Small Patches Research Articles

Two new species of Luciogobius Gill (Teleostei: Gobiidae) from the Matsu Islands in Taiwan

Two new gobiid fishes of Luciogobius Gill, 1859 have recently been collected from the intertidal waters of the Matsu Islands in Taiwan. The first new species, Luciogobius matsuensis sp. nov., is characterized by the following unique combination of features: (1) second dorsal fin rays: I/12 and anal fin rays I/12; (2) pectoral fin rays modally 16 and with one upper, short free soft ray; (3) vertebral count modally 17+20–21=37–38; and (4) specific coloration: second dorsal fin translucent with tiny brown spots; caudal fin with many tiny brown spots; anal fins pale yellow and translucent, spotless, and darker in its rays; and pectoral fin creamy yellow with anterior 2/3 region with tiny brownish to black spots. The second new species, Luciogobius dongyinensis sp. nov., is characterized by the following unique combination of features: (1) second dorsal fin rays: I/16 and anal fin rays I/16; (2) pectoral fin rays modally 14 and with 2 upper, short free soft rays; (3) vertebral count modally 18+23=41; and (4) specific coloration: a long infraorbital deep brown stripe below eye; a long deep brown stripe above and along upper jaw; pectoral fin with many small patches of melanophores except posterior, distal 1/5 region; and caudal fin brown with many light rounded spots. A brief discussion of their own related species will also be addressed.

Leveraging textured flickers: a leap toward practical, visually comfortable, and high-performance dry EEG code-VEP BCI

Reactive Brain-Computer Interfaces (rBCIs) typically rely on repetitive visual stimuli, which can strain the eyes and cause attentional distraction. To address these challenges, we propose a novel approach rooted in visual neuroscience to design visual Stimuli for Augmented Response (StAR). The StAR stimuli consist of small, randomly-oriented Gabor or Ricker patches that optimize foveal neural response while reducing peripheral distraction.

Methods: In a factorial design study, 24 participants equipped with an 8-dry electrode EEG system focused on series of target flickers presented under three formats: traditional Plain flickers, Gabor-based, or Ricker-based flickers. These flickers were part of a five-class Code Visually Evoked Potentials (c-VEP) paradigm featuring low-frequency, short, and aperiodic visual flashes.

Results: Subjective ratings revealed that Gabor and Ricker stimuli were visually comfortable and nearly invisible in peripheral vision compared to plain flickers. Moreover, Gabor and Ricker-based textures achieved higher accuracy (93.6% and 96.3%, respectively) with only 88 seconds of calibration data, compared to plain flickers (65.6%). A follow-up online implementation of this experiment was conducted to validate our findings in naturalistic operations. During this trial, remarkable accuracies of 97.5% in a cued task and 94.3% in an asynchronous digicode task were achieved, with a mean decoding time as low as 1.68 seconds.

Conclusion: This work demonstrates the potential to expand BCI applications beyond the lab by integrating visually unobtrusive systems with gel-free, low-density EEG technology, thereby making BCIs more accessible and efficient. The datasets, algorithms, and BCI implementations are shared through open-access repositories.

Multi-scale forest heterogeneity promotes occupancy of dusky-footed woodrats in the Sierra Nevada

Forested landscapes are naturally heterogeneous, with the distribution of resources influencing animal habitat selection at multiple spatial scales. However, anthropogenic activities and changing disturbance regimes have reorganized how forests are structured from fine- to landscape-scales, generally with unknown consequences for forest-associated wildlife. For instance, fire suppression and selective logging in the western US has led to more homogeneous forests with fewer small patches of early-successional vegetation. As forest management aims to improve forest resilience to extreme fire and drought by restoring historical disturbance regimes and modifying forest structure through fuel management, there is a need for studies that evaluate how animals respond to forest heterogeneity at multiple scales. Here, we estimated occupancy for the dusky-footed woodrat (Neotoma fuscipes), an important prey species for many forest predators including the California spotted owl (Strix occidentalis occidentalis), relative to forest structure and composition at site-, patch-, and landscape-scales within landscapes where forest heterogeneity was created by even-aged timber management. Woodrats were more likely to occupy sites with greater canopy cover, understory cover, and hardwoods – particularly tanoak (Notholithocarpus densiflorus) – and smaller patches of young forest. Woodrats were also more likely to occupy mature forests in close proximity to younger forests, suggesting that young forest patches with more favorable local conditions can produce populations that recruit into adjacent, lower-quality mature forests. Our results suggest that creating small (∼2 ha) patches of high-quality woodrat habitat (i.e., young forests with dense understory and hardwoods) could provide “fishing holes” for spotted owls and other predators by supporting higher woodrat densities in surrounding mature forests managed for fuels – thus helping to meet both spotted owl conservation and forest resilience objectives. More broadly, we highlight the benefits of multi-scale studies and demonstrate that restoring landscape heterogeneity, including the creation of small early-successional forests, may benefit species conservation without compromising efforts to improve resilience in forest ecosystems globally.

Aberration correction in complex media over multiple isoplanatic patches by exploiting their spatial correlation

Optical imaging in complex media, such as biological tissues, poses significant challenges due to the presence of aberrations and scattering that distort wavefronts and degrade image quality. Wavefront correction has emerged as a crucial technique for mitigating these effects. Recent advances, such as adaptive optics, wavefront shaping, and matrix-based methods, have made significant strides in correcting for wavefront distortions to achieve high-resolution imaging. However, current approaches face challenges when addressing spatially varying distortions and small isoplanatic patches, where the corrections lose reliability due to the rapid spatial variation of distortions. To address this limitation, we introduce a method that exploits the spatial correlation of wavefront distortions across neighboring isoplanatic patches. This approach, termed "inward-outward progression", enables a more reliable wavefront correction across multiple small patches. The process involves two key steps: (1) the inward progression, where a small zone surrounding a pixel is optimized while progressively shrinking the optimized region, and (2) the outward progression, where the wavefront correction phases of the corrected zone serve as the initial guess to optimize adjacent areas, extending the correction from the small zone at the inward progression until the entire field of view is covered. We validate this method by imaging a USAF resolution target under 700-µm-thick chicken breast. Our approach shows a significant improvement in image quality and superior performance over existing techniques, paving the way for noninvasive imaging where conventional methods face substantial limitations due to the spatially varying aberrations and scattering.

Kinematics of Post-Wildfire Debris Flow Initiation Mechanism: Impact of Hydrophobic Layer Spatial Variability and Particle Size

Post-wildfire debris flow events have been more frequent due to climate change and increased wildfire adversity. Changes in non-cohesive soil hydrophobicity, burn, and vegetation removal during wildfires dramatically enhance slopes' vulnerability to rainfall-induced failure in the arid Southwest USA and similar areas worldwide. This paper contributes to a better understanding the hydrophobic sand slope failure mechanism using experiments and theory. In total, 36 indoor raining experiments use different configurations of fine, medium, and coarse hydrophobic sands subjected to various rain intensities on different slope inclinations. Specific findings contribute to understanding how the spatial variability of the post-wildfire hydrophobic layer, concerning depth and the sand grain size variations, affects the slope failure mechanisms. Clarifying slope failure mechanisms in different layouts is crucial for understanding the initiation and further spatiotemporal debris flow evolution. Results indicate that the surficial hydrophobic layer fails because erosion develops simultaneously from many small failure patches. Erosion pattern, time to failure, water, and sediment overflow temporal dynamics correlate to the dominant sand grain size. Furthermore, seepage-induced shallow infinite slope occurs when the hydrophobic sand layer develops below the surface. Finally, this study identifies the fine sand as the most vulnerable to failure in both configurations.

Carbon stocks and sequestration from small tree patches in grassland landscapes in Aotearoa-New Zealand

ABSTRACT Small patches of trees add structural heterogeneity to grassland landscapes, support biodiversity, and provide essential ecosystem services including carbon stocks and sequestration, erosion control, and shade provision. In Aotearoa-New Zealand (A-NZ) small patches of trees have further cultural significance within Te Ao Māori – the worldview of the indigenous Māori people. However, economic pressures have driven the management of grasslands either towards removing tree cover to enhance agricultural productivity, or large-scale conversion of grassland to production forests. Protecting existing small patches of trees, and encouraging their establishment across grassland landscapes, is challenging since the current extent and benefits of these patches is not known. This study demonstrates the critical contributions of small tree patches (those less than one hectare in area) in A-NZ grassland landscapes. Using a high-resolution tree cover dataset, we mapped 1,639,015 small tree patches in grasslands across A-NZ, with grassland small tree patches covering a total land area of between 185,589 ha and 187,928 ha. We used a probabilistic simulation approach to estimate carbon stocks and annual sequestration, revealing a potential aboveground carbon stock between 11.6 and 29.3 million tonnes (Mt) of carbon and an annual biomass sequestration of 0.3 Mt to 0.8 Mt. Despite their current exclusion from the national carbon emissions market, economic valuation suggests a liability of between $NZ 86.9 million and $NZ 8.6 billion (€47.9 million to €4.7. billion) if the small tree patches were felled, and a market value of between $NZ 2.0 million and $NZ 237.6 million (€1.1 and 130.9 million) annually for sequestration. Existing policies, including afforestation incentives, do not encourage protection or establishment of small patches of trees. Significant policy adjustments are required to recognize, protect, and incentivize the conservation and establishment of small patches of trees within grassland landscapes.

Dual attention model with reinforcement learning for classification of histology whole-slide images

Digital whole slide images (WSIs) are generally captured at microscopic resolution and encompass extensive spatial data (several billions of pixels per image). Directly feeding these images to deep learning models is computationally intractable due to memory constraints, while downsampling the WSIs risks incurring information loss. Alternatively, splitting the WSIs into smaller patches (or tiles) may result in a loss of important contextual information. In this paper, we propose a novel dual attention approach, consisting of two main components, both inspired by the visual examination process of a pathologist: The first soft attention model processes a low magnification view of the WSI to identify relevant regions of interest (ROIs), followed by a custom sampling method to extract diverse and spatially distinct image tiles from the selected ROIs. The second component, the hard attention classification model further extracts a sequence of multi-resolution glimpses from each tile for classification. Since hard attention is non-differentiable, we train this component using reinforcement learning to predict the location of the glimpses. This approach allows the model to focus on essential regions instead of processing the entire tile, thereby aligning with a pathologist’s way of diagnosis. The two components are trained in an end-to-end fashion using a joint loss function to demonstrate the efficacy of the model. The proposed model was evaluated on two WSI-level classification problems: Human epidermal growth factor receptor 2 (HER2) scoring on breast cancer histology images and prediction of Intact/Loss status of two Mismatch Repair (MMR) biomarkers from colorectal cancer histology images. We show that the proposed model achieves performance better than or comparable to the state-of-the-art methods while processing less than 10% of the WSI at the highest magnification and reducing the time required to infer the WSI-level label by more than 75%. The code is available at github.

Why there are more species in several small patches versus few large patches: A multispecies modelling approach

Abstract As global biodiversity is rapidly declining due to habitat loss, it is important to determine how to protect it. The policies of many conservation agencies are still prioritizing the preservation of a single large habitat area (SL) versus several small areas of the same size (SS), despite empirical support favouring SS. However, to date, while many studies have explored this issue using model communities, the results are mixed. In competitive community models, fragmentation has a negative effect at low habitat amounts, whereas neutral community models suggest positive effects. This work aims to explore spatial multispecies models to verify the SS > SL pattern and determine its causes. We used three types of models: a classical neutral, neutral with habitat selection and a competitive hierarchical model. All models have three parameters, namely extinction, reproduction and dispersal distance. In the classical neutral model, species are equivalent and have the same parameters; when there is a reproduction event, they send the propagule to a surrounding patch blindly, and if the patch is already occupied, the propagule dies. In the neutral with habitat selection model, the propagules select an empty patch, so their survival is ensured. In the hierarchical model, species have competitive dominance and more dominant ones can replace the less dominant with a replacement rate parameter. We use 100 species and start simulating the colonization of an empty area; then, we destroy a fixed amount of habitat using different regular patch sizes. The results for all models are almost always that SS retains more species than SL. The extinction of species in patches depends on the quotient between reproduction and extinction rates in relation to patch size. The only case when SL > SS is when dispersal is insufficient to connect patches, and patch size is smaller than the minimum to prevent extinction. If patch size is above the critical size to maintain local populations, the SS > SL pattern is due to the sampling effect of aggregated species distribution combined with the reduction of dispersal ability of species. High‐dispersal rates produce the homogenization of species distribution and a reduction of species richness and this is why habitat fragmentation by habitat loss retains more species when patches are smaller. The model predicts that if a set of species have more dispersal capabilities, the SS effect would be lower than for species with less dispersal. Read the free Plain Language Summary for this article on the Journal blog.

Stable Isotopes Analysis of Black Lion Tamarins Reveals Increasing Arthropod Consumption When Fruit Productivity Decreases in Forest Fragments.

Given the cryptic and elusive nature of prey consumption, quantifying its contribution to the diet of free-ranging primates using behavioral methods is challenging. In this context, the use of carbon and nitrogen-stable isotopes represents a promising alternative approach. Here, we used stable isotope analysis to estimate the proportion of arthropods and fruits in the diet of black lion tamarins (Leontopithecus chrysopygus), an endangered primate endemic to the Brazilian Atlantic Forest. To do so, we ran stable isotope mixing models using isotopic data from hair samples of black lion tamarins living in six forest fragments showing different levels of habitat quality. Furthermore, we ran linear mixed models to assess the influence of habitat quality-fruit productivity (estimated by tree total basal area) and arthropod biomass - and individual characteristics (sex and body mass) on tamarins' δ15N values (a proxy for trophic position). Our results revealed that arthropods contributed more to black lion tamarins' diet than reported in previous behavioral studies, suggesting that behavioral observations may considerably underestimate the importance of arthropodivory in the diet of arboreal primates. The degree of arthropodivory and frugivory was similar within groups, in line with the strong group cohesion and synchronization of feeding behaviors of this species and supporting the role of site-specific habitat characteristics on dietary choice. Arthropod consumption was higher in areas with lower fruit productivity and did not increase when arthropod biomass increased, suggesting that fruits represent a limiting but preferred resource for this species. These results demonstrate the dietary plasticity of black lion tamarins in areas of lower forest quality, where they manage to compensate low fruit productivity by shifting to a diet richer in arthropods. Considering that this species occurs within a highly fragmented landscape, preserving and protecting small forest patches remains crucial for the conservation of this species.

Long-term patterns of post-fire harvest diverge among ownerships in the Pacific West, U.S.A.

Abstract Post-fire harvest (PFH) is a forest management practice designed to salvage value from burned timber, mitigate safety hazards from dead trees, reduce long-term fuels, and prepare sites for replanting. Despite public controversy and extensive ecological research, little is known about how much PFH occurs on private and public lands in the U.S. Pacific West, or how practices changed with shifting forest policy and increasing area burned over the last three decades. We mapped PFH across 2.2M burned hectares in California, Oregon, and Washington between 1986-2017 and used time series intervention analysis to compare trends in area, rate (% of burned area harvested), and mean patch size between private (0.5M ha) and federal (1.6M ha) forest land and across a gradient of burn severity. Harvest rates varied by ownership (4.9% federal, 18.6% private, 8.0% overall), and practices evolved and diverged over the study period. PFH area and rate declined across all ownerships in the mid-1990s during a period of reduced fire activity. As area burned increased between the early 2000s and late 2010s, PFH area rebounded and surpassed late-1980s levels, while rates remained relatively low. On federal lands, PFH practices shifted in the early-to-mid 1990s towards lower rates (10.3% to 3.8%) and smaller patches (6.0 to 3.3 ha), following policy changes and increased litigation. PFH rates on federal lands decreased at all levels of burn severity, with the largest decreases (6.2% to 1.2%) in forests with low tree mortality (i.e. fire refugia). Conversely, private PFH rates and mean patch sizes more than doubled in forests burned at very low-to-moderate severity. Our results highlight how PFH practices have shifted with policy, socio-economic pressure, and increasing area burned over 31 years in the Pacific West. A similar area of post-fire harvest is now dispersed over larger fires, with practices diverging substantially between ownerships.

Deep Convolutional Neural Network for Accurate Classification of Myofibroblastic Lesions on Patch-Based Images.

This study aimed to implement and evaluate a Deep Convolutional Neural Network for classifying myofibroblastic lesions into benign and malignant categories based on patch-based images. A Residual Neural Network (ResNet50) model, pre-trained with weights from ImageNet, was fine-tuned to classify a cohort of 20 patients (11 benign and 9 malignant cases). Following annotation of tumor regions, the whole-slide images (WSIs) were fragmented into smaller patches (224 × 224 pixels). These patches were non-randomly divided into training (308,843 patches), validation (43,268 patches), and test (42,061 patches) subsets, maintaining a 78:11:11 ratio. The CNN training was caried out for 75 epochs utilizing a batch size of 4, the Adam optimizer, and a learning rate of 0.00001. ResNet50 achieved an accuracy of 98.97%, precision of 99.91%, sensitivity of 97.98%, specificity of 99.91%, F1 score of 98.94%, and AUC of 0.99. The ResNet50 model developed exhibited high accuracy during training and robust generalization capabilities in unseen data, indicating nearly flawless performance in distinguishing between benign and malignant myofibroblastic tumors, despite the small sample size. The excellent performance of the AI model in separating such histologically similar classes could be attributed to its ability to identify hidden discriminative features, as well as to use a wide range of features and benefit from proper data preprocessing.

Habitat Fragmentation Affects Richness—A View Through a Metacommunity Lens

Habitat fragmentation is often assumed to negatively impact species diversity because smaller, more isolated populations on smaller habitat patches are at a higher extinction risk. However, some empirical and theoretical studies suggest that landscapes with numerous small habitat patches may support higher species richness, although the circumstances remain elusive. We used an agent-based metacommunity model to investigate this and simulate landscapes of the same total area but diverse patch sizes. Our model, as generic and unbiased by specific assumptions as possible, aimed to explore which circumstances may be more conducive to supporting higher biodiversity. To this end, most parameters and behaviors were random. The model included generalized species traits, dispersal, and interactions to explore species richness dynamics in fragmented landscapes of distinct patch sizes. Our results show that landscapes with many small patches maintain higher species richness than those with fewer large patches. Moreover, the relationship between patch connectivity and species richness is more pronounced in landscapes with smaller patches. High connectivity in these landscapes may support species diversity by preventing local extinctions and facilitating recolonization. In contrast, connectivity is less significant in large-patch landscapes, where generalist species dominate. The findings highlight the complex interplay between patch size quality, connectivity, species traits, and diverse interactions among species in determining species richness. We suggest the patterns produced by the model represent null predictions and may be useful as a reference for a diversity of more specialized questions and predictions. These insights may also have specific implications for conservation strategies, suggesting that maintaining a mosaic of small, well-connected patches could enhance biodiversity in fragmented landscapes.

Overcoming artificial structures in resolution-enhanced Hi-C data by signal decomposition and multi-scale attention.

Computational enhancement is an important strategy for inferring high-resolution features from genome-wide chromosome conformation capture (Hi-C) data, which typically have limited resolution. Deep learning has been highly successful in this task but we show that it creates prevalent artificial structures in the enhanced data due to the need to divide the large contact matrix into small patches. In addition, previous deep learning methods largely focus on local patterns, which cannot fully capture the complexity of Hi-C data. Here we propose Smooth, High-resolution, and Accurate Reconstruction of Patterns (SHARP) for enhancing Hi-C data. It uses the novel approach of decomposing the data into three types of signals, due to one-dimensional proximity, contiguous domains, and other fine structures, and applies deep learning only to the third type of signals, such that enhancement of the first two is unaffected by the patches. For the deep learning part, SHARP uses both local and global attention mechanisms to capture multi-scale contextual information. We compare SHARP with state-of-the-art methods extensively, including application to data from new samples and another species, and show that SHARP has superior performance in terms of resolution enhancement accuracy, avoiding creation of artificial structures, identifying significant interactions, and enrichment in chromatin states.

Muriqui House: conservation management to support the recovery of the northern muriqui Brachyteles hypoxanthus in Ibitipoca, Minas Gerais, Brazil

Abstract Ensuring the demographic and genetic viability of small populations of threatened primates requires a range of management approaches. Here we describe a novel mixed in situ and ex situ management project that was developed to restore a population of the Critically Endangered northern muriqui Brachyteles hypoxanthus. This isolated population, located in Ibitipoca, Lima Duarte, Minas Gerais, Brazil, had declined to two adult males and would have gone extinct without intervention. A first attempt at in situ management in 2017 involved the translocation of a solitary female from another region, but this female did not associate or interact with the males and disappeared after 9 months. We thus initiated a second and ongoing ex situ management project that involved constructing a complex consisting of a large, open-air enclosure abutting a small patch of forest surrounded by an open area in the process of restoration, all of which is protected by electric fencing. The entire area within the fencing is called Muriqui House. The two Ibitipoca males and two solitary, wild females from another location were captured and released into the enclosed part of Muriqui House between March 2019 and January 2020 and into the forested part of Muriqui House in February 2020. The birth of an infant in this group in November 2020 and the acceptance by the group of a third female translocated from another area in January 2021 demonstrate the potential of this approach for the recovery of this isolated population, with positive implications for the conservation of the species.

All Deforestation Matters: Deforestation Alert System for the Caatinga Biome in South America’s Tropical Dry Forest

This study provides a comprehensive overview of Phase I of the deforestation dryland alert system. It focuses on its operation and outcomes from 2020 to 2022 in the Caatinga biome, a unique Brazilian dryland ecosystem. The primary objectives were to analyze deforestation dynamics, identify areas with highest deforestation rates, and determine regions that require prioritization for anti-deforestation efforts and conservation actions. The research methodology involved utilizing remote sensing data, including Landsat imagery, processed through the Google Earth Engine platform. The data were analyzed using spectral unmixing, adjusted Normalized Difference Fraction Index, and harmonic time series models to generate monthly deforestation alerts. The findings reveal a significant increase in deforestation alerts and deforested areas over the study period, with a 148% rise in alerts from 2020 to 2022. The Caatinga biome was identified as the second highest in detected deforestation alerts in Brazil in 2022, accounting for 18.4% of total alerts. Hexagonal assessments illustrate diverse vegetation cover and alert distribution, enabling targeted conservation efforts. The Bivariate Choropleth Map demonstrates the nuanced relationship between alert and vegetation cover, guiding prioritization for deforestation control and native vegetation restoration. The analysis also highlighted the spatial heterogeneity of deforestation, with most deforestation events occurring in small patches, averaging 10.9 ha. The study concludes that while the dryland alert system (SAD-Caatinga—Phase I) has effectively detected deforestation, ongoing challenges such as cloud cover, seasonality, and more frequent and precise monitoring persist. The implementation of DDAS plays a critical role in sustainable forestry by enabling the prompt detection of deforestation, which supports targeted interventions, helps contain the process, and provides decision makers with early insights to distinguish between legal and illegal practices. These capabilities inform decision-making processes and promote sustainable forest management in dryland ecosystems. Future improvements, including using higher-resolution imagery and artificial intelligence for validation, are essential to detect smaller deforestation alerts, reduce manual efforts, and support sustainable dryland management in the Caatinga biome.

Time-frequency comovements between news sentiments, Non-fungible tokens, and DeFi assets: evidence from the wavelet analysis

ABSTRACT Growth in digitalization has created a potential boost for Non-fungible tokens (NFTs) and decentralized finance (DeFis) assets in the modern world. Therefore, this study aims to examine the comovement between the recently developed comprehensive measure of news sentiment index (NSI) and selected digital assets. For this purpose, we have utilized the wavelet transform, wavelet correlation, and wavelet coherence econometric model to assess interdependency in both time and frequency between news sentiments and digital assets. Our wavelet correlation and covariance results suggest that almost all the digital assets exhibit a negative relationship with NSI. Moreover, the wavelet coherence results confirm that there is no significant comovement in the short to medium-term horizon, suggesting that both NFTs and DeFi can be used as hedges against the NSI. Furthermore, we observe small patches of significant negative comovement between NSI and digital assets in the long term, which correspond to the initial days of COVID-19. Our results confirm selected digital assets’ hedging role against news-driven uncertainty. This study finding provides essential information to policymakers, international investors, and investment managers to make effective decisions.

Small forest patches in West Africa: mapping how they are changing to better inform their conservation

Summary In West Africa, vast areas are being deforested; the remnant forest patches provide a wealth of ecosystem services and biodiversity conservation potential, yet they are threatened by human activity. Forest patches <100 ha have not been widely catalogued before; we mapped forest loss of small forest patches outside of protected areas in the Guinean savannah and humid Guineo-Congolian bioclimatic regions of Togo, Benin, Nigeria and Cameroon between 2000 and 2022. Focusing on the dynamics of small patches, without considering the splitting process of larger patches, we quantified changes in their number and area and the rate and trend of forest loss. Small forest patches are widespread, yet their area and number have decreased, while the forest loss rate is increasing. Primary forest patches lost almost half of their area annually – twice as much as secondary forests, and this loss was especially pronounced across small patches (0.5 – 10 ha), suggesting deforestation preferentially occurs in the smallest patches of primary forest. If forest loss continues at the current rate, 14% of the total forest area mapped in this study will have disappeared by 2032, jeopardizing their potential to provide ecosystem services and emphasizing the need for measures to counter their deforestation.

Helical coiled nucleosome chromosome architectures during cell cycle progression

Recent studies showed an interphase chromosome architecture-a specific coiled nucleosome structure-derived from cryopreserved EM tomograms, and dispersed throughout the nucleus. The images were computationally processed to fill in the missing wedges of data caused by incomplete tomographic tilts. The resulting structures increased z-resolution enabling an extension of the proposed architecture to that of mitotic chromosomes. Here, we provide additional insights into the chromosome architecture that was recently published [M. Elbaum et al., Proc. Natl. Acad. Sci. U.S.A. 119, e2119101119 (2022)]. We build on the defined chromosomes time-dependent structures in an effort to probe their dynamics. Variants of the coiled chromosome structures, possibly further defining specific regions, are discussed. We propose, based on generalized specific uncoiling of mitotic chromosomes in telophase, large-scale reorganization of interphase chromosomes. Chromosome territories, organized as micron-sized small patches, are constructed, satisfying complex volume considerations. Finally, we unveiled the structures of replicated coiled chromosomes, still attached to centromeres, as part of chromosome architecture.

Exploring the distribution pattern of native and alien forests and their woody species diversity in a small Mediterranean city

Recent studies have explored the ecological relationship between native urban forests and self-sown non-native forests in large cities and metropolises but further research efforts dedicated to analyzing this relationship in small cities are still needed. To improve our understanding of the ecology of urban native and alien forests in Mediterranean small cities, we analyzed the woody species richness, the community-weight mean of moisture and nitrogen ecological indicators, and soil disturbance indicators in the main urban wood types of the city of Campobasso (Italy), as well as their spatial distribution pattern across a gradient of cover and aggregation of green areas. The study showed that both native oak forests and Robinia pseudoacacia forests contributed to the maintenance of woody species richness. If we exclude the riparian environment, R. pseudoacacia forests occupied small marginal patches, tolerating soil disturbance and a high disturbance frequency, thus occupying habitats where the native oak forests could not grow. Conversely, R. pseudoacacia forests shared the ecological niche with the native riparian forests, which calls for action to prevent the spread of this alien species along river banks. Our results highlighted that urban remnant forests should be considered important assets for the planning and upkeep of urban green areas.

Conservation ecology of land snails: a synthesis for Estonia

ABSTRACT We provide a synthesis of how the regional fauna of land snails, a flagship group among invertebrates, is distributed across ecosystems and how that translates to conservation priorities in Estonia. The data were compiled from 24 assemblage studies (mostly sample quadrats or substrate volume sampling; totalling >80,000 individuals) and from species records of infrequent species in the country since the 1970s. These data were quantitatively analysed for snail diversity and species frequencies by ecosystem types, and for the conservation status and indicator value of species. The known Estonian extant fauna contains 80 native and 12 presumably non-native species, of which 11 native species were assessed as threatened (2 not found in the 21st century). Hydrologically functional fens, old eutrophic forests, wooded meadows and calcareous areas appeared hotspots for threatened species and for overall snail diversity and abundance. As conservation measures, strict protection of natural forests and fens is fundamental, whereas the consequences of ecological restoration of alvars and fens require further study. Invasion of non-native species has greatly accelerated in the last 15 years, but it still mostly affects human settlements and their surroundings. We conclude that the Estonian land snail fauna is in a vulnerable state that largely depends on the integrity of hotspot ecosystems. There is a critical lack of knowledge on the value of small habitat patches and ecological restoration, and ecological responses to the snail invasions.