Nearest-neighbor Distance Research Articles

Spatial Patterns and the Evolution of Logistics Service Node Facilities in Large Cities—A Case from Wuhan

Logistics services are integral to urban economic activity, and delving into the spatial distribution traits and evolutionary pathways of various kinds of logistics service node facilities (LSNF) is markedly valuable for understanding a city’s functional spatial makeup and refining the spatial layout of logistics services. This study quantitatively and qualitatively analyzes the spatial congregation and spreading characteristics of diverse LSNFs in Wuhan in 2011, 2014, 2017, and 2020, employing kernel density analysis, average nearest neighbor index, mean center, and distance distribution frequency, seeking to characterize the spatial evolution characteristics of LSNF, alongside examining the trends in distances to city cores, principal adjoining roads, and production and consumption sites. The following conclusions were made: (1) Between 2011 and 2020, various types of LSNFs in Wuhan experienced a pattern characterized by the noticeable coexistence of spatial expansion and agglomeration, particularly visible after 2014. The degree of agglomeration is classified in a descending order as follows: CWC, STN, PSN, and PDN. (2) An “absolute diffusion” phenomenon characterizes the distribution of distances between various kinds of LSNFs and city cores or neighboring roads, with the lion’s share of high-frequency distribution zones spreading beyond city cores by 5–10 km, and a majority of the LSNFs being situated within 1 km from adjacent roads. (3) While the LSNF collective exhibits a stronger tendency towards the consumption facet, it reflects a surrounding of industrial production sites on the production facet and locations of manufactured goods consumption on the consumption facet, followed by locations of agricultural product consumption and comprehensive consumption sites.

Abstract A053: Understanding geospatial relationships in ovarian cancer risk

Abstract To examine the geographic distribution of ovarian cancer cases in the New England area and identify potential case clusters. Methods: This was a case-control study utilizing 1580 ovarian cancer patients from a single healthcare system (MGB). Using electronic health record (EHR) review, patient primary addresses were geocoded. To account for spatial distribution confounded by access to the MGB health system, 1750 patients from the MGB biobank system were geocoded as controls. Generalized additive models were used to determine the spatial patterning of cases and controls, controlled for age and race. Geospatial analysis was performed using ArcGIS software and R. Results: 3325 patients (1576 ovarian cancer patients, 1749 biobank controls) were successfully geocoded. Distribution of ovarian cancer cases and biobank patient controls were similar (average nearest neighbor distance 6337m vs 5623 m). Among the cohort of patients in New England (defined as MA, ME, NH, VT, RI, CT), there were 1476 ovarian cancer patients and 1663 biobank control patients. Use of a generalized additive model demonstrated higher incidence of ovarian cancer in Western CT, western MA, VT, and southern ME. These data are similar to SEER reported county-level incidence of late-stage ovarian cancer. Conclusions: Understanding the geospatial distribution of ovarian cancer cases can highlight potential clusters of higher incidences of disease. Causal relationships have yet to be established and require future investigation, but these data suggest spatially patterned exposures are worth examination. Citation Format: Victoria Wang, Jaime Hart, Kevin Elias. Understanding geospatial relationships in ovarian cancer risk [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A053.

A novel algorithm to generate representative volume elements with cylindrical fibers and sphere particles

In the article, we propose a new method to generate representative volume element (RVE) of random spatial distributions with cylindrical fibers and spherical particles based on the Improved Artificial Bee Colony (IABC) algorithm. In this employed bee phase of IABC, the proposed algorithm adopts a new search strategy, which improves the computational efficiency. To analyze the differences between the fiber distribution generated by this algorithm and the actual fiber distribution, we conducted statistical analysis on the distribution of the generated RVE. The statistical analysis results of the nearest neighbor distance (NND), Second-order intensity function, and pair correlation function were in good agreement with the experiment and complete spatial randomness (CSR) patterns. In addition, the predicted elastic properties were compared with experimental measurements and theoretical prediction methods. The results demonstrate the accuracy and efficiency of the proposed algorithm. This algorithm can quickly generate the RVE of cylindrical fibers and spherical particles with volume fractions of 80% and 62%, and the calculation time for generating the RVE of cylindrical fibers is about 17s.

Occurrence and formation of clast-free circular depressions in the southern Namib Desert, Tsau ǁKhaeb (Sperrgebiet) National Park, Namibia

Circular depressions are concave, shallow depressions found on planar landscape surfaces in the southern Namib Desert. They occur on gravelly substrates with nearly level to very slightly inclined surfaces. The depressions range from 6 to 10 m in diameter with centers typically depressed 10–20 cm below the level of the surrounding terrain. Locations of individual circular depressions were mapped at one site using ground-based measurements and at three additional sites using Google Earth imagery. At all sites, circular depressions are highly overdispersed with densities ranging from approximately 10–20/ha and corresponding nearest neighbor distances of 17–24 m. Large fragments of weathered calcrete and stones occur on soil surfaces surrounding circular depressions, but not within the depressions. Circular depressions at one site contained active burrow systems of Brants’ whistling rat ( Paratomys brantsii). Bioturbation by these rodents contributes to the non-cohesive nature of the sandy substrate, which promotes aeolian deflation and formation of the depressions. Excavations of the burrow systems by the honey badger ( Mellivora capensis) in search of rodent prey can transfer large stones and calcrete fragments from the subsurface to the surface and subsequently move those materials about the surface. Even if such sequential, horizontal displacements are in random directions, such movements can eventually yield a central, clast-free area surrounded by a peripheral zone where the clasts accumulate once they have been displaced beyond the margin of the area to which the predator is drawn in search of rodent prey. A conceptual model consisting of a two-dimensional random walk of large clasts about the surface until they are displaced from the focal “arena” of rodent occupation provides a novel explanation for origin of a spatially organized pattern that is initiated through the random displacement of those materials. Comparable microtopographic patterning associated with bioturbation in other arid and semi-arid environments may have similar origins.

Assessing dependence between land use/land cover and water quality

Changes in land use/land cover (LULC) directly or indirectly affect water quality in watercourses and impoundments. Sustainable management strategies aimed to enhance ecosystem health and community well-being require an accurate water-quality evaluation. This study looks into the correlation between temporal changes in LULC, represented by selected landscape variables (land cover area and proportion, patch density, Euclidean nearest-neighbor distance, mean shape index, and Shannon index), and water quality variables (nitrate, total phosphorus, and total suspended solids) at catchment scale. To compare the watershed-size influence, this analysis was performed at two different spatial scales represented by two Uruguayan basins of different sizes, San Salvador (3,118 km2) and Del Tala (160 km2). Partial Least Squares and Random Forest unsupervised machine-learning models were employed for this analysis. By exploiting a non-model-biased method based on game theory (SHAP), the LULC characteristics were quantified and ranked based on their level of importance in the water-quality evaluation. The main outcomes of this study proved that patch density is one of the most influencing metrics in both watersheds and for both models. Agricultural land use is the most critical one at both catchments and agricultural with a forage crop land uses are the most important ones for both algorithms. Furthermore, it is possible to state that the adopted techniques are valuable tools that can provide an adequate overview of the water‐quality behavior in space and time and the correlations between water-quality variables and LULC.

Kinematic performance declines as group size increases during escape responses in a schooling coral reef fish

IntroductionEscaping predation is essential for species survival, but prey must effectively match their response to the perceived threat imposed by a predator. For social animals, one mechanism to reduce risk of predation is living in larger group sizes, which dilutes each individual's risk of capture. When a predator attacks, individuals from a range of taxa (e.g., fishes, sharks, and amphibians) perform an escape response, to evade the attack.MethodsUsing the schooling coral reef damselfish Chromis viridis, we assess if there is an optimal group size that maximizes both individual escape response performance as well as group cohesion and coordination following a simulated predator attack, comparing schools composed of four, eight, and sixteen fish. The escape response was assessed through simulated predator attacks, measuring escape latency, kinematics (average turning rate, and distance covered), and group dynamics (school cohesion and coordination). The experiments were conducted with varying group sizes to analyze the impact on escape performance and group behavior.ResultsWe found that fish in various group sizes exhibited no difference in their reaction timing to a simulated predator attack (i.e., escape latency), but larger groups exhibited slower kinematics (i.e., lower average turning rate and shorter distance covered during the escape response), potentially because larger groups perceived the predator attack as less risky due to safety in numbers. Both school cohesion and coordination (as measured through alignment and nearest neighbor distance, respectively) declined in the 100 ms after the predator's attack. While there was no impact of group size on alignment, larger group sizes exhibited closer nearest neighbor distances at all times.DiscussionThe findings suggest that larger group sizes in schooling coral reef fish may lead to energy conservation by displaying less costly behavioral responses to predator threats. This potential energy saving could be attributed to a higher threshold of perceived threat required to trigger a rapid escape response in larger groups. The study emphasizes the intricate interplay between individual and collective behaviors in response to predation and sheds light on the nuanced dynamics of group living in the face of predation.

Abstract C045: Multiplex fluorescent immunohistochemistry reveals immune microenvironment alterations in COMPASS-like complex gene mutated pancreatic cancer

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is highly resistant to chemoradiation and immune therapies. There is limited biomarker to identify subsets of PDAC that responds to immunotherapy or targeted therapy. We have identified a subset of PDACs (approximately 25%) carrying COMPASS-like complex (CLC) gene mutations. Analysis of the clinicopathologic and molecular features of this PDAC subset revealed that these tumors are an aggressive group of PDACs with poor or squamous histologic differentiation, increased rates of TP53 mutations, and poor patient survival compared to control PDACs. Our preliminary data showed that PDACs carrying mutations in two members of the CLC genes (KDM6A and KMT2D) have immunosuppressive tumor microenvironment (TME), suggesting that CLC genes are candidate biomarkers for immunotherapy. However, a comprehensive analysis of the immune composition, immune checkpoint expression, and the relationship between tumor cells and immune cells in CLC gene mutated PDACs compared to controls has not been performed. In this study, we characterized the immune composition in CLC gene mutated PDACs compared to paired control PDACs using tyramide signal amplification multiplex fluorescent immunohistochemistry (mfIHC). Methods: Human PDAC tissue slides were stained with 7 markers using mfIHC and allowed for phenotyping of 7 cell types: PD-L1- epithelial cells (ECs) (pancytokeratin+PD-L1-), PD-L1+ ECs (pancytokeratin+PD-L1+), cytotoxic T lymphocytes (CTLs) (CD3+CD8+), helper T cells (CD3+CD8-FoxP3-), Tregs (CD3+CD8-FoxP3+), PD-L1- antigen presenting cells (APCs) (CD163+PD-L1-), and PD-L1+ APCs (CD163+PD-L1+). Random image sections were selected in each sample (5~8 sections per sample) and divided into wild-type (WT) group (n=49) and mutant group (n=49) and analyzed using inForm Cell Analysis software. Tissue segmentation training was performed to separate stromal and epithelial elements. Cell percentage, cell density, and nearest neighbor distance of each cell type were calculated using R program. Results: There is an increased infiltration of T cells, Tregs, and helper T cells in the epithelial component of the mutant group compared with WT group. The epithelial cells are more frequent to express PD-L1. Interestingly, we also observed more Treg infiltration in the stromal component and total tissue in the mutant group compared with WT group. The CTLs are more engaged with the epithelial cells, regardless of their PD-L1 status, in the mutant group compared with WT group. Conclusions: Our results provide insight into the effects of CLC gene mutations on shaping the immune microenvironment of PDAC and suggest that CLC gene mutated PDACs have a different immune microenvironment than other PDACs and may respond differently to immunotherapy. Citation Format: Shungang Zhang, Jake McGue, Elaina Daniels, Hong Sun Kim, Dafydd Thomas, Jiaqi Shi. Multiplex fluorescent immunohistochemistry reveals immune microenvironment alterations in COMPASS-like complex gene mutated pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C045.

Thermodynamic properties of chalcogenide and pnictide ternary tetrahedral semiconductors

In this paper, we present thermodynamic properties such as heat of formation, heat of fusion and entropy of fusion for chalcopyrite structured solids with the product of ionic charges and nearest neighbour distance d (Å). The heat of formation (∆Hf) of these compounds exhibit a linear relationship when plotted on a log-log scale against the nearest neighbour distance d (Å), but fall on different straight lines according to the ionic charge product of the compounds. On the basis of this result two simple heat of formation (∆Hf)heat of fusion (∆HF), and heat of formation (∆Hf)entropy of fusion (∆SF), relationship are proposed and used to estimate the heat of fusion (∆HF) and entropy of fusion (∆SF) of these semiconductors. We have applied the proposed relation to AIIBIVC2 V and AI BIIIC2 VI chalcopyrite semiconductor and found a better agreement with the experimental data than the values found by earlier researchers. The results for heat of formation differ from experimental values by the following amounts: 0.3% (CuGaSe2), 6.7% (CuInSe2), 5% (AgInSe2), 5% (ZnGeP2), 6% (ZnGeP2), 0.4% (ZnSnP2), 0.7% (ZnSiAs2), 2.6% (ZnGeAs2), 1.2% (ZnSnAs2), 3.8% (CdGeP2), 6.4% (CdGeAs2), the results for heat of fusion differ from experimental values by the following amounts: 2.6% (CuGaS2), 0.6% (CuInTe2), 6% (ZnGeAs2), 8.8% (ZnSiAs2) and the results for entropy of fusion differ from experimental values by the following amounts: 6% (CuInSe2), 8% (CdSiP2).

Study on Thermodynamic Properties and Elastic Deformation of Full-Heusler Alloys Co2TaGa and Co2VGa by Statistical Moment Method

Heusler alloy is a ferromagnetic alloy based on the Heusler phase. It is an intermetallic alloy between metallic and non-metallic elements that can be non-ferromagnetic and has a BCC crystal structure. This paper presents the theory of thermodynamics and elastic deformation of full-Heusler A2BC alloy with BCC structure built on the basis of statistical moment method (SMM). The paper presents numerical results for the temperature and pressure dependence of the mean nearest neighbor distance between two atoms, the density, the volume, the thermal expansion coefficient, the isotherm and adiabatic compressibilities, the isothermal elastic modulus, the heat capacities at constant volume and pressure, Young’s modulus, the bulk modulus, longitudinal and transverse wave velocities of alloys Co2TaGa and Co2VGa when using the coordination sphere method and the Mie–Lennard-Jones pair interaction potential. Some SMM calculation results agree well with available ab initio calculation results.

Bioclimatic similarity between species locations and their environment revealed by dimensionality reduction analysis

Species distribution modeling is an active research topic with applications in conservation management, pest risk assessment, and population ecology. Several machine-learning methods have been applied to estimate species distribution. Non-linear dimensionality reduction techniques aim to preserve the similarity among objects at a reduced dimension for visualization, clustering, and feature selection. We propose a framework that uses Uniform Manifold Approximation and Projection (UMAP) to analyze bioclimatic variables associated with environmental (background) and species samples. Our objective was to identify geographic areas similar to those inhabited by the species. We hypothesize that the similarity between species locations and their environment in the reduced dimension will reflect similarity in the multivariate bioclimatic space. We estimated the probability of background points near a species point utilizing the latent nearest neighbor distance distribution. We tested this procedure with ten insect pest species of global importance and found that UMAP was able to generate a gradient of similarity between geographic areas and species occurrence. We also found that background-species latent distance tends to have a convergent non-linear relationship with the mean value of bioclimatic variables, thus supporting our key assumption. The performance of UMAP as a binary classifier and comparison with MaxEnt supports its use in modeling of species distribution. Potential applications are discussed for multi-species and multi-scenario analysis, as well as projection to new regions.

Knockout of Hermansky-Pudlak syndrome 5 (hps5) leads to red tilapia with reduced melanophores and iridophores

Tilapia as an economically important fish is also an excellent model for studying pigment cell biology and body color formation. In the present study, we engineered a red tilapia by mutation of hps5 using CRISPR/Cas9 gene editing of a target site in exon 2. Disruption of HPS5 led to a significant decrease in the numbers of melanophores and iridophores, and a significant increase in xanthophores, which led to a yellowish-transparent body color in early stages (5–30 dpf, days post fertilization). Slow recovery of iridophore numbers, and increased numbers of xanthophores with shorter nearest-neighbor distances than in wild-type fish was observed at 150 dpf, which finally led to a red tilapia with reddish pigmentation in fins. The hps5−/− mutants also showed several transparent cracks (absence of melanin, iridophores and xanthophores) in iris development. Besides, hps5 was also found to be fundamental for xanthophore development, and even the distance between each of them. Our hps5 mutants provide an excellent new model for studies of HPS5 function. Additionally, the red tilapia mutants may also have potential to serve as new germplasm for aquaculture, or function as a gene resource for genetic modification and breeding of red tilapia and the other related ornamental and food fish in aquaculture. More importantly, this study may have significant values in the area of development and evolution of pigmentation patterns of fish species.

Novel insight into the physics of short-range ordered nanoholes: Newly defined lattice model and transmittance response related to lattice parameters and ordering evolution

This paper presents unforeseen conceptualization, methods and results on the physics of short-range ordered (SRO) gold nanohole (NH) distributions, fabricated by a recent protocol developed by the authors. The straightforward extension to SRONHs of the existing knowledge about periodic NH arrays is confuted and an alternative interpretative picture is proposed and discussed based on three main advancements. First, it is set up a so-called short-range lattice (SR-Lat) method to rigorously and fully characterize the coverage-dependent short-range ordering through the determination of local coordination and periodicity length (aSR) of the NH arrangement. Second, it is demonstrated the failure of the common assumption that the average center-to-center distance of nearest neighbor colloids/nanoholes (dNN) is the characteristic length-scale of SRONHs and aSR is set as the proper periodicity parameter. Third, a predictive relationship is formulated between the wavelength of the propagating plasmon modes and aSR that highlights inherent differences with respect to periodic NHs.The presented results lay rigorous foundation for studying systems with correlated diosrdering in general and for making predictions useful not only in design and applications of SRONHs, but also on the surface physics in the photonics and sensing fields.

Properties of a Random Bipartite Geometric Associator Graph Inspired by Vehicular Networks.

We consider a point process (PP) generated by superimposing an independent Poisson point process (PPP) on each line of a 2D Poisson line process (PLP). Termed PLP-PPP, this PP is suitable for modeling networks formed on an irregular collection of lines, such as vehicles on a network of roads and sensors deployed along trails in a forest. Inspired by vehicular networks in which vehicles connect with their nearest wireless base stations (BSs), we consider a random bipartite associator graph in which each point of the PLP-PPP is associated with the nearest point of an independent PPP through an edge. This graph is equivalent to the partitioning of PLP-PPP by a Poisson Voronoi tessellation (PVT) formed by an independent PPP. We first characterize the exact distribution of the number of points of PLP-PPP falling inside the ball centered at an arbitrary location in R2 as well as the typical point of PLP-PPP. Using these distributions, we derive cumulative distribution functions (CDFs) and probability density functions (PDFs) of kth contact distance (CD) and the nearest neighbor distance (NND) of PLP-PPP. As intermediate results, we present the empirical distribution of the perimeter and approximate distribution of the length of the typical chord of the zero-cell of this PVT. Using these results, we present two close approximations of the distribution of node degree of the random bipartite associator graph. In a vehicular network setting, this result characterizes the number of vehicles connected to each BS, which models its load. Since each BS has to distribute its limited resources across all the vehicles connected to it, a good statistical understanding of load is important for an efficient system design. Several applications of these new results to different wireless network settings are also discussed.

Structure-function correlation of retinal photoreceptors in PRPH2-associated central areolar choroidal dystrophy patients assessed by high-resolution scanning laser imaging and microperimetry.

High Magnification Module (HMM™, Heidelberg Engineering, Heidelberg, Germany) imaging is a novel technique, designed to visualize the retina at a cellular level. To assess the potential of HMM™-based metrics as endpoints for future trials, we evaluated correlations between structural HMM™ cone metrics, spectral-domain OCT (SD-OCT, Heidelberg Engineering, Heidelberg, Germany) and retinal sensitivity on microperimetry (MP, MAIA, CenterVue, Padova, Italy) in healthy subjects and p.(Arg142Trp) PRPH2-associated Central Areolar Choroidal Dystrophy (CACD) patients. We projected a default 10° MP grid on composite HMM™ images and performed automated cone density (CD), intercell distance (ICD) and nearest neighbour distance (NND) analysis at stimuli located at 3° and 5° retinal eccentricity. We manually measured intrasubject outer retinal thickness on SD-OCT in absolute and relative scotomas, located outside of focal atrophy. We included 15 CACD patients and five healthy subjects. We found moderate-to-strong correlations of HMM™ metrics and MP sensitivity at 3° eccentricity from the fovea. We found the outer retina at the locations of absolute scotomas to be statistically significant thinner (p = 0.000003, one-sample t-test), as the outer retinal thickness at locations of relative scotomas. Interestingly, HMM™ metrics of these areas did not differ significantly. We found significant correlations between structural photoreceptors metrics on HMM™ imaging and retinal sensitivity on MP in healthy subjects and CACD patients. A multimodal approach, combining SD-OCT, MP and HMM™ imaging, allows for detailed mapping of retinal photoreceptor integrity and restitution potential, important data that could serve as biomarkers in future clinical trials.

Measuring Convective Organization

Abstract Organized systems of deep convective clouds are often associated with high-impact weather and changes in such systems may have implications for climate sensitivity. This has motivated the derivation of many organization indices that attempt to measure the level of deep convective aggregation in models and observations. Here we conduct a comprehensive review of existing methodologies and highlight some of their drawbacks, such as only measuring organization in a relative sense, being biased toward particular spatial scales, or being very sensitive to the details of the calculation algorithm. One widely used metric, Iorg, uses statistics of nearest-neighbor distances between convective storms to address the first of these concerns, but we show here that it is insensitive to organization beyond the meso-β scale and very contingent on the details of the implementation. We thus introduce a new and complementary metric, Lorg, based on all-pair convective storm distances, which is also an absolute metric that can discern regular, random, and clustered cloud scenes. It is linearly sensitive to spatial scale in most applications and robust to the implementation methodology. We also derive a discrete form suited to gridded data and provide corrections to account for cyclic boundary conditions and finite, open boundary domains of nonequal aspect ratios. We demonstrate the use of the metric with idealized synthetic configurations, as well as model output and satellite rainfall retrievals in the tropics. We claim that this new metric usefully supplements the existing family of indices that can help to understand convective organization across spatial scales. Significance Statement The clustering and organization of convection is associated with high-impact weather and changes could impact climate sensitivity, but no consensus exists on how to best measure organization. Here we suggest a new metric that is robust to the calculation details and can classify scenes as random, clustered, or regular. This new metric can therefore account for spacing of organized convective systems and convective storms on scales spanning tens of kilometers to the entire tropics. We suggest that the new metric Lorg addresses many shortcomings of existing measures and can act as a useful additional tool to further understanding of convective organization.

Root-centric β diversity reveals functional homogeneity while phylogenetic heterogeneity in a subtropical forest.

Root-centric studies have revealed fast taxonomic turnover across root neighborhoods, but how such turnover is accompanied by changes in species functions and phylogeny (i.e., β diversity) remains largely unknown. As β diversity can reflect the degree of community-wide biotic homogenization, such information is crucial for better inference of below-ground assembly rules, community structuring, and ecosystem processes. We collected 2480 root segments from 625 0-30 cm soil profiles in a subtropical forest in China. Root segments were identified into 138 species with DNA-barcoding with six root morphological and architectural traits measured per species. By using the mean pairwise (Dpw ) and mean nearest neighbor distance (Dnn ) to quantify species ecological differences, we first tested the non-random functional and phylogenetic turnover of root neighborhoods that would lend more support to deterministic over stochastic community assembly processes. Additionally, we examined the distance-decay pattern of β diversity, and finally partitioned β diversity into geographical and environmental components to infer their potential drivers of environmental filtering, dispersal limitation, and biotic interactions. We found that functional turnover was often lower than expected given the taxonomic turnover, whereas phylogenetic turnover was often higher than expected. Phylogenetic Dpw (e.g., interfamily species) turnover exhibited a distance-decay pattern, likely reflecting limited dispersal or abiotic filtering that leads to the spatial aggregation of specific plant lineages. Conversely, both functional and phylogenetic Dnn (e.g., intrageneric species) exhibited an inverted distance-decay pattern, likely reflecting strong biotic interactions among spatially and phylogenetically close species leading to phylogenetic and functional divergence. While the spatial distance was generally a better predictor of β diversity than environmental distance, the joint effect of environmental and spatial distance usually overrode their respective pure effects. These findings suggest that root neighborhood functional homogeneity may somewhat increase forest resilience after disturbance by exhibiting an insurance effect. Likewise, root neighborhood phylogenetic heterogeneity may enhance plant fitness by hindering the transmission of host-specific pathogens through root networks or by promoting interspecific niche complementarity not captured by species functions. Our study highlights the potential role of root-centric β diversity in mediating community structures and functions largely ignored in previous studies.

A method for stitching remote sensing images with Delaunay triangle feature constraints

The process of synthesizing multiple images into a seamless panoramic image is referred to as remote sensing image stitching. Existing studies focus less on the influence of topography on the appearance and texture of images and the perturbation of image spectra by topographic changes. This paper presents a remote sensing image stitching method that considers the impact of topography and geomorphology. First, the feature matching was optimized using the Euclidean distance similarity of texture features and the nearest neighbor distance ratio of feature points in remote sensing images as constraints. Then, the Delaunay triangle mesh of feature points in the image overlapping region was constructed, the geometric features of Delaunay triangles were used to optimize the triangle matching and reduce the matching redundancy, and the affine transformation matrix was solved based on the comprehensive consideration of the geometric features of Delaunay triangles and the texture features of the remote sensing images. Finally, the weighted fusion algorithm was applied to stitch and fuse the images. Three image datasets were selected for the experiments, one in which there were large terrain undulations in the imaging regions, one in which the main body of the imaging regions was water, and one in which the overall terrain of the imaging regions had relatively gentle slopes but obscuring features were also present. The results showed that the average correct rates of method feature matching were 89.78%, 94.99%, and 96.17%, which were the best for each algorithm, and the average feature matching times were 4.13, 8.27 and 7.19 s. These times are much lower than those obtained with the APAP and AANAP algorithms and basically the same as those achieved with the SPHP and SURF algorithms. In terms of visual effect, the AG, and indices of the proposed method were all significantly improved compared to the APAP, SPHP, AANAP, and SURF algorithms, the advantages were most obvious when dealing with datasets with large topographic relief in the imaging regions, with the maximum improvement of the AG, and indices were 85.61%, 95.68%, and 93.12%, respectively. Therefore, it is possible to conclude that the proposed method is more suitable for remote sensing image stitching and fusion of different topographic and geomorphological conditions.

Nest characteristics of African crowned eagles and black sparrowhawks in urban mosaic landscapes: Potential constraints in finding nesting sites and implications for exotic tree management

The increase in human population and continuous landscape transformations, especially in urban areas, will result in most of the natural habitats being degraded, significantly reduced in size and lost. Consequently, constraints in acquiring resources such as nesting sites and food may occur. In this study, we investigated the nesting site characteristics of two raptor species in the urban mosaic landscape of Durban, KwaZulu Natal, South Africa, to determine the potential constraints affecting acquiring nesting sites. Between October 2020 and July 2021, we visited a total of 52 nests occupied by the African crowned eagle (Stephanoaetus coronatus, hereafter crowned eagle) and the black sparrowhawk (Accipiter melanoleucus) in our study area and compared the nest characteristics of the two raptors. Our results showed that exotic tree plantations were the most commonly used as nest sites by both species, suggesting that exotic trees may be crucial in providing nesting sites for both species in this highly modified landscape. Furthermore, our results showed that there was no significant difference in nest height, tree cover, nest cover and distance to (i) road, (ii) building and (iii) water of nests occupied by the two species. However, there was a significant difference between tree height and nearest neighbour distance. Tall, mature trees, slightly isolated from other trees, influenced nest site use for our study species. Innovative conservation measures and strategies could be vital in protecting raptor nesting sites (i.e., exotic tree plantations) in urban mosaic landscapes with natural and managed green spaces.

Bunching behaviour in housed dairy cows at higher ambient temperatures

Bunching behavior in cattle may occur for several reasons including enabling social interactions, a response to stress or danger, or due to shared interest in resources such as feeding or watering areas. There is evidence in pasture grazed cattle that bunching may occur more frequently at higher ambient temperatures, possibly due to sharing of fly-load or to seek shade from the direct sun under heat stress conditions. Here we demonstrate how bunching behavior is associated with higher ambient temperatures in a barn-housed UK dairy herd. A real-time local positioning system was used, as part of a precision livestock farming (PLF) approach, to track the spatial position and activity of a commercial dairy herd (∼100 cows) in a freestall barn continuously at high temporal resolution for 4 mo between August and November 2014. Bunching was determined using 4 different spatial measures determined on an hourly basis: herd full and core range size, mean herd intercow distance (ICD), and mean herd nearest-neighbor distance (NND). For hourly mean ambient temperatures above 20°C, the herd showed higher bunching behavior with increasing ambient temperature (i.e., reduced full and core range size, ICD, and NND). Aggregated space-use intensity was found to positively correlate with localized variations in temperature across the barn (as measured by animal-mounted sensors), but the level of correlation decreased at higher ambient barn temperatures. Bunching behavior may increase localized temperatures experienced by individuals and hence may be a maladaptive behavioral response in housed dairy cattle, which are known to suffer heat stress at higher temperatures. Our study is the first to use high-resolution positional data to provide evidence of associations between bunching behavior and higher ambient temperatures for a barn-housed dairy herd in a temperate region (UK). Further studies are needed to explore the exact mechanisms for this response to inform both welfare and production management.

Shoaling behaviour in response to turbidity in three-spined sticklebacks.

Many fresh and coastal waters are becoming increasingly turbid because of human activities, which may disrupt the visually mediated behaviours of aquatic organisms. Shoaling fish typically depend on vision to maintain collective behaviour, which has a range of benefits including protection from predators, enhanced foraging efficiency and access to mates. Previous studies of the effects of turbidity on shoaling behaviour have focussed on changes to nearest neighbour distance and average group-level behaviours. Here, we investigated whether and how experimental shoals of three-spined sticklebacks (Gasterosteus aculeatus) in clear (<10 Nephelometric Turbidity Units [NTU]) and turbid (~35 NTU) conditions differed in five local-level behaviours of individuals (nearest and furthest neighbour distance, heading difference with nearest neighbour, bearing angle to nearest neighbour and swimming speed). These variables are important for the emergent group-level properties of shoaling behaviour. We found an indirect effect of turbidity on nearest neighbour distances driven by a reduction in swimming speed, and a direct effect of turbidity which increased variability in furthest neighbour distances. In contrast, the alignment and relative position of individuals was not significantly altered in turbid compared to clear conditions. Overall, our results suggest that the shoals were usually robust to adverse effects of turbidity on collective behaviour, but group cohesion was occasionally lost during periods of instability.