Visual Eosin Y-Based Photosensitization Sensing Systems for Ultrasensitive Detection of Diclofenac with Single-Atom Co─N2O2 Site-Immobilized g-C3N4 Nanosheets

It is highly desired to develop a visual sensing system for ultrasensitive detection of colorless diclofenac (DCF), yet with a significant challenge. Herein, a novel dye-based photosensitization sensing system has been successfully developed for detecting DCF for the first time, in which the used dye eosin Y (DeY) can strongly absorb visible light and then be decolorized obviously by transferring photogenerated electrons to g-C3N4 nanosheets (CN), while the built single-atomic Co─N2O2 sites on CN by boron-oxygen connection can competitively adsorb DCF to impede the photosensitization decoloration of DeY. This system exhibits a broad detection range from 8 ng L-1 to 2 mg L-1 with 535 nm light, an exceptionally low detection limit (3.5 ng L-1), and remarkable selectivity. Through the time-resolved, in situ technologies, and theoretical calculations, the decolorization of DeY is attributed to the disruption of DeY's conjugated structure caused by the triplet excited state electron transfer from DeY to CN, meanwhile, the adsorbed oxygen facilitates the charge transfer process. The preferential adsorption of DCF mainly depends on the strong interactions between the as-constructed single-atom Co and Cl in DCF. This study opens an innovative light-driven sensing system by combining dye and single-atom metal/nanomaterial for visually intuitive detection of environmental pollutants.

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmental change.

Quantification of Foraging Areas for the Northern Bald Ibis (Geronticus eremita) in the Northern Alpine Foothills: A Random Forest Model Fitted with Optical and Actively Sensed Earth Observation Data

The Northern Bald Ibis (Geronticus eremita, NBI) is an endangered migratory species, which went extinct in Europe in the 17th century. Currently, a translocation project in the frame of the European LIFE program is carried out, to reintroduce a migratory population with breeding colonies in the northern and southern Alpine foothills and a common wintering area in southern Tuscany. The population meanwhile consists of about 200 individuals, with about 90% of them carrying a GPS device on their back. We used biologging data from 2021 to model the habitat suitability for the species in the northern Alpine foothills. To set up a species distribution model, indices describing environmental conditions were calculated from satellite images of Landsat-8, and in addition to the well-proven use of optical remote sensing data, we also included Sentinel-1 actively sensed observation data, as well as climate and urbanization data. A random forest model was fitted on NBI GPS positions, which we used to identify regions with high predicted foraging suitability within the northern Alpine foothills. The model resulted in 84.5% overall accuracy. Elevation and slope had the highest predictive power, followed by grass cover and VV intensity of Sentinel-1 radar data. The map resulting from the model predicts the highest foraging suitability for valley floors, especially of Inn, Rhine, and Salzach-Valley as well as flatlands, like the Swiss Plateau and the agricultural areas surrounding Lake Constance. Areas with a high suitability index largely overlap with known historic breeding sites. This is particularly noteworthy because the model only refers to foraging habitats without considering the availability of suitable breeding cliffs. Detailed analyses identify the transition zone from extensive grassland management to intensive arable farming as the northern range limit. The modeling outcome allows for defining suitable areas for further translocation and management measures in the frame of the European NBI reintroduction program. Although required in the international IUCN translocation guidelines, the use of models in the context of translocation projects is still not common and in the case of the Northern Bald Ibis not considered in the present Single Species Action Plan of the African-Eurasian Migratory Water bird Agreement. Our species distribution model represents a contemporary snapshot, but sustainability is essential for conservation planning, especially in times of climate change. In this regard, a further model could be optimized by investigating sustainable land use, temporal dynamics, and climate change scenarios.

Bird migration: Flying high to avoid overheating?

Acts of flight have always baffled humans. Recent tracking studies of birds only add to the awe and mystery. A new study shows that migrating great snipes fly high - over two kilometres high - during the day and lower at night. Why?

Monarch Butterfly Migration as an Integrative Model of Complex Trait Evolution

AbstractUnderstanding the genetic architecture of complex trait adaptation in natural populations requires the continued development of tractable models that explicitly confront organismal and environmental complexity. A decade of high-throughput sequencing-based investigations into the genomic basis of migration points to an integrative framework that incorporates quantitative genetics, evolutionary developmental biology, phenotypic plasticity, and epigenetics to explain migration evolution. In this perspective, I argue that the transcontinental migration of the monarch butterfly (Danaus plexippus) can serve as a compelling system to study the mechanism of evolutionary lability of a complex trait. Monarchs show significant phenotypic and genotypic diversity across their global range, with phenotypic switching that allows for explicit study of evolutionary lability. A developmental approach for elucidating how migratory traits are generated and functionally integrated will be important for understanding the evolution of monarch migration traits. I propose a plasticity threshold model to describe migration lability, and I describe novel functional techniques that will help resolve open questions and model assumptions. I conclude by considering the relationships between adaptive genetic architecture, anthropogenic climate change, and conservation management practice and the timeliness of the monarch migration model to illuminate these connections given the rapid decline of the North American migration.

Timely poacher detection and localization using sentinel animal movement

Wildlife crime is one of the most profitable illegal industries worldwide. Current actions to reduce it are far from effective and fail to prevent population declines of many endangered species, pressing the need for innovative anti-poaching solutions. Here, we propose and test a poacher early warning system that is based on the movement responses of non-targeted sentinel animals, which naturally respond to threats by fleeing and changing herd topology. We analyzed human-evasive movement patterns of 135 mammalian savanna herbivores of four different species, using an internet-of-things architecture with wearable sensors, wireless data transmission and machine learning algorithms. We show that the presence of human intruders can be accurately detected (86.1% accuracy) and localized (less than 500 m error in 54.2% of the experimentally staged intrusions) by algorithmically identifying characteristic changes in sentinel movement. These behavioral signatures include, among others, an increase in movement speed, energy expenditure, body acceleration, directional persistence and herd coherence, and a decrease in suitability of selected habitat. The key to successful identification of these signatures lies in identifying systematic deviations from normal behavior under similar conditions, such as season, time of day and habitat. We also show that the indirect costs of predation are not limited to vigilance, but also include (1) long, high-speed flights; (2) energetically costly flight paths; and (3) suboptimal habitat selection during flights. The combination of wireless biologging, predictive analytics and sentinel animal behavior can benefit wildlife conservation via early poacher detection, but also solve challenges related to surveillance, safety and health.

Migrant birds and mammals live faster than residents

Billions of vertebrates migrate to and from their breeding grounds annually, exhibiting astonishing feats of endurance. Many such movements are energetically costly yet there is little consensus on whether or how such costs might influence schedules of survival and reproduction in migratory animals. Here we provide a global analysis of associations between migratory behaviour and vertebrate life histories. After controlling for latitudinal and evolutionary patterns, we find that migratory birds and mammals have faster paces of life than their non-migratory relatives. Among swimming and walking species, migrants tend to have larger body size, while among flying species, migrants are smaller. We discuss whether pace of life is a determinant, consequence, or adaptive outcome, of migration. Our findings have important implications for the understanding of the migratory phenomenon and will help predict the responses of bird and mammal species to environmental change.

Migration is costly. In the first global analysis of migratory vertebrates, authors report that migratory birds and mammals have faster paces of life than their non-migratory relatives, and that among swimming and walking species, migrants tend to be larger, while among flying species, migrants are smaller.

Flux towers in the sky: global ecology from space

Global ecology - the study of the interactions among the Earth's ecosystems, land, atmosphere and oceans - depends crucially on global observations: this paper focuses on space-based observations of global terrestrial ecosystems. Early global ecology relied on an extrapolation of detailed site-level observations, using models of increasing complexity. Modern global ecology has been enabled largely by vegetation indices (greenness) from operational space-based imagery but current capabilities greatly expand scientific possibilities. New observations from spacecraft in orbit allowed an estimation of gross carbon fluxes, photosynthesis, biomass burning, evapotranspiration and biomass, to create virtual eddy covariance sites in the sky. Planned missions will reveal the dimensions of the diversity of life itself. These observations will improve our understanding of the global productivity and carbon storage, land use, carbon cycle-climate feedback, diversity-productivity relationships and enable improved climate forecasts. Advances in remote sensing challenge ecologists to relate information organised by biome and species to new data arrayed by pixels and develop theory to address previously unobserved scales.

Planetary Epidemiology: Towards First Principles

PURPOSE OF REVIEW

To combine evolutionary principles of competition and co-operation with limits to growth models, generating six principles for a new sub-discipline, called "planetary epidemiology." Suggestions are made for how to quantify four principles.

RECENT FINDINGS

Climate change is one of a suite of threats increasingly being re-discovered by health workers as a major threat to civilization. Although "planetary health" is now in vogue, neither it nor its allied sub-disciplines have, as yet, had significant impact on epidemiology. Few if any theorists have sought to develop principles for Earth system human epidemiology, in its ecological, social, and technological milieu. The principles of planetary epidemiology described here can be used to stimulate applied, quantitative work to explore past, contemporary, and future population health, at scales from local to planetary, in order to promote enduring health. It is also proposed that global well-being will decline this century, without radical reform.

Time, geography and weather provide insights into the ecological strategy of a migrant species

Farmland and migratory bird populations are in decline. The Common quail (Coturnix coturnix) provides an exception to this trend and its populations have remained stable over the last two decades. However, some basic facts regarding quail biology and ecology, such as the geographic distribution of age and sex classes during the summer, remain poorly understood. We analyzed 43,194 Spanish quail ringing records from 1961 to 2014 to assess the effects of geography and weather conditions on the probability that individuals will be ringed during the various stages of their annual cycle (arrival -spring migration-, stationary breeding period, departure -autumn migration- and winter) for the different quail age-sex classes over time. We found that spatial distribution of the age and sex classes can be explained by date, latitude, longitude, altitude, rainfall, and temperature. Our results suggest that date accounts for most of the variation in the distribution of quail age classes, followed by the weather variables, and then latitude, and altitude. Similarly, date also accounts for most of the variation in the distribution of the two sexes. These results could partially explain why this species has avoided population decline, since its ecological strategy is based on its temporal and spatial distribution combined with the segregation of age and sex groups. We hypothesize that the distribution of quail age and sex classes follows variations in weather and habitat suitability to exploit seasonal and geographic variations in resource availability. The migratory and nomadic movements of quail, combined with the occurrence of multiple breeding attempts within a single season, may also allow these birds to overcome the impacts of predators and anthropogenic environmental change. Conservation and management efforts should therefore take account of these age and sex related temporal and spatial patterns.

Decreasing brown bear (Ursus arctos) habitat due to climate change in Central Asia and the Asian Highlands

Around the world, climate change has impacted many species. In this study, we used bioclimatic variables and biophysical layers of Central Asia and the Asian Highlands combined with presence data of brown bear (Ursus arctos) to understand their current distribution and predict their future distribution under the current rate of climate change. Our bioclimatic model showed that the current suitable habitat of brown bear encompasses 3,430,493 km2 in the study area, the majority of which (>65%) located in China. Our analyses demonstrated that suitable habitat will be reduced by 11% (378,861.30 km2) across Central Asia and the Asian Highlands by 2,050 due to climate change, predominantly (>90%) due to the changes in temperature and precipitation. The spatially averaged mean annual temperature of brown bear habitat is currently -1.2°C and predicted to increase to 1.6°C by 2,050. Mean annual precipitation in brown bear habitats is predicted to increase by 13% (from 406 to 459 mm) by 2,050. Such changes in two critical climatic variables may significantly affect the brown bear distribution, ethological repertoires, and physiological processes, which may increase their risk of extirpation in some areas. Approximately 32% (1,124,330 km2) of the total suitable habitat falls within protected areas, which was predicted to reduce to 1,103,912 km2 (1.8% loss) by 2,050. Future loss of suitable habitats inside the protected areas may force brown bears to move outside the protected areas thereby increasing their risk of mortality. Therefore, more protected areas should be established in the suitable brown bear habitats in future to sustain populations in this region. Furthermore, development of corridors is needed to connect habitats between protected areas of different countries in Central Asia. Such practices will facilitate climate migration and connectivity among populations and movement between and within countries.

Can animals predict earthquakes?: Bio-sentinels as seismic sensors in communist China and beyond

This paper examines the international research on abnormal animal behavior prior to earthquakes, with a focus on Chinese seismology during the Cultural Revolution. China experienced a series of powerful earthquakes in the 1960s and 1970s; in response, its scientists developed approaches to earthquake prediction, including the use of bio-sentinels. The paper demonstrates that Chinese seismology did not treat an earthquake simply as a geophysical event, but rather as an amalgam of environmental phenomena, including sensory experiences. Hence, distributive experience and sensory networks of humans and bio-sentinels constituted an important component of studying the environment. This historical case suggests insights into bio-monitoring of the global environment.