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BackgroundThe rapid growth of research in artificial intelligence (AI) and machine learning (ML) continues. However, it is unclear whether this growth reflects an increase in desirable study attributes or merely perpetuates the same issues previously raised in the literature. ObjectiveThis study aims to evaluate temporal trends in AI/ML studies over time and identify variations that are not apparent from aggregated totals at a single point in time. MethodsWe identified AI/ML studies registered on ClinicalTrials.gov with start dates between January 1, 2010, and December 31, 2023. Studies were included if AI/ML-specific terms appeared in the official title, detailed description, brief summary, intervention, primary outcome, or sponsors’ keywords. Studies registered as systematic reviews and meta-analyses were excluded. We reported trends in AI/ML studies over time, along with study characteristics that were fast-growing and those that remained unchanged during 2010-2023. ResultsOf 3106 AI/ML studies, only 7.6% (n=235) were regulated by the US Food and Drug Administration. The most common study characteristics were randomized (56.2%; 670/1193; interventional) and prospective (58.9%; 1126/1913; observational) designs; a focus on diagnosis (28.2%; 335/1190) and treatment (24.4%; 290/1190); hospital/clinic (44.2%; 1373/3106) or academic (28%; 869/3106) sponsorship; and neoplasm (12.9%; 420/3245), nervous system (12.2%; 395/3245), cardiovascular (11.1%; 356/3245) or pathological conditions (10%; 325/3245; multiple counts per study possible). Enrollment data were skewed to the right: maximum 13,977,257; mean 16,962 (SD 288,155); median 255 (IQR 80-1000). The most common size category was 101-1000 (44.8%; 1372/3061; excluding withdrawn or missing), but large studies (n>1000) represented 24.1% (738/3061) of all studies: 29% (551/1898) of observational studies and 16.1% (187/1163) of trials. Study locations were predominantly in high-income countries (75.3%; 2340/3106), followed by upper-middle-income (21.7%; 675/3106), lower-middle-income (2.8%; 88/3106), and low-income countries (0.1%; 3/3106). The fastest-growing characteristics over time were high-income countries (location); Europe, Asia, and North America (location); diagnosis and treatment (primary purpose); hospital/clinic and academia (lead sponsor); randomized and prospective designs; and the 1-100 and 101-1000 size categories. Only 5.6% (47/842) of completed studies had results available on ClinicalTrials.gov, and this pattern persisted. Over time, there was an increase in not only the number of newly initiated studies, but also the number of completed studies without posted results. ConclusionsMuch of the rapid growth in AI/ML studies comes from high-income countries in high-resource settings, albeit with a modest increase in upper-middle-income countries (mostly China). Lower-middle-income or low-income countries remain poorly represented. The increase in randomized or prospective designs, along with 738 large studies (n>1000), mostly ongoing, may indicate that enough studies are shifting from an in silico evaluation stage toward a prospective comparative evaluation stage. However, the ongoing limited availability of basic results on ClinicalTrials.gov contrasts with this field’s rapid advancements and the public registry’s role in reducing publication and outcome reporting biases.

Abstract Loss of natural habitat due to land-use change is one of the major threats to biodiversity worldwide. It not only affects the diversity of local species communities (alpha diversity) but can also lead to large-scale homogenization of community composition (reduced beta diversity) and loss of regional diversity (gamma diversity), but these effects are still rarely investigated. We assessed the impact of land-use change on taxonomic, functional and phylogenetic diversity of amphibians in Rwanda, both on the local (community-level) and regional scale (country-wide). Alpha diversity in local communities was higher in farmland than in natural habitats; however, species turnover among farmland sites was much lower than among natural sites, resulting in highly homogenized communities and reduced taxonomic, functional and phylogenetic gamma diversity in farmland across Rwanda. Amphibians found in farmland were mostly disturbance-tolerant species that are widespread in eastern Africa and beyond. In contrast, most of the regionally endemic frog species that make this region a continent-wide hotspot of amphibian diversity were found only in the natural habitats. Ongoing habitat conversion might result in further homogenization of amphibian communities across sub-Saharan Africa and the loss of regional endemism, unique evolutionary lineages, and multifunctionality.

Vertebrate frugivores play important ecological roles. Here, the authors analyse a global dataset on plants and birds and find that plant-frugivore networks are more dissimilar, yet structurally consistent, across ecoregion and biome boundaries.

Recent studies suggest that differences in species composition across habitat types lead to increased multifunctionality on the regional scale. However, data about species turnover—and especially complementarity in the functional composition—across neighbouring habitat types from natural communities are rare. We studied frog communities in lowland rainforest in Malaysian Borneo and compared the species composition and functional-trait composition of different habitat types (alluvial forest, limestone forest, kerangas). Forest types differed strongly in their species composition and, to a lesser extent, in their functional-trait composition. We also compared functional-trait combinations of frogs directly across the forest types and identified six clusters of functionally similar species: three were found in all forest types, the others were absent from at least one forest type. The complementarity in species and functional-trait composition between the forest resulted in high regional gamma diversity, and most of this regional functional diversity was unique to individual forest types. Moreover, the strict separation in species composition suggests that even functionally similar frog species from different forest types cannot easily replace each other in case of local extinctions. The maintenance of ecological functions fulfilled by frogs on the landscape scale therefore requires the conservation of all forest-specific frog communities.

As atmospheric carbon dioxide concentrations, [CO2Air], continue their uncontrolled rise, the capacity of soils to accumulate or retain carbon is uncertain. Free-air CO2 enrichment (FACE) experiments have been conducted to better understand the plant, soil and ecosystem response to elevated [CO2], frequently employing commercial CO2 that imparts a distinct isotopic signal to the system for tracing carbon. We conducted a FACE experiment in 1998 and 1999, whereby sorghum (C4 photosynthetic pathway) was grown in four replicates of four treatments using a split-strip plot design: (i) ambient CO2/ample water (365 μmol mol−1, “Control–Wet”), (ii) ambient CO2/water stress (“Control–Dry”), (iii) CO2-enriched (560 μmol mol−1, “FACE–Wet”), and (iv) CO2-enriched/water stressed (“FACE–Dry”). The stable-carbon isotope composition of the added CO2 (in FACE treatments) was close to that of free atmosphere background values, so the subsequent similar 13C-enriched carbon signal photosynthetically fixed by C4 sorghum plants could be used to trace the fate of carbon in both FACE and control treatments. Measurement of soil organic carbon content (SOC (%) = gC/gdry soil × 100%) and δ13C at three depths (0–15, 15–30, and 30–60 cm) were made on soils from the beginning and end of the two experimental growing seasons. A progressive ca. 0.5‰–1.0‰ δ13C increase in the upper soil SOC in all treatments over the course of the experiment indicated common entry of new sorghum carbon into the SOC pools. The 0–15 cm SOC in FACE treatments was 13C-enriched relative to the Control by ca. 1‰, and according to isotopic mass balance, the fraction of the new sorghum-derived SOC in the Control–Wet treatment at the end of the second season was 8.4%, 14.2% in FACE–Wet, 6.5% in Control–Dry, and 14.2% in FACE–Dry. The net SOC enhancement resulting from CO2 enrichment was therefore 5.8% (or 2.9% y−1 of experiment) under ample water and 7.7% (3.8% y−1 of experiment) under limited water, which matches the pattern of greater aboveground biomass increase with elevated [CO2Air] under the Dry treatment, but no parallel isotopic shifts were found in deeper soils. However, these increased fractions of new carbon in SOC at the end of the experiment do not necessarily mean an increase in total SOC content, because gravimetric measurements of SOC did not reveal a significant increase under elevated [CO2Air], at least within the limits of SOC-content error bars. Thus, new carbon gains might be offset by pre-experiment carbon losses. The results demonstrate successful isotopic tracing of carbon from plants to soils in this sorghum FACE experiment showing differences between FACE and Control treatments, which suggest more dynamic cycling of SOC under elevated [CO2Air] than in the Control treatment.

In addition to affecting individual species, climate change can modify species interactions. Coupling simulation models with networks between plants and animal pollinators and seed dispersers, Schleuninget al. show that animal persistence under climate change depends more strongly on plant persistence than vice versa.

Germinal centers (GCs) are essential structures of the humoral immune response, which form in the periphery in response to T cell dependent antigens. During the GC reaction, B cells undergo critical differentiation steps, which ultimately lead to the generation of antibodies with altered effector function and higher affinity for the selected antigen. Remarkably, many of the B cell tumors have their origin in the GCs; thus, understanding how the formation of these structures is regulated or deregulated is of high medical importance. This review gives an overview of the transcription factors that have been linked to the generation of GCs, and of their roles in the process.

The Intergovernmental Platform for Biodiversity and Ecosystem Services (IPBES), established in 2012 to counter the biodiversity crisis, requires the best scientific input available to function as a successful science-policy interface that addresses the knowledge needs of governments for safeguarding nature and its services. For the macroecological research community, IPBES presents a great opportunity to contribute knowledge, data and methods, and to help identify and address knowledge gaps and methodological impediments. Here, we outline our perspectives on how macroecology may contribute to IPBES. We focus on three essential topics for the IPBES process, where contributions by macroecologists will be invaluable: biodiversity data, biodiversity modelling, and modelling of ecosystem services. For each topic, we discuss the potential for contributions from the macroecological community, as well as limitations, challenges, and knowledge gaps. Overall, engagement of the macroecological community with IPBES should lead to mutual benefits. Macroecologists may profit as their contributions to IPBES may strengthen and inspire them as a community to design and conduct research that provides society-relevant results. Furthermore, macroecological contributions will help IPBES become a successful instrument of knowledge exchange and uncover the linkages between biodiversity and human well-being.