• Energy Research

Biomass production in grasslands, a key component of food provision for domestic herbivores, is known to depend on climate, resource availability, and on the functional characteristics of communities. However, the combined effects of these different factors remain largely unknown. The aim of the present study was to unravel the causes of variations in the standing biomass of plant communities using a long‐term experiment conducted in a Mediterranean rangeland of Southern France. Two management regimes, sheep grazing and grazing associated with mineral fertilization, were applied to different areas of the study site over the past 25 years. Abiotic (temperature, available water, nutrients) and biotic (components of the functional structure communities) factors were considered to explain interannual and spatial variations in standing biomass in these rangelands.Standing biomass was highly predictable, with the best model explaining ∼80% of variations in the amount of biomass produced, but the variation explained by abiotic and biotic factors was dependent on the season and on the management regime. Abiotic factors were found to have comparable effects in both management regimes: The amount of biomass produced in the spring was limited by cold temperatures, while it was limited by water availability and high temperatures in the summer. In the fertilized community, the progressive change in the functional structure of the communities had significant effects on the amount of biomass produced: the dominance of few productive species which were functionally close led to higher peak standing biomass in spring.

Biomass production in grasslands, a key component of food provision for domestic herbivores, is known to depend on climate, resource availability, and on the functional characteristics of communities. However, the combined effects of these different factors remain largely unknown. The aim of the present study was to unravel the causes of variations in the standing biomass of plant communities using a long‐term experiment conducted in a Mediterranean rangeland of Southern France. Two management regimes, sheep grazing and grazing associated with mineral fertilization, were applied to different areas of the study site over the past 25 years. Abiotic (temperature, available water, nutrients) and biotic (components of the functional structure communities) factors were considered to explain interannual and spatial variations in standing biomass in these rangelands.Standing biomass was highly predictable, with the best model explaining ∼80% of variations in the amount of biomass produced, but the variation explained by abiotic and biotic factors was dependent on the season and on the management regime. Abiotic factors were found to have comparable effects in both management regimes: The amount of biomass produced in the spring was limited by cold temperatures, while it was limited by water availability and high temperatures in the summer. In the fertilized community, the progressive change in the functional structure of the communities had significant effects on the amount of biomass produced: the dominance of few productive species which were functionally close led to higher peak standing biomass in spring.

AbstractAimLarge tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot‐level forest structure properties and biomass from only the largest trees.LocationPan‐tropical.Time periodEarly 21st century.Major taxa studiedWoody plants.MethodsUsing a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees.ResultsMeasuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents.Main conclusionsOur approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change.

AbstractAimLarge tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot‐level forest structure properties and biomass from only the largest trees.LocationPan‐tropical.Time periodEarly 21st century.Major taxa studiedWoody plants.MethodsUsing a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees.ResultsMeasuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents.Main conclusionsOur approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change.