Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees?

For more than three decades, major efforts in sampling and analyzing tree diversity in South America have focused almost exclusively on trees with stems of at least 10 and 2.5 cm diameter, showing highest species diversity in the wetter western and northern Amazon forests. By contrast, little attention has been paid to patterns and drivers of diversity in the largest canopy and emergent trees, which is surprising given these have dominant ecological functions. Here, we use a machine learning approach to quantify the importance of environmental factors and apply it to generate spatial predictions of the species diversity of all trees (dbh ≥ 10 cm) and for very large trees (dbh ≥ 70 cm) using data from 243 forest plots (108,450 trees and 2832 species) distributed across different forest types and biogeographic regions of the Brazilian Amazon. The diversity of large trees and of all trees was significantly associated with three environmental factors, but in contrasting ways across regions and forest types. Environmental variables associated with disturbances, for example, the lightning flash rate and wind speed, as well as the fraction of photosynthetically active radiation, tend to govern the diversity of large trees. Upland rainforests in the Guiana Shield and Roraima regions had a high diversity of large trees. By contrast, variables associated with resources tend to govern tree diversity in general. Places such as the province of Imeri and the northern portion of the province of Madeira stand out for their high diversity of species in general. Climatic and topographic stability and functional adaptation mechanisms promote ideal conditions for species diversity. Finally, we mapped general patterns of tree species diversity in the Brazilian Amazon, which differ substantially depending on size class.

MASTREE+: Time-series of plant reproductive effort from six continents.

Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics.

Aún existen importantes vacíos en la comprensión de la respuesta reproductiva de las plantas al cambio medioambiental, en parte, porque su monitoreo en especies de plantas longevas requiere una observación directa durante muchos años, y estos conjuntos de datos rara vez han estado disponibles. Aquí presentamos a MASTREE +, una base de datos que recopila series de tiempo de la reproducción de las plantas de todo el planeta, poniendo a disposición estos datos de libre acceso para la comunidad científica. MASTREE + incluye 73.828 puntos de observación de la reproducción anual georreferenciados (ej. conteos de semillas y frutos) en poblaciones de plantas perennes en todo el mundo. Estas observaciones consisten en 5971 series temporales a nivel de población provenientes de 974 especies en 66 países. La mediana de la duración de las series de tiempo es de 10 años (media = 12.4 años) y el conjunto de datos incluye 1.122 series de al menos dos décadas (≥20 años de observaciones). Para un subconjunto de especies bien estudiadas, MASTREE +incluye un amplio conjunto de series temporales replicadas en gradientes geográficos y climáticos. Describimos el conjunto de datos de acceso abierto disponible como un archivo.csv y presentamos una aplicación web asociada para la exploración de datos. MASTREE+ proporcionará la base para mejorar la comprensión sobre la respuesta reproductiva de plantas longevas al cambio medioambiental. Además, MASTREE+ facilitará los avances en la investigación de la ecología y la evolución de las estrategias reproductivas en plantas perennes y el papel de la reproducción vegetal como determinante de la dinámica de ecosistemas.