Average Nearest-neighbor Distance Research Articles

Active Learning for Deep Visual Tracking.

Convolutional neural networks (CNNs) have been successfully applied to the single target tracking task in recent years. Generally, training a deep CNN model requires numerous labeled training samples, and the number and quality of these samples directly affect the representational capability of the trained model. However, this approach is restrictive in practice, because manually labeling such a large number of training samples is time-consuming and prohibitively expensive. In this article, we propose an active learning method for deep visual tracking, which selects and annotates the unlabeled samples to train the deep CNN model. Under the guidance of active learning, the tracker based on the trained deep CNN model can achieve competitive tracking performance while reducing the labeling cost. More specifically, to ensure the diversity of selected samples, we propose an active learning method based on multiframe collaboration to select those training samples that should be and need to be annotated. Meanwhile, considering the representativeness of these selected samples, we adopt a nearest-neighbor discrimination method based on the average nearest-neighbor distance to screen isolated samples and low-quality samples. Therefore, the training samples' subset selected based on our method requires only a given budget to maintain the diversity and representativeness of the entire sample set. Furthermore, we adopt a Tversky loss to improve the bounding box estimation of our tracker, which can ensure that the tracker achieves more accurate target states. Extensive experimental results confirm that our active-learning-based tracker (ALT) achieves competitive tracking accuracy and speed compared with state-of-the-art trackers on the seven most challenging evaluation benchmarks. Project website: https://sites.google.com/view/altrack/.

DNA mismatch repair defect and intratumor heterogeneous deficiency differently impact immune responses in diffuse large B-cell lymphoma

ABSTRACT Deficient (d) DNA mismatch repair (MMR) is a biomarker predictive of better response to PD-1 blockade immunotherapy in solid tumors. dMMR can be caused by mutations in MMR genes or by protein inactivation, which can be detected by sequencing and immunohistochemistry, respectively. To investigate the role of dMMR in diffuse large B-cell lymphoma (DLBCL), MMR gene mutations and expression of MSH6, MSH2, MLH1, and PMS2 proteins were evaluated by targeted next-generation sequencing and immunohistochemistry in a large cohort of DLBCL patients treated with standard chemoimmunotherapy, and correlated with the tumor immune microenvironment characteristics quantified by fluorescent multiplex immunohistochemistry and gene-expression profiling. The results showed that genetic dMMR was infrequent in DLBCL and was significantly associated with increased cancer gene mutations and favorable immune microenvironment, but not prognostic impact. Phenotypic dMMR was also infrequent, and MMR proteins were commonly expressed in DLBCL. However, intratumor heterogeneity existed, and increased DLBCL cells with phenotypic dMMR correlated with significantly increased T cells and PD-1+ T cells, higher average nearest neighbor distance between T cells and PAX5+ cells, upregulated immune gene signatures, LE4 and LE7 ecotypes and their underlying Ecotyper-defined cell states, suggesting the possibility that increased T cells targeted only tumor cell subsets with dMMR. Only in patients with MYC¯ DLBCL, high MSH6/PMS2 expression showed significant adverse prognostic effects. This study shows the immunologic and prognostic effects of genetic/phenotypic dMMR in DLBCL, and raises a question on whether DLBCL-infiltrating PD-1+ T cells target only tumor subclones, relevant for the efficacy of PD-1 blockade immunotherapy in DLBCL.

Soil flooding filters evolutionary lineages of tree communities in Amazonian riparian forests.

Inundations in Amazonian black-water river floodplain result in the selection of different tree lineages, thus promoting coexistence between species. We investigated whether Amazonian tree communities are phylogenetically structured and distributed along a flooding gradient from irregularly flooded forests along streams embedded within upland (terra-firme) forest to seasonally flooded floodplains of large rivers (igapós). Floristic inventories and hydrological monitoring were performed along the Falsino River, a black-water river in the eastern Amazon within the Amapá National Forest. We constructed a presence-and-absence matrix and generated a phylogeny using the vascular plant database available in GenBank. We calculated the standardized values of the metrics of phylogenetic diversity (ses.PD), average phylogenetic distance (ses.MPD), and average nearest-neighbor distance (ses.MNTD) to test whether the history of relationships between species in the community is influenced by inundation. We used the phylogenetic endemism (PE) metric to verify the existence of taxa with restricted distribution. Linear regressions were used to test whether phylogenetic metrics have a significant relationship with the variables: maximum flood height, maximum water table depth, and maximum flood amplitude. The results show that forests subject to prolonged seasonal flooding have reduced taxon richness, low phylogenetic diversity, and random distribution of lineages within communities. On the other hand, terra-firme riparian forests showed higher rates of taxon richness, diversity, and phylogenetic dispersion, in addition to greater phylogenetic endemism. These results indicate that seasonal and predictable soil flooding filters tree lineages along the hydrographic gradient. Different adaptations to root waterlogging are likely requirements for colonization in these environments and may represent an important factor in the diversification of tree lineages in the Amazon biome.

Local and global expansivity in water.

The supra-molecular structure of a liquid is strongly connected to its dynamics, which in turn control macroscopic properties such as viscosity. Consequently, detailed knowledge about how this structure changes with temperature is essential to understand the thermal evolution of the dynamics ranging from the liquid to the glass. Here, we combine infrared spectroscopy (IR) measurements of the hydrogen (H) bond stretching vibration of water with molecular dynamics simulations and employ a quantitative analysis to extract the inter-molecular H-bond length in a wide temperature range of the liquid. The extracted expansivity of this H-bond differs strongly from that of the average nearest neighbor distance of oxygen atoms obtained through a common conversion of mass density. However, both properties can be connected through a simple model based on a random loose packing of spheres with a variable coordination number, which demonstrates the relevance of supra-molecular arrangement. Furthermore, the exclusion of the expansivity of the inter-molecular H-bonds reveals that the most compact molecular arrangement is formed in the range of ∼316-331K (i.e., above the density maximum) close to the temperature of several pressure-related anomalies, which indicates a characteristic point in the supra-molecular arrangement. These results confirm our earlier approach to deduce inter-molecular H-bond lengths via IR in polyalcohols [Gabriel et al. J. Chem. Phys. 154, 024503 (2021)] quantitatively and open a new alley to investigate the role of inter-molecular expansion as a precursor of molecular fluctuations on a bond-specific level.

Spatial Distribution Analysis of Urban Retail Industry Using POI Big Data

With the development of social economy, it is very important to identify urban functional areas and understand the spatial distribution characteristics of urban functional areas for urban scientific planning and government decision-making. Reasonable spatial distribution of urban retail industry is of great significance to promote urban economic development, optimize urban structure, and meet the consumption needs of urban residents. Based on the data of retail industry's POI, GDP, population and transportation in Nanning, China, this paper analyzes the spatial distribution characteristics and formation mechanism of different retail industry clusters in the city, and studies the spatial correlation between retail industry and population, economy, transportation, etc., using the methods of kernel density method, spatial correlation analysis, Getis-Ord G * index statistics, and average nearest neighbor distance. The results show that:(1)On the whole, the retail industry is concentrated in the central urban area of Nanning, spreading from the middle to the surrounding areas. (2)The retail hot spots have formed a multi-center development and surrounding spread pattern in spatial distribution. (3) The spatial distribution of the retail industry is highly related to the main traffic lines. At the same time, the concentration and distribution of the retail industry have a strong spatial correlation with the economy and population.

Transmission electron microscopy reveals clusters of Au–Ag nanoparticles formed in TiO2 thin film, with enhanced plasmonic response

This work reports on the influence of nanoparticle (NP) size distribution and the chemical nature of gold (Au) and/or silver (Ag) NPs in the localized surface plasmon resonance (LSPR) responses. The NPs were produced embedded in a titanium dioxide (TiO2) thin film, deposited by reactive magnetron sputtering technique followed by in-vacuum thermal treatment at 400 °C. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) gave quantitative key information in terms of both the size and distribution of the noble metal NPs. The average Feret diameter was 17 nm (σ = 8) and 55 nm (σ = 28) for Au/TiO2 and Ag/TiO2 films, respectively, while the Au–Ag/TiO2 film showed intermediate values, with an average size of 22 nm (σ = 9). HAAD-STEM, complemented by EDX chemical mapping, revealed an unusual formation of cluster structures containing local distributions of bimetallic (alloyed) Au–Ag NPs. The synergetic characteristics and properties of such bimetallic Au–Ag NPs resulted in an outstanding LSPR sensitivity compared to the monometallic counterparts. Furthermore, the analysis of the average nearest neighbor distances (about one order of magnitude lower than counterparts) suggests the existence of plasmonic hotspots relevant to be explored in sensing and surface-enhanced spectroscopies.

A spatial autocorrelation analysis of road traffic crash by severity using Moran’s I spatial statistics: A comparative study of Addis Ababa and Berlin cities

Methodological advancements in road safety research reveal an increasing inclination toward integrating spatial approaches in hot spot identification, spatial pattern analysis, and developing spatially lagged models. Previous studies on hot spot identification and spatial pattern analysis have overlooked crash severities and the spatial autocorrelation of crashes by severity, missing valuable insights into crash patterns and underlying factors. This study investigates the spatial autocorrelation of crash severity by taking two capital cities, Addis Ababa and Berlin, as a case study and compares patterns in low and high-income countries. The study used three-year crash data from each city. It employed the average nearest neighbor distance (ANND) method to determine the significance of spatial clustering of crash data by severity, Global Moran's I to examine the statistical significance of spatial autocorrelation, and Local Moran's I to identify significant cluster locations with High-High (HH) and Low-Low (LL) crash severity values. The ANND analysis reveals a significant clustering of crashes by severity in both cities, except in Berlin's fatal crashes. However, different Global Moran's I results were obtained for the two cities, with a strong and statistically significant value for Addis Ababa compared to Berlin. The Local Moran's I result indicates that the central business district and residential areas have LL values, while the city's outskirts exhibit HH values in Addis Ababa. With some persistent HH value locations, Berlin's HH and LL grid clusters are intermingled on the city's periphery. Socio-economic factors, road user behavior and roadway factors contribute to the difference in the result. Nevertheless, it is interesting to note the similarity of significant HH value locations on the outskirts of both cities. Finally, the results are consistent with previous studies and indicate the need for further investigation in other locations.

Fine-tuning the electronic properties of Au toward two-dimensional clusters with higher activity for ethanol conversion

Efficient Au/m-ZrO2 catalysts for the conversion of ethanol to acetaldehyde and ethyl acetate were obtained by the deposition precipitation method. The present work investigates the impact of the electronic properties of Au supports on m-ZrO2 catalysts on ethanol dehydrogenation. The Au4f7/2 binding energy (BE) and the average Au-Au nearest-neighbor distances (RAu-Au) were associated with surface defects characterized by CO adsorption. The BE and RAu-Au properties are correlated among themselves, changing by Au loading and pretreatments in an inert atmosphere at different temperatures. Although the RAu-Au unveils a boost of the reaction rates for shorter distances, the coupling of Au and m-ZrO2 produced a bifunctional catalyst. Theoretical studies indicate that molecular ethanol adsorption and formation of the ethoxy intermediate represented a feasible pathway for the activation of ethanol on the Au-ZrO2 interface. The RAu-Au toward of 2D clusters conferred high catalytic activity and low apparent activation energy for ethanol dehydrogenation.

Spatial and temporal assessment of snake encounters in urban Delhi, India

Delhi, the capital city of India is, highly urbanized and surrounded by remnant forest, farms, ridges, and other green areas experience regular snake encounters in and around residential, institutional, and industrial areas. A total of 41 months of sampling from January 2019 to May 2022 was conducted wherein we, studied the snake assemblage in Delhi to determine the species composition, encounter frequency, seasonal activity patterns, and probable encounter sites in an urban setup. We documented 372 individuals belonging to 15 species from seven families out of 23 species found in Delhi. Snakes were found inside forests, public parks, homes, drain networks, streets, office buildings, and even in school-college buildings. The most recorded species being Ptyas mucosa (37.37%, n = 139), Naja naja (19.62%, n = 73), and Lycodon aulicus (13.44%, n = 50). The highest numbers of incidents were reported in the month of July (22.04%, n = 82) and August (19.89%, n = 74) during the peak monsoon season, for identifying high encounter sites, we used a geostatistical modeling tool, Ordinary kriging to identify places having more snake occurrences. We further used a statistical spatial method called average nearest neighbor distance to detect the pattern distribution of snake species. Spatial interpolation done through Ordinary kriging highlighted two areas having concentrated snake encounters. The results of the average nearest neighbor distance analysis showed three species having clustered and two species having dispersed distribution. The incidence of snake encounters was found to be highly seasonal and appeared to be associated mainly with monthly rainfall, temperature, and humidity. The findings of this study on snakes’ distribution patterns provide valuable insights into the conservation of these species. Understanding their habitat preferences and spatial distribution is crucial for the implementation of effective conservation strategies.

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.

Local stability and long distance reliability of tongue ultrasound spline metrics

Tongue ultrasound data arecommonly analyzed by using different metrics. In this study, we evaluate the local stability and long distance reliability of Average Nearest Neighbour Distance (Zharkova and Hewlett, 2009), Median Point-by-Point Distance (Palo, 2020), Procrustes analysis and Modified Curvature Index (Dawson et al., 2015). A metric which has good local stability should map a time-series of splines to a smooth scalar (or vector) time-series and not be very sensitive to small errors in the splining. Similarly, a metric with good long distance reliability should differentiate dissimilar tongue contours—such as different phoneme targets—reliably and without small splining errors significantly affecting the results. We test the metrics with simulated data generated from actual spline data. First, we select keyframes at phoneme target positions. Second, we vary the sampling frequency artificially by interpolating the splines between the keyframes. Third, we vary the level of splining noise by adding small perturbations to the splines at varying magnitudes and frequencies. Based on the simulation results, we will calculate the distributions of each of the metrics as conditioned by sampling frequency and noise level. The code and simulation data will be publicly available.

Spatial assessment of audience accessibility to historical monuments and museums in Qatar during the 2022 FIFA World Cup

Hosting mega sports events is a key driver for sustainable development, particularly through fostering tourism marketing and planning. Although the 2022 FIFA World Cup has received considerable attention, as the first global event hosted in the Middle East and Arab world, studies that highlight and investigate the potential benefits of hosting such an event are rare. This study assessed the geographical accessibility to archaeological sites, monuments, and museums across Qatar, providing clear guidelines on how to represent the national cultural and historical heritage to global audiences during the 2022 mega event, to maximise socioeconomic revenue.Spatial data were assembled within GIS platforms to assess accessibility utilising geospatial techniques, such as the average nearest neighbour, near analysis, spatial autocorrelation (Moran ‘I Index), and cost distance to estimate travel times. The analysis indicated that the archaeological sites are spatially clustered, predominantly concentrated in Doha and Al-Rayan municipalities, where historical and cultural landmarks are located. However, most castles, forts, and archaeological sites located outside the capital zone are less accessible, and at a long distance from hotels and residential areas. As the hosting stadiums are located along the northeast coast and within the most populous zone, the museums, towers, and cultural landscapes are easily accessible within a short travel time (less than 10 min). As a host community, planners and policymakers in Qatar may benefit from this research, as a spatial guideline to promote sustainable development of tourism, through facilitating accessibility to monuments and museums, as well as enriching the representation of the national tangible heritage to a global audience.

Geographic Space and the Issues of Utilization of Primary Health Facilities in Isiala-Mbano, Imo, Nigeria

Primary Health Care is the first point of contact for most Nigerians with respect to the health care system, but the level of clients’ access and utilization are mostly plagued with distinct problems across geographic locations, thereby impeding sustainable development of rural communities. The aim of this study is to evaluate the intriguing relationships existing among location, distance, and the utilization of government-owned primary health care facilities (PHCF) by residents in Isiala-Mbano, Imo State. A stratified random sampling method was used to select a sample population of 475. Questionnaire and interviews were used to elicit information from the respondents, while geospatial tools were used for mapping the spatial distributions of three Health Posts and fourteen Health Centers. Analyses of data using descriptive statistics, geographic information system, nearest neighbour analysis, Pearson product moment correlation coefficient, and student’s t-test revealed that: (i) PHCF’s are randomly distributed within the study area as indicated by the Nearest Neighbour Index of R = 1.164. (ii) Estimated Euclidean distances from users’ houses to nearest PHCFs showed that 66.5 percent of the users live within 1 km and 33.5 percent live between 1 km to 2.3 km from the nearest PHCFs. (iii) Average Nearest Neighbour Distance gave 1.3708 km with good topography. (iv) The ratio of population to health center gave 11,972:1, implying that Isiala-Mbano is adequately served by primary health care centers, but the levels of utilizations were generally very low due to lack of doctors and valid drugs for patients. A test of Hypothesis showed that there is no significant relationship between the distance of primary health care facilities and the level of utilization in the study area. Hence, this study recommended timely health care facility reform through the supply of essential drugs and employment of specialized manpower sustainably to attend to patients in the study area.

Quantification of Spatial Association between Commercial and Residential Spaces in Beijing Using Urban Big Data

Commercial and residential spaces are two core types of geographical objects in urban areas. However, these two types of spaces are not independent of each other. Spatial associations exist between them, and a thorough understanding of this spatial association is of great significance for improving the efficiency of urban spatial allocation and realizing scientific spatial planning and governance. Thus, in this paper, the spatial association between commercial and residential spaces in Beijing is quantified with GIS spatial analysis of the average nearest neighbor distance, kernel density, spatial correlation, and honeycomb grid analysis. Point-of-interest (POI) big data of the commercial and residential spaces is used in the quantification since this big data represents a comprehensive sampling of these two spaces. The results show that the spatial distributions of commercial and residential spaces are highly correlated, maintaining a relatively close consumption spatial association. However, the degrees of association between different commercial formats and residential spaces vary, presenting the spatial association characteristics of “integration of daily consumption and separation of nondaily consumption”. The commercial formats of catering services, recreation and leisure services, specialty stores, and agricultural markets are strongly associated with the residential spaces. However, the development of frequently used commercial formats of daily consumption such as living services, convenience stores, and supermarkets appears to lag behind the development of residential spaces. In addition, large-scale comprehensive and specialized commercial formats such as shopping malls, home appliances and electronics stores, and home building materials markets are lagging behind the residential spaces over a wide range. This paper is expected to provide development suggestions for the transformation of urban commercial and residential spaces and the construction of “people-oriented” smart cities.

Computational Exploration on the Structural and Optical Properties of Gold-Doped Alkaline-Earth Magnesium AuMgn (n = 2-12) Nanoclusters: DFT Study.

Using CALYPSO crystal search software, the structural growth mechanism, relative stability, charge transfer, chemical bonding and optical properties of AuMgn (n = 2–12) nanoclusters were extensively investigated based on DFT. The shape development uncovers two interesting properties of AuMgn nanoclusters contrasted with other doped Mg-based clusters, in particular, the planar design of AuMg3 and the highly symmetrical cage-like of AuMg9. The relative stability study shows that AuMg10 has the robust local stability, followed by AuMg9. In all nanoclusters, the charge is transferred from the Mg atoms to the Au atoms. Chemical bonding properties were confirmed by ELF analysis that Mg-Mg formed covalent bonds in nanoclusters larger than AuMg3. Static polarizability and hyperpolarizability calculations strongly suggest that AuMg9 nanocluster possesses interesting nonlinear optical properties. Boltzmann distribution weighted average IR and Raman spectroscopy studies at room temperature verify that these nanoclusters are identifiable by spectroscopic experiments. Finally, the average bond distance and average nearest neighbor distance were fully investigated.

Use of Habitat Suitability Model as a Tool to Highlight Best Conservation Area for the Red-bellied Monkey (Cercopithecus erythrogaster erythrogaster) in Southern-Benin, West Africa.

Wildlife habitats are increasingly degraded as a result of anthropogenic pressures. The IUCN recently updated the red list category of the red-bellied monkey (Cercopithecus erythrogaster erythrogaster) from Endangered to Critically Endangered due to its population decrease, habitats degradation and various threats to its conservation. It is therefore important to identify areas of great importance for the sustainable conservation of the subspecies. The Species Distribution Model (SDM) is a method increasingly used by conservationists to help find these areas and thus limit areas of intervention. In this study, maximum entropy model was used to identify suitable habitats for the red-bellied monkey in landscape of southern-Benin from occurrence data and selected predictor variables according to ecological habitat requirements of the subspecies. The suitable habitat model for the red-bellied monkey has a good predictive power (AUC = 0.97). The variables that contributed most to the final model, as indicated by the permutation importance, were: Distance to Water (47.7%), Land Cover Class (23.1%), Brightness (17.0%), Wetness (4.7%), Human Population Size (2.8%) and Elevation (2.2%). Thus, using Maximum Training sensitivity and Specificity threshold, 3.62% of the landscape was classified as suitable and 96.38% was classified as unsuitable for the red-bellied monkey. The largest area of suitable habitat is found in protected areas (57.46%), mainly in the Lama Forest Reserve central core (49.5%). The landscape is fragmented and 91.49% of suitable habitats are between 0 and 0.01 km2 in size. The mean size of suitable habitats in the landscape is 0.017 ± 0.545 km2. Nevertheless, there is no significant difference between the mean size of suitable habitats in protected areas and those in the unprotected area (P = 0.061, Mann-Whitney U tests). The Average Nearest Neighbor Distance of suitable habitats in the landscape is low (0.139 km) and the Average Nearest Neighbor Ratio (R) is less than 1 (R = 0.408, p < 0.001). Those features indicate a clustered pattern of suitable habitats for the red-bellied monkey in the landscape. This makes it possible to foresee the establishment of connections between the isolated suitable habitats and thus allow for the long-term conservation of the species populations.

西双版纳地区森林变化碳效应与生态效益评估

减少发展中国家因森林砍伐与森林退化导致的碳排放和保持碳储量（REDD+），不仅能减少因森林砍伐和森林退化造成的碳排放，而且还可以带来其它生态效益，如减缓森林破碎化、保护生物多样性和增强水土保持功能等。以中国的西双版纳地区为研究区域，以毁林最严重的1976-2007年为REDD+基线，基于卫星影像，并结合植被指数，提取了研究区的土地利用变化信息。基于IPCC温室气体清单方法，计算了研究区的森林碳储量变化。在此基础上，对REDD+的碳汇效益和生态效益进行了系统综合评估。结果显示：（1）1976-2007年间天然林碳储量从占总碳储量的78.24%减少至50.52%，这是造成西双版纳地区碳储量减少的主要原因。（2）1976-2007年，天然林的斑块数量和平均最近邻距离分别增加了120.00%和25.21%，平均斑块面积下降了71.98%，说明天然林的破碎化程度加剧。从研究区整体景观格局来看，斑块数量、Shannon多样性指数和Shannon均一性指数分别增加了8.16%、51.39%和34.07%；与此同时，平均斑块面积和景观内聚力指数分别下降了26.26%和2.13%，表明研究区整体景观格局朝破碎化方向发展，这和碳排放的增加相一致。（3）该区的土壤侵蚀程度逐年加剧，并与碳储量的减少密切相关。分析表明，土壤侵蚀剧烈的区域，其平均碳排放也相对较高。1999年到2007年间，剧烈侵蚀区域的平均碳排放是轻度侵蚀区域的6倍多。这些结果说明：如果REDD+政策得以实施，不仅能减少因毁林和森林退化导致的碳排放，而且能带来高的生态效益。从这个角度出发，REDD+的本质可以认为是以"增汇"或"减排"为主导功能，同时提升生态效益的一种管理方式。;The REDD+ partnership works to promote the reduction of greenhouse gas (GHG) emissions by reducing emissions from deforestation and forest degradation in the developing countries through positive incentives and conversation of forest carbon stocks. It is regarded as an essential component of the post-2012 climate regime to stabilize GHG emissions and engage the developing countries in worldwide mitigation endeavors. If cost-efficient carbon benefits can be achieved through REDD+, increases in atmospheric CO₂ concentrations could be slowed, effectively buying much needed time for countries to move to lower emissions technologies. We chose tropical forests in Xishuangbanna of China as our study area and took the most severe deforestation from 1976 to 2007 as the baseline of REDD+. Land use information was obtained through the combination of Landsat TM images and Normalized Difference Vegetation Index masks. Forest carbon storage change in the study area was firstly calculated based on IPCC methodology. Secondly ecosystem-based benefits from REDD+ were assessed systematically. Our results showed that from 1976 to 2007, the natural forest carbon storage decreased from 78.24% to 50.52% of total carbon storage, which was the main reason for the reduction of carbon storage in Xishuangbanna. At the meantime, significant degradation of ecosystem services emerged. This was demonstrated by two important indicators:forest fragmentation and soil erosion. For example, from 1976 to 2007 the percentage change in the carbon stocks was 1.4%, accompanying with increasing 8.16% in number of patches, 51.39% in Shannon's diversity index and 34.07% in shannon's evenness index. Meanwhile, mean path area and patch cohesion index decreased by 26.26% and 2.13%, respectively. It suggested that the forest ecosystem was changing in both carbon storage and forest landscape structure. The number of patches and average nearest neighbor distance of natural forest increased by 120.00% and 25.21%, respectively, and the average patch area decreased by 71.98%, indicating the degree of exacerbated fragmentation in natural forest. In this sense, carbon emission and forest fragmentation were well integrated. Furthermore, we investigated relationship between carbon emission and soil erosion and high correlation was found. For example, carbon emissions which accounted for 45% of the total located in the high erosion area, which is 18% of the whole study area. As a result, when forests that would have been lost or degraded are retained or restored through REDD+, they deliver ‘multiple benefits’ in addition to protecting or enhancing carbon stocks. These ecosystem-based benefits may include conservation of forest biodiversity, water regulation, soil conservation, timber, forest foods and other non-timber forest products, most of which have been demonstrated or proved in this study. By securing benefits beyond carbon, REDD+ has the potential to encourage countries to realize a broader range of values.

Co-registration of single tree maps and data captured by a moving sensor using stem diameter weighted linking

A new method for the co-registration of single tree data in forest stands and forest plots applicable to static as well as dynamic data capture is presented. This method consists of a stem diameter weighted linking algorithm that improves the linking accuracy when operating on diverse diameter stands with stem position errors in the single tree detectors. A co-registration quality metric threshold, QT, is also introduced which makes it possible to discriminate between correct and incorrect stem map co-registrations with high probability (&gt;99%). These two features are combined to a simultaneous location and mapping-based co-registration method that operates with high linking accuracy and that can handle sensors with drifting errors and signal bias. A test with simulated data shows that the method has an 89.35% detection rate. The statistics of different settings in a simulation study are presented, where the effect of stem density and position errors were investigated. A test case with real sensor data from a forest stand shows that the average nearest neighbor distances decreased from 1.90 m to 0.51 m, which indicates the feasibility of this method.

Rapid Initial Morphospace Expansion and Delayed Morphological Disparity Peak in the First 100 Million Years of the Archosauromorph Evolutionary Radiation

Adaptive radiations have played a major role in generating modern and deep-time biodiversity. The Triassic radiation of the Archosauromorpha was one of the most spectacular vertebrate radiations, giving rise to many highly ecomorphologically varied lineages—including the dinosaurs, pterosaurs, and stem-crocodylians—that dominated the larger-bodied land fauna for the following 150 Ma, and ultimately gave rise to today’s &amp;gt; 10,000 species of birds and crocodylians. This radiation provides an outstanding testbed for hypotheses relating to adaptive radiations more broadly. Recent studies have started to characterize the tempo and mode of the archosauromorph early adaptive radiation, indicating very high initial rates of evolution, non-competitive niche-filling processes, and previously unrecognized morphological disparity even among non-crown taxa. However, these analyses rested primarily either on discrete characters or on geometric morphometrics of the cranium only, or even failed to fully include phylogenetic information. Here we expand previous 2D geometric morphometric cranial datasets to include new taxa and reconstructions, and create an analogous dataset of the pelvis, thereby allowing comparison of anatomical regions and the transition from “sprawling” to “upright” posture to be examined. We estimated morphological disparity and evolutionary rates through time. All sampled clades showed a delayed disparity peak for sum of variances and average nearest neighbor distances in both the cranium and pelvis, with disparity likely not saturated by the end of the studied time span (Late Jurassic); this contrasts with smaller radiations, but lends weight to similar results for large, ecomorphologically-varied groups. We find lower variations in pelvic than cranial disparity among Triassic-Jurassic archosaurs, which may be related to greater morphofunctional constraints on the pelvis. Contrasting with some previous work, but also confirming some previous findings during adaptive radiations, we find relatively widespread evidence of correlation between sampled diversity and disparity, especially at the largest phylogenetic scales and using average displacement rather than sum of variances as disparity metric; this also demonstrates the importance of comparing disparity metrics, and the importance of phylogenetic scale. Stem and crown archosauromorphs show a morphological diversification of both the cranium and pelvis with higher initial rates (Permian–Middle Triassic and at the base of major clades) followed by lower rates once diversification into niches has occurred (Late Triassic–Jurassic), indicating an “early burst” patternsensu lato. Our results provide a more detailed and comprehensive picture of the early archosauromorph radiation and have significant bearing on the understanding of deep-time adaptive radiations more broadly, indicating widespread patterns of delayed disparity peaks, initial correlation of diversity and disparity, and evolutionary early bursts.