Testing the generality of above-ground biomass allometry across plant functional types at the continent scale

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15,054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for prediction above-ground biomass. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multi-stemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalisation (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9 to 356 Mg ha(-1) ). Losses in efficiency of prediction were < 1% if generalised models were used in place of species-specific models. Furthermore, application of generalised multi-species models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). This article is protected by copyright. All rights reserved

Allometric equations for integrating remote sensing imagery into forest monitoring programmes.

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed - specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.T.J. was funded by NERC (grant number: NE/K016377/1). This work has benefited from ANR grants to J.C. (CEBA, ref. ANR-10-LABX-25-01 and TULIP, ref. ANR-10-LABX-0041). The Sustainable Landscapes Brazil project was supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, and USAID, and the US Department of State. Data collection for the UNECE ICP Forests PCC Collaborative Database was cofinanced by national or regional organizations and by the European Commission under regulations (EEC) No 2158/86, Forest Focus (EC) No 2152/200, FutMon (EC) LIFE07 ENV/D/218.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1111/gcb.1338

Christmas tree species trials in Arizona's east-central mountains

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Reducing Reforestation Costs in Lebanon: Adaptive Field Trials

Lebanon’s Ministry of Environment initiated a project in 2009 to determine low-cost reforestation techniques for stone pine (Pinus pinea) and Lebanon cedar (Cedrus libani) for large-scale land rehabilitation activities in the arid Middle East. Irrigation (several techniques vs. no water), planting (8- to 18-month-old seedlings), seeding, and soil preparation methods were evaluated in three sets of adaptive management field trials. The aim was to reduce reforestation costs while still achieving sufficient regeneration. A key result for management was that non-irrigated seed planting of stone pine and possibly of Lebanon cedar showed promise for cost-effective reforestation and could be competitive with seedlings, given correct seed source and planting conditions. Stone pine seeds collected from nearby mother trees and planted without irrigation on sandy soil showed 35% survival for <600 USD/ha; seedlings planted without irrigation cost about 2500 USD/ha and achieved 50–70% survival (costs based on 800 seedlings/ha). Water supplements increased establishment costs over 2 years without concomitant improvements to survival. Future studies should evaluate how soil texture and soil preparation interact with other factors to affect seed germination and survival for each species