Variation In Cover Research Articles

EVALUATION OF DEFORESTATION IN THE MUNICIPALITY OF BRASIL NOVO IN THE STATE OF PARÁ - BRAZIL, USING MACHINE LEARNING TECHNIQUES

The agricultural frontier of the Brazilian Amazon, is undergoing significant changes in its land cover, primarily driven by the expansion of cattle ranching and cocoa cultivation. Through the analysis of Landsat 8 satellite images and the WorldCover 10m 2020 product, combined with climatic and socioeconomic data, this study investigated land use dynamics between 2015 and 2023, on the municipality of Brasil Novo. The results revealed a substantial reduction in forest cover, with the expansion of pasturelands as the main driver of deforestation. The temporal analysis of the Normalized Difference Vegetation Index (NDVI) indicated interannual variations in vegetation cover, associated with extreme weather events and anthropogenic pressure. Although the municipality still maintains 43.8% of forest cover, with the Arara Indigenous Land being a notable example, the pressure on natural resources demands the implementation of public policies and sustainable management practices to mitigate environmental impacts and ensure the conservation of Amazonian biodiversity. Keywords: Amazon, NDVI, remote sensing, climate change, livestock, land use.

Spatial Variation in Upper Limits of Coral Cover on the Great Barrier Reef

ABSTRACTAimIdentifying the maximum coral cover that a coral community can sustain (i.e., its ‘upper limit’) is important for predicting community dynamics and improving management strategies. Here, we quantify the relationship between estimated upper limits and key environmental factors on coral reefs: hard substrate availability, temperature and water clarity.LocationGreat Barrier Reef (GBR), Australia (over 1400 km).Time Period1990 to 2022.Major Taxa StudiedScleractinian corals.MethodsWe used 32 years of data on coral cover around reef perimeters. Each reef was divided into four wave‐exposure habitats depending on prevailing wind conditions. For each site, we determined if hard coral cover had reached a plateau or upper limit. Next, we extracted existing estimates of hard substrate availability, modelled water temperature and Secchi depth. Then, we quantified the relationship between these environmental variables and the upper limits.ResultsWe found varying upper limits across the GBR, with a median of 33% coral cover and only 17% of the estimated upper limits exceeded 50% coral cover. Upper limits increased towards the southern reefs. Our results show that upper limits increased with increasing hard substrate availability and decreased with temperature and, to a lesser extent, with water clarity.Main ConclusionsThe upper limits estimated in this study are much lower than what is commonly assumed when modelling ecological dynamics, most likely resulting in predicted recovery rates being inappropriately high. Although hard substrate ultimately restricted upper limits, there are mechanisms constraining the proportion of hard substrate that is covered by hard corals. The negative relationship between temperature and upper limits cannot be explained by changes in macroalgal abundance but may be related to changes in species composition. The quantitative relationships between the upper limits of coral cover and environmental variables will provide critical information to prioritise sites for management interventions.

Barn Owl (Tyto alba)† Habitat Suitability, Nest Box Occupancy, and Management Implications Based on Kentucky Surveys 2010–2022

ABSTRACT Barn Owls (Tyto alba) are a species of conservation interest, but management of nesting populations can require significant effort. To focus management activities, we conducted analyses of statewide survey data collected for Barn Owl nests (n = 515) and roosts (n = 145) in Kentucky, USA, from 2010–2022. Nest and roost sites included natural (e.g., trees, rock shelters) and human-made (e.g., barns, attics, hunting blinds, silos, etc.) structures and nest boxes (n = 270) installed on various substrates. Using data related to land cover, agricultural features, and other habitat-related variables, we examined factors influencing Barn Owl site occupancy by creating habitat suitability models. Additionally, we assessed changes in nest box occupancy over time and the factors that influenced nest box occupancy. The Shannon habitat diversity index and number of buildings within 75 m were the most important variables for habitat suitability throughout the study area, though the proportion of hay/pasture/grassland within 625 m and distance to an area intensively managed for Barn Owls were important regionally. Barn Owl nest box occupancy increased over the course of our study, likely due to management efforts. Owls were more likely to occupy nest boxes if they were installed on tall feed silos, retired utility poles, or barns. Moreover, nest boxes installed at sites where we observed owl pairs (prior to installation) were more likely to become occupied and used sooner than nest boxes installed opportunistically. Future management should focus on installing nest boxes for known pairs, on unused feed silos, on retired utility poles on reclaimed surface mines, and near areas intensively managed for the species.

Diversity, Equity, Inclusion, and Access Coverage in Technology-focused Courses

Diversity, equity, inclusion, and access (DEIA) is a controversial topic. Technological improvements help to incorporate DEIA to everyday life, but it also comes with its own problems like algorithmic bias, and legal issues. Computing technology is not neutral; adversely affecting marginalized groups through policy decisions and their creators’ unconscious biases; the limitations of the programs and equipment. The American Library Association Core Competences (ALACCs) require basic knowledge on social justice, diversity, equity, and inclusion gained through LIS education. This study will analyze technology-focused Master of Library and Information Science (MLIS) courses to assess how DEIA principles are addressed in the light of ALACCs in technology requirement. Syllabi from select ALA accredited MLIS programs on the Eastern United States are collected. Preliminary results will be presented at the Conference. Efforts to collect the remaining syllabuses are continuing. Study hopes to fill a major gap by providing a concrete data about technological biases that inversely affect specific populations as well as possible remedies to it.

Identifying Factors Mediating the Carnivore Richness–Productivity Relationship Across a Precipitation‐Driven Ecotone

ABSTRACTAimPrimary productivity is an important mechanism influencing the species richness of animal taxa such as mammals. However, the factors that mediate the relationship between carnivore species richness, for example, and productivity are not well understood. We examined whether the relationship between carnivore species richness and primary productivity followed a hump‐shaped relationship and explored potential pathways by which productivity influences carnivore communities.LocationWestern Great Basin, USA.MethodsWe deployed a camera‐trap grid across a strong precipitation—and the corresponding productivity—gradient and estimated carnivore species richness using a novel application of a multisession community occupancy model. To quantify the relationship between carnivore species richness and productivity, we included the linear and quadratic effects of average annual precipitation as covariates on carnivore species richness. We fit additional community models linking carnivore species richness to vegetation and land cover variables to identify factors that mediate the relationship between carnivore richness and productivity.ResultsThe linear effect of precipitation on carnivore richness was positive and the quadratic effect was negative, supporting the hump‐shaped relationship where richness declines at the highest levels of productivity. Similarly, carnivore species richness followed a quadratic relationship with vegetation height along the productivity gradient. The relationship between carnivore species richness and proportion tree cover was positive, with limited evidence that open vegetation types in the surrounding landscape increased site‐level richness.Main ConclusionsIn addition to supporting the notion that primary productivity has a strong and nonlinear influence on local‐scale carnivore species richness, our results suggest that vegetation structure may be an important mediator of this relationship. Although future changes in precipitation and productivity due to climate change are uncertain, our results indicate that targeting areas of intermediate productivity and vegetation height, such as woodlands, may be key for conserving species‐rich carnivore communities along productivity gradients.

Exploring perceived relationships between weather, climate and mental health: biometeorological perspectives of healthcare practitioners.

Over the last decade, there has been an increase in research examining the influence of weather and climate in mental health caseloads. Variations in temperature, sunshine hours, cloud cover, precipitation and extreme weather events have been statistically linked to diagnoses and increases in hospital admissions for several mental health conditions. This study aimed to explore whether mental health practitioners perceive there to be a link between mental health and daily, seasonal, or inter-annual shifts in various climate variables in South Africa, and the timing and causal mechanisms thereof. Semi-structured interviews were conducted with 50 practicing healthcare practitioners, and the data was analysed using thematic analysis. The findings of this research show that all 50 participants were aware of the link between weather, climate and mental health, primarily through their awareness of seasonal affective disorder. Of the 50 participants, 38 participants could explain the aetiology of seasonal affective disorder. Participants perceived sunlight and temperature to exert an influence on mental health. All 50 participants perceived exposure to sunlight to exert a positive influence on several mental health conditions. Of the 50 participants, 36 participants perceived increases in temperature to exert an adverse effect on mental health symptomology. A minority of 11 participants perceived precipitation to influence mental health conditions such as seasonal affective disorder, bipolar disorder, and substance abuse disorder. Participants' perceptions of the influence of precipitation on mental health provided a unique potential explanation of this relationship, which, at the time of writing, has not been discussed in formal research.

Comparison and Optimization of Light Use Efficiency-Based Gross Primary Productivity Models in an Agroforestry Orchard

The light-use efficiency-based gross primary productivity (LUE-GPP) model is widely utilized for simulating terrestrial ecosystem carbon exchanges owing to its perceived simplicity and reliability. Variations in cloud cover and aerosol concentrations can affect ecosystem LUE, thereby influencing the performance of the LUE-GPP model, particularly in humid regions. In this study, the performance of six big-leaf LUE-GPP models and one two-leaf LUE-GPP model were evaluated in a humid agroforestry ecosystem from 2018–2020. All big-leaf LUE-GPP models yielded GPP values consistent with that derived from the eddy covariance system (GPPEC), with R2 ranging from 0.66–0.73 and RMSE ranging from 1.81–3.04 g C m−2 d−1. Differences in model performance were attributed to the differences in the quantification of temperature (Ts) and moisture constraints (Ws) and their combination forms in the models. The Ts and Ws algorithms in the eddy covariance-light-use efficiency (EF-LUE) model well characterized the environmental constraints on LUE. Simulation accuracy under the common limitation of Ts and Ws (Ts × Ws) was higher than the maximum limitation of Ts or Ws (Min (Ts, Ws)), and the combination of the Ts algorithm in the Carnegie–Ames–Stanford Approach (CASA) and the Ws algorithm in the EF-LUE model was optimized in combination forms, thereby constraining LUE for GPP estimates (GPPBLO, R2 = 0.76). Various big-leaf LUE-GPP models overestimated or underestimated GPP on sunny or cloudy days, respectively, while the two-leaf LUE-GPP model, which considered the transmission of diffuse radiation and the difference in photosynthetic capacity of canopy leaves, performed well (R2 = 0.72, p < 0.01). Nevertheless, the underestimation/overestimation for shaded/sunlit leaves remained under different weather conditions. Then, the clearness index (Kt) was introduced to calculate the dynamic LUE in the big-leaf and two-leaf LUE-GPP models in the form of exponential or power functions, resulting in consistent performance even in different weather conditions and an overall higher simulation accuracy. This study confirmed the potential applicability of different LUE-GPP models and emphasized the importance of dynamic LUE on model performance.

Investigating spatial-temporal trend of snow cover over the three provinces of Northeast China based on a cloud-free MODIS snow cover product

Snow serves as a pivotal water resource in the three provinces of Northeast China (TPNC), the investigation of spatial and temporal distribution changes of snow cover is essential for the region’s efficient water resource management. The Moderate Resolution Spectroradiometer (MODIS) snow cover product has proven effective in providing detailed spatial–temporal distribution and identification of snow cover. However, its accuracy and reliability are significantly hampered by cloud obscuration. To address this issue, we have developed a novel four-step cloud removal approach, which includes Terra and Aqua combination, 5-day temporal combination, snowline method (IMS) as well as 8-pixel and 24-pixel adjacent pixel method. Results indicate that the proposed approach successfully eliminates all cloud cover, yielding a highly accurate cloud-free snow cover product with validation accuracies of 92% and 97% when using in situ snow depth measurements and cloud masking method, respectively. We investigated the spatial and temporal variations of snow cover for the TPNC during 2003–2018 with snow coverage and snow cover days (SCD) and analyzed the correlation between snow cover and climate factors. The results showed that the annual basin-averaged snow coverage increased at a rate of 1.27% yr−1 before 2009 and decreased at a rate of 1.80% yr−1 after 2009. The Mann-Kendall tests indicated that about 72% of the total area showed an increasing trend of annual SCD during 2003–2018. Conversely, 94% of the total area exhibited a decreasing trend of annual SCD for the period of 2009–2018 due to the increasing trend of temperature and decreasing trend of precipitation. Our approach shows a promising application of generating accurate cloud-free products and its potential to examine spatial–temporal variations of snow cover under climate change for other snow-covered regions globally.

Ecological drivers of sexual size dimorphism in northernchamois.

Male-biased sexual size dimorphism (SSD) is common in ungulates. The dominant scenario for the evolution of ungulate SSD suggests that habitat openness leads to greater SSD by increasing group size and thus sexual selection through male-male competition for mates. At a more proximate level, adaptive changes in SSD may result from the plastic response of individuals to environmental variation. In this study, we used 161,948 body mass data from a seasonally size-dimorphic species, the northern chamois Rupicapra rupicapra, to examine the role of forest cover and other environmental variables in the expression of SSD. Data were collected from individuals hunted in the Austrian Alps, grouped into 28 mountain ranges with different forest cover, geological substrate and population density. Population-specific growth curves were fitted using monomolecular models, and SSD was calculated as the log-transformed ratio of male to female asymptotic body mass. A path model in which environmental factors indirectly influenced SSD via male or female body mass suggested that SSD increased with increasing density via reduced female body mass and decreased on siliceous substrates via reduced male body mass. Forest cover was negatively associated with body mass in both sexes, but not with variation in SSD.

Detecting small-scale landslides along electrical lines using robust satellite-based techniques

Robust Satellite Technique (RST) was applied to detect small-scale landslides along electrical lines in Sicily, Italy. To this end, electrical poles were selected as targets within the study area. The methodology, implemented in Google Earth Engine (GEE) environment, exploits the Copernicus Sentinel-2 platform to identify anomalous land cover variation, in terms of Normalized Difference Vegetation Index (NDVI), possibly related to small displacements affecting electric poles. Since the applied methodology is based on land cover change, dense vegetation plays an important role in detecting small-scale landslides. Therefore, we targeted months with the highest vegetation density, such as February, March, and April from 2016–2023. The results obtained reveal that out of the five targeted electrical poles, four of them exhibited anomalies > 2-sigma indicating significant changes in land cover possibly related to local ground movement as confirmed by aerial photos collected in the period 2015–2023. Our findings reveal anomalies of −2.17 and −2.36 on 7/17/2017 and 9/05/2017 for pole 1. For pole 2, the results show an anomaly of −2.02 on 8/11/2018. The results also indicate anomalies of −4.40 and −2.99 on 7/09/2021 and 9/27/2022 for pole 3. For pole 4, the findings show an anomaly of −3.10 on 1/18/2019.

Machine learning algorithms for the evaluation of risk by tick-borne pathogens in Europe

Background Tick-borne pathogens pose a major threat to human health worldwide. Understanding the epidemiology of tick-borne diseases to reduce their impact on human health requires models covering large geographic areas and considering both the abiotic traits that affect tick presence, as well as the vertebrates used as hosts, vegetation, and land use. Herein, we integrated the public information available for Europe regarding the variables that may affect habitat suitability for ticks and hosts and tested five machine learning algorithms (MLA) for predicting the distribution of four prominent tick species across Europe. Materials and methods A grid of cells 20 km in diameter was prepared to cover the entire territory, containing data on vegetation, points of water, habitat fragmentation, forest density, grass extension, or imperviousness, with information on temperature and water deficit. The distribution of the hosts (162 species) was modelled and included in the dataset. We used five MLA, namely, Random Forest, Neural Networks, Naive Bayes, Gradient Boosting, and AdaBoost, trained with reliable coordinates for Ixodes ricinus, Dermacentor reticulatus, Dermacentor marginatus, and Hyalomma marginatum in Europe. Results Both Random Forest and Gradient Boosting best predicted ticks and host environmental niches. Our results demonstrate that MLA can identify trait-matching combinations of environmental niches. The inclusion of land cover and land use variables has a superior capacity for predicting areas suitable for ticks, compared to classic methods based on the use of climate data alone. Conclusions Flexible MLA-driven models may offer several advantages over traditional models. We anticipate that these results may be extrapolated to other regions and combinations of tick-vertebrates. These results highlight the potential of MLA for inference in ecology and provide a background for the evolution of a completely automatized tool to calculate the seasonality of ticks for early warning systems aimed at preventing tick-borne diseases.

Where are the biggest gaps in phylogenetic coverage of insect diversity?

AbstractGaps in phylogenetic knowledge are unlikely to be filled in an optimal manner in the absence of a quantitative descriptive framework of phylogenetic coverage to date and a strategy for addressing the remainder (the Darwinian Shortfall). One strategy would be modelling phylogenetic progress on a framework of insect diversity, such as a taxonomic database. I herein sampled existing phylogenetic coverage by collating a machine‐readable tree from each of 1000 insect publications. Processing comprised primarily taxonomic harmonization, the standardization of terminal labels and pruning of uninformative terminal sets such as taxon duplicates. The phylogeny database contained 94,173 unique species IDs over 154,938 terminals in total, with a respective mean and median number of species per phylogeny of 155 and 44. Omics phylogenies contained the most species on average, though not the most novel species, and mitogenome phylogenies contributed the fewest novel species. Synthesis phylogenies were very few in number, but nonetheless predicted to contribute most to increasing phylogenetic coverage of insect diversity. 6.2% of the 970,000 species of the Catalogue of Life were contained amongst the terminals of the database of phylogenies. Phylogenetic coverage of insect families was often disproportionate to species‐richness; those most undersampled were beetles and included families Curculionidae, Staphylinidae, Cerambycidae, and Scarabaeidae, and those with disproportionately high phylogenetic coverage included families of the dragonflies, bees, butterflies and ants. The work herein provides a foundation for quantification of the Darwinian Shortfall, and for shifting to an objective strategy for completing the insect Tree of Life.

Potential environmental implications of sandbar afforestation: Insights from ecosystem restoration initiatives in a sandbar of Brahmaputra River Assam, India

Plantation in riverine sandbars offers an excellent opportunity for restoration of ecosystem with a vast potential for enhancing carbon stock. Afforestation on barren islands is challenging task; however, Padmashree Jadav Payeng has single-handedly transformed a sandbar of the river Brahmaputra into a forested landscape in India’s northeastern state of Assam. Such inspiring initiative needs more attention in terms of scientific assessment to quantify ecosystem value and services that can be enriched through such activities. This study uses remote sensing data viz., Landsat4–5TM and Sentinel 2 A data to provide a detailed information on spatio-temporal variability of land use land cover of study region from 1990 to 2021. It aims to conduct a scientific and systematic assessment of biophysical changes that have occurred in the sandbars, understand the status of afforestation, and evaluate the current levels of aboveground biomass (AGB), belowground biomass (BGB), and carbon stock in the selected sandbars. The spatial distribution of AGB, BGB and carbon stock is derived using linear regression model between SAR backscatter and field-based AGB. The results demonstrate that forest cover increased by 31.92 % and sandbar area is reduced by 26.87 % from 1990 to 2021. Spatially derived AGB ranges from 9 to 1295.89 Mg per ha, BGB from 2.35 to 290.50 Mg per ha and carbon stock from 6.18 to 763.34 Mg per ha. Ficus religiosa exhibits a high biomass, ranging from 564.7 Mg per ha to 994.7 Mg per ha, and a high carbon stock, ranging from 8 to 557.30 Mg per ha, attributed to its larger diameter at breast height (DBH). Moreover, phytosociological assessment was conducted for the studied forest, which reveal a total tree species richness of 79. The forest exhibits a total tree density of 395 individuals per hectare. Different biodiversity indices provide a comprehensive understanding of species composition; where results show a Shannon diversity index of 2.81, a Simpson's index of 0.08, a Menhinick's richness index of 2.7, and a Margalef's richness index of 5.26. The article provides detailed information on change in forest cover and present status of AGB, BGB and Carbon stock, providing evidence-based narratives on ecosystem restoration. The initiative by a single person has created a forested landscape and habitat for a large number of wild animals, contributing to better carbon stock and a healthier ecosystem. With regard to the current debate of carbon market, the study suggests the need of instrumentalization of carbon credits for such restoration activities to encourage increase in carbon stock. It also concludes that in-depth research should be taken up on long-term effectiveness of such plantation activities and the potential for scaling up these initiatives for ecosystem restoration in view of climate change mitigation and sustainable forest development.

Effect of Land Cover Variations on the Fertility Status of Soils of Umuhu in Ngor-Okpala Area of Imo State

The study was conducted to ascertain the effect of four different land covers (cassava cultivated field (CCF), oil palm plantation (OPP), plantain plantation (PP) and forest land (FL)) on the fertility status of soils of Umuhu in Ngor-Okpala area of Imo State, Nigeria. Random sampling technique was used in the collection of soil samples from the four different land covers. The sampling was done at the beginning, middle and end of each land cover. Twelve (12) composite samples were collected from all the land cover types with 3 per land cover. The composite samples were prepared for routine laboratory analyses. Data generated were analyzed statistically using analysis of variance. The textural classes of all the sampled soils were of loamy sand. The soil which had plantain plantation as its cover had the highest pH (6.4), Total N (0.229 %), Soil organic matter 4.70%, Available P (27.05 mg kg-1), Exch. Ca (6.492 cmolc kg-1), Exch. Mg (3.942 cmolc kg-1), Exch. K (0.953 cmolc kg-1), Exch. Na (0.06 cmolc kg-1), Exch. H (1.2 cmolc kg-1) and CEC (28.4 cmolc kg-1) with its Exch. Al in trace amount (<0.001 cmolc kg-1). The soil under CCF, despite being under low cover, did not show much degeneration due to the shifting cultivation being practiced in the study location. However, the result obtained from the study indicated that the different land covers especially that under plantain plantation (PP) have affected the soils fertility at different rates. This observed factor is strongly controlled by high content of organic materials, a dense vegetative cover which mitigates erosion effects and the addition of ash as a means of fertilizing the soils under plantain plantation being practiced in the study area.

Predicting conservation priority areas in Borneo for the critically endangered helmeted hornbill (Rhinoplax vigil)

The critically endangered helmeted hornbill (Rhinoplax vigil) is under threat around its Southeast Asian range due to hunting and habitat loss. Dependant on primary rainforest habitats, the species is thought to be highly sensitive to habitat disturbance. Compounding this is the threat of climate change where equatorial ecosystems, such as those found on Borneo, are predicted to increase in temperature and precipitation. It is therefore important to identify whether the species’ suitable habitats, both now and in the future, are protected from further anthropogenic disturbance. In this study we used species distribution models to assess the extent of suitable habitat for R. vigil across Borneo, an island which has undergone rapid deforestation in recent years, and a stronghold for the species. Using 302 R. vigil occurrence records, four environmental and three land-use cover variables, we modelled R. vigil current habitat suitability, and two future projections under climate change scenarios RCP 4.5 and RCP 8.5 for 2041–2060. Our results suggest that a quarter of Borneo's landmass is currently suitable for R. vigil. However, there is a steep decline in the predicted suitable habitat from 335,963 km2 (current scenario) to 73,170 km2 (future RCP 4.5), to 54,839 km2 (future RCP 8.5). Our model predicts that the amount of suitable habitat protected by current protected areas (PAs) and the planned Heart of Borneo (HoB) initiative will increase under future climate change, with the HoB protecting > 65 % of R. vigil suitable habitat across all projections. This is likely worsened by future land-use change not included in these models, which is a limitation to our study. We therefore encourage the connectivity of lowland PAs, and the continuation of HoB targets to prevent further decline of R. vigil habitat around Borneo. This study provides the first species-specific spatial assessment of the critically endangered helmeted hornbill distribution in response to climate change across current and planned protected regions in Borneo.

Re-organization of Pacific overturning circulation across the Miocene Climate Optimum

The response of the ocean overturning circulation to global warming remains controversial. Here, we integrate a multiproxy record from International Ocean Discovery Program Site U1490 in the western equatorial Pacific with published data from the Pacific, Southern and Indian Oceans to investigate the evolution of deep water circulation during the Miocene Climate Optimum (MCO) and Middle Miocene Climate Transition (MMCT). We find that the northward export of southern-sourced deep waters was closely tied to high-latitude climate and Antarctic ice cover variations. Global warming during the MCO drove a progressive decrease in carbonate ion concentration and density stratification, shifting the overturning from intermediate to deeper waters. In the western equatorial Pacific, carbonate dissolution was compensated by increased pelagic productivity, resulting in overall elevated carbonate accumulation rates after ~16 Ma. Stepwise global cooling and Antarctic glacial expansion during the MMCT promoted a gradual improvement in carbonate preservation and the initiation of a near-modern Pacific overturning circulation. We infer that changes in the latitudinal thermal gradient and in Southern Ocean zonal wind stress and upper ocean stratification drove radically different modes of deep water formation and overturning across the MCO and MMCT.

Tracing 40,000 years of vegetation change in the Baetic-Rifan biodiversity hotspot

This study presents a 40,000-year-old pollen record from Los Tollos Lake in the Baetic-Rifan region of southernmost Spain. The data offer insights into the past ecosystems of a current biodiversity hotspot situated at the ecotone between the Atlantic and the Mediterranean. This new sequence encompasses Mediterranean and Ibero-North African sclerophylls, broad-leaf trees, conifers, and Tertiary relicts. The full-glacial abundance of mesothermophytes, particularly oaks, is among the highest recorded for the European Quaternary. Notably, the presence of ecologically significant pollen taxa, which are poorly dispersed and currently occur outside the study area, suggests that this biodiversity hotspot was more extensive in the Pleistocene. During the period of c. 40.8–36.5 ka, three Artemisia maxima at 40.6, 38.9, and 36.9 ka coincide with decreases in Quercus, indicating the spread of steppes in response to the abrupt coolings of the GS10, GS9 (HS4), and GS8 events. Similarly, increases in Quercus around 41, 40, and 37.2–38.3 ka parallel the GI10, GI9, and GI8 warm events. A forested period from 36.5–32 ka includes oak expansions during the GI7 and GI6 interstadials. From 32 to 19.2 ka, more xerophytic vegetation is observed, including the HS3, GS5-GS3, HS2, and GS2.1b-c cold spells, although the correlation with vegetation changes is not synchronous. As early as approximately 21 ka, Artemisia definitively declines, while the region was reforesting, likely due to the presence of stationary populations of broadleaf trees and conifers in the southern Baetic mountains. From approximately 12 ka onwards, the highest values of angiosperm trees are recorded, with oaks dominating throughout most of the Holocene. The pollen record and the correlation with marine records suggest a more intense hydrological regime during the first half of the Holocene, but there is also archaeobotanical evidence for human activity during the second half, resulting in a more open landscape, making it difficult to discriminate the impact of each factor. Some abrupt aridity events during the Holocene coincide with small variations in tree cover, particularly at 9.2, 8.2, 6.8, 5.5–4.8, 4.2, and 2.8 ka. Since the Neolithic and during the metallurgic stages, forest species, especially broad-leaf trees, experienced range retraction accompanied by population extinctions. The region's plant communities have been subject to fire regimes since the Pleistocene, seemingly dependent on the available tree biomass.

Chemoinformatic Characterization of NAPROC-13: A Database for Natural Product 13C NMR Dereplication.

Natural products (NPs) are secondary metabolites of natural origin with broad applications across various human activities, particularly the discovery of bioactive compounds. Structural elucidation of new NPs entails significant cost and effort. On the other hand, the dereplication of known compounds is crucial for the early exclusion of irrelevant compounds in contemporary pharmaceutical research. NAPROC-13 stands out as a publicly accessible database, providing structural and 13C NMR spectroscopic information for over 25 000 compounds, rendering it a pivotal resource in natural product (NP) research, favoring open science. This study seeks to quantitatively analyze the chemical content, structural diversity, and chemical space coverage of NPs within NAPROC-13, compared to FDA-approved drugs and a very diverse subset of NPs, UNPD-A. Findings indicated that NPs in NAPROC-13 exhibit properties comparable to those in UNPD-A, albeit showcasing a notably diverse array of structural content, scaffolds, ring systems of pharmaceutical interest, and molecular fragments. NAPROC-13 covers a specific region of the chemical multiverse (a generalization of the chemical space from different chemical representations) regarding physicochemical properties and a region as broad as UNPD-A in terms of the structural features represented by fingerprints.

Evaluating habitat use and relative abundance of Iowa's river otter with harvest data

AbstractThe North American river otter (Lontra canadensis) was extirpated from much of the United States in the early 20th century due to habitat loss, pollution of waterways, and overharvesting. The Iowa Department of Natural Resources began a river otter reintroduction effort in 1985, which placed otters in 14 sites across the state. Otters have since been known to occur in every county in Iowa and appear to have successfully repopulated their former range throughout the state. Our objective was to relate land cover characteristics and otter abundance using harvest data. We used data collected by agency staff to map the locations of otter harvest in Iowa from 2006 to 2016. We mapped otter harvest locations at the subwatershed level (also called 12‐digit Hydrologic Unit Code or HUC‐12). We related otter harvest to land cover variables and predicted otter abundance by land cover type. We found that roads, forests, larger waterways, and Ictaluridae (catfish) presence were negatively correlated with otter harvest. Variables positively correlated with otter harvest were areas with greater land cover diversity, wetland patch density, average stream density, and waterway and wetland areas. The land cover model predicted otters in equal or greater numbers than the harvest data in 62.8% of HUC‐12s. The areas of greatest otter abundance estimates were located near recreation areas and urban areas, indicating the underutilization of these heavy‐trafficked areas by trappers. Areas of fewer predicted otters were not concentrated in a single area of the state but occurred along the Interstate 80 corridor.

Earth observation data uncover green spaces’ role in mental health

The prevalence of mental health disorders, a key disability cause, is linked to demographic and socioeconomic factors. However, limited data exists on mental health and the urban environment. Urbanization exposes populations to environmental stressors, particularly affecting low-middle-income countries with complex urban arrangements. We used remote sensing and census data to investigate potential connections between environmental factors and mental health disorders. Land cover variables were assessed using the European Space Agency (ESA) global WorldCover product at 10 m resolution together with the database of mental health diagnosed cases (n = 5769) from the Brazilian Unified Health System’s Department of Informatics (DATASUS) from every health facility of the city of Porto Alegre. The association of mental health data with land cover was established with machine learning algorithms and polynomial regression models. The results suggest that higher trees cover at neighborhood level was associated with better mental health index. A lower mental health index was also found to be associated with an higher Human Development Index. Our results highlight the potential of greenness in the city environment to achieve substantially better mental health outcomes.