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China is reported as the leading country in the Earth's greening. However, it is a challenge to capture the gradual recovery in forest cover and distinguish the contribution of trees from herbaceous vegetation using remote sensing data. We developed a new fractional tree cover product (GLOBMAP FTC China) from MODIS time series data to investigate change patterns of China's forests during 2000–2022. This annual product showed high consistency with China's National Forest Inventory. We found a significant increase (∼4 Mha/year) in the annual forest area in China from ∼154.47 Mha in 2000 to ∼236.01 Mha in 2015. This rate then slowed by 50% in 2015–2022 (∼2 Mha/year). The forest recovery primarily started in 2000–2004, and reached saturation in 2015. It was primarily contributed by the tree cover gain (92%) from forest conservation and restoration programs. Our findings can support forest management and carbon neutrality achievement for the country. Plain Language Summary As the largest carbon reservoir in terrestrial ecosystems, forests are an indispensable part of China's carbon sink. Explicitly monitoring when, where, and how the forest recovery happening in China is crucial. In this work, a fractional tree cover product (named GLOBMAP FTC China) is generated, providing the coverage of trees within pixels. Compared to other remote sensing products, this product is proved to have the best consistency with China's National Forest Inventory (NFI). Applying the product for analysis, we found that China's forests have been recovering since 2000, and the increasing rate then slowed by 50% after 2015. Forest area in southwestern China shows the fastest increasing rate during 2000–2022, which is more than 0.2 Mha per year. The changes primarily show a stepwise transition from forests with a low fractional tree cover to forests with a higher fractional tree cover, which mainly thanks to the forest conservation and restoration programs. This study underscores that trees' growth dominates the greening in China's forests, highlighting the importance of the new fractional tree cover product for future accurate forest change studies and implications for forest management. Our findings are crucial for climate change mitigation as proposed by the Paris Agreement. Key Points This work generates a fractional tree cover product GLOBMAP to separate the mixed effect of herbaceous vegetation from woody cover Using GLOBMAP, we can obtain detailed and nuanced forest recovery in China, which is consistent with China's National Forest Inventory During 2000–2022, China's forests primarily presented as a stepwise transition from low tree cover forests to higher ones

Aim As anuran reproduction is generally linked to the availability of water, frogs and toads are particularly sensitive to climate. We tested the effect of climate on anuran reproductive phenology and daily activity by analysing temporal patterns of reproductive behaviour based on citizen‐collected observations. Location Brazil. Methods We obtained vocalizations and photographs of frogs with inflated air sacs, as well as images of amplectant couples, nests, eggs or tadpoles in initial stages of development from iNaturalist. We analysed hourly patterns, seasonality and duration of the reproductive period using circular statistics in different climate types and tested phylogenetic signals. We analysed data for Bufonidae, Hylidae, Leptodactylidae and Phyllomedusidae in detail. We also reviewed relevant literature. Results Among the 8478 (acoustic and photographic) records, 738 (8.7%) had evidence of reproduction with 284 acoustic records and 454 photographs, representing 184 taxa identified at the species level belonging to 16 families. Climate affected the period and duration of the reproductive season, as well as daily patterns of vocalization. These results were considered phylogenetically independent, as the reconstructions of ancestral character states did not suggest strong phylogenetic signals for temporal patterns of vocalization or reproduction. In Brazil, most frogs reproduce between October and January. Patterns were similar to the results of the literature review, however in the literature data, Bufonidae start reproduction 2 months earlier, and many Hylidae species reproduce until February. In general, frogs from warmer and drier climate regions had shorter and aggregated reproductive seasons, while in tropical monsoon climate they had a uniform temporal pattern. Main conclusions At the continental scale, reproductive phenology of anurans and their daily activity is affected by climatic conditions regardless of phylogeny. We found that community science can provide valuable information in Brazil that can be harnessed to monitor effects of climate change on amphibian reproduction.

1. Plant-microbe competition for available nitrogen (N) has been suggested to be an important mechanism controlling N limitation of plants in a variety of ecosystems. However, spatio-temporal patterns of competition between plants and microbes for soil N remain unclear. 2. Short-term ¹⁵N tracer experiments were conducted during a growing season (July, August and September) in an alpine meadow on the Tibetan Plateau to unravel spatio-temporal patterns of plant-microbe competition for NH₄ ⁺ and NO₃ ⁻. 3. Alpine plants were poorer competitors than soil microorganisms for inorganic N in July compared with August and September. Occupation of soil volume by roots and root density (high in August and September) played a greater role in plant-microbe competition than air temperature or precipitation (high in July). 4. In topsoils (0-5 cm, highest root density), alpine plants effectively competed with soil microorganisms for N and showed a preference for ¹⁵NO₃ ⁻, while soil microorganisms that preferentially took up ¹⁵NH₄ ⁺ out-competed plants below 5 cm soil depth (lower root density). Competition between plants and soil microorganisms for inorganic N strongly depended on root density (P < 0.0001, R² = 0.93, exponential decay model). 5. Synthesis. Plant-microbe competition for inorganic N showed a clear spatio-temporal pattern in alpine meadows depending on (i) root density and therefore soil depth, (ii) inorganic N form, and (iii) different periods during the growing season. These findings have important implications for our understanding of above-ground-below-ground interactions and plant-microbial competition for available N.

Genetic differentiations and phylogeographical patterns of small organisms may be shaped by spatial isolation, environmental gradients, and gene flow. However, knowledge about genetic differentiation of rotifers at the intercontinental scale is still limited. Polyarthra dolichoptera and P. vulgaris are cosmopolitan rotifers that are tolerant to environmental changes, offering an excellent model to address the research gap. Here, we investigated the populations in Southeastern China and eastern North America and evaluated the phylogeographical patterns from their geographical range sizes, geographic–genetic distance relationships and their responses to spatial‐environmental factors. Using the mitochondrial cytochrome c oxidase subunit I gene as the DNA marker, we analyzed a total of 170 individuals. Our results showed that some putative cryptic species, also known as entities were widely distributed, but most of them were limited to single areas. The divergence of P. dolichoptera and P. vulgaris indicated that gene flow between continents was limited while that within each continent was stronger. Oceanographic barriers do affect the phylogeographic pattern of rotifers in continental waters and serve to maintain genetic diversity in nature. The genetic distance of P. dolichoptera and P. vulgaris populations showed significant positive correlation with geographic distance. This might be due to the combined effects of habitat heterogeneity, long‐distance colonization, and oceanographic barriers. Furthermore, at the intercontinental scale, spatial distance had a stronger influence than environmental variables on the genetic differentiations of both populations. Wind‐ and animal‐mediated transport and even historical events of continental plate tectonics are potential factors for phylogeography of cosmopolitan rotifers. Oceanographic barriers affect the phylogeographic pattern of rotifers in continental waters and maintaining genetic diversity in nature. The divergence indicates that gene flow between eastern North America and Southeastern China is limited while that within eastern North America or Southeastern China was higher. Spatial variables are key factors in affecting the genetic differentiation of rotifers when compared with environmental variables on the intercontinental scale.

Most of the Earth's surface has now been modified by humans. In many countries, natural and semi‐natural ecosystems mostly occur as islands, isolated by land converted for agriculture and a variety of other land‐uses. In this fragmented state, long‐distance dispersal may be the only option for species to adapt their ranges in response to changing climate. The order of arrival of species may leave a lasting imprint on community assembly. Although mostly studied at and above the species level, such priority effects also apply at the intraspecific level. We suggest that this may be particularly important in subarctic and arctic ecosystems. Mountain birch (Betula pubescens ssp. tortuosa) is characterized by great intraspecific variation. We explored spatio‐temporal patterns of the first two mountain birch generations on a homogeneous, early successional glacial outwash plain in SE Iceland that was the recipient of spatially extensive long‐distance dispersal ca. 30 years ago. We evaluated the decadal progress of the young population by remeasuring in 2018, tree density and growth form, plant size, and reproductive effort on 30 transects (150 m2) established in 2008 at four sites on the plain and two adjacent sites ca. 10 km away. All measured variables showed positive increases, but contrary to our predictions of converging dynamics among sites, they had significantly diverged. Thus, two of the sites (only 500 m apart) could not be distinguished in 2008, but by 2018, one of them had much faster growth rates than the other, a higher growth form index reflecting more upright tree stature, greater reproductive effort, and much greater second‐generation seedling recruitment. We discuss two hypotheses that may explain the diverging dynamics, site‐scale environmental heterogeneity, and legacies of intraspecific priority effects. We explored the spatio‐temporal dynamics of the first two generations of mountain birch (Betula pubescens ssp. tortuosa) on four sites on an outwash plain in SE Iceland. Contrary to predictions of converging dynamics, sites showed significant divergence from 2008 to 2018, and we discuss two hypotheses that may explain this, site‐scale environmental heterogeneity and legacies of intraspecific priority effects. The massive long‐distance (≥10 km) dispersal, spatially extensive colonization (>35 km2 area from ca. 1990–2016), and high, although spatially variable, recruitment of the second generation, all illustrate the mountain birch's ability to rapidly adjust its range in a shifting environment.

Understanding spatio-temporal patterns of grassland evapotranspiration (ET) and water use efficiency (WUE) in arid areas is important for livestock production and ecological conservation. Xinjiang, China, was used as an example in the Biome-BGC model to explore spatio-temporal patterns of grassland ET and WUE from 1979 to 2012 in arid areas. The ET ranked from high to low as follows: among seasons, summer (142.4 mm), spring (49.7 mm), autumn (45.9 mm) and winter (7.7 mm); among regions, the Tianshan Mountains (357.9 mm), northern Xinjiang (221.3 mm) and southern Xinjiang (183.2 mm); among grassland types, mid-mountain meadow (387.7 mm), swamp meadow (358.3 mm), typical grassland (343.9 mm), desert grassland (236.2 mm), alpine meadow (229.7 mm), and saline meadow (154.7 mm). The WUE ranked from high to low as follows: among seasons, summer (0.60 g C kg H 2 O −1 ), autumn (0.48 g C kg H 2 O −1 ) and spring (0.43 g C kg H 2 O −1 ); among regions, northern Xinjiang (0.73 g C kg H 2 O −1 ), the Tianshan Mountains (0.69 g C kg H 2 O −1 ) and southern Xinjiang (0.26 g C kg H 2 O −1 ); among grassland types, mid-mountain meadow (0.86 g C kg H 2 O −1 ), typical grassland (0.84 g C kg H 2 O −1 ), swamp meadow (0.77 g C kg H 2 O −1 ), saline meadow (0.52 g C kg H 2 O −1 ), alpine grassland (0.37 g C kg H 2 O −1 ) and desert grassland (0.34 g C kg H 2 O −1 ). In Xinjiang grasslands, the spatio-temporal ET patterns were more strongly influenced by precipitation than by temperature, whereas most high WUE values occurred when precipitation and temperature were relatively conducive to grass growth.

Exploring land use structure and dynamics is critical for urban planning and management. This study attempts to understand the Wuhan development mode since the beginning of the 21st century by profoundly investigating the spatio-temporal patterns of land use/land cover (LULC) change under urbanization in Wuhan, China, from 2000 to 2019, based on continuous time series mapping using Landsat observations with a support vector machine. The results indicated rapid urbanization, with large LULC changes triggered. The built-up area increased by 982.66 km2 (228%) at the expense of a reduction of 717.14 km2 (12%) for cropland, which threatens food security to some degree. In addition, the natural habitat shrank to some extent, with reductions of 182.52 km2, 23.92 km2 and 64.95 km2 for water, forest and grassland, respectively. Generally, Wuhan experienced a typical urbanization course that first sped up, then slowed down and then accelerated again, with an obvious internal imbalance between the 13 administrative districts. Hanyang, Hongshan and Dongxihu specifically presented more significant land dynamicity, with Hanyang being the active center. Over the past 19 years, Wuhan mainly developed toward the east and south, with the urban gravity center transferred from the northwest to the southeast of Jiang’an district. Lastly, based on the predicted land allocation of Wuhan in 2029 by the patch-generating land use simulation (PLUS) model, the future landscape dynamic pattern was further explored, and the result shows a rise in the northern suburbs, which provides meaningful guidance for urban planners and managers to promote urban sustainability.

In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—served as a proxy for more than two months of mobility within four urban test areas in Northern Italy. In contrast to previous work, our approach relies entirely on visualization and mapping techniques, implemented in several software applications. We purposefully avoid statistical or probabilistic modeling and, nonetheless, reveal characteristic and exceptional mobility patterns. The results show, for example, surprising similarities and symmetries amongst the total mobility and people flows between the test areas. Moreover, the exceptional patterns detected can be associated to real-world events such as soccer matches. We conclude that the visual analytics approach presented can shed new light on large-scale collective urban mobility behavior and thus helps to better understand the “pulse” of dynamic urban systems.

Changes in vegetation activity are driven by multiple natural and anthropogenic factors, which can be reflected by Normalized Difference Vegetation Index (NDVI) derived from satellites. In this paper, NDVI trends from 1982 to 2012 are first estimated by the Theil–Sen median slope method to explore their spatial and temporal patterns. Then, the impact of climate variables and human activity on the observed NDVI trends is analyzed. Our results show that on average, NDVI increased by 0.46 × 10−3 per year from 1982 to 2012 globally with decadal variations. For most regions of the world, a greening (increasing)–browning (decreasing)–greening (G-B-G) trend is observed over the periods 1982–2004, 1995–2004, and 2005–2012, respectively. A positive partial correlation of NDVI and temperature is observed in the first period but it decreases and occasionally becomes negative in the following periods, especially in the Humid Temperate and Dry Domain Regions. This suggests a weakened effect of temperature on vegetation growth. Precipitation, on the other hand, is found to have a positive impact on the NDVI trend. This effect becomes stronger in the third period of 1995–2004, especially in the Dry Domain Region. Anthropogenic effects and human activities, derived here from the Human Footprint Dataset and the associated Human Influence Index (HII), have varied impacts on the magnitude (absolute value) of the NDVI trends across continents. Significant positive effects are found in Asia, Africa, and Europe, suggesting that intensive human activity could accelerate the change in NDVI and vegetation. A more accurate attribution of vegetation change to specific climatic and anthropogenic factors is instrumental to understand vegetation dynamics and requires further research.

Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for numerous real-world applications. Recent deep learning approaches have reached outstanding accuracy in such tasks, but their implementation on conventional embedded solutions is still very computationally and energy expensive. Tactile sensing in robotic applications is a representative example where real-time processing and energy-efficiency are required. Following a brain-inspired computing approach, we propose a new benchmark for spatio-temporal tactile pattern recognition at the edge through braille letters reading. We recorded a new braille letters dataset based on the capacitive tactile sensors/fingertip of the iCub robot, then we investigated the importance of temporal information and the impact of event-based encoding for spike-based/event-based computation. Afterwards, we trained and compared feed-forward and recurrent spiking neural networks (SNNs) offline using back-propagation through time with surrogate gradients, then we deployed them on the Intel Loihi neuromorphic chip for fast and efficient inference. We confronted our approach to standard classifiers, in particular to a Long Short-Term Memory (LSTM) deployed on the embedded Nvidia Jetson GPU in terms of classification accuracy, power/energy consumption and computational delay. Our results show that the LSTM outperforms the recurrent SNN in terms of accuracy by 14%. However, the recurrent SNN on Loihi is 237 times more energy-efficient than the LSTM on Jetson, requiring an average power of only 31mW. This work proposes a new benchmark for tactile sensing and highlights the challenges and opportunities of event-based encoding, neuromorphic hardware and spike-based computing for spatio-temporal pattern recognition at the edge.