneity throughout the test provides a new measure of performance that indicates the suitability of both microstructure and macroscopic performance for engineering applications.

Tumour texture features from preoperative CT predict high-risk disease in endometrial cancer

To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM: To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients. Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age. High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06). CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies.

New advances in radiomics of gastrointestinal stromal tumors

Gastrointestinal stromal tumors (GISTs) are uncommon neoplasms of the gastrointestinal tract with peculiar clinical, genetic, and imaging characteristics. Preoperative knowledge of risk stratification and mutational status is crucial to guide the appropriate patients’ treatment. Predicting the clinical behavior and biological aggressiveness of GISTs based on conventional computed tomography (CT) and magnetic resonance imaging (MRI) evaluation is challenging, unless the lesions have already metastasized at the time of diagnosis. Radiomics is emerging as a promising tool for the quantification of lesion heterogeneity on radiological images, extracting additional data that cannot be assessed by visual analysis. Radiomics applications have been explored for the differential diagnosis of GISTs from other gastrointestinal neoplasms, risk stratification and prediction of prognosis after surgical resection, and evaluation of mutational status in GISTs. The published researches on GISTs radiomics have obtained excellent performance of derived radiomics models on CT and MRI. However, lack of standardization and differences in study methodology challenge the application of radiomics in clinical practice. The purpose of this review is to describe the new advances of radiomics applied to CT and MRI for the evaluation of gastrointestinal stromal tumors, discuss the potential clinical applications that may impact patients’ management, report limitations of current radiomics studies, and future directions.

Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets

Recognizing land cover heterogeneity is essential for the assessment of spatial patterns to guide conservation planning. One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics. However, due to the diversity of land cover types and their varied distribution, a consistent, larger-scale, and standardized framework for heterogeneity information extraction from this complex perspective is still lacking. Consequently, we developed a new Land Cover Complexity Index (LCCI), which is based on information-theory. The LCCI contains two foundational aspects of heterogeneity, composition and configuration, thereby capturing more comprehensive information on land cover patterns than any single metric approach. In this study, we compare the performance of the LCCI with that of other landscape metrics at two different scales, and the results show that our newly developed indicator more accurately characterizes and distinguishes different land cover patterns. LCCI provides an alternative way to measure the spatial variation of land cover distribution. Classification maps of land cover heterogeneity generated using the LCCI provide valuable insights and implications for regional conservation planning. Thus, the LCCI is shown to be a consistent indicator for the quantification of land cover heterogeneity that functions in an adaptive way by simultaneously considering both composition and configuration.

Quantification of Structural Heterogeneity Using Fractal Analysis of Contrast-Enhanced CT Image to Predict Survival in Gastric Cancer Patients.

Malignant tumor essentially implies structural heterogeneity. Fractal analysis of medical imaging has a potential to quantify this structural heterogeneity in the tumor AIMS: The purpose of this study is to quantify this structural abnormality in the tumor applying fractal analysis to contrast-enhanced computed tomography (CE-CT) image and to evaluate its biomarker value for predicting survival of surgically treated gastric cancer patients. A total of 108 gastric cancer patients (77 men and 31 women; mean age: 69.1years), who received curative surgery without any neoadjuvant therapy, were retrospectively investigated. Portal-phase CE-CT images were analyzed with use of a plug-in tool for ImageJ (NIH, Bethesda, USA), and the fractal dimension (FD) in the tumor was calculated using a differential box-counting method to quantify structural heterogeneity in the tumor. Tumor FD was compared with clinicopathologic features and disease-specific survival (DSS). High FD value of the tumor significantly associated with high T stage and high pathological stage (P = 0.009, 0.007, respectively). In Kaplan-Meier analysis, patients with higher FD tumors (FD > 0.9746) showed a significantly worse DSS (P = 0.009, log rank). Multivariate analysis demonstrated that tumor FD, T stage, and N stage were independent prognostic factors for DSS. In subset analysis of lymph-node positive gastric cancers, only tumor FD was an independent prognostic factor for DSS. CT fractal analysis can be a useful biomarker for gastric cancer patients, reflecting survival and clinicopathologic features.

Non-Gaussian information of heterogeneity in soft matter

Heterogeneity in dynamics in the form of non-Gaussian molecular displacement distributions appears ubiquitously in soft matter. We address the quantification of such heterogeneity using an information-theoretic measure of the distance between the actual displacement distribution and its nearest Gaussian estimation. We explore the usefulness of this measure in two generic scenarios of random walkers in heterogeneous media. We show that our proposed measure leads to a better quantification of non-Gaussianity than the conventional ones based on moment ratios.

Use of inkjet-printed single cells to quantify intratumoral heterogeneity

Quantification of intratumoral heterogeneity is essential for designing effective therapeutic strategies in the age of personalized medicine. In this study, we used a piezoelectric inkjet printer to enable analysis of intratumoral heterogeneity in a bladder cancer for the first time. Patient-derived tumor organoids were dissociated into single cell suspension and used as a bioink. The individual cells were precisely allocated into a microwell plate by drop-on-demand inkjet printing without any additive or treatment, followed by culturing into organoids for further analysis. The sizes and morphologies of the organoids were observed, so as the expression of proliferation and apoptotic markers. The tumor organoids also showed heterogeneous responses against chemotherapeutic agent. Further, we quantified mRNA expression levels of representative luminal and basal genes in both type of tumor organoids. These results verify the heterogeneous expression of various genes among individual organoids. This study demonstrates that the fully automated inkjet printing technique can be used as an effective tool to sort cells for evaluating intratumoral heterogeneity.

Quantification of small-scale heterogeneity in aquatic aminopeptidase activity

Leucine aminopeptidase (LAP) is one of the enzymes involved in the hydrolysis of peptides, and is sometimes used to indicate potential nitrogen limitation in microbes. Small-scale variability has the potential to confound interpretation of underlying patterns in LAP activity in time or space. An automated flow-injection analysis instrument was used to address the small-scale variability of LAP activity within contiguous regions of the Hudson River plume (New Jersey, USA). LAP activity had a coefficient of variation (CV) of ca. 0.5 with occasional values above 1.0. The mean CVs for other biological parameters—chlorophyll fluorescence and nitrate concentration—were similar, and were much lower for salinity. LAP activity changed by an average of 35 nmol l-1 h-1 at different salinities, and variations in LAP activity were higher crossing region boundaries than within a region. Differences in LAP activity were ±100 nmol l-1 h-1 between sequential samples spaced &lt;10 m apart. Variogram analysis indicated an inherent spatial variability of 52 nmol l-1 h-1 throughout the study area. Large changes in LAP activity were often associated with small changes in salinity and chlorophyll fluorescence, and were sensitive to the sampling frequency. This study concludes that LAP measurements in a sample could realistically be expected to range from zero to twice the average, and changes between areas or times should be at least 2-fold to have some degree of confidence that apparent patterns (or lack thereof) in activity are real.

Quantification of heterogeneity to classify benign parotid tumors: a feasibility study on most frequent histotypes.

Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D* median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.

Prognostic value of myocardial perfusion entropy in patients with normal thallium-201 myocardial perfusion with a CZT camera : PROMHETE study

Objectives We assessed the prognostic value of myocardial perfusion heterogeneity (entropy) in patients with normal myocardial perfusion as estimated from a dual isotope high-speed protocol (Thallium-201 stress and technetium- 99m-sestamibi rest) performed on a semiconductor camera. Background The prognostic value of normal myocardial perfusion scintigraphic imaging has been widely established for over twenty years but the clinical value of perfusion heterogeneity quantification beyond perfusion imaging as routinely performed is unknown. Methods From May 2011 to September 2012, 1159 patients with a normal scan or a non-significant perfusion abnormality (SSS 45%) were retrospectively identified. This study reports an interim analysis of 443 patients. A dual isotope high-speed protocol was performed on a semiconductor camera following exercise testing (37%) or pharmacological stress (63%). Myocardial perfusion images were then used to quantify myocardial perfusion heterogeneity as estimated by stress and rest image entropy. The primary endpoint was the occurrence of a cardiovascular event (cardiovascular death, non-fatal myocardial infarction, coronary angiography with or without revascularization, and stroke). Results The primary endpoint occurred in 73 patients during follow-up (3.3 ± 0.4 years). In a multivariate analysis, age (HR 1.04 [1.01; 1.06] P 4.06) underwent more events than those with a lower entropy ( Conclusions Myocardial perfusion heterogeneity (entropy) determined from thallium-201 stress perfusion images acquired on a semiconductor camera represent an independent prognostic factor of cardiovascular events with additive value over the classical interpretation of images from patients with normal myocardial perfusion scintigraphy. Myocardial perfusion heterogeneity (entropy) might represent a surrogate of coronary microvascular dysfunction.

Plasma Generating—Chemical Looping Catalyst Synthesis by Microwave Plasma Shock for Nitrogen Fixation from Air and Hydrogen Production from Water for Agriculture and Energy Technologies in Global Warming Prevention

Simultaneous generation of plasma by microwave irradiation of perovskite or the spinel type of silica supported porous catalyst oxides and their reduction by nitrogen in the presence of oxygen is demonstrated. As a result of plasma generation in air, NOx generation is accompanied by the development of highly heterogeneous regions in terms of chemical and morphological variations within the catalyst. Regions of almost completely reduced catalyst are dispersed within the catalyst oxide, across micron-scale domains. The quantification of the catalyst heterogeneity and evaluation of catalyst structure are studied using Scanning Electron Microscopy, Energy Dispersive X-ray Spectroscopy and XRD. Plasma generating supported spinel catalysts are synthesized using the technique developed by the author (Catalysts; 2016; 6; 80) and BaTiO3 is used to exemplify perovskites. Silica supported catalyst systems are represented as M/Si = X (single catalysts) or as M(1)/M(2)/Si = X/Y/Z (binary catalysts) where M; M(1) M(2) = Cr; Mn; Fe; Co; Cu and X, Y, Z are the molar ratio of the catalysts and SiO2 support. Composite porous catalysts are synthesized using a mixture of Co and BaTiO3. In all the catalysts, structural heterogeneity manifests itself through defects, phase separation and increased porosity resulting in the creation of the high activity sites. The chemical heterogeneity results in reduced and oxidized domains and in very large changes in catalyst/support ratio. High electrical potential activity within BaTiO3 particles is observed through the formation of electrical treeing. Plasma generation starts as soon as the supported catalyst is synthesized. Two conditions for plasma generation are observed: Metal/Silica molar ratio should be &gt; 1/2 and the resulting oxide should be spinel type; represented as MaOb (a = 3; b = 4 for single catalyst). Composite catalysts are represented as {M/Si = X}/BaTiO3 and obtained from the catalyst/silica precursor fluid with BaTiO3 particles which undergo fragmentation during microwave irradiation. Further irradiation causes plasma generation, NOx formation and lattice oxygen depletion. Partially reduced spinels are represented as MaOb–c. These reactions occur through a chemical looping process in micron-scale domains on the porous catalyst surface. Therefore; it is possible to scale-up this process to obtain NOx from MaOb for nitric acid production and H2 generation from MaOb–c by catalyst re-oxidized by water. Re-oxidation by CO2 delivers CO as fuel. These findings explain the mechanism of conversion of combustion gases (CO2 + N2) to CO and NOx via a chemical looping process. Mechanism of catalyst generation is proposed and the resulting structural inhomogeneity is characterized. Plasma generating catalysts also represent a new form of Radar Absorbing Material (RAM) for stealth and protection from radiation in which electromagnetic energy is dissipated by plasma generation and catalytic reactions. These catalytic RAMs can be expected to be more efficient in frequency independent microwave absorption.

Geological Heterogeneity of Coastal Unconsolidated Groundwater Systems Worldwide and Its Influence on Offshore Fresh Groundwater Occurrence

Numerous coastal areas worldwide already experience fresh water shortages due to overexploitation and salt water intrusion. Future climate change and population growth will further intensify this threat in more areas in coming decades. Therefore, it is necessary to explore any potential fresh water source, such as offshore fresh groundwater, that could alleviate this fresh water shortage and provide valuable time for adaptation measures implementation and changes in water management strategies. Recent evidence suggests that a disproportionally large portion of human population living in coastal areas relies on groundwater resources stored in underlying unconsolidated groundwater systems. These systems are often very heterogeneous, combining numerous high permeability aquifers interlaid with low permeability aquitards with varying total thickness. This heterogeneity is a major control on the fresh groundwater volume and groundwater salinity distribution within such systems. Thus, the quantification of geological heterogeneity is often the limiting factor when estimating fresh groundwater volumes, both inland and offshore, along the global coastline. To overcome this obstacle, we combine conceptual geological models with available state-of-the-art global datasets to derive a set of geological heterogeneity parameter distributions quantifying geological heterogeneity of coastal unconsolidated groundwater systems as formed over last 1 Ma. These are then used in an algorithm designed to build synthetic heterogenic parameterizations of coastal unconsolidated groundwater systems along the global coastline. These, in turn, provide key input for modelling variable-density groundwater flow and coupled salt transport to analyze changes in groundwater salinities and offshore fresh groundwater volume. Such an analysis is performed over one full glacial-interglacial cycle (the last 0.13 Ma) to account for oscillating sea-level conditions and shifts in coast-line positions and salinity incursions. Our simulation results show a close match between the modelling scenarios and values presented by literature sources demonstrating the potential of the hereby presented methodology to be applied in similar future studies.

Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software

BackgroundCell-type heterogeneity of tumors is a key factor in tumor progression and response to chemotherapy. Tumor cell-type heterogeneity, defined as the proportion of the various cell-types in a tumor, can be inferred from DNA methylation of surgical specimens. However, confounding factors known to associate with methylation values, such as age and sex, complicate accurate inference of cell-type proportions. While reference-free algorithms have been developed to infer cell-type proportions from DNA methylation, a comparative evaluation of the performance of these methods is still lacking.ResultsHere we use simulations to evaluate several computational pipelines based on the software packages MeDeCom, EDec, and RefFreeEWAS. We identify that accounting for confounders, feature selection, and the choice of the number of estimated cell types are critical steps for inferring cell-type proportions. We find that removal of methylation probes which are correlated with confounder variables reduces the error of inference by 30–35%, and that selection of cell-type informative probes has similar effect. We show that Cattell’s rule based on the scree plot is a powerful tool to determine the number of cell-types. Once the pre-processing steps are achieved, the three deconvolution methods provide comparable results. We observe that all the algorithms’ performance improves when inter-sample variation of cell-type proportions is large or when the number of available samples is large. We find that under specific circumstances the methods are sensitive to the initialization method, suggesting that averaging different solutions or optimizing initialization is an avenue for future research.ConclusionBased on the lessons learned, to facilitate pipeline validation and catalyze further pipeline improvement by the community, we develop a benchmark pipeline for inference of cell-type proportions and implement it in the R package medepir.

Radiomics of hepatocellular carcinoma.

The diagnosis of hepatocellular carcinoma relies largely on non-invasive imaging, and is well suited for radiomics analysis. Radiomics is an emerging method for quantification of tumor heterogeneity by mathematically analyzing the spatial distribution and relationships of gray levels in medical images. The published studies on radiomics analysis of HCC provide encouraging data demonstrating potential utility for prediction of tumor biology, molecular profiles, post-therapy response, and outcome. The combination of radiomics data and clinical/laboratory information provides added value in many studies. Radiomics is a multi-step process that requires optimization and standardization, the development of semi-automated or automated segmentation methods, robust data quality control, and refinement of algorithms and modeling approaches for high-throughput data analysis. While radiomics remains largely in the research setting, the strong associations of predictive models and nomograms with certain pathologic, molecular, and immune markers with tumor aggressiveness and patient outcomes, provide great potential for clinical applications to inform optimized treatment strategies and patient prognosis.

Earth observation based indication for avian species distribution models using the spectral trait concept and machine learning in an urban setting

Abstract Birds respond strongly to vegetation structure and composition, yet typical species distribution models (SDMs) that incorporate Earth observation (EO) data use discrete land-use/cover data to model habitat suitability. Since this neglects factors of internal spatial composition and heterogeneity of EO data, we suggest a novel scheme deriving continuous indicators of vegetation heterogeneity from high-resolution EO data. The deployed concepts encompass vegetation fractions for determining vegetation density and spectral traits for the quantification of vegetation heterogeneity. Both indicators are derived from RapidEye data, thus featuring a continuous spatial resolution of 6.5 m. Using these indicators as predictors, we model breeding bird habitats using a random forest (RF) classifier for the city of Leipzig, Germany using a single EO image. SDMs are trained for the breeding sites of 44 urban bird species, featuring medium to very high accuracies (59–90%). Analysing similarities between the models regarding variable importance of single predictors allows species groups to be determined based on their preferences and dependencies regarding the amount of vegetation and its spatial and structural heterogeneity. When combining the SDMs, models of urban bird species richness can be derived. The combination of high-resolution EO data paired with the RF machine learning technique creates very detailed insights into the ecology of the urban avifauna, opening up opportunities of optimising greenspace management schemes or urban development in densifying cities concerning overall bird species richness or single species under threat of local extinction.

The heterogeneity of pore structure in lacustrine shales: Insights from multifractal analysis using N2 adsorption and mercury intrusion

Abstract A series of parameters from a variety of techniques, such as pore size distribution, surface area, pore volume, etc., have been used to characterize the pore structure of unconventional shale reservoirs. However, the investigation on the quantification of pore structure heterogeneity is still scarce. In this aspect, a multifractal theory combined with N2 adsorption and mercury intrusion was used to obtain pore structure characteristics and quantify the heterogeneity of pore size distribution of nine lacustrine shale samples from the second member of Kongdian Formation (Ek2) in Cangdong Sag, Bohai Bay Basin, China. The results show that the Ek2 shale contains complex pore network, and pores with small pore size predominate in pore system. Both N2 adsorption branches and pore throat size distributions from mercury intrusion demonstrate multifractal nature. The width of singularity spectra from multifractal analysis is used to quantitatively characterize the heterogeneity degree of pore size distribution and shows good consistency with pore size distributions derived from N2 adsorption and mercury intrusion. The pore structure from mercury intrusion is much heterogeneous than that from N2 adsorption, indicating that an increased number of large pores will increase the heterogeneity of pore size distributions. Compared with other rock compositions, TOC has an obvious impact on the heterogeneity of pore structure in small pore size range.