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It is a biogeographical trope that after several centuries of explora-tion, our knowledge of the world's biodiversity is still staggeringly incomplete (Meyer et al., 2016), even for well-studied groups such as trees (Keppel et al., 2021). Thus, when a study publishes a new esti-mate of the number of known (and unknown) tree species on Earth, it often gains global media attention. Recently, a new study suggested that there were approximately 73,000 tree species worldwide and as much as 14% of the world's tree flora still remains unknown to science (Gatti et al., 2022). But how accurate are such estimates?

Continental runoff is an important source of solutes and nutrients to coastal coral reefs. Nevertheless, they can also act as local stressors due to high coastal urbanization and the associated release of untreated effluents. Here we aimed to qualitatively evaluate the effects of seasonality over reefs from the Costa dos Corais Marine Protected Area (Brazil) and to identify the influence of rivers and submarine groundwater discharge (SGD) on the reefs' environmental status. Surface waters from the reef lagoon, local rivers and shoreline porewaters were sampled monthly during a year and abiotic parameters were determined. The results showed that the reef lagoon is oligotrophic throughout most of the year, with conditions that generally favor biological activities, such as calcification. Chlorophyll-a, with an average of 0.78 ± 0.43 mg m−3, was significantly correlated with salinity and radon in excess. This indicates the influence of rivers and SGD over the reefs, especially during the rainy season. These are important sources of nutrients, regulating primary production. However, signs of anthropogenic pressure were found in the local rivers. In addition, porewaters had a N:P ratio (27.68 ± 24.45) which could potentially impact surface waters through SGD by increasing the local trophic status. In summary, the studied reefs still present good water quality conditions, although continental runoff is a significant transport vector of anthropogenic solutes to the area

Species distribution models (SDMs) are subject to many sources of uncertainty, lim-iting their application in research and practice. One of their main limitations is the quality of the distributional data used to calibrate them, which directly influences the accuracy of model predictions. We propose a standardized methodology to cre-ate maps, describing the limitations of occurrence data for covering the distribution of a species. We develop a set of tools based on the general framework of Maps of Biogeographical Ignorance to describe the main sources of data-driven uncertainty: taxonomic stability, environmental similarity, geographical proximity and temporal decay of the underlying biodiversity data. The so-derived indicators of data-driven uncertainty account for inventory completeness, taxonomic quality, time since the surveys and geographical (and environmental) distance to localities with information. These indicators form the basis of ignorance maps, which can be used to visualize the reliability of SDM projections in geographical space, to estimate the uncertainty of these predictions and to identify target survey areas. To demonstrate the application of our approach, we use data on fourteen Iberian species of Scarabaeidae dung beetles. Data-driven uncertainty is widespread even for this well-surveyed group; more than 60% of the region has distributional uncertainty values higher than 0.6, and 30% higher than 0.7. Ignorance maps can be jointly evaluated with SDM predictions to generate spatially explicit maps of uncertainty, identifying where predictions are reli-able/unreliable. Neglecting such uncertainty can severely affect SDM effectiveness, as it can introduce biases and inaccuracies into the measured species–environment rela-tionships. These errors could result in incorrect theoretical or practical applications, including ill-advised conservation actions. We therefore advocate for the routine use of ignorance maps or similar techniques as supporting in

[Aims]: The survival and distribution of plant species in the extreme environmental conditions of semi-arid regions is strongly dependent on traits associated with drought resistance. Seed weight may be particularly important, since larger seeds are predicted to promote survival in harsh environments, especially those of low soil moisture. Here, we test this hypothesis using data on the seed weight of 277 woody plant species in the semi-arid Caatinga biome of northeast Brazil., [Methods]: We used Structural Equation Models (SEM) to test for associations between seed weight and biophysical conditions, including temperature, precipitation, climatic seasonality, soil-vegetation interaction and soil compaction., [Results]: Species occurrence data were geographically biased due to large areas of the biome that remain under-collected. The strongest statistical association was between seed weight and soil compaction, with mean temperature of the driest quarter and aridity directly influencing soil compaction (and indirectly influencing seed weight)., [Conclusions]: We conclude that the larger seeds of woody species in the Caatinga are primarily an adaptation to compacted soil, uneven distribution of rainfall and high temperatures, intrinsic conditions of the Caatinga biome.

The ongoing digital revolution in the age of big data is opening new research opportunities. Culturomics and iEcology, two emerging research areas based on the analysis of online data resources, can provide novel scientific insights and inform conservation and management efforts. To date, culturomics and iEcology have been applied primarily in the terrestrial realm. Here, we advocate for expanding such applications to the aquatic realm by providing a brief overview of these new approaches and outlining key areas in which culturomics and iEcology are likely to have the highest impact, including the management of protected areas; fisheries; flagship species identification; detection and distribution of threatened, rare, and alien species; assessment of ecosystem status and anthropogenic impacts; and social impact assessment. When deployed in the right context with awareness of potential biases, culturomics and iEcology are ripe for rapid development as low-cost research approaches based on data available from digital sources, with increasingly diverse applications for aquatic ecosystems