ABSTRACT
Closer collaboration among ecologists, systematists, and evolutionary biologists working in tropical forests, centred on studies within long-term permanent plots, would be highly beneficial for their respective fields. With a key unifying theme of the importance of vouchered collection and precise identification of species, especially rare ones, we identify four priority areas where improving links between these communities could achieve significant progress in biodiversity and conservation science: (i) increasing the pace of species discovery; (ii) documenting species turnover across space and time; (iii) improving models of ecosystem change; and (iv) understanding the evolutionary assembly of communities and biomes.
Subject(s)
Biodiversity , Forests , Tropical Climate , Ecosystem , TreesABSTRACT
Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.
Subject(s)
Biomass , Forests , Models, Theoretical , Trees/growth & development , Tropical Climate , South AmericaABSTRACT
La composición florística de 17 parcelas (0,5 - 2 ha) de Jenaro Herrera, Loreto, Perú fue analizada utilizando el método multivariado de agrupamiento por promedio aritmético de grupos de pares no ponderados (UPGMA). Nueve grupos florísticos fueron reportados y correspondieron a los siguientes tipos de bosque descritos anteriormente en la zona: 1) bosque ribereño, un grupo; 2) bosque latifoliado de aguas negras, dos grupos; 3) bosque de arena blanca, dos grupos(más un grupo con parcela que incluye parte de otro tipo de bosque); 4) bosque de terraza, un grupo; 5) bosque de palmeras de aguas negras, un grupo; y 6) bosque de palmeras de terraza baja, un grupo. Problemas taxonómicos en el nivel de especies fueron minimizados con la remoción de las especies raras.
The floristic composition of 17 plots (0,5 - 2 ha) of Jenaro Herrera, Loreto, Peru were analyzed using the unweighted pair group method with arithmetic mean (UPGMA). Nine floristic groups were reported corresponding to the following types of forests described in the study area before: 1) riverine forest -one group, 2) black water broad leaf forest -two groups, 3) white sand forest -two groups (plus one group with a plot including part of another type of forest), 4) terrace forest -one group, 5) black water palm forest -one group, and 6) low terrace palm forest -one group. Taxonomic problems were detected in species level; however, these were minimized when rare species were removed.
