Terrestrial Surface Research Articles

Embedded physical constraints in machine learning to enhance vegetation phenology prediction

ABSTRACT Vegetation phenology plays a pivotal role in ecological processes on terrestrial surfaces and the interactions between the biosphere and atmospheric feedback. Current attempts to retrieve vegetation phenology have primarily depended on vegetation indices extracted from satellite remote sensing imagery. These approaches often neglect the underlying physical mechanisms associated with climatic factors, and there is a notable absence of evaluations and comparisons with field-observed phenology inventory data. To address these limitations, this paper proposes an innovative physical constraint neural networks (PCNNs) model that combines machine learning techniques with physical mechanisms to enhance the accuracy of vegetation phenology predictions. By incorporating meteorological variables into a machine learning model and by using the Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset to identify the vegetation phenology of four vegetation types in North America, this study delved into the relationship between vegetation phenology and climate factors as well as its impacts on ecosystems. Our model demonstrated high accuracy compared to machine learning methods without physical mechanisms when validated by field observations from PhenoCam and the USA National Phenology Network (USA-NPN) spanning from 2001 to 2021. The results show that the overall root mean square error (RMSE) with physical constraints is reduced to 12.37 days, higher by 2.6 days than the machine learning method without physical constraints. We compared four vegetation types using different machine learning and traditional rule-based methods, deciduous vegetation (DV) exhibited the most favorable prediction results, with the RMSE and mean bias error (MBE) as low as 5.71 days and 4.06 days in PCNNs model, respectively. This was followed by evergreen needle-leaved forests and mixed forests with RMSE of 12.32 and 13.28 days, respectively. The stressed deciduous vegetation type had the worst prediction result of 19.86 days (RMSE), and the weighted index of agreement (WIA) attained a value of 0.68. These findings suggest that the model embedded with physical constraints significantly boosted prediction accuracy for four common vegetation types, particularly for DV, compared to the unconstrained ML model. It offers valuable insights into the incorporation of physical mechanisms within machine learning models. This research paves the way for substantial advancements in the field of land surface phenology, enabling more accurate and reliable predictions of vegetation phenology in various ecological and climatic contexts.

Impact of climate changes on agroresources of Ukrainian Polissia based on geospatial data

Aim. To determine the patterns of the climate change impact on the transformation of agricultural production and the ecosystem of Ukrainian Polissia in terms of time and space. Methods. Satellite and statistical data for the last 40 years (1982–2022) were used. The mean temperature for the vegetation period was defined by the sum of radiation temperatures of the terrestrial surface, calculated using the data of the infrared range (10.3–11.3; 11.4–12.4 μm) of the high-precision AVHRR radiometer of artificial meteorological Earth's satellites, NOAA, and the precipitation dynamics – using the data of ERA5 ECMWF/Copernicus Climate Change Service. The impact of climate change on the vegetation state and phenological parameters, including the beginning, end, and duration of the vegetation season, was determined by the normalized difference vegetation index (NDVI), obtained using the data of the infrared (0.72–1.1 μm) and red (0.58–0.68 μm) ranges of the AVHRR radiometer on the website of STAR NESDIS NOAA. Crop yields and the dynamics of sown areas were determined by the data from the State Statistics Service of Ukraine. The information about the dynamics of the forest cover was obtained using the Global Forest Watch satellite data. To evaluate the impact of climate change on Ukraine's forests, the investigation was conducted on burnt forest areas, using the MCD64A1 6.1 index, developed on the basis of the MODIS satellite data. Results. According to the satellite data, the radiation temperature of the terrestrial surface during the growing period increased by 2.2 ºС on average in the territory of Ukrainian Polissia over the last 40 years. There is a regional difference in the temperature regime observed in the direction from west to east. In the territory of western Polissia, the increase in the temperature of the terrestrial surface in recent decades was within the range of 1.2–1.6, and in the central and eastern parts – within 2.3–2.9 ºС. Due to the warming, the duration of the growing period was extended by 21–35 days, mostly because of earlier spring onset. There is a descending trend in the average annual precipitation amount down to 20–30 mm, which is especially notable for central and eastern Polissia. The warming was the reason for the introduction of the crops, new for this region, into the structure of sown areas, especially corn and sunflower, which had a generally positive effect on the vegetation state by the NDVI index, which increased from 0.30 in 1982–1992 to 0.36 in 2012–2022 on average. The crop yield increased accordingly, and according to the statistical data for the recent years, amounted to: corn – 7.0–9.5 t/ha, winter wheat – 4.5–5.0, and sunflower – 1.5–2.0 t/ha, which is close to the level of their yield on chornozem. At the same time, due to climate change and the transformation of agricultural activity, there has been a higher risk of deterioration in the ecological state of typical Polissia landscapes, droughts, and soil degradation. According to the results of the analysis of twenty-two years of the dynamics in forest fires, the largest areas of burnt forests were registered in 2012 (694.30 sq.km), 2015 (1,078.81 sq.km), and 2020 (776.27 sq.km), which demonstrated the increase in fires during the recent decade along with the tendency towards longer fire hazard period. Conclusions. The increase in the temperature of the terrestrial surface of the Ukrainian Polissia during the growing period and the lengthening of the growing period created the conditions for corn and sunflower to be introduced into the arable areas, which had a positive impact on the vegetation state index, NDVI. As a result of these transformations both in the sown area of these crops and their yield, Polissia is becoming a new grain-oil belt of Ukraine. Concurrently, there are higher risks associated with maintaining high performance of agroecosystems and the increase in the risks for soil degradation processes, the deterioration of the ecological state of wetlands and forests, as well as drying-out of small rivers and lakes. Balancing the high yield of modern agroecosystems and safe nature management requires systemic measures in adapting the agricultural activity and nature management to new climatic conditions, which requires implementing the management of soil, water, and bio-resources, achieving optimal parameters of fertility for mineral and peaty-swampy soils. Reconstructing current land reclamation systems to optimize water regimes for the agricultural lands and protect typical Polissia ecosystem is needed.

Characteristics of deep-sea microbial cellulases: key determinants of the ultimate fate of plant biomass on Earth

Land plants, especially those with significant woody biomass, represent the largest source of biomass on Earth, making the biodegradation of lignocellulosic materials critical to understanding the global carbon cycle. Cellulose, a major component of lignocellulose, is notoriously resistant to degradation due to its highly crystalline structure. While the degradation of cellulose by terrestrial microbes has been extensively studied, the mechanisms of cellulose degradation in deep-sea environments remain largely unexplored. The deep-sea ecosystem depends on organic matter, such as cellulose, that is synthesized in terrestrial environments and surface waters and descends to the deep sea. Recent studies suggest that a significant amount of cellulose is likely to reach the deep sea. Here, we present an in-depth study of cellulases from a novel deep-sea γ-proteobacterial strain TOYAMA8, isolated from Toyama Bay, Japan, using Surface Pitting Observation Technology (SPOT), a highly sensitive assay for enzymatic cellulose hydrolysis. The cellulases of strain TOYAMA8 show similarities to those of a previously reported deep-sea cellulolytic microbe, Marinagarivorans cellulosilyticus strain GE09. Genomic and transcriptomic analyses of these strains reveal novel cellulase genes and mechanisms that differ from terrestrial counterparts, shedding light on the unique adaptations of deep-sea microbes to recalcitrant biomass. In particular, these strains produce high-molecular-weight cellulases with unique domain architectures, likely optimized for membrane anchoring, which prevents enzyme diffusion and ensures efficient localized activity. Our findings provide critical insights into the microbial cellulose degradation in the deep sea, highlighting its role in the fate of organic carbon and the potential for biotechnological applications in biorefineries.

Long-term variations of global radiation in Central Europe 1950–2020 and their impact on terrestrial surface air warming

Long-term variations of global radiation in Central Europe 1950–2020 and their impact on terrestrial surface air warming

Using Google Earth Engine open-source code for land surface temperature estimation from Landsat data in Chuong My district, Hanoi city, Vietnam

Land surface temperature (LST) in association with urbanization has significantly influenced on local climates and terrestrial surface processes. By using multi-temporal Landsat data in the GEE platform, the study has found that there have been changes in land covers due to the main drivers of industrial development, urban and built-up expansion. This study estimated land surface temperature (LST) in Chuong My district from Landsat 5, 7, 8 and 9 thermal infrared sensors, using different surface emissivity sources. The Google Earth Engine (GEE), an advanced earth science data and analysis platform, offers the estimation of LST products, covering the time period from 2000 to 2024 in study site. RF algorithm for land cover classification and mapping is suggested to be applied in Chuong My district, with overall accuracy of land cover mapping in 2024 being 91.9% with Kappa coefficient of 0.89. The period 2000-2010 showed that 327.0 ha of land were converted to land for industrial development, urban and residential land, while the period 2010-2024 continued to witness a continued conversion of land to other land use purposes, with a decrease in agricultural land area (65.7 ha) and an increase in industrial land use (65.2 ha), but the rate of conversion was much lower than the previous period (2000-2024). The periods of 2000-2010 and 2010-2024 showed that there have been significant changes in land surface temperature. Most of the surface temperature in the entire region increased by over 20C, especially in the period 2003-2015 when a total area of 1424 ha had the temperature increased by above 30C. This is a consequence of the process of urbanization and industrialization, which began to take place in 2008, along with the process of changing the land cover status of the study area. Further studies are needed to better understand the thermal conductivity of surface materials and to plan how to reduce LST in such areas.

Factors influencing carbon and water use efficiency in changing environments

IntroductionVegetation plays a crucial role in terrestrial ecosystems, acting as a vital link connecting the lithosphere, hydrosphere, and atmosphere in terms of energy flow and material cycling. Changes in surface vegetation significantly regulate the water cycle, energy flow within terrestrial surfaces, and global carbon balance.MethodsThis study focuses on nine major river basins in China to quantitatively investigate the impacts of climate factors, vegetation dynamics, and land use changes on carbon use efficiency (CUE) and water use efficiency (WUE).ResultsThe primary controlling factors of WUE trends are NDVI (average contribution: 33.75% ± 6.90%) and VPD (average contribution: 28.04% ± 3.98%). NDVI predominates in the Haihe, Yellow River, Yangtze River, Pearl River, and Songliao River basins, while shortwave radiation (Srad) dominates in the southeastern rivers and inland river areas, and humidity (Shum) in the southwestern river basins. For CUE trends, the main controlling factors are Srad (average contribution: 36.46% ± 3.40%) and precipitation (Pre) (average contribution: 26.72% ± 5.20%). NDVI negatively influences the Huaihe River and southeastern river basins, while Pre negatively influences the Songliao River and Yellow River basins, and Srad negatively influences the Huaihe and southwestern river basins. Pre predominates in the Huaihe, Songliao, Haihe, southwestern river basins, and inland river areas, while Srad predominates in the Pearl River, Yangtze River, and Yellow River basins.DiscussionClimate factors and vegetation dynamics have significant regional impacts on WUE and CUE across different river basins, especially the roles of NDVI and VPD on WUE, and Srad and precipitation on CUE. These differences underscore the importance of developing region-specific management strategies to optimize ecosystem services in each basin.

Understanding the effects of livestock grazing on dryland plant communities within the context of abiotic variability

AbstractDrylands, which cover more than 40% of the Earth's terrestrial surface, face rising agricultural demand and the influence of climate change. Understanding how livestock grazing pressure and local climate affect these environments is pivotal for informed land management. We studied big sagebrush plant communities in southwestern Wyoming over grazing gradients created by artificial livestock watering points. To explore the role of abiotic factors in shaping plant community response to grazing, we assessed the response of plant functional groups to grazing while accounting for soil texture variability across a precipitation gradient. Our models estimated that sagebrush cover responded positively to grazing intensity, with a 6% increase in cover with intensity when comparing the heaviest grazing treatment with the lowest grazing intensity. Perennial bunchgrass cover, the primary forage component, had a small negative response, a 3% decrease in cover from the lowest grazing intensity to the highest. Grazing intensity had no effect on bunchgrass density, perennial forbs, or rhizomatous grasses. Compared with abiotic factors, grazing intensity had a small effect on perennial bunchgrass and bare ground. We found that precipitation explained a 13% increase in perennial bunchgrass cover and a 34% decrease in bare ground cover compared with a 6% increase with increasing intensity across our grazing gradients. Sand content also had a larger effect on perennial bunchgrass cover and density than grazing. Increased sand content was associated with increased bunchgrass cover and density, supporting the inverse texture hypothesis. Our results show that while livestock grazing impacts sagebrush plant communities, its effect is small when compared with the effects of climate and soil. Our study contributes to a growing body of research emphasizing the need to contextualize plant community responses to grazing within specific climatic and edaphic conditions, which will promote effective land management in dryland ecosystems.

Indigenous justice frameworks for relational ethics in land-based design

ABSTRACT In the face of systematic expropriation, massive biodiversity loss, and the ongoing climate crisis, Indigenous peoples, knowledge, and labor have protected over 80% of the global biodiversity. This is remarkable given that Indigenous management or tenure remains over 20–25% of the planet’s terrestrial surface. Indigenous people’s capacity to protect biodiversity within their territories cannot be separated from the ethical frameworks that shape their relationships with land. These frameworks have been articulated by a diverse array of Indigenous scholars across the globe, and while they cannot be generalized, many share principles that go beyond dominant Western Scientific approaches that normalize utilitarian or idealized (e.g. ideals of wilderness) ethical systems. We argue that dominant policy and research discourses around land-based practices such as nature-based solutions and green infrastructure, will not be effective ‘solutions’ to ongoing crises of climate change and biodiversity loss. Instead, we must go beyond paradigms of improvement and anthropocentric utility and ground land-based practices in the paradigm of relational ethics. Through this perspective paper, we argue that rather than seeking solutions through redesigning ecosystems for utilitarian reasons, all interventions on Indigenous ancestral lands (recognized by settler states or not) should first center relational ethical approaches for land-based design practices and ground efforts in Indigenous justice. Our proposed ‘Indigenous Justice Frameworks for Relational Ethics in Land-based Design’ is based on the inseparability of bodies, lands, and knowledges, and is guided by the following elements: (1) generative refusal, (2) centering healing, reparation, and right relations, and (3) restoring and evolving Indigenous governance.

A Multiscalar Standardized Vapor Pressure Deficit Index for Drought Monitoring and Impacts

ABSTRACTVapour pressure deficit (VPD) is a critical measure of the atmospheric demand for water and can be used to assess short‐term and seasonal drought. To provide for probabilistic comparisons of VPD across space and time, we develop a Standardized Vapor Pressure Deficit Index (SVPDI). Similar to the way that other standardised drought indices are used, SVPDI allows for the analysis and comparison of changes in VPD across regions with different base level VPD values. It also should be useful for analysing impacts on vegetation that has varying levels of adaptation to high VPD. We use 1‐, 3‐, 6‐ and 12‐month timescales for the development of SVPDI and show that the gamma distribution is superior to other zero‐limited probability distributions for analysing VPD and, therefore, for calculating SVPDI. Then, focusing on the short‐term variations at the 1‐ and 3‐month timescales, we show how SVPDI has changed globally from 1958 to 2023 and how those changes differ from those of the commonly used Standardized Precipitation Evaporation Index (SPEI). We find that SVPDI shows more widespread drying conditions that also are larger in magnitude compared to those of SPEI. Although the two indices are moderately well correlated across the terrestrial surface, we discover that they are more decoupled in humid and arid regions compared to dry sub‐humid and semi‐arid regions. Using four locations that have recently experienced severe drought, we find that SVPDI generally showed longer drought duration and more severe drought events in the last decade when compared to SPEI.

Algae-fungi symbioses and bacteria-fungi co-exclusion drive tree species-specific differences in canopy bark microbiomes.

With over 3 trillion trees, forest ecosystems comprise nearly one-third of the terrestrial surface of the Earth. Very little attention has been given to the exploration of the above-ground plant microbiome of trees, its complex trophic interactions, and variations among tree species. To address this knowledge gap, we applied a primer-independent shotgun metatranscriptomic approach to assess the entire living canopy bark microbiome comprising prokaryotic and eukaryotic primary producers, decomposers, and various groups of consumers. With almost 1500 genera, we found a high microbial diversity on three tree species with distinct bark textures: oak (Quercus robur), linden (Tilia cordata), both with rough bark, and maple (Acer pseudoplatanus) with smooth bark. Core co-occurrence network analysis revealed a rich food web dominated by algal primary producers, and bacterial and fungal decomposers, sustaining a diverse community of consumers, including protists, microscopic metazoans and predatory bacteria. Whereas maple accommodated a depauperate microbiome, oak and linden accommodated a richer microbiome mainly differing in their relative community composition: Bacteria exhibited an increased dominance on linden, whereas co-occurring algae and fungi dominated on oak, highlighting the importance of algal-fungal lichen symbioses even at the microscopic scale. Further, due to bacteria-fungi co-exclusion, bacteria on bark are not the main beneficiaries of algae-derived carbon compounds as it is known from aquatic systems.

Uncovering true significant trends in global greening

The global greening trend, marked by significant increases in vegetation cover across ecoregions, has attracted widespread attention. However, even robust traditional methods, like the non-parametric Mann-Kendall test, often overlook crucial factors such as serial correlation, spatial autocorrelation, and multiple testing, particularly in spatially gridded data. This oversight can lead to inflated significance of detected spatiotemporal trends. To address these limitations, this research introduces the True Significant Trends (TST) workflow, which enhances the conventional approach by incorporating pre-whitening to control for serial correlation, Theil-Sen (TS) slope for robust trend estimation, the Contextual Mann-Kendall (CMK) test to account for spatial and cross-correlation, and the adaptive False Discovery Rate (FDR) correction. Using AVHRR NDVI data over 42 years (1982–2023), we found that conventional workflow identified up to 50.96% of the Earth's terrestrial land surface as experiencing statistically significant vegetation trends. In contrast, the TST workflow reduced this to 38.16%, effectively filtering out spurious trends and providing a more accurate assessment. Among these significant trends identified using the TST workflow, 76.07% indicated greening, while 23.93% indicated browning. Notably, considering areas (pixels) with NDVI values above 0.15, greening accounted for 85.43% of the significant trends, with browning making up the remaining 14.57%. These findings strongly validate the ongoing global greening of vegetation. They also suggest that incorporating more robust analytical methods, such as the True Significant Trends (TST) approach, could significantly improve the accuracy and reliability of spatiotemporal trend analyses.

Is there really such a thing as Tropical Biology?

AbstractThe ecosystems of The Tropics comprise a majority of the planet's biodiversity, approximately 40% of its terrestrial surface area, and half the human population. Despite this, Tropical Biology has historically been conceptualized as a specialized subdiscipline of the Biological Sciences. I assessed the validity of this assumption and conclude that it depends on the framework and evidence used to evaluate it. I suggest that the way forward as a discipline is not for Tropical Biologists to drop the geographic adjective that unites them, but to recenter The Tropics as the foundation of ecology and evolutionary biology.Abstract in Spanish is available with online material.

The Global Dam Watch database of river barrier and reservoir information for large-scale applications.

There are millions of river barriers worldwide, ranging from wooden locks to concrete dams, many of which form associated impoundments to store water in small ponds or large reservoirs. Besides their benefits, there is growing recognition of important environmental and social trade-offs related to these artificial structures. However, global datasets describing their characteristics and geographical distribution are often biased towards particular regions or specific applications, such as hydropower dams affecting fish migration, and are thus not globally consistent. Here, we present a new river barrier and reservoir database developed by the Global Dam Watch (GDW) consortium that integrates, harmonizes, and augments existing global datasets to support large-scale analyses. Data curation involved extensive quality control processes to create a single, globally consistent data repository of instream barriers and reservoirs that are co-registered to a digital river network. Version 1.0 of the GDW database contains 41,145 barrier locations and 35,295 associated reservoir polygons representing a cumulative storage capacity of 7,420 km3 and an artificial terrestrial surface water area of 304,600 km2.

Selecting Erosion- and Deposition-Dominated Zones in the Jezero Delta Using a Water Flow Model for Targeting Future In Situ Mars Surface Missions

Identifying surface sites with significant astrobiological potential on Mars requires a comprehensive understanding of past geological processes and conditions there, including the shallow subsurface region. Numerical modelling could distinguish between regions dominated by erosion and those characterized by sediment accumulation in ancient wet environments. The target area of Jezero Crater is relatively well explored and thus is an ideal site to evaluate model calculations; however, important works are still missing on expectations related to its shallow subsurface . In this work, the best available approaches were followed, and only surface morphology was considered (supposedly formed by the last fluvial episode). The shallow subsurface became an important target recently, and this model could provide new inputs in this area. Erosion–accumulation models are suitable for terrestrial surface features, but few have been applied to Mars. This work addresses this challenge using the SIMWE (SIMulated Water Erosion) model on the Jezero Crater delta, the landing site of the Perseverance rover. For calculations, the average grain size according to the THEMIS TI data was applied to the target area. The flow depth varied between 1.89 and 34.74 m (average of 12.66 m). The water-filled channel width ranged from 35.3 to 341.42 m. A flow velocity of 0.008–11.6 m/s, a maximum erosion rate of 5.98 g/m2/h, and a deposition 4.07 g/m2/h were estimated. These calculated values are close to the range of estimations from other authors assuming precipitation of 1–20 mm/h and discharges of 60–400 m3/s. The model was able to distinguish between erosion- and accumulation-dominated areas about 1 m above Jezero Crater’s delta that are not visible from above. This model helps to identify the accumulation-dominated areas with the finest grain size with good preservation capability for the shallow but invisible subsurface.

Topographic Roughness as an Emergent Property of Geomorphic Processes and Events

AbstractEarth's terrestrial surfaces commonly exhibit topographic roughness at the scale of meters to tens of meters. In soil‐ and sediment‐mantled settings topographic roughness may be framed as a competition between roughening and smoothing processes. In many cases, roughening processes may be specific eco‐hydro‐geomorphic events like shrub deaths, tree uprooting, river avulsions, or impact craters. The smoothing processes are all geomorphic processes that operate at smaller scales and tend to drive a diffusive evolution of the surface. In this article, we present a generalized theory that explains topographic roughness as an emergent property of geomorphic systems (semi‐arid plains, forests, alluvial fans, heavily bombarded surfaces) that are periodically shocked by an addition of roughness which subsequently decays due to the action of all small scale, creep‐like processes. We demonstrate theory for the examples listed above, but also illustrate that there is a continuum of topographic forms that the roughening process may take on so that the theory is broadly applicable. Furthermore, we demonstrate how our theory applies to any geomorphic feature that can be described as a pit or mound, pit‐mound couplet, or mound‐pit‐mound complex.

A Mathematical Model of Diel Activity and Long Time Survival in Phototrophic Mixed-Species Subaerial Biofilms

Subaerial biofilms (SAB) are intricate microbial communities living on terrestrial surfaces, of interest in a variety of contexts including cultural heritage preservation, microbial ecology, biogeochemical cycling, and biotechnology. Here we propose a mathematical model aimed at better understanding the interplay between cyanobacteria and heterotrophic bacteria, common microbial SAB constituents, and their mutual dependence on local environmental conditions. SABs are modeled as thin mixed biofilm-liquid water layers sitting on stone. A system of ordinary differential equations regulates the dynamics of key SAB components: cyanobacteria, heterotrophs, polysaccharides and decayed biomass, as well as cellular levels of organic carbon, nitrogen and energy. These components are interconnected through a network of energetically dominant metabolic pathways, modeled with limitation terms reflecting the impact of biotic and abiotic factors. Daily cylces of temperature, humidity, and light intensity are considered as input model variables that regulate microbial activity by influencing water availability and metabolic kinetics. Relevant physico-chemical processes, including pH regulation, further contribute to a description of the SAB ecology. Numerical simulations explore the dynamics of SABs in a real-world context, revealing distinct daily activity periods shaped by water activity and light availability, as well as longer time scale survivability conditions. Results also suggest that heterotrophs could play a substantial role in decomposing non-volatile carbon compounds and regulating pH, thus influencing the overall composition and stability of the biofilm.

Global expansion of human-wildlife overlap in the 21st century.

Understanding the extent to which people and wildlife overlap in space and time is critical for the conservation of biodiversity and ecological services. Yet, how global change will reshape the future of human-wildlife overlap has not been assessed. We show that the potential spatial overlap of global human populations and 22,374 terrestrial vertebrate species will increase across ~56.6% and decrease across only ~11.8% of the Earth's terrestrial surface by 2070. Increases are driven primarily by intensification of human population densities, not change in wildlife distributions caused by climate change. The strong spatial heterogeneity of future human-wildlife overlap found in our study makes it clear that local context is imperative to consider, and more targeted area-based land-use planning should be integrated into systematic conservation planning.

Rise in water vapour driven by moisture transport facilitates water availability for the greening of global deserts

There are substantial changes in the global drylands owing to climate change and anthropogenic activities. However, this aspect is not adequately explored in the context of recent climate change and global warming. Therefore, we analyse the role of water vapour in driving precipitation and corresponding surface greenness in the global deserts using satellite measurements. Statistical techniques such as partial correlation and Randon Forest (RF) are employed to understand the relationship among the physical processes that drive water availability for desert greening. Our analysis shows that water vapour is relatively lower (<25 kg/m2) in the deserts than rest of the globe, but comparable to the polar and high-altitude regions. Among the deserts, Thar (25 kg/m2) and Sahara (15–20 kg/m2) show higher water vapour, in contrast to the American and Gobi deserts (<10 kg/m2). Trajectory analysis reveals that water vapour transport from the south Atlantic Ocean is very high (90 kg/m/s) to the Sahel region of Sahara. Similarly, water vapour comes from Arabian Sea and Indian Ocean to Thar, mainly during Indian Summer Monsoon (ISM). There is an increase in water vapour driven by a rise in moisture transport to the American, Arabian, Thar and Sub-Sahara deserts during the period 2003–2020. The rise in moisture transport and associated water vapour in the deserts enhance water availability through precipitation and soil moisture, influencing surface greenness, as illustrated by the partial correlation and RF analyses. Enhanced water vapour and water availability, together with anthropogenic activities such as agriculture and afforestation in the deserts drive greening, which is more pronounced in Thar and Sub-Sahara. This study, thus, reveals the role of atmospheric moisture in regulating the terrestrial water availability and surface greenness in the extreme arid regions on the earth.

Limb Loss and Specialized Leg Dynamics in Tiny Water-Walking Insects.

The air-water interface of the planet's water bodies, such as ponds, lakes, and streams, presents an uncertain ecological niche with predatory threats from above and below. As Microvelia americana move across the water surface in small ponds, they face potential injury from attacks by birds, fish, and underwater invertebrates. Thus, our study investigates the effects of losing individual or pairs of tarsi on M. americana's ability to walk on water. Removal of both hind tarsi causes M. americana to rock their bodies (yaw) while running across the water surface at $\pm 19^{\circ }$, compared to $\pm 7^{\circ }$ in nonablated specimens. This increase in yaw, resulting from the removal of hind tarsi, indicates that M. americana use their hind legs as "rudders" to regulate yaw, originating from the contralateral middle legs' strokes on the water's surface through an alternating tripod gait. Ablation of the ipsilateral middle and hind tarsi disrupts directionality, making M. americana turn in the direction of their intact limbs. This loss of directionality does not occur with the removal of contralateral middle and hind tarsi. However, M. americana lose their ability to use the alternating tripod gait to walk on water on the day of contralateral ablation. Remarkably, by the next day, M. americana adapt and regain the ability to walk on water using the alternating tripod gait. Our findings elucidate the specialized leg dynamics within the alternating tripod gait of M. americana, and their adaptability to tarsal loss. This research could guide the development and design strategies of small, adaptive, and resilient micro-robots that can adapt to controller malfunction or actuator damage for walking on water and terrestrial surfaces.

Effect of Al Substitution on Visible Short-Wave Infrared Reflectance Spectroscopy (VSWIR) of Goethite and Ferrihydrite

Goethite and ferrihydrite are the two major iron hydroxides, essential mineral constituents in the terrestrial surface system. Aluminum (Al) is the most common substituent in iron hydroxides, and it may significantly change the bulk and surficial physicochemical properties of iron hydroxides. Consequently, a practical and convenient approach is needed to efficiently identify the Al substitution degrees of iron hydroxides in natural occurrences. This study presents a comprehensive investigation of the VSWIR characteristics of laboratory-synthesized Al-substituted goethite and ferrihydrite, to establish diagnostic VSWIR parameters for the identification and quantification of Al substitution levels in iron hydroxides. The findings revealed that Al substitution can affect the band positions (P) of goethite and ferrihydrite at ~650 nm, ~900 nm, and ~1400 nm. The relationships between the Al substitution of ferrihydrite and VSWIR parameters can be expressed as P900 = −0.43 × Al(%) + 931 and P1400 = −0.07 × Al(%) + 1428, while that of goethite can be expressed as P650 = 0.42 × Al(%) + 657 and P900 = 2.29 × Al(%) + 936. The peak fitting results showed that the absorption intensity at 480–550 nm linearly decreases with increased Al substitution. The obtained VSWIR spectra of Al-substituted goethite and ferrihydrite provide a critical supplement to the spectral library for (Al) iron hydroxides, and these VSWIR parameters can be utilized for the semi-quantitative determination of Al substitution in natural iron hydroxides