Significance: Identifying and explaining regional differences in tropical forest dynamics, structure, diversity, and composition are critical for anticipating region-specific responses to global environmental change. Floristic classifications are of fundamental importance for these efforts. Here we provide a global tropical forest classification that is explicitly based on community evolutionary similarity, resulting in identification of five major tropical forest regions and their relationships: ( i ) Indo-Pacific, ( ii ) Subtropical, ( iii ) African, ( iv ) American, and ( v ) Dry forests. African and American forests are grouped, reflecting their former western Gondwanan connection, while Indo-Pacific forests range from eastern Africa and Madagascar to Australia and the Pacific. The connection between northern-hemisphere Asian and American forests is confirmed, while Dry forests are identified as a single tropical biome.

The Sundarbans, the largest mangrove ecosystem in the world, is under threat from historical and future human exploitation and sea level rise. Limited scientific knowledge on the spatial ecology of the mangroves in this world heritage ecosystem has been a major impediment to conservation efforts. Here, for the first time, we report on habitat suitability analyses and spatial density maps for the four most prominent mangrove species -Heritiera fomes, Excoecaria agallocha, Ceriops decandraandXylocarpus mekongensis. Globally endangeredH. fomesabundances declined as salinity increased. Responses to nutrients, elevation and stem density varied between species.H. fomesandX. mekongensispreferred upstream habitats.E. agallochaandC. decandrapreferred down-stream and mid-stream habitats. Historical harvesting had negative influences onH. fomes, C. decandraandX. mekongensisabundances. The established protected area network does not support the most suitable habitats of these threatened species. We therefore recommend a reconfiguration of the network to include these suitable habitats and ensure their immediate protection. These novel habitat insights and spatial predictions can form the basis for future forest studies and spatial conservation planning and have implications for more effective conservation of the Sundarbans mangroves and the many other species that rely on them.

Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change.Location: Tropical and subtropical moist forests.Time period: Current.Major taxa studied: Palms (Arecaceae).Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure.Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work.Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

Knowledge gaps in spatiotemporal changes in mangrove diversity and composition have obstructed mangrove conservation programs across the tropics, but particularly in the Sundarbans (10,017 km2), the world's largest remaining natural mangrove ecosystem. Using mangrove tree data collected from Earth's largest permanent sample plot network at four historical time points (1986, 1994, 1999 and 2014), this study establishes spatially explicit baseline biodiversity information for the Sundarbans. We determined the spatial and temporal differences in alpha, beta, and gamma diversity in three ecological zones (hypo-, meso-, and hypersaline) and also uncovered changes in the mangroves' overall geographic range and abundances therein. Spatially, the hyposaline mangrove communities were the most diverse and heterogeneous in species composition while the hypersaline communities were the least diverse and most homogeneous at all historical time points. Since 1986, we detect an increasing trend of compositional homogeneity (between-site similarity in species composition) and a significant spatial contraction of distinct and diverse areas over the entire ecosystem. Temporally, the western and southern hypersaline communities have undergone radical shifts in species composition due to population increase and range expansion of the native invasive species Ceriops decandra and local extinction or range contraction of specialists including the globally endangered Heritiera fomes. The surviving biodiversity hotspots are distributed outside the legislated protected area network. In addition to suggesting the immediate coverage of these hotspots under protected area management, our novel biodiversity insights and spatial maps can form the basis for spatial conservation planning, biodiversity monitoring and protection initiatives for the Sundarbans.

Aim: Mangrove forests are among the most threatened and rapidly vanishing, but poorly understood ecosystems. We aim to uncover the variables driving mangrove biodiversity and produce baseline biodiversity maps for the Sundarbans world heritage site—the Earth's largest contiguous mangrove ecosystem.Location: The Bangladesh Sundarbans, South Asia.Methods: We collected species abundance, environmental and disturbance data from 110 permanent sample plots (PSPs) covering the entire Bangladesh Sundarbans (6,017 km²). We applied generalized additive models to determine the key variables shaping the spatial distributions of mangrove diversity and community composition. Biodiversity maps were constructed using covariate‐driven habitat models, and their predictive performances were compared with covariate‐free (i.e., direct interpolation) approaches to see whether the inclusion of habitat variables bolster spatial predictions of biodiversity or whether we can rely on direct interpolation approaches when environmental data are not available.Results: Historical forest exploitation, disease, siltation and soil alkalinity were the key stressors causing loss of alpha and gamma diversity in mangrove communities. Both alpha and gamma diversity increased along the downstream‐to‐upstream and riverbank‐to‐forest interior gradients. Mangrove communities subjected to intensive past tree harvesting, disease outbreaks and siltation were more homogeneous in species composition (beta diversity). In contrast, heterogeneity in species composition increased along decreasing salinity and downstream‐to‐upstream gradients. We find that the surviving biodiversity hotspots (comprising many globally endangered tree species) are located outside the established protected area network and hence open to human exploitation. We therefore suggest bringing them immediately under protected area management.Main conclusions: We provide the first habitat‐based modelling and mapping of alpha, beta and gamma diversity in threatened mangrove communities. In general, habitat‐based models showed better predictive ability than the covariate‐free approach. Nevertheless, the small margin of differences between the approaches demonstrates the utility of direct interpolation approaches when environmental data are unavailable.

Forecasting productivity and stress across an ecosystem is complicated by the multiple interactions between competing species, the unknown levels of intra‐ and interspecific trait plasticity, and the dependencies between those traits within individuals. Integrating these features into a trait‐based quantitative framework requires a conceptual and quantitative synthesis of how multiple species and their functional traits interact and respond to changing environments, a challenge known in community ecology as the “fourth‐corner problem.” We propose such a novel synthesis, implemented as an integrated Bayesian hierarchical model. This allows us to (1) simultaneously model trait–trait and trait–environment relationships by explicitly accounting for both intra‐ and interspecific trait variabilities in a single analysis using all available data types, (2) quantify the strength of the trait–environment relationships, (3) identify trade‐offs between multiple traits in multiple species, and (4) faithfully propagate our modeling uncertainties when making species‐specific and community‐wide trait predictions, reducing false confidence in our spatial prediction results. We apply this integrated approach to the world’s largest mangrove forest, the Sundarbans, a sentinel ecosystem impacted simultaneously by both climate change and multiple types of human exploitation. The Sundarbans presents extensive variability in environmental variables, such as salinity and siltation, driven by changing seawater levels from the south and freshwater damming from the north. We find that tree species growing under stress have a typical functional response to the environmental drivers with inter‐specific variability around this average, and the amount of variability is further contingent upon the nature and magnitude of the environmental drivers. Our model captures the retreat in traits related to resource acquisition and a plastic enhancement of traits related to resource conservation, both clear indications of stress. We predict that, if historical increases in salinity and siltation are maintained, one‐third of whole‐ecosystem productivity will be lost by 2050. Our integrated modeling approach bridges community and ecosystem ecology through simultaneously modeling trait–environment correlations and trait–trait trade‐offs at organismal, community, and ecosystem levels; provides a generalizable foundation for powerful modeling of trait‐environment linkages under changing environments to predict their consequences on ecosystem functioning and services; and is readily applicable across the Earth’s ecosystems.