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The Caatinga is an exclusively Brazilian biome, and is the largest and most biodiverse Seasonal Tropical Dry Forest in the world. Despite that, the mammalian fauna, especially small mammals, is the least studied of all Brazilian biomes. In order to fill gaps and provide detailed information on small mammals (Didelphimorphia, Rodentia) in the Caatinga biome, we compiled reliable records focusing on richness, composition and some biometric data. These records came from mammal collections, papers, theses, books, and unpublished data, prioritizing records with vouchers housed in scientific collections. We compiled a total of 3133 records from 816 locations, resulting in a richness of 47 native species (12 marsupials and 35 rodents, plus three exotic rodents, Rattus rattus, Rattus norvegicus, and Mus musculus). This dataset includes records of three new species for the biome and its transition zone: the rodents Calomys mattevii, Holochilus oxe, and Nectomys squamipes. Of the total number of records, 1808 (57.71%) are from consulting activities, 95 (3.03%) are from zoonoses studies and 104 (3.32%) are from the National Plague Service (SNP). All nine Brazilian states with territory in the Caatinga have sampling data for small mammals, but the number of records and localities are unevenly distributed, with the state of Rio Grande do Norte having the lowest number of records and locations sampled. Our dataset is the first of its kind for the Caatinga biome and has considerable potential value for studies of habitat use, landscape ecology, macroecology, biogeography, and conservation. There are no copyright restrictions on the data. Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. [ABSTRACT FROM AUTHOR]

Inland waters are among the most threatened biodiversity hotspots. Ponds located in alpine areas are experiencing more rapid and dramatic water temperature increases than any other biome. Despite their prevalence, alpine ponds and their biodiversity responses to climate change have been poorly explored, reflecting their small size and difficult access. To understand the effects of climate change on alpine pond biodiversity, we performed a comprehensive literature review for papers published since 1955. Through analysis of their geographic distribution, environmental features, and biodiversity values, we identified which environmental factors related to climate change would have direct or indirect effects on alpine pond biodiversity. We then synthesized this information to produce a conceptual model of the effects of climate change on alpine pond biodiversity. Increased water temperature, reduced hydroperiod, and loss of connectivity between alpine ponds were the main drivers of biodiversity geographic distribution, leading to predictable changes in spatial patterns of biodiversity. We identified three major research gaps that, if addressed, can guide conservation and restoration strategies for alpine ponds biodiversity in an uncertain future. [ABSTRACT FROM AUTHOR]

For most of the 20th century, the hypothesis was accepted that Madagascar's extensive grass‐dominated ecosystems were of anthropogenic origin, carved out of pristine forests after a mere two millennia of human settlement. We tested an alternative hypothesis that these C4 grassy ecosystems were part of the general Late Miocene expansion of tropical grassy biomes, using diverse data from published sources (Bond et al. 2008). Joseph and Seymour (2021) criticised this paper, which they see as seminal to subsequent studies on the grasslands. Here we respond to their critique of our study. We also briefly note diverse studies since 2008 pointing to the ancient origin of Madagascar's C4 grasses and the ecosystems they dominate. We conclude with key research needs that will help promote open‐minded research on these long neglected grassy biomes. The answers would be of considerable scientific and public interest but may also contribute to enlightened management of forest/grassland mosaics. [ABSTRACT FROM AUTHOR]

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi‐arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long‐term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate–ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi‐arid biomes for the assessment of climate–ecosystem interactions that contribute to abrupt shifts. [ABSTRACT FROM AUTHOR]

The resource‐use hypothesis, proposed by E.S. Vrba, states that habitat fragmentation caused by climatic oscillations would affect particularly biome specialists (species inhabiting only one biome), which might show higher speciation and extinction rates than biome generalists. If true, lineages would accumulate biome‐specialist species. This effect would be particularly exacerbated for biomes located at the periphery of the global climatic conditions, namely, biomes that have high/low precipitation and high/low temperature such as rainforest (warm‐humid), desert (warm‐dry), steppe (cold‐dry) and tundra (cold‐humid). Here, we test these hypotheses in swallowtail butterflies, a clade with more than 570 species, covering all the continents but Antarctica, and all climatic conditions. Swallowtail butterflies are among the most studied insects, and they are a model group for evolutionary biology and ecology studies. Continental macroecological rules are normally tested using vertebrates, this means that there are fewer examples exploring terrestrial invertebrate patterns at global scale. Here, we compiled a large Geographic Information System database on swallowtail butterflies' distribution maps and used the most complete time‐calibrated phylogeny to quantify diversification rates (DRs). In this paper, we aim to answer the following questions: (1) Are there more biome‐specialist swallowtail butterflies than biome generalists? (2) Is DR related to biome specialization? (3) If so, do swallowtail butterflies inhabiting extreme biomes show higher DRs? (4) What is the effect of species distribution area? Our results showed that swallowtail family presents a great number of biome specialists which showed substantially higher DRs compared to generalists. We also found that biome specialists are unevenly distributed across biomes. Overall, our results are consistent with the resource‐use hypothesis, species climatic niche and biome fragmentation as key factors promoting isolation. [ABSTRACT FROM AUTHOR]

The trichomycterid catfish Listrura menezesi, new species, is described from a flooded area adjacent to Rio das Panelas, Rio São João basin, Cachoeiras de Macacu municipality, Rio de Janeiro State, Brazil. It represents a most valuable remnant of Atlantic Forest biome that still resists the devastation of Brazilian coastlands. Listrura menezesi can be distinguished from its congeners, except L. boticario and L. depinnai, by the absence of a dorsal fin. It mainly differs from L. boticario and L. depinnai by a continuous midlateral dark stripe along the entire body (vs. discontinuous) and a longitudinal row of irregular dots along the dorsal limit of the abdomen extending for nearly the entire body (vs. only on the posterior half of the body in L. boticario and not forming a distinct row in L. depinnai). Although the new species shares with L. boticario and L. depinnai the absence of dorsal fin, recent phylogenetic analyses show a close relationship between L. menezesi and L. macaensis, the latter having a dorsal fin. A putative apomorphic condition for this clade is presented: the abrupt widening on the mesethmoid axis starting posteriorly on the horizontal through the middle region of the autopalatine (vs. anteriorly, on the horizontal through the anterior region of the autopalatine). Listrura menezesi comes as an addition to the ichthyofauna of the Rio São João drainage, a region extensively sampled for the past 20 years and supposedly well known. This paper also highlights the vulnerability of this species and the possibility of its disappearance in the near future. [ABSTRACT FROM AUTHOR]

This study documents annual carbon stocks and fluxes from 1986 to 2010 at 30‐m resolution across southeastern U.S. forests, analyzing trends and regional greenhouse gas exchange. We used forest inventory data to guide a carbon cycle model representing postdisturbance carbon dynamics for diverse forest and site conditions. We mapped carbon stocks and fluxes with stand age inferred from spaceborne disturbance monitoring and biomass. We assessed the fate of harvested biomass with a wood products model. We found that pine forests experienced the largest biomass removals, with paper products leading all end‐uses. Averaging across all SE forestlands, mean annual net ecosystem productivity decreased from 116 gC · m−2 · year−1 in 1986 to 71 gC · m−2 · year−1 in 2007, and 85 gC · m−2 · year−1 in 2010, equating to a range of 25 to 41 Tg C/year (mean of 34 Tg C/year). Interannual variability in forest‐atmosphere carbon exchange is dominated by the extent of harvesting, with removals ranging from 23 to 56 Tg C/year. Region‐wide live biomass stocks varied little over time, averaging 5.0 kg C/m2 for aboveground biomass or 1,780 TgC, with average annual biomass growth balanced by harvest removals. However, net biome productivity exhibited large interannual variability, spanning a sink of 16 Tg C/year in 1986 to a source of −30 Tg C/year in the year of peak harvest. Two thirds of harvest removals are emitted within 50 years, 8% as methane, causing the forest sector to act as a large CO2‐equivalent source. Uncertainties are estimated at ± 25%. Key Points: We estimate annual carbon stocks and fluxes in southeastern U.S. forests at 30 m with remote sensing, inventory data and a carbon cycle modelNet ecosystem productivity of 34 ± 9 Tg C/year equals harvest removals, leading to no net change in biomassTwo thirds of harvest removals are emitted within 50 years, 8% as methane, causing the forest sector to act as a large CO2‐equivalent source [ABSTRACT FROM AUTHOR]

Temperature imposes a constraint on the rates and outcomes of ecological processes that determine community-and ecosystem-level patterns. The application of metabolic scaling theory has advanced our understanding of the influence of temperature on pattern and process in marine communities. Metabolic scaling theory uses the fundamental and ubiquitous patterns of temperature-dependent metabolism to predict how environmental temperature influences patterns and processes at higher levels of biological organization. Here, we outline some of these predictions to review recent advances and illustrate how scaling theory might be applied to new challenges. For example, warming can alter species interactions and food-web structure and can also reduce total animal biomass supportable by a given amount of primary production by increasing animal metabolism and energetic demand. Additionally, within a species, larval development is faster in warmer water, potentially influencing dispersal and other demographic processes like population connectivity and gene flow. These predictions can be extended further to address major questions in marine ecology, and present an opportunity for conceptual unification of marine ecological research across levels of biological organization. Drawing on work by ecologists and oceanographers over the last century, a metabolic scaling approach represents a promising way forward for applying ecological understanding to basic questions as well as conservation challenges. [ABSTRACT FROM AUTHOR]

Citizen science can facilitate in‐depth learning for pupils and students, contribute to scientific research, and permit civic participation. Here, we describe the development of the transnational school‐based citizen science project Phenology of the North Calotte. Its primary goal is to introduce pupils (age 12–15; grades 7–10) in northern Norway, Russia, and Finland to the local and global challenges of climate change resulting in life cycle changes at different trophic and ecosystem levels in their backyards. Partnerships between regional scientists and staff from NIBIO Svanhovd, State nature reserves, national parks, and teachers and pupils from regional schools aim to engage pupils in project‐based learning. The project uses standardized protocols, translated into the different languages of participating schools. The phenological observations are centered around documenting clearly defined life cycle phases (e.g., first appearance of species, flowering, ripening, leaf yellowing, snow fall, and melt). The observations are collected either on paper and are subsequently submitted manually to an open‐source online database or submitted directly via a newly developed mobile app. In the long term, the database is anticipated to contribute to research studying changes in phenology at different trophic levels. In principle, guided school‐based citizen science projects have the potential to contribute to increased environmental awareness and education and thereby to transformative learning at the societal level while contributing to scientific progress of understudied biomes, like the northern taiga and (sub)arctic tundra. However, differences in school systems and funding insecurity for some schools have been major prohibiting factors for long‐term retention of pupils/schools in the program. Project‐based and multidisciplinary learning, although pedagogically desired, has been partially difficult to implement in participating schools, pointing to the need of structural changes in national school curricula and funding schemes as well as continuous offers for training and networking for teachers. [ABSTRACT FROM AUTHOR]

Aim: Biomes, biogeographical realms and ecoregions have become central concepts of biotic organization and biodiversity research. Recent data‐intensive analysis has shown that, while ecoregions do delineate biotic communities, how distinct they are from one another varies considerably across regions and taxa. Given their central importance to global models of the earth system and to the development of conservation plans, it is key to understand in what regions, and for which taxa, ecoregion classification schemes best describe the underlying variability in biological communities. Location: Global. Taxa: Plants, animals, fungi. Methods: In this paper, we integrate ecoregion maps with data on spatially continuous changes in environmental conditions, biodiversity and species traits to quantify the descriptive power of ecoregions around the globe. Capitalizing on the troves of newly available global biodiversity data, we model the abiotic and biotic factors that describe how distinct ecoregions are from one another. Results: From an abiotic perspective, we report compelling evidence that, first, ecoregions are more distinct in tropical zones with higher temperatures, less temperature seasonality and greater rainfall seasonality. Second, we also find that ecoregions are more distinct in regions with steeper slopes. From a biotic perspective, we find that ecoregions tend to be more distinct for reptiles and amphibians than they are for mammals or birds. Likewise, ecoregions tend to be more distinct for smaller‐bodied species and, to a lesser extent, species at lower trophic levels. Main conclusions: While ecoregion‐based conservation planning can provide a crucial tool for developing holistic conservation interventions, we show here that the ability to capture and describe communities is not uniform across regions or taxa. In particular, ecoregions tend to best describe communities of small‐bodied species, less vagile and tropical taxa that are typically underrepresented in the scientific literature. While ecoregion classification schemes will continue to provide invaluable conservation guidance, we must think critically about when an ecoregional approach is best suited to informing management. [ABSTRACT FROM AUTHOR]

Brazilian Cerrado biome is the largest and richest tropical savanna in the world. In order to understand the effects of climate changes on the hydrology of the Cerrado basins, this paper investigates the hydrological impacts of climate change throughout the 21st century under different emissions scenarios on the streamflow and on the droughts in the Sono, Manuel Alves da Natividade and Palma basins, located in the Brazilian Cerrado. For this purpose, the SWAT hydrological model driven by the downscaling of the HadGEM2‐ES and MIROC5 global climate models associated with RCP4.5 and RCP8.5 scenarios were used in three time slices (2011–2040, 2041–2070 and 2071–2099). The Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSFI) were used to characterize droughts. In general, the results showed that the duration, intensity and frequency of the meteorological and hydrological droughts are expected to increase during the future periods. However, the hydrological droughts are projected to be larger than the meteorological droughts. Reductions in the streamflow are indicated in all future time slices and under both RCPs, especially, during dry periods, which may cause negative impacts in the ecological functions of the Cerrado biome, risk for reduction of the recharge of aquifers and risk for the electric energy production in northern Brazil. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed-scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO3-N dynamics in wetlands. The modified equations produced Nash-Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO3-N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO3-N predictions from the contributing watershed. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series. [ABSTRACT FROM AUTHOR]

Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections. Plain Language Summary: Climate change has caused substantial vegetation growth that was detected by satellite observations ("greening") over northern permafrost regions. However, the consequences or feedbacks of vegetation greening remain largely unknown, hindering the understanding of near‐surface thermal dynamics and bringing considerable uncertainty in model projections. Here we aimed to decipher the biophysical impact of permafrost greening on the summer surface offset (SSO), which is an indicator of permafrost degradation. We found latitude‐ and biome‐dependent patterns of SSO changes and divergent responses of SSO to greening. Increases in satellite‐observed leaf area index lead to higher SSO in relatively cold and wet areas but lower SSO in warm‐dry regions. Biophysical mechanisms associated with surface albedo, evapotranspiration, and SM can help explain various effects of greening on SSO. Our results highlight greening feedbacks on the thermal dynamics of permafrost with climate warming, calling for the improvement of current projections. Key Points: Vegetation greening impacts the thermal dynamics of permafrost surfaceBiophysical effects of greening on surface offset could be related to surface albedo, evapotranspiration, and soil moisture [ABSTRACT FROM AUTHOR]

The ecological and genetic changes that underlie the evolution of host–microbe interactions remain elusive, primarily due to challenges in disentangling the variables that alter microbiome composition. To understand the impact of host habitat, host genetics, and evolutionary history on microbial community structure, we examined gut microbiomes of river‐ and three cave‐adapted morphotypes of the Mexican tetra, Astyanax mexicanus, in their natural environments and under controlled laboratory conditions. Field‐collected samples were dominated by very few taxa and showed considerable interindividual variation. We found that lab‐reared fish exhibited increased microbiome richness and distinct composition compared to their wild counterparts, underscoring the significant influence of habitat. Most notably, however, we found that morphotypes reared on the same diet throughout life developed distinct microbiomes suggesting that genetic loci resulting from cavefish evolution shape microbiome composition. We observed stable differences in Fusobacteriota abundance between morphotypes and demonstrated that this could be used as a trait for quantitative trait loci mapping to uncover the genetic basis of microbial community structure. [ABSTRACT FROM AUTHOR]

The anthropogenic impacts on the environment, including deforestation and the escalating emissions of greenhouse gases, have significantly contributed to global climate change that can lead to alterations in ecosystems. In this context, protected areas (PAs) are pillars for biodiversity conservation by being able, for example, to maintain the viability of populations of endangered species. On the other hand, the species range shifts do not follow the limits of PAs, jeopardizing the conservation of these species. Furthermore, the effectiveness of PAs is consistently undermined by impacts stemming from land use, hunting activities, and illegal exploitation, both within the designated areas and in their adjacent zones. The objectives of this study are to quantify the impacts of climate change on the distribution of threatened and endemic birds of the Amazon biome, evaluate the effectiveness of PAs in protecting the richness of threatened birds, and analyze the representativeness of species within PAs. We found with our results that climate suitability loss is above 80 for 65% of taxa in the optimistic scenario and above 93% in the pessimistic scenario. The results show that PAs are not effective in protecting the richness of Amazonian birds, just as they are ineffective in protecting most of the taxa studied when analyzed individually Although some taxa are presented as "Protected," in future scenarios these taxa may suffer major shrinkages in their distributions and consequently present population unviability. The loss of climatically suitable areas and the effectiveness of PAs can directly influence the loss of ecosystem services, fundamental to maintaining the balance of biodiversity. Therefore, our study paves the way for conservation actions aimed at these taxa so that they can mitigate current and future extinctions due to climate change. [ABSTRACT FROM AUTHOR]

Copyright of Applications in Plant Sciences is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: Geographic structure is a fundamental organising principle in ecological and Earth sciences, and our planet is conceptually divided into distinct geographic clusters (e.g. ecoregions and biomes) demarcating unique diversity patterns. Given recent advances in technology and data availability, however, we ask whether geographically clustering diversity time‐series should be the default framework to identify meaningful patterns of diversity change. Location: North America. Taxon: Aves. Methods: We first propose a framework that recognises patterns of diversity change based on similarities in the behaviour of diversity time‐series, independent of their specific or relative spatial locations. Specifically, we applied an artificial neural network approach, the self‐organising map (SOM), to group time‐series of over 0.9 million observations from the North American Breeding Birds Survey (BBS) data from 1973 to 2016. We then test whether time‐series identified as having similar behaviour are geographically structured. Results: We find little evidence of strong geographic structure in patterns of diversity change for North American breeding birds. The majority of the recognised diversity time‐series patterns tend to be indistinguishable from being independently distributed in space. Main Conclusions: Our results suggest that geographic proximity may not correspond to shared temporal trends in diversity; assuming that geographic clustering is the basis for analysis may bias diversity trend estimation. We suggest that approaches that consider variability independently of geographic structure can serve as a useful addition to existing organising rules of biodiversity time‐series. [ABSTRACT FROM AUTHOR]

Insects are the most biodiverse terrestrial eukaryotic organisms on earth, representing around 75% of the world's recorded fauna. As such, they are central players in most of the major biomes of the world, notably the tropics where they display an enormous species richness and range of specialisations, although they are largely absent from high polar and marine ecosystems. Because of their abundance and diversity, they often come into direct competition with humans, as pests threatening our crops and stored products, attacking our clothes and paper products, including books, and as vectors transmitting diseases, some deadly, to ourselves, livestock, crops, and to wildlife. Meanwhile, many species are highly beneficial as pollinators and as biological control agents used to protect our crops and products. Others still are of conservation importance. For centuries, pest species have been combatted using a variety of approaches, mainly chemical during the 19th into the 21st centuries, but problems have arisen due to the evolution of insecticide resistance. Resistance has even recently evolved against such novel bio-pesticides as Bt ( Bacillus thuringiensis Berliner) toxins. This is perhaps not surprising considering the often short life cycles of many pest insects, their powers of dispersal, and ability to adapt and evolve in the face of novel ecological challenges. Humankind has responded by developing strategies, including the use of natural biological control agents. Mark Jervis was an expert on the deployment of these agents, especially parasitic Hymenoptera, in the control of insect pests, both from a theoretical and applied standpoint. Here, I briefly outline, with special reference to the UK, how cutbacks in research funding threaten the vital entomological research base, while highlighting some of the main ways pest insect populations have been, and are being, studied and controlled. Last, as Mark was a keen, long-term Fellow of the Royal Entomological Society, I also outline the role of the Society in advancing the understanding and dissemination of insect science to a national and international audience. [ABSTRACT FROM AUTHOR]

Aim The continuous increase in anthropogenic nitrogen (N) may have a substantial impact on soil carbon (C) fluxes; thus, understanding the dynamics of soil C fluxes under N enrichment is important. Our main goal was to resolve the conflicting results presented to date and to expand our knowledge about the response of soil respiration (Rs) to N enrichment, which may be affected by the physicochemical properties of soil and environmental factors. Methods We assembled a large dataset for meta-analysis, including 563 datasets on annual and seasonal Rs with N enrichment from 154 published papers at 163 sites, covering seven types of biomes world-wide. Results (1) N enrichment was not significantly related to global Rs but we found a negative relationship in forests and a positive one in other biomes. (2) Rs showed a negative correlation with the N levels in forests and croplands and a positive correlation with the N levels in deserts; heterotrophic respiration exhibited negative correlations with N levels globally, and its response was correlated with the incubation environment. (3) The response of Rs to N enrichment was also correlated with mean annual temperature and soil properties, with 15 °C being the threshold for switching between increasing and decreasing Rs. (4) The estimated total C flux for global terrestrial lands was 97.01 Pg C year-1, and 1 kg of N enrichment at ha-1 year-1 induced an average efflux of 1.33 kg C ha-1 year-1. Main conclusions The response of Rs to future N enrichment should be predicted separately for each biome. The association between changes in Rs and temperature and soil properties under N enrichment makes soil C flux a more complex challenge in the context of future increases in temperature and N deposition. [ABSTRACT FROM AUTHOR]

The memory timescale that characterizes root-zone soil moisture remains the dominant measure in seasonal forecasts of land-climate interactions. This memory is a quasi-deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however, represents a distribution of time periods where soil moisture resides above or below some prescribed threshold and is therefore inherently probabilistic. Using multiple soil moisture data sets collected at high resolution (subhourly) across different biomes and climates, this paper explores the differences, underlying dynamics, and relative importance of memory and persistence timescales in root-zone soil moisture. A first-order Markov process, commonly used to interpret soil moisture fluctuations derived from climate simulations, is also used as a reference model. Persistence durations of soil moisture below the plant water-stress level (chosen as the threshold), and the temporal spectrum of upcrossings and downcrossings of this threshold, are compared to the memory timescale and spectrum of the full time series, respectively. The results indicate that despite the differences between meteorological drivers, the spectrum of threshold-crossings is similar across sites, and follows a unique relation with that of the full soil moisture series. The distribution of persistence times exhibits an approximate stretched exponential type and reflects a likelihood of exceeding the memory at all sites. However, the rainfall counterpart of these distributions shows that persistence of dry atmospheric periods is less likely at sites with long soil moisture memory. The cluster exponent, a measure of the density of threshold-crossings in a time frame, reveals that the clustering tendency in rainfall events (on-off switches) does not translate directly to clustering in soil moisture. This is particularly the case in climates where rainfall and evapotranspiration are out of phase, resulting in less ordered (more independent) persistence in soil moisture than in rainfall. [ABSTRACT FROM AUTHOR]

Aim Our aims were to provide new pollen data for establishing a sub-continental surface pollen database (East Asian Pollen Database, EAPD) and to study relationships between vegetation and climate. Location The sample sites covered most regions of East Asia, including China, Mongolia, the Russian Far East, Vietnam, Cambodia and Thailand. Methods Data quality control procedures were applied, including taxonomic standardization, removal of duplicates, and adjustment of geographical coordinates. Vegetation types and climate parameters were assigned to each sample. Modern pollen distribution maps were drawn using circle scattergrams. The plots of pollen percentages versus climate variables allowed quantitative estimates of climate values. The modern analogue technique (MAT) was used to predict modern biomes and climate parameters. Results Pollen assemblages extracted from 2858 sites were used to model the geographical distribution of selected taxa and their relationships with climate. For most taxa, the reconstructed range fitted the observed geographical distribution rather well. Arboreal pollen (AP) and Pinus dominated the transition zone between forest and steppe. Use of the MAT revealed that the predicted and observed biomes matched in 71% of the cases. The warm temperate evergreen broadleaf forest had the best agreement between predictions and observations. Climate values reconstructed using MAT were highly correlated with observed values in January temperature. The correlation coefficient of the temperature variables ranged from 0.799 to 0.930 and was as high as 0.939 for precipitation. Main conclusions This paper documents a new modern pollen database for East Asia and makes the data readily available. The reconstructed biomes and climate variables are significantly correlated with the observed values, thus demonstrating the utility of the pollen database for future multiscale palaeoenvironmental studies. [ABSTRACT FROM AUTHOR]

Occupancy modeling is an essential tool for understanding species‐habitat associations, thereby helping to plan the conservation of rare and threatened wildlife species. The conservation status and ecology of several avian species, particularly ground‐dwelling birds, are poorly known in Ethiopia. We used camera trap‐based occupancy modeling to investigate habitat covariate influence on occupancy (Ψ) and detection probability (ρ) estimates of Moorland Francolins Scleroptila psilolaema from spatially replicated surveys across both relatively pristine and disturbed landscapes in the Afroalpine biome of Ethiopia. Model‐averaged estimate of ψ̂$$ \hat{\uppsi} $$ across all sites was 0.76 (SD = 0.28) and ρ̂$$ \hat{\uprho} $$ was 0.77 (SD = 0.13) in the pristine landscape. The ψ̂$$ \hat{\uppsi} $$ of the species in the disturbed landscape was 0.56 (SD = 0.19) and ρ̂$$ \hat{\uprho} $$ was 0.48 (SD = 0.06). As hypothesized, based on our model‐averaged beta coefficient estimates (βmean ± SE), predators significantly negatively influenced the occupancy of Moorland Francolins in pristine habitat. We also found a significant positive association of occupancy with herb species richness. Contrary to our prediction, distance to road significantly negatively influence the occupancy of the species, suggesting that occupancy probability was highest in proximity to roadsides and trails in the pristine habitat. There was no significant influence of habitat covariates on the occupancy of the species in the disturbed habitat. The most important covariates that significantly influence the detectability of the species in pristine habitat included sampling occasion and precipitation. The greater occupancy and detectability of this endemic species in the pristine habitat could be linked with the particular conservation status and management of this biodiversity hotspot in the central highlands of Ethiopia. Our results suggest that strict legal enforcement is required to sustainably preserve Moorland Francolins and the ecological integrity of the entire Afroalpine biome. We recommend using camera traps in order to develop realistic and effective conservation and management strategies for rare, sensitive, cryptic, and ground‐dwelling animals in the region. [ABSTRACT FROM AUTHOR]

Background: Skin microorganisms co‐develop with the human body and age influences the skin microenvironment and thus the skin bacterial community. Objectives: To investigate the changes in the skin microbiota during male development. Methods: High‐throughput 16S ribosomal RNA pyrosequencing was utilized to analyze the differences in bacterial composition of the skin in healthy males aged 0–25 years. Results: There were significant differences in facial skin bacterial diversity (Shannon index) and richness (Chao index) among the 4 groups of subjects (p < 0.05). Streptococcus, Staphylococcus, Cutibacterium are dominant in males during growth, and regular changes occur with age after birth. Further analysis of skin bacteria between the 4 groups showed that the bacterial abundance of Cutibacterium acnes and Staphylococcus epidermidis tended to increase with age, and the bacterial abundance of Streptococcus, Rothia mucilaginosa, and Staphylococcus hominis tended to decrease with age. Conclusions: There are some changes in cheek skin bacterial diversity during male development, and there is a relationship between skin bacterial changes and skin development processes. [ABSTRACT FROM AUTHOR]

In a model simulating dynamics of a system, parameters can represent system sensitivities and unresolved processes, therefore affecting model accuracy and uncertainty. Taking a light use efficiency (LUE) model as an example, which is a typical approach for estimating gross primary productivity (GPP), we propose a Simultaneous Parameter Inversion and Extrapolation approach (SPIE) to overcome issues stemming from plant‐functional‐type (PFT)‐dependent parameterizations. SPIE refers to predicting model parameters using an artificial neural network based on collected variables, including PFT, climate types, bioclimatic variables, vegetation features, atmospheric nitrogen and phosphorus deposition, and soil properties. The neural network was optimized to minimize GPP errors and constrain LUE model sensitivity functions. We compared SPIE with 11 typical parameter extrapolating methods, including PFT‐ and climate‐specific parameterizations, global and PFT‐based parameter optimization, site‐similarity, and regression approaches. All methods were assessed using Nash‐Sutcliffe model efficiency (NSE), determination coefficient and normalized root mean squared error, and contrasted with site‐specific calibrations. Ten‐fold cross‐validated results showed that SPIE had the best performance across sites, various temporal scales and assessing metrics. Taking site‐level calibrations as a benchmark (NSE = 0.95), SPIE performed with an NSE of 0.68, while all the other investigated approaches showed negative NSE. The Shapley value, layer‐wise relevance and partial dependence showed that vegetation features, bioclimatic variables, soil properties and some PFTs determine parameters. SPIE overcomes strong limitations observed in many standard parameterization methods. We argue that expanding SPIE to other models overcomes current limits and serves as an entry point to investigate the robustness and generalization of different models. Plain Language Summary: Parameters can represent ecosystem properties and sensitivities of ecosystem processes to environmental changes, affecting model accuracy and output uncertainties. Therefore determining parameters is of great importance for applying models. Current ecosystem‐level models mostly determine parameters according to biomes. For example, light use efficiency (LUE) models, a typical tool to estimate gross primary productivity (GPP), use plant‐functional‐type (PFT)‐specific parameters. However, PFT‐specific parameters cannot represent the spatial variance of GPP sensitivities to environmental conditions within PFT and introduce significant estimation errors. To overcome these issues, we propose a Simultaneous Parameter Inversion and Extrapolation method (SPIE). Taking an LUE model as an example, we estimated model parameters using SPIE based on the input features representing vegetation, climate and soil properties at 196 observational sites. We compared SPIE with 11 other parameter extrapolating methods and all of these methods with site‐specific calibrations based on full‐time‐series observed GPP. The results were validated and showed that SPIE was the best method to extrapolate parameters across various temporal and spatial scales. According to the importance of input features, vegetation features, bioclimatic variables, soil properties and some PFTs are dominating spatial changes of parameters. Overall, SPIE is a robust method that overcomes strong limitations in many standard parameter extrapolating methods. Key Points: We propose a machine‐learning‐based parameterization method to model gross primary productivityThe method overcomes significant biases in extrapolations using assumptions of biome‐dependent and globally fixed parameterizationsVegetation, climate and soil properties explain most variability in model parameters, challenging current prescriptions of their patterns [ABSTRACT FROM AUTHOR]

Nitrogen (N) and phosphorus (P) are essential elements limiting plant–microbial growth in forest ecosystems. However, whether the pattern of plant–microbe nutrient limitation is consistent across forest biomes and the associated potential mechanisms remain largely unclear, limiting us to better understand the biogeochemical processes under future climate change.Here, we investigated patterns of plant–microbial N/P limitation in forests across a wide environmental gradient and biomes in China to explore the divergence of plant–microbial N/P limitation and the driving mechanisms.We revealed that 42.6% of the N/P limitation between plant–microbial communities was disconnected. Patterns in plant–microbial N/P limitations were consistent only for 17.7% of N and 39.7% of P. Geospatially, the inconsistency was more evident at mid‐latitudes, where plants were mainly N limited and microbes were mainly P limited. Furthermore, our findings were consistent with the ecological stoichiometry of plants and microbes themselves and their requirements. Whereas plant N and P limitation was more strongly responsive to meteorological conditions and atmospheric deposition, that of microbes was more strongly responsive to soil chemistry, which exacerbated the plant–microbe N and P limitation divergence.Our work identified an important disconnection between plant and microbial N/P limitation, which should be incorporated into future Earth System Model to better predict forest biomes–climate change feedback. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a scientific mission that collects high spatio‐temporal resolution (∼70 m, 1–5 days average revisit time) thermal images since its launch on 29 June 2018. As a predecessor of future missions, one of the main objectives of ECOSTRESS is to retrieve and understand the spatio‐temporal variations in terrestrial evapotranspiration (ET) and its responses to soil water availability and atmospheric aridity. In the European ECOSTRESS Hub (EEH), by taking advantage of land surface temperature (LST) retrievals, we generated ECOSTRESS ET products over Europe and Africa using three models with different structures and parameterization schemes, namely Surface Energy Balance System (SEBS) and Two Source Energy Balance (TSEB) parametric models, as well as the non‐parametric Surface Temperature Initiated Closure (STIC) model. A comprehensive evaluation of the EEH ET products was conducted with respect to flux measurements from 19 eddy covariance sites in Europe over six different biomes with diverse aridity levels. Results revealed comparable performances of STIC and SEBS (RMSE of ∼70 W m−2). However, the relatively complex TSEB model produced a higher RMSE of ∼90 W m−2. Comparison between STIC ET estimates and the operational ECOSTRESS ET product from NASA PT‐JPL model showed a larger RMSE (around 50 W m−2 higher) for the PT‐JPL ET estimates. Substantial overestimation (>80 W m−2) in PT‐JPL ET estimates was evident over shrublands and savannas, presumably due to weak constraint of LST in the model. Overall, the EEH supports ET retrieval for the future high‐resolution thermal missions. Key Points: Evapotranspiration products over Europe and Africa were generated using three models (Surface Temperature Initiated Closure, Surface Energy Balance System, and Two Source Energy Balance) in the European ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) HubComparison at 19 eddy covariance sites revealed noteworthy model divergence with increasing aridity and vegetation sparsenessA substantial overestimation of the official NASA ECOSTRESS PT‐JPL evapotranspiration product was found under high water limitations [ABSTRACT FROM AUTHOR]

Madagascar is home to many endemic plant and animal species owing to its ancient isolation from other landmasses. This unique fauna includes several lineages of termites, a group of insects known for their key role in organic matter decomposition in many terrestrial ecosystems. How and when termites colonised Madagascar remains unknown. In this study, we used 601 mitochondrial genomes, 93 of which were generated from Malagasy samples, to infer the global historical biogeography of Neoisoptera, a lineage containing more than 80% of described termite species. Our results indicate that Neoisoptera colonised Madagascar between 7 and 10 times independently during the Miocene, between 8.4 and 16.6 Ma (95% HPD: 6.1-19.9 Ma). This timing matches that of the colonization of Australia by Neoisoptera. Furthermore, the taxonomic composition of the Neoisopteran fauna of Madagascar and Australia are strikingly similar, with Madagascar harbouring an additional two lineages absent from Australia. Therefore, akin to Australia, Neoisoptera colonised Madagascar during the global expansion of grasslands, possibly helped by the ecological opportunities arising from the spread of this new biome. [ABSTRACT FROM AUTHOR]

Gross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS‐ and GPP‐related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP‐only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs. Plain Language Summary: Carbon uptake by boreal forests is highly sensitive to environmental changes. There is large uncertainty about how much carbon dioxide (CO2) boreal forests absorb through photosynthesis, as represented by land surface models. Carbonyl sulfide (COS), a trace gas that tracks photosynthesis, can help improve the representation of simulated plant CO2 uptake because COS and CO2 share a common pathway during leaf uptake. Using a mechanistic model of biospheric COS processes implemented in the ORCHIDEE land surface model, we assimilated ecosystem COS flux and plant CO2 uptake measured at Hyytiälä boreal forest. We find that this joint assimilation improves the simulated plant CO2 uptake, as well as transpiration because of the strong link between COS, CO2 and H2O fluxes through stomatal diffusion. Scaling up this assimilation framework to evergreen needleleaf boreal forests, we find that assimilating ecosystem COS flux and plant CO2 uptake data increases the vegetation COS uptake for this biome, but not plant CO2 uptake. Our results imply that COS has the potential to constrain both plant carbon uptake and transpiration in land surface models, which should be further investigated, especially during drought events. Key Points: Jointly assimilating ecosystem carbonyl sulfide (COS) flux and gross primary production data improves both simulated plant carbon uptake and transpirationAssimilating ecosystem COS flux does not increase gross primary production (GPP) over boreal evergreen needleleaf forests, in contrast with previous inversion studiesCOS flux observations help to identify misrepresentation of the sensitivity of GPP to droughts in models [ABSTRACT FROM AUTHOR]

Fire–vegetation feedbacks potentially maintain global savanna and forest distributions. Accordingly, vegetation in savanna and forest ecosystems should have differential responses to fire, but fire response data for herbaceous vegetation have yet to be synthesized across biomes. Here, we examined herbaceous vegetation responses to experimental fire at 30 sites spanning four continents. Across a variety of metrics, herbaceous vegetation increased in abundance where fire was applied, with larger responses to fire in wetter and in cooler and/or less seasonal systems. Compared to forests, savannas were associated with a 4.8 (±0.4) times larger difference in herbaceous vegetation abundance for burned versus unburned plots. In particular, grass cover decreased with fire exclusion in savannas, largely via decreases in C4 grass cover, whereas changes in fire frequency had a relatively weak effect on grass cover in forests. These differential responses underscore the importance of fire for maintaining the vegetation structure of savannas and forests. [ABSTRACT FROM AUTHOR]

The magnitude and spatial pattern of anomalous net biome exchange (NBE) induced by the 2015/16 El Niño over Amazonian rainforests remain uncertain. We here investigated them using multi‐model posterior NBE products in the Orbiting Carbon Observatory‐2 (OCO‐2) version 10 modeling intercomparison project. Results suggest that relative to the annual NBE average in 2017/18, larger anomalous carbon release occurred over the eastern and northern Amazonian rainforests in 2015/16, with a total flux of approximately 0.4 PgC yr−1 after assimilating satellite‐observed column CO2 concentrations (XCO2) over land. We further find that this anomalous spatial pattern was predominantly determined by soil dryness, while the total positive NBE anomaly was dominated by higher temperature with its contribution of approximately 68～70%. We believe that atmospheric inversions assimilating more satellite‐observed XCO2 in future can provide us more comprehensive understanding how Amazonian rainforests cope with the abiotic stresses induced by El Niño events. Plain Language Summary: Interannual variability of carbon flux associated with its drivers over Amazonian rainforests are not fully understood. We here used several groups' newly available posterior CO2 flux estimates to comprehensively investigate the net carbon flux anomaly induced by the 2015/16 extreme El Niño. A total net carbon flux anomaly of approximately 0.4 PgC yr−1 was estimated, which showed larger carbon release over the eastern and northern Amazonian rainforests. We further suggest that although dry conditions greatly shaped the spatial pattern of the anomalous carbon flux, the total carbon flux anomaly was controlled by the higher temperature, with its contribution of approximately 68∼70%. Key Points: Net biome exchange (NBE) anomalies over Amazonian rainforests induced by the 2015/16 El Niño were investigated based on multiple atmospheric inversionsThe spatial pattern of NBE anomaly was regulated by soil water with larger anomalies over the eastern and northern Amazonian rainforestsThe total NBE anomaly was estimated at about 0.4 PgC yr−1 in 2015/16 relative to the average in 2017/18, dominated by higher temperature [ABSTRACT FROM AUTHOR]

Ecosystem stability represents the ability of the ecosystem to maintain and restore its functions. The indicators of ecosystem stability include temporal stability, resistance, and resilience, which are crucial parameters to predict the basic functions of the earth under global change. However, the correlation between the indicators of ecosystem stability and the dimensions of ecosystem stability at global scale remains unclear. Here, we quantified the global dimensions of ecosystem stability using moderate resolution imaging spectrometer (MODIS) enhanced vegetation index (EVI) data from 2001 to 2018 as well as climate variables and land standard species richness data. We revealed a strong positive correlation between temporal stability and resistance and no correlation between resistance and resilience at global scale. The dimension of ecosystem stability changed along the gradients of latitude or altitude. The dimensions of ecosystem stability were different among biomes, showing the lowest in the evergreen broad‐leaved forest (EBF) and the highest in the grassland (GRA). Climate factors were strongly associated with the changes in dimensions of ecosystem stability at global scale. These findings highlight the crucial role of dimensions in exploring ecosystem stability, potentially eliminating contradictions in the ecosystem service mechanism of the earth. [ABSTRACT FROM AUTHOR]

Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)‐based approach against a novel top‐down, machine learning‐based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model–data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT‐based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF‐based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT‐based and EF‐based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel‐by‐pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF‐based approach matches or outperforms the PFT‐based approach at 55% of pixels—a narrow majority. However, NBE estimates from the EF‐based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF‐based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT‐free and trait‐based approaches. [ABSTRACT FROM AUTHOR]

Link to the Virtual Issue [ABSTRACT FROM AUTHOR]

Aim: Palaeoclimate legacies have been reported to influence microbial communities and carbon (C) stocks even after thousands of years. However, the direct and indirect influences of climate legacies on microbial C processes remain poorly understood and thus limit our capacity to predict how climate legacies regulate C cycling. Here, we conducted microbial, soil and vegetation surveys along a continental latitudinal transect of 4200 km covering a wide range of forest biomes. With these data, we evaluated the potential capacity of climate legacies to predict direct and indirect variations in microbial metabolic quotient (MMQ) across and within three main forest biomes: tropical, subtropical and temperate forests. Location: North–south transect (4200 km), China. Time period: 2019. Major taxa studied: Soil microbes. Methods: We used molecular ecology technology to determine microbial biomass and diversity, in addition to a soil incubation experiment to measure MMQ. Results: Palaeoclimate explained a unique portion of the variation in the continental distribution of MMQ, which showed a hump‐shaped pattern with latitude. Locations with increased isothermality (an index of temperature) over the last 20,000 years also showed the highest MMQ in the present day. Moreover, we found multiple indirect effects of climate legacies on MMQ caused either by changes in key soil properties, such as soil organic carbon and ammonium (NH4+), in lower latitudinal regions or by plant traits in higher latitudinal regions. Furthermore, MMQ was positively related to bacterial richness but negatively to fungal richness across forest biomes. Main conclusions: Climate legacies associated with continuous changes in temperature over the last 20,000 years influenced MMQ across forest biomes. Our findings demonstrate that including climate legacies in climate carbon models is essential for better prediction of the microbe‐driven ecosystem processes under global environmental change. [ABSTRACT FROM AUTHOR]

Aim: We evaluated the relative importance of geographical and environment variables for taxonomic, phylogenetic and functional β‐diversity of phyllostomid bats along the entire Amazon biome and specifically in the lowlands. Location: Amazon biome. Taxon: Chiroptera. Methods: We carried out a bibliographic review and compiled a wide and unprecedented database of 106 phyllostomid bat species at 102 sites throughout the Amazon biome. For all possible pairs of sites in both datasets, we estimated the Jaccard pairwise dissimilarity, that is, β‐diversity, considering its three dimensions—taxonomic, phylogenetic and functional—for its two components—turnover (substitution of species) and differences in species richness. The association between dissimilarity measurements and geographical and environment variables was assessed using multiple regressions on distance matrices (MRM). Results: We found that turnover and differences in species richness had similar contributions to the taxonomic β‐diversity. However, for phylogenetic and functional β‐diversity, lineages and functions richness differences contribute slightly more than turnover for total β‐diversity. In the lowlands, species, lineages and functions richness differences were slightly higher than turnover for all diversity dimensions. When accounting for all the sites, elevation was the main predictor of phyllostomid bats' taxonomic, phylogenetic and functional turnover. For lowland sites, ecoregions was the main (but relatively weak) predictor associated with all β‐diversity dimensions. Main conclusions: Analysis of filtering sites according to elevation revealed that species in the Amazonian lowlands are taxonomically and phylogenetically different from species in the Andes, and present taxonomic, phylogenetic and functional redundancy between assemblages. When accounting for the whole range of distribution of bats, results showed the predominant effect of elevation over other geographical and environmental predictors. This indicates that the diversity of good dispersers such as bats is more affected by specialisation along environment and climatic gradients than by geographical barriers throughout the Amazon biome. [ABSTRACT FROM AUTHOR]

This article discusses the growing field of microbiome research and its impact on various aspects of life sciences. The article highlights the role of microbial communities in human health, environmental sustainability, and industrial processes. Specifically, it explores the interplay between the gut microbiota and human health conditions such as Non-alcoholic Fatty Liver Disease (NAFLD) and nutritional imbalances in children. Additionally, it examines the potential of microbial communities in bioremediation strategies for environmental pollution and their application in biotechnology and industrial processes. The article concludes by emphasizing the promise of microbiome research in addressing societal and global sustainability challenges and fostering innovation in various fields. [Extracted from the article]

The latitudinal diversity gradient (LDG) is frequently described as the most dramatic biodiversity pattern on Earth, yet ecologists and biogeographers have failed to reach consensus on its primary cause. A key problem in explaining the LDG involves collinearity between multiple factors that are predicted to affect species richness in the same direction. In terrestrial systems, energy input, geographic area, and evolutionary time for species accumulation tend to covary positively with species richness at the largest spatial scales, such that their individual contributions to the LDG are confounded in global analyses. I review three diversity patterns from marine and freshwater systems that break this collinearity and which may thus provide stronger tests of the influence of time on global richness gradients. Specifically, I contrast biodiversity patterns along oceanic depth gradients, in geologically young versus ancient lakes, and in the north versus south polar marine biomes. I focus primarily on fishes due to greater data availability but synthesize patterns for invertebrates where possible. I find that regional‐to‐global species richness generally declines with depth in the oceans, despite the great age and stability of the deep‐sea biome. Geologically ancient lakes generally do not contain more species than young lakes, and the Antarctic marine biome is not appreciably more species rich than the much younger Arctic marine biome. However, endemism is consistently higher in older systems. Patterns for invertebrate groups are less clear than for fishes and reflect a critical need for primary biodiversity data. In summary, the available data suggest that species richness is either decoupled from or only weakly related to the amount of time for diversification. These results suggest that energy, productivity, or geographic area are the primary drivers of large‐scale diversity gradients. To the extent that marine and terrestrial diversity gradients result from similar processes, these examples provide evidence against a primary role for evolutionary time as the cause of the LDG. [ABSTRACT FROM AUTHOR]

The dominant species of a biome can be regarded as its genuine indicator. Evergreen broadleaved forests (EBLFs) in subtropical East Asia harbor high levels of species biodiversity and endemism and are vital to regional carbon storage and cycling. However, the historical assembly of this unique biome is still controversial. Fagaceae is the most essential family in East Asian subtropical EBLFs and its dominant species are vital for the existence of this biome. Here, we used the dominant Fagaceae species to shed light on the dynamic process of East Asian subtropical EBLFs over time. Our results indicate high precipitation in summer and low temperature in winter are the most influential climatic factors for the distribution of East Asian subtropical EBLFs. Modern East Asian subtropical EBLFs did not begin to appear until 23 Ma, subsequently experienced a long‐lasting development in the Miocene and markedly deteriorated at about 4 Ma, driven jointly by orogenesis and paleoclimate. We also document that there is a lag time between when one clade invaded the region and when its members become dominant species within the region. This study may improve our ability to predict and mitigate the threats to biodiversity of East Asian subtropical EBLFs and points to a new path for future studies involving multidisciplinary methods to explore the assembly of regional biomes. [ABSTRACT FROM AUTHOR]

Motivation: The subdivision of the Earth's terrestrial surface into different biomes, ecozones, bio‐climatic realms or other large ecological land units is an essential reference for global biogeographical and ecological studies. Various classification schemes exist. These differ significantly in terms of the considered criteria for classification and the underlying methodology of class assignments. Evident divergences between global biome concepts are elusive, weakening hereon based analyses and assumptions. Compilation and standardization are essential for obtaining a framework that enables the comparison of different products. To address this need, we created a catalogue of standardized categorial biome maps comprising 31 different global products based on various methodological approaches. These products were processed individually to facilitate their use in large‐scale biogeographical and ecological analyses. Main types of variables contained: We provide a unified RasterStack containing 31 terrestrial biome and land‐cover classifications in different layers. Additional ancillary and processing information is allocated. Spatial location and grain: Global, 10 km × 10 km grain size in equal‐area Mollweide projection. Major taxa and level of measurement: Biomes, ecozones, bio‐climatic zones, and ecological land units. Software format: GeoTiff. [ABSTRACT FROM AUTHOR]

Carbon and nitrogen stable isotope ratios (δ13C and δ15N) have been widely employed in food web analysis. In lotic environments, periphyton is a major primary producer that makes a large contribution to food web production as well as carbon and nitrogen cycling. While the δ13C and δ15N values have many advantages as a natural tracer, the controls over their high spatial and temporal variability in stream periphyton are not well known. Here, we present the global dataset of δ13C and δ15N values of lotic periphyton from 54 published and two unpublished sources, including 978 observations from 148 streams/rivers in 38 regions around the world, from arctic to tropical sites. The 54 published sources were articles recorded during the period of 1994-2016 in 25 academic journals. The two unpublished sources were from the authors’ own data. The dataset showed that δ13C and δ15N values of periphyton ranged from −47.3 to −9.3‰ and from −5.6 to + 22.6‰, respectively. The dataset also includes physicochemical factors (altitude, coordinates, catchment area, width, depth, geology, vegetation, canopy coverage, biome, season, presence of anadromous salmon, temperature, pH, current velocity, and discharge), nutrient data (nitrate and ammonium concentrations), and algal attributes (chlorophyll a concentration, algal species compositions, and carbonates removal) in streams/rivers studied, all of which may help interpret the δ13C and δ15N values of periphyton. The metadata file outlines structure of all the data and with references for data sources, providing a resource for future food web studies in stream and river ecosystems. [ABSTRACT FROM AUTHOR]

Aim: Agriculture is one of the greatest pressures on biodiversity. Regional studies have shown that the presence of natural habitat and landscape heterogeneity are beneficial for biodiversity in agriculture, but it remains unclear whether their importance varies geographically. Here, we use local biodiversity data to determine which local and landscape variables are most associated with biodiversity patterns and whether their association varies between tropical and non‐tropical regions. Location: Global terrestrial area in forest biomes. Major taxa studied: More than 21,000 species of vertebrates, invertebrates, plants and other taxa. Methods: We used generalized linear mixed‐effects models to analyse the relationships between either community total abundance or species richness (derived from the PREDICTS database) and a number of site‐level (predominant land use and land‐use intensity) and landscape‐level variables (distance to forest, the percentage of natural habitat in the surrounding landscape, landscape homogeneity, the number of land‐cover types in the landscape, and total fertilizer application). We compared the associations of these variables with biodiversity in tropical and non‐tropical regions. Results: In most cases, changes in biodiversity associated with landscape‐level variables were greater than those associated with local land use and land‐use intensity. Increased natural habitat availability was associated with the most consistent increases in biodiversity. Landscape homogeneity was also important but showed different directions of biodiversity change between regions. Associations with fertilizer application or the number of land‐cover types were generally weaker, although still of greater magnitude than for the local land‐use measures. Main conclusions: Our results highlight similarities and differences in the association of local‐ and landscape‐scale variables with local biodiversity in tropical and non‐tropical regions. Landscape natural habitat availability had a consistent positive association with biodiversity, highlighting the key role of landscape management in the maintenance of biodiversity in croplands. Landscape‐scale variables were almost always associated with greater changes in biodiversity than the local‐scale measures. [ABSTRACT FROM AUTHOR]

Aim: Climate change is expected to impact mountain biodiversity by shifting species ranges and the biomes they shape. The extent and regional variation in these impacts are still poorly understood, particularly in the highly biodiverse Andes. Regional syntheses of climate change impacts on vegetation are pivotal to identify and guide research priorities. Here we review current data, knowledge and uncertainties in past, present and future climate change impacts on vegetation in the Andes. Location: Andes. Taxon: Plants. Methods: We (i) conducted a literature review on Andean vegetation responses to past and contemporary climatic change, (ii) analysed future climate projections for different elevations and slope orientations at 19 Andean locations using an ensemble of model outputs from the Coupled Model Intercomparison Project 5, and (iii) calculated changes in the suitable climate envelope area of Andean biomes and compared these results to studies that used species distribution models. Results: Future climatic changes (2040–2070) are projected to be stronger at high‐elevation areas in the tropical Andes (up to 4°C under RCP 8.5), while in the temperate Andes temperature increases are projected to be up to 2°C. Under this worst‐case scenario, temperate deciduous forests and the grasslands/steppes from the Central and Southern Andes are predicted to show the greatest losses of suitable climatic space (30% and 17%–23%, respectively). The high vulnerability of these biomes contrasts with the low attention from researchers modelling Andean species distributions. Critical knowledge gaps include a lack of an Andean wide plant checklist, insufficient density of weather stations at high‐elevation areas, a lack of high‐resolution climatologies that accommodates the Andes' complex topography and climatic processes, insufficient data to model demographic and ecological processes, and low use of palaeo data for distribution modelling. Main conclusions: Climate change is likely to profoundly affect the extent and composition of Andean biomes. Temperate Andean biomes in particular are susceptible to substantial area contractions. There are, however, considerable challenges and uncertainties in modelling species and biome responses and a pressing need for a region‐wide approach to address knowledge gaps and improve understanding and monitoring of climate change impacts in these globally important biomes. [ABSTRACT FROM AUTHOR]

Aim: Biomisation has been the most widely used technique to reconstruct past regional vegetation patterns because it does not require an extensive modern pollen dataset. However, it has well‐known limitations including its dependence on expert judgement for the assignment of pollen taxa to plant functional types (PFTs) and PFTs to biomes. Here we present a new method that combines the strengths of biomisation with those of the alternative dissimilarity‐based techniques. Location: The Eastern Mediterranean‐Black Sea Caspian Corridor (EMBSeCBIO). Taxon: Plants Methods: Modern pollen samples, assigned to biomes based on potential natural vegetation data, are used to characterize the within‐biome means and standard deviations of the abundances of each taxon. These values are used to calculate a dissimilarity index between any pollen sample and every biome, and thus assign the sample to the most likely biome. We calculate a threshold value for each modern biome; fossil samples with scores below the threshold for all modern biomes are thus identified as non‐analogue vegetation. We applied the new method to the EMBSeCBIO region to compare its performance with existing reconstructions. Results: The method captured changes in the importance of individual taxa along environmental gradients. The balanced accuracy obtained for the EMBSeCBIO region using the new method was better than obtained using biomisation (77% vs. 65%). When the method was applied to high‐resolution fossil records, 70% of the entities showed more temporally stable biome assignments than obtained using biomisation. The technique also identified likely non‐analogue assemblages in a synthetic modern dataset and in fossil records. Main conclusions: The new method yields more accurate and stable reconstructions of vegetation than biomisation. It requires an extensive modern pollen dataset, but is conceptually simple, and avoids subjective choices about taxon allocations to PFTs and PFTs to biomes. [ABSTRACT FROM AUTHOR]

The boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic ground‐based ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift. [ABSTRACT FROM AUTHOR]

Aim: The aim was to create global maps of foliar nitrogen‐to‐phosphorus (N:P) ratios across ecosystems, based on modelled climate, soil, and N and P deposition data, to identify global drivers of woody vegetation N:P ratios and to explore the role of genetic legacy (phylogenetics) in foliar N:P ratios of woody plants. Location: Woody cover globally. Time period: Present; data collected from 1990 to 2016. Major taxa studied: Woody plants. Methods: We compiled a database of 20,851 foliar N:P records and assigned them into boreal, temperate coniferous, temperate broadleaved and tropical groups. We applied neural networks to predict N:P global distribution maps, generalized linear models to assess environmental drivers and generalized linear mixed models to disentangle the effect of genetic legacy. Results and main conclusions: Foliar N:P ratios are negatively associated with latitude, with higher N:P ratios occurring in tropical forests and lower N:P ratios in boreal forests. Globally, N:P ratios indicate greater levels of P limitation than N limitation. The influence of environmental factors varied among the four forest biomes, probably owing to contrasting combined environmental conditions; this finding would have been obscured had we conducted a single "forest biome" analysis. Genetic legacy explained significant variation in woody plant foliar N:P ratios, and we suggest its inclusion in future studies to improve N:P ratio predictions. [ABSTRACT FROM AUTHOR]

The development of several large‐, "continental"‐scale ecosystem research infrastructures over recent decades has provided a unique opportunity in the history of ecological science. The Global Ecosystem Research Infrastructure (GERI) is an integrated network of analogous, but independent, site‐based ecosystem research infrastructures (ERI) dedicated to better understand the function and change of indicator ecosystems across global biomes. Bringing together these ERIs, harmonizing their respective data and reducing uncertainties enables broader cross‐continental ecological research. It will also enhance the research community capabilities to address current and anticipate future global scale ecological challenges. Moreover, increasing the international capabilities of these ERIs goes beyond their original design intent, and is an unexpected added value of these large national investments. Here, we identify specific global grand challenge areas and research trends to advance the ecological frontiers across continents that can be addressed through the federation of these cross‐continental‐scale ERIs. Plain Language Summary: The development of several large‐, "continental"‐scale ecosystem research infrastructures over recent decades has provided a unique opportunity in the history of ecological science. By bringing together these research infrastructures and harmonizing their respective data will more broadly enable cross‐continental ecological research. It will also improve the capabilities of the research community to anticipate and address future global scale ecological challenges to the planet. Moreover, increasing the international capabilities of these research infrastructures goes beyond their original design intent, and is an unexpected added value of these large national investments. Here, we identify specific global grand challenge areas and research trends to advance the ecological frontiers across continents that can be addressed through the federation of these cross‐continental‐scale ecosystem research infrastructures. Key Points: For the first time in history, we are able to bring together continental‐scale Ecosystem Research Infrastructures globallyThis effort enables macrosystem ecologists to ask research questions from continent‐to‐continent in ways not available beforeThis effort provides baseline data to tackle current and future unknown ecological challenges that society will face [ABSTRACT FROM AUTHOR]

Soil priming is a microbial‐driven process, which determines key soil–climate feedbacks in response to fresh carbon inputs. Despite its importance, the microbial traits behind this process are largely undetermined. Knowledge of the role of these traits is integral to advance our understanding of how soil microbes regulate carbon (C) emissions in forests, which support the largest soil carbon stocks globally. Using metagenomic sequencing and 13C‐glucose, we provide unprecedented evidence that microbial traits explain a unique portion of the variation in soil priming across forest biomes from tropical to cold temperature regions. We show that microbial functional profiles associated with the degradation of labile C, especially rapid simple sugar metabolism, drive soil priming in different forests. Genes involved in the degradation of lignin and aromatic compounds were negatively associated with priming effects in temperate forests, whereas the highest level of soil priming was associated with β‐glucosidase genes in tropical/subtropical forests. Moreover, we reconstructed, for the first time, 42 whole bacterial genomes associated with the soil priming effect and found that these organisms support important gene machinery involved in priming effect. Collectively, our work demonstrates the importance of microbial traits to explain soil priming across forest biomes and suggests that rapid carbon metabolism is responsible for priming effects in forests. This knowledge is important because it advances our understanding on the microbial mechanisms mediating soil–climate feedbacks at a continental scale. [ABSTRACT FROM AUTHOR]

Disease in wild plant populations has received less attention from plant pathologists than diseases of managed plants in agriculture, horticulture, and plantation forestry. Plant ecologists, however, have contributed much to an understanding of how pathogens, other plant–microbe interactions, and arthropods affect population structure and community assemblages of wild plants. Consequentially, this lack of attention has meant that the potential impacts of climate change on disease in wild plant populations are less appreciated than on major food crops, where modelling of such impacts is now well established. However, plant ecologists and soil microbiologists have long studied long‐term climatic effects through a combination of observational studies and manipulative field experiments. Here, strategies are discussed to bring together these different perspectives into an integrated approach to address the future impacts of climate change on plant, environmental, and ecosystem health. The approach taken will be first to note the temporal and spatial scales that can be considered, ranging from microhabitats to whole biomes, review what is known about climate change impacts on natural vegetation, referring briefly to climate change impacts on crop diseases, and then what is known about impacts in wild populations at both the individual species and also the ecosystem level. The more general area of plant–soil–microbe–pathogen interactions is covered as one of the more important areas where climate change may have much impact on plant health through indirect rather than direct effects. The special cases of introduced invasive plants and the connectedness of agricultural systems with the wider landscape are discussed. [ABSTRACT FROM AUTHOR]

The boreal biome plays an important role in the global carbon cycle. However, current estimates of its sink‐source strength and responses to changes in climate are primarily derived from models and thus remain uncertain. A major challenge is the validation of these models at a regional scale since empirical flux estimates are typically confined to ecosystem or continental scales. The Integrated Carbon Observation System (ICOS)‐Svartberget atmospheric station (SVB) provides observations including tall tower eddy covariance (EC) and atmospheric concentration measurements that can contribute to such validation in Northern Sweden. Thus, the overall aim of this study was to quantify the carbon balance in Northern Sweden region by integrating land‐atmosphere fluxes and atmospheric carbon dioxide (CO2) concentrations. There were three specific objectives. First, to compare flux estimates from four models (VPRM, LPJ‐GUESS, ORCHIDEE, and SiBCASA) to tall tower EC measurements at SVB during the years 2016–2018. Second to assess the fluxes' impact on atmospheric CO2 concentrations using a regional transport model. Third, to assess the impact of the drought in 2018. The comparison of estimated concentrations with ICOS observations helped the evaluation of the models' regional scale performance. Both the simulations and observations indicate there were similar reductions in the net CO2 uptake during drought. All the models (except for SiBCASA) and observations indicated the region was a net carbon sink during the 3‐year study period. Our study highlights a need to improve vegetation models through comparisons with empirical data and demonstrate the ICOS network's potential utility for constraining CO2 fluxes in the region. Plain Language Summary: As the largest global carbon sink, the boreal region can play an important role in climate mitigation strategies. Thus, it is important to estimate the region's sink strength properly. However, due to limitations in measurement techniques at the regional scale, the sink strength estimates are often obtained from models, which require robust validation. Therefore, we combined flux and atmospheric concentration data from one of the stations in Northern Europe to validate estimates generated using four vegetation models. We also used a transport model to connect the fluxes to atmospheric concentration dynamics, then compared the modeled CO2 concentration patterns with observations to provide a regional scale validation of the vegetation models. These observed and modeled fluxes and concentrations are also used to investigate the impact of the 2018 drought over Nordic vegetation. We find that the 2018 European drought had only limited impact on the carbon fluxes over Northern Sweden. Both the modeling and measurements show that the study region was a carbon sink during the study period (2016–2018), with some variation in estimates from the four models. Key Points: Northern Sweden region was a carbon sink in the years 2016–2018 according to vegetation model estimates and observationsBoth concentration and flux measurements suggest 2018 drought had limited impact on the Nordic carbon balanceEmpirical measurements can improve vegetation models by integrating them into model simulations at site and regional scaleHowever, annual net ecosystem exchange values generated by the models varied between −275 and −25 gC m−2 year−1 [ABSTRACT FROM AUTHOR]