Strong Pattern Research Articles

Mule deer selection of fuel reductions is restricted by site fidelity and structured by circadian and seasonal patterns

Forests in the western US have undergone a profound transformation over the last 100 years due to chronic fire suppression and a cycle of extensive timber harvest followed by little silvicultural activity. Forested landscapes in this region are now dominated by intermediate age, denser stands of coniferous trees that reduce transmission of light and precipitation to the understory, with potential consequences for ungulate nutrition. We used a 20-year dataset of mule deer locations (560 animal-years of data) to evaluate long-term patterns of selection of forest stands that had been thinned and burned compared to untreated reference stands. We evaluated within home-range (3rd order) selection at 3 temporal scales (hourly, daily, annually) and landscape-scale (2nd order) use annually. We found that annual selection of treated stands during summer generally increased with two peaks, once immediately after treatments were applied and again 15 years later. Mule deer also showed strong seasonal and temporal patterns in selection of treated forest stands. Deer selected treated stands at night in July and August immediately after treatments. After 4–6 years, mule deer selected treated stands both during the day and at night in May, July, and August, but with stronger selection at night. We hypothesize that preference for treated forest stands were driven by differences in forage quantity and quality among forest stands. Vegetation surveys during years of peak selection showed that treated stands had significantly higher biomass and digestible energy of neutrally selected forage and lower biomass of avoided forage species, although there was no difference in biomass of preferred forage species. A subset of female mule deer with multiple years of data did not shift home ranges to overlap with treated forest stands over time (2nd order use) but did show increasing selection over time for treated forest stands within their home ranges (3rd order). Our results show that thinning and burning of forest stands can benefit mule deer both immediately and for up to 15 years after treatment and that researchers should evaluate temporal and seasonal patterns in studies of habitat selection. Given the diverse habitat needs of mule deer, treatments would be most beneficial if they were scattered across large landscapes and staggered in time to provide a diversity of forage and cover types.

Investigating fish reproduction phenology and essential habitats by identifying the main spatio-temporal patterns of fish distribution

Abstract Fish spawning phenology is a major concern for conservation and fisheries management. New intensive data sources, such as GPS-based tracking data and high-resolution catch declaration data, are becoming increasingly available in the field of marine ecology. These data benefit from high spatiotemporal resolution and open new research avenues for investigating the interannual variability in fish phenology. In this paper, we demonstrate how an integrated species distribution model informed by commercial catch data combined with spatiotemporal dimension reduction methods known as empirical orthogonal functions (EOFs) can be used to synthesize spatiotemporal signals in fish reproduction phenology. Specifically, we address the following questions: (1) Can we identify seasonal spatial patterns that can be interpreted in terms of reproductive phenology and essential habitats? (2) Can we identify changes in reproductive phenology over time? (3) Are these changes related to environmental drivers? The analysis illustrates the reproductive phenology of three key commercial species in the Bay of Biscay (sole, hake, and sea bass). The EOF analysis emphasized strong seasonal spatiotemporal patterns that correspond to reproduction patterns and feeding patterns. Based on this methodology, we identified seasonal variations in the timing of reproduction, and we related these variations to sea surface temperature, a key driver of fish reproduction.

Sterolysin from a 1950s culture of Karlodinium veneficum (aka Gymnodinium veneficum Ballantine) forms lethal sterol dependent membrane pores

In 1957 Abbott and Ballantine described a highly toxic activity from a dinoflagellate isolated from the English Channel in 1949 by Mary Park. From a culture maintained at Plymouth Laboratory since 1950, we have been able to isolate two toxic molecules (abbotoxin and 59-E-Chloro-abbotoxin), determine the planar structures by analysis of HRMS and 1D and 2D NMR spectra, and found them to be karlotoxin (KmTx) congeners. Both toxins kill larval zebrafish with symptoms identical to those described by Abbot and Ballantine for gobies (Gobius virescens). Using surface plasma resonance the sterol binding specificity of karlotoxins is shown to require desmethyl sterols. Our results with black lipid membranes indicate that karlotoxin forms large-conductance channels in the lipid membrane, which are characterized by large ionic conductance, poor ionic selectivity, and a complex gating behavior that exhibits strong voltage dependence and multiple gating patterns. In addition, we show that KmTx 2 pore formation is a highly targeted mechanism involving sterol-specificity. This is the first report of the functional properties of the membrane pores formed by karlotoxins and is consistent with the initial observations of Abbott and Ballantine from 1957.

A widespread, consistent, and perplexing biphasic pattern in log catch‐at‐age data from a widely harvested family of tropical reef fishes

AbstractPatterns of cohort decline are key demographic traits that provide a unique temporal perspective vital to understanding population dynamics. The discovery of multidecadal lifespans in tropical surgeonfishes in the 1990s created a paradigm shift to the notion that they are highly vulnerable species with low population recovery rates; however, research into the mortality patterns of surgeonfishes (Acanthuridae) has been sparse until recently. Recent studies on this family have demonstrated an unusual (possibly unique), two‐phase pattern of adult catch‐at‐age, whereby there is a population‐level shift from higher‐than‐expected rates of decline early in life to lower‐than‐expected decline rates for the remainder of the lifespan. To examine the geographic and phylogenetic ubiquity of this pattern, we compiled age‐based information from demographic samples of 70 populations of 25 tropical species spanning the Indo‐Central Pacific and Central‐Western Atlantic. Overall, we found that 79% of populations exhibited strong biphasic patterns, including 88% of populations across the Indo‐Central Pacific. By accounting for empirical relationships instead of using linear catch curves or classical assumptions of natural population decay based on lifespan, we demonstrate that surgeonfishes have turnover times that are two to four times faster than previously believed. Faster turnover times may suggest a higher level of sustainability for surgeonfish fisheries throughout the global tropics than previously estimated.

Two sub-annual timescales and coupling modes for terrestrial water and carbon cycles.

To bridge the knowledge gap between (a) our (instantaneous-to-seasonal-scale) process understanding of plants and water and (b) our projections of long-term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models-two-dimensional linear models-and observation-based data from satellites, eddy covariance towers, weather stations, and machine-learning-derived products to determine the dominant sub-annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal-scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics-positively sloped tangent lines to a convex long-term mean-state curve-is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean-state pattern, and hypothesize that this may be due to lack of water-carbon feedbacks at daily scales.

Genetic network analysis uncovers spatial variation in diversity and connectivity of a species presenting a continuous distribution

The conservation of genetic diversity and connectivity is essential for the long-term persistence and adaptive ability of a species. Recent calls have been made for the inclusion of genetic diversity and differentiation measures in the assessment, management, and conservation of species. However, the literature often lacks direction on how to do so for species with continuous distributions or no distinct breaks in genetic connectivity. There are many considerations to overcome when investigating genetic diversity and connectivity of such species. We combine multiple genetic network methodologies with more traditional population genetic analyses within a single framework to address the challenges of investigating population structure and quantifying variation in genetic diversity and connectivity of wide-ranging species with continuous distributions. We demonstrate the efficacy and applicability of our framework through a study on woodland caribou (Rangifer tarandus) occupying the boreal forest of Canada; a species of significant conservation concern. The dataset consisted of 4911 unique individuals genotyped at 9 microsatellite loci, which were subsequently partitioned into 103 spatial nodes to create a population-based genetic network. The Walktrap community detection algorithm was used to detect hierarchical population genetic structure within the study area and node-based network metrics such as mean inverse edge weight and clustering coefficient were used to quantify the variation in genetic connectivity across the range. Lastly, genetic diversity was assessed by calculating allelic richness and heterozygosity of the nodes making up the network. The community detection analysis identified two communities at the coarsest scale to nine communities at the optimal partition. A strong pattern of Isolation by Distance (IBD) was found across the range at multiple scales. Furthermore, signs of genetic erosion along the study area’s southern boundaries were depicted by nodes presenting low genetic diversity and low centrality values. These results are important to the species status assessments in providing previously unavailable information on connectivity and diversity within and beyond the current local population units used in management. Our approach to quantify the patterns and extent of connectivity across the boreal range is comprehensive and could easily be adapted to other species. The results are robust and provide a solid foundation for the continued monitoring and recovery of the species.

Seasonal hot spots of pollution and risks in Western Kenya: A spatial-temporal analysis of almost 800 organic micropollutants

The release of chemicals into the environment presents a significant threat to aquatic ecosystems dependent on the proximity to emission sources and seasonal dynamics of emission and mobilization. While spatial-temporal information on water pollution in Europe is increasing, there are substantial knowledge gaps on seasonal pollution dynamics in tropical countries. Thus, we took Lake Victoria South Basin in western Kenya as a case study to identify spatial and seasonal hot spots of contamination, quantified toxic risks to different groups of organisms, and identified seasonal risk drivers. For this purpose, we analyzed grab water samples from five rivers with agricultural and wastewater treatment plants in their catchment in four different seasons. We used liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) with a target list of 785 organic micropollutants. A total of 307 compounds were detected with concentrations ranging from 0.3 ng/L to 6.6 μg/L. Using a Toxic Unit (TU) approach based on mixture toxicity to standard test organisms, crustaceans were identified as the most affected group followed by algae and fish. For crustaceans, chronic risk thresholds were exceeded in 96 % of all the samples, while 56 % of all samples are expected to be acutely toxic, with the highest risk in February during the dry season. High toxic unit values for algae and fish were recorded in July dry season and May wet season. Diazinon, imidacloprid, clothianidin and pirimiphos-methyl were the major drivers for crustacean toxicity while triclosan and different herbicide mixtures drive risks to algae in dry and wet seasons, respectively. A total of 18 chemicals were found to exceed acute and chronic environmental risk thresholds. With this study, strong spatial-temporal patterns of pollution, risks and risk drivers could be confirmed informing prioritization of monitoring and abatement to enhance water quality and reduce toxic risks.

Soils of two Antarctic Dry Valleys exhibit unique microbial community structures in response to similar environmental disturbances

BackgroundIsolating the effects of deterministic variables (e.g., physicochemical conditions) on soil microbial communities from those of neutral processes (e.g., dispersal) remains a major challenge in microbial ecology. In this study, we disturbed soil microbial communities of two McMurdo Dry Valleys of Antarctica exhibiting distinct microbial biogeographic patterns, both devoid of aboveground biota and different in macro- and micro-physicochemical conditions. We modified the availability of water, nitrogen, carbon, copper ions, and sodium chloride salts in a laboratory-based experiment and monitored the microbial communities for up to two months. Our aim was to mimic a likely scenario in the near future, in which similar selective pressures will be applied to both valleys. We hypothesized that, given their unique microbial communities, the two valleys would select for different microbial populations when subjected to the same disturbances.ResultsThe two soil microbial communities, subjected to the same disturbances, did not respond similarly as reflected in both 16S rRNA genes and transcripts. Turnover of the two microbial communities showed a contrasting response to the same environmental disturbances and revealed different potentials for adaptation to change. These results suggest that the heterogeneity between these microbial communities, reflected in their strong biogeographic patterns, was maintained even when subjected to the same selective pressure and that the ‘rare biosphere’, at least in these samples, were deeply divergent and did not act as a reservoir for microbiota that enabled convergent responses to change in environmental conditions.ConclusionsOur findings strongly support the occurrence of endemic microbial communities that show a structural resilience to environmental disturbances, spanning a wide range of physicochemical conditions. In the highly arid and nutrient-limited environment of the Dry Valleys, these results provide direct evidence of microbial biogeographic patterns that can shape the communities’ response in the face of future environmental changes.

Logistical and preference bias in participatory science butterfly data

The volume of and interest in unstructured participatory science data has increased dramatically in recent years. However, unstructured participatory science data contain taxonomic biases—encounters with some species are more likely to be reported than encounters with others. Taxonomic biases are driven by human preferences for different species and by logistical factors that make observing certain species challenging. We investigated taxonomic bias in reports of butterflies by characterizing differences between a dedicated participatory semi‐structured dataset, eButterfly, and a popular unstructured dataset, iNaturalist, in spatiotemporally explicit models. Across 194 butterfly species, we found that 53 species were overreported and 34 species were underreported in opportunistic data. Ease of identification and feature diversity were significantly associated with overreporting in opportunistic sampling, and strong patterns in overreporting by family were also detected. Quantifying taxonomic biases not only helps us understand how humans engage with nature but also is necessary to generate robust inference from unstructured participatory data.

Climatology, trends, and future projections of aerosol optical depth over the Middle East and North Africa region in CMIP6 models

This study assesses the aerosol optical depth (AOD) from historical simulations (2003–2014) and future climate scenarios (2015–2100) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) over the Middle East and North Africa (MENA) region. Multi-model mean (MME) AOD statistics are generated as the average of those from the five best-performing CMIP6 models, which reproduce observational climate statistics. These models were selected based on the validation of various climate metrics, including strong pattern correlations with observations (>0.8). The resulting MME reproduces the observed AOD seasonal cycle well. The observed positive trends (summer and annual) over the Arabian Peninsula (AP) and negative trends (winter) over North Africa are well captured by MME, as regional meteorological drivers associated with observed AOD trends, with few discrepancies. Crucially, the MME fails to capture the AOD trends over North West Africa (NWA). For MENA and NWA regions, two high-emission scenarios, SSP370 and SSP585, project a continuous rise in the annual mean AOD until the end of the century. In contrast, the low-emission scenarios, SSP126 and SSP245, project a decreasing AOD trend. Interestingly, the projected future AOD area-averaged over the AP region varies significantly across all four scenarios in time. Notably, a substantial decrease of about 8–10% in the AOD is projected by the SSP126, SSP245, and SSP585 scenarios at the end of the century (2080–2100) relative to the current period. This projected decrease in annual-mean AOD, including the frequency of extreme AOD years under SSP585, is potentially associated with a concurrent increase in annual-mean rainfall over the AP.

Geographic Drivers of Mercury Entry into Aquatic Food Webs Revealed by Mercury Stable Isotopes in Dragonfly Larvae.

Atmospheric mercury (Hg) emissions and subsequent transport and deposition are major concerns within protected lands, including national parks, where Hg can bioaccumulate to levels detrimental to human and wildlife health. Despite this risk to biological resources, there is limited understanding of the relative importance of different Hg sources and delivery pathways within the protected regions. Here, we used Hg stable isotope measurements within a single aquatic bioindicator, dragonfly larvae, to determine if these tracers can resolve spatial patterns in Hg sources, delivery mechanisms, and aquatic cycling at a national scale. Mercury isotope values in dragonfly tissues varied among habitat types (e.g., lentic, lotic, and wetland) and geographic location. Photochemical-derived isotope fractionation was habitat-dependent and influenced by factors that impact light penetration directly or indirectly, including dissolved organic matter, canopy cover, and total phosphorus. Strong patterns for Δ200Hg emerged in the western United States, highlighting the relative importance of wet deposition sources in arid regions in contrast to dry deposition delivery in forested regions. This work demonstrates the efficacy of dragonfly larvae as biosentinels for Hg isotope studies due to their ubiquity across freshwater ecosystems and ability to track variation in Hg sources and processing attributed to small-scale habitat and large-scale regional patterns.

Measuring Patriarchy in Italy*

ABSTRACT Patriarchy is an abstract concept; however, its consequences are visible and substantial in society in an endless list of events that mainly affect women’s lives, but do not exclude men’s life experience either. By defining a patriarchy index for Italy—for the first time ever—this article aims at describing patriarchy, from an economic perspective, as a complex aggregate, based on several stereotypes, represented by a series of variables related to behaviours, classified in four domains: the degree of patrilocality, the dominance of men over women, the dominance of older over younger generations, and socio-economic domination. As it is structured, the patriarchy index might complement the more famous Gender Equality Index (GEI), calculated by the European Institute of Gender Equality (EIGE), with a measure that focuses on the ‘invisible’ component of gender inequality. This case study on Italy represents an opportunity to confirm the well-known socio-economic dualism between regions in the North and South from a gender perspective. Regions in the North and Central regions score very close results and show that, although patriarchal stereotypes are still present and strong, patriarchy is becoming minoritarian. On the opposite side, the South still shows strong and majoritarian patriarchal patterns.

Pituitary Crooke cell neuroendocrine tumor of adrenocorticotropic hormone differentiation-specific transcription factor lineage: a clinicopathological analysis of six cases

Objective: To investigate the clinicopathological features of Crooke cell tumor of adrenocorticotropic hormone differentiation specific transcription factor (TPIT, also known as transcription factor 19, TBX19) lineage neuroendocrine tumors. Methods: Six cases of Crooke cell tumor diagnosed at the First Affiliated Hospital of University of Science and Technology of China, Hefei, China from October 2019 to October 2023 were collected. The clinical and pathological features of these cases were analyzed. Results: Among the six cases, one was male and five were female, with ages ranging from 26 to 75 years, and an average age of 44 years. All tumors occurred within the sella turcica. Clinical presentations included visual impairment in two cases, menstrual disorders in one case, Cushing's syndrome in one case, headache in one case, and one asymptomatic case discovered during a physical examination. Preoperative serum analyses revealed elevated levels of cortisol and adrenocorticotropic hormones in two cases, elevated cortisol in two cases, elevated adrenocorticotropic hormone in one case, and one case with a mild increase in prolactin due to the pituitary stalk effect. Magnetic resonance imaging revealed uneven enhancement of masses with maximum diameters ranging from 1.7 to 3.2 cm, all identified as macroadenomas. Microscopically, tumor cells exhibited irregular polygonal shapes, solid sheets, or pseudo-papillary arrangements around blood vessels. The cell nuclei were eccentric or centrally located, varying in size, with abundant cytoplasm. Some tumor cells showed perinuclear halo. Immunohistochemistry demonstrated diffuse strong positivity for TPIT in five cases, focal weak positivity for TPIT in one case, diffuse strong positivity for adrenocorticotropic hormone in all cases, and faint staining around the nuclei in a few cells. CK8/18 showed a strong positive ring pattern in more than 50% of tumor cells, focal weak positive expression of p53, and the Ki-67 positive index ranged 1%-5%. Periodic acid-Schiff staining revealed positive cytoplasm and negative perinuclear areas. Conclusions: Crooke cell tumor is a rare type of pituitary neuroendocrine tumors. Its pathological characteristics include a distinctive perinuclear clear zone and immunohistochemical markers, such as CK8/18 exhibiting a ring or halo pattern. This entity represents a high-risk subtype among pituitary neuroendocrine tumors, displaying a high risk of invasion and a propensity for recurrence. Accurate diagnosis is crucial for the postoperative follow-up and multimodal treatment planning.

Evaluating synthetic aperture radar surface winds for convective squalls in the Gulf of Mexico

AbstractThe detection and quantification of strong sea surface winds, reaching up to 25 m·s−1, whether associated with deep convection aloft or not, have been extensively discussed in previous studies. This method involves the combined observation of the same event from both low‐orbit altitude and geostationary (GEO) satellites. Strong surface winds observed by the Sentinel‐1 C‐band synthetic aperture radar (SAR) are robustly associated with deep convective clouds detected by GEO infrared sensors. The current paper aims to generalize the previous assessment of several convective wind events by collecting a larger dataset and comparing these data to in‐situ wind observations. To achieve this, we evaluated wind speeds retrieved from Sentinel‐1 SAR images against corresponding in‐situ wind measurements from all active buoys/stations in the Gulf of Mexico. Significant agreement between satellite‐based winds and in‐situ data was achieved, particularly for wind speeds exceeding 3 m·s−1, with even better agreement for wind speeds over 10 m·s−1. From this dataset, three specific convective cases were extracted to illustrate various stages of convective squall events: before, during, and after the occurrence of a squall peak. In each case, comparison with in‐situ measurements showed that SAR‐estimated wind speeds closely matched observed speeds, including the peak convective winds, which were estimated at 18.90 m·s−1 and measured at 20.69 m·s−1. Furthermore, combining these findings with GOES‐16 sequential images illustrates the temporal and spatial similarity between deep convection areas, estimated strong sea surface wind patterns, and measured wind speeds.

Investigating the interplay between urban dynamics and environmental factors in Thimphu, Bhutan: a satellite remote sensing approach.

The ability of the land surface temperature (LST) and normalized difference vegetation index (NDVI) to examine land surface change is regarded as an important climate variable. However, no significant systematic examination of urbanization concerning environmental variables has been undertaken in the narrow valley of Thimphu, Bhutan. Therefore, this study investigated the impact of land use/land cover (LULC) dynamics on LST, NDVI, and elevation, using Moderate Resolution Imaging Spectroradiometer (MODIS) data collected in Thimphu, Bhutan, from 2000 to 2020. The results showed that LSTs varied substantially among different land use types, with the highest occurring in built-up areas and the lowest occurring in forests. There was a strong negative linear correlation between the LST and NDVI in built-up areas, indicating the impact of anthropogenic activities. Moreover, elevation had a noticeable effect on the LST and NDVI, which exhibited very strong opposite patterns at lower elevations. In summary, LULC dynamics significantly influence LST and NDVI, highlighting the importance of understanding spatiotemporal patterns and their effects on ecological processes for effective land management and environmental conservation. Moreover, this study also demonstrated the applicability of relatively low-cost, moderate spatial resolution satellite imagery for examining the impact of urban development on the urban environment in Thimphu city.

Task and stimulus coding in the multiple-demand network.

In the human brain, a multiple-demand (MD) network plays a key role in cognitive control, with core components in lateral frontal, dorsomedial frontal and lateral parietal cortex, and multivariate activity patterns that discriminate the contents of many cognitive activities. In prefrontal cortex of the behaving monkey, different cognitive operations are associated with very different patterns of neural activity, while details of a particular stimulus are encoded as small variations on these basic patterns (Sigala etal, 2008). Here, using the advanced fMRI methods of the Human Connectome Project and their 360-region cortical parcellation, we searched for a similar result in MD activation patterns. In each parcel, we compared multivertex patterns for every combination of three tasks (working memory, task-switching, and stop-signal) and two stimulus classes (faces and buildings). Though both task and stimulus category were discriminated in every cortical parcel, the strength of discrimination varied strongly across parcels. The different cognitive operations of the three tasks were strongly discriminated in MD regions. Stimulus categories, in contrast, were most strongly discriminated in a large region of primary and higher visual cortex, and intriguingly, in both parietal and frontal lobe regions adjacent to core MD regions. In the monkey, frontal neurons show a strong pattern of nonlinear mixed selectivity, with activity reflecting specific conjunctions of task events. In our data, however, there was limited evidence for mixed selectivity; throughout the brain, discriminations of task and stimulus combined largely linearly, with a small nonlinear component. In MD regions, human fMRI data recapitulate some but not all aspects of electrophysiological data from nonhuman primates.

Microstructures evolution, texture characteristics and mechanical properties of extruded Mg-9Gd-3Nd-1Zn-1Sn-0.5Zr alloy

In this study, a comprehensive investigation was conducted to explore the microstructural evolution, texture characteristics, and mechanical properties of extruded Mg-9Gd-3Nd-1Zn-1Sn-0.5Zr alloys with varying extrusion ratios (ERs). Moreover, the high-temperature mechanical properties of the alloy and analyzed the corresponding fracture mechanisms were investigated. The findings unveiled a refinement in grain size and an improvement in homogeneity with increasing ER. Such refinement coincided with the disruption of coarse Mg5(Gd, Nd, Zn) eutectic phases, facilitating dynamic recrystallization. As a result, the extruded alloy manifested small grains, significant orientation difference in grain boundaries, and a weakened texture. In particular, the average grain size in the extrusion direction (ED) diminished to 13.29 μm (ER4), 9.62 μm (ER16), and 4.05 μm (ER25). And the ED texture of the ER4 alloy featured a strong (0001) basal bimodal pattern, whereas the ER16 and ER25 alloys showcased a random texture. Furthermore, the ER25 alloy displayed notable work hardening at temperatures of 200 °C or below, exerting a significant influence on its stress–strain curve. The ultimate tensile strength (UTS) of the alloy remained consistently above 275.09 MPa, demonstrating ductile fracture characteristics characterized by numerous dimples at temperatures of 200 °C or higher. The study identified the second phase as the primary contributor to enhancing the high-temperature tensile characteristics of the alloy. In summary, this research developed a unique high-strength Mg-9Gd-3Nd-1Zn-1Sn-0.5Zr alloy characterized by fine grain and texture strengthening. The alloy exhibited remarkable stability at temperatures of 250 °C or lower, making it a promising candidate for applications in high-temperature applications.

Vegetation patterns associated with nutrient availability and supply in high-elevation tropical Andean ecosystems

Abstract. Plants absorb nutrients and water through their roots and modulate soil biogeochemical cycles. The mechanisms of water and nutrient uptake by plants depend on climatic and edaphic conditions, as well as the plant root system. Soil solution is the medium in which abiotic and biotic processes exchange nutrients, and nutrient concentrations vary with the abundance of reactive minerals and fluid residence times. High-altitude ecosystems of the tropical Andes are interesting for the study of the association between vegetation, soil hydrology, and mineral nutrient availability at the landscape scale for different reasons. First of all, because of low rock-derived nutrient stocks in intensely weathered volcanic soils, biocycling of essential nutrients by plants is expected to be important for plant nutrient acquisition. Second, the ecosystem is characterized by strong spatial patterns in vegetation type and density at the landscape scale and hence is optimal to study soil-water–vegetation interactions. Third, the area is characterized by high carbon stocks but low rates of organic decomposition that might vary with soil hydrology, soil development, and geochemistry, all interconnected with vegetation. The páramo landscape forms a vegetation mosaic of bunch grasses, cushion-forming plants, and forests. In the nutrient-depleted nonallophanic Andosols, the plant rooting depth varies with drainage and soil moisture conditions. Rooting depths were shallower in seasonally waterlogged soils under cushion plants and deeper in well-drained soils under forest and tussock grasses (>100 cm). Vegetation composition is a relevant indicator of rock-derived nutrient availability in soil solutions. The soil solute chemistry revealed patterns in plant-available nutrients that were not mimicking the distribution of total rock-derived nutrients nor the exchangeable nutrient pool but clearly resulted from strong biocycling of cations and removal of nutrients from the soil by plant uptake or deep leaching. Soils under cushion plants showed solute concentrations of Ca, Mg, and Na of about 3 times higher than forest and tussock grasses. Differences were even stronger for dissolved Si with solute concentrations that were 16 times higher than forest and 6 times higher than tussock grasses. Amongst the macronutrients derived from lithogenic sources, P was a limiting nutrient with very low solute concentrations (<1 µM) for all three vegetation types. In contrast K showed greater solute concentrations under forest soils with values that were 2 to 3 times higher than under cushion-forming plants or tussock grasses. Our findings have important implications for future management of Andean páramo ecosystems where vegetation type distributions are dynamically changing as a result of warming temperatures and land use change. Such alterations may lead not only to changes in soil hydrology and solute geochemistry but also to complex changes in weathering rates and solute export downstream with effects on nutrient concentrations in Andean rivers and high-mountain lakes.

Biogeographical patterns in the seasonality of bird collisions with aircraft

Abstract Bird collisions with aircraft pose a serious threat to human safety. However, broad‐scale patterns in how bird strikes might vary through space and time have yet to be fully understood. Here, we conducted a biogeographical study of bird strikes to answer two questions: (1) Are bird strikes higher at certain times of the year in the Northern and Southern Hemispheres? and (2) Is seasonality in bird strikes more prominent in the Northern Hemisphere than in the Southern Hemisphere? To answer these questions, we collated data on monthly bird strikes from 122 airports across the globe and used circular statistics to test for hemispherical asymmetries in the circular mean and variance in bird strikes. Results showed that annual peaks in bird strikes occurred between late summer to autumn seasons, and as a result, they occurred at opposite times of year in the northern and southern hemispheres. Results also showed that bird strikes were more seasonal in the Northern Hemisphere than in the Southern Hemisphere, where strikes tended to occur more consistently throughout the year. Practical implication: Overall results indicate that avian collisions with aircraft show strong biogeographical patterning, concomitant with global patterns in bird breeding seasons and migration tendencies.

Montane diversification as a mechanism of speciation in neotropical butterflies.

The mountains in the Atlantic Forest domain are environments that harbor a high biodiversity, including species adapted to colder climates that were probably influenced by the climatic variations of the Pleistocene. To understand the phylogeographic pattern and assess the taxonomic boundaries between two sister montane species, a genomic study of the butterflies Actinote mantiqueira and A. alalia (Nymphalidae: Acraeini) was conducted. Analyses based on partial sequences of the mitochondrial gene COI (barcode region) failed to recover any phylogenetic or genetic structure discriminating the two species or sampling localities. However, single nucleotide polymorphisms gathered using Genotyping-by-Sequencing provided a strong isolation pattern in all analyses (genetic distance, phylogenetic hypothesis, clustering analyses, and F ST statistics) which is consistent with morphology, separating all individuals of A. alalia from all populations of A. mantiqueira. The three sampled mountain ranges where A. mantiqueira populations occur-Serra do Mar, Serra da Mantiqueira, and Poços de Caldas Plateau-were identified as three isolated clusters. Paleoclimate simulations indicate that both species' distributions changed according to climatic oscillations in the Pleistocene period, with the two species potentially occurring in areas of lower altitude during glacial periods when compared to the interglacial periods (as the present). Besides, a potential path between their distribution through the Serra do Mar Mountain range was inferred. Therefore, the Pleistocene climatic fluctuation had a significant impact on the speciation process between A. alalia and A. mantiqueira, which was brought on by isolation at different mountain summits during interglacial periods, as shown by the modeled historical distribution and the observed genetic structure.