The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone—US$166 billion to 490 billion per year according to our estimation—is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities. (Résumé d'auteur

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Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. standlevel basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within a median -2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.Additional co-authors: T. F. Domingues, M. Drescher, P. M. Fearnside, M. B. Franca, N. M. Fyllas, G. Lopez-Gonzalez, A. Hladik, N. Higuchi, M. O. Hunter, Y. Iida, K. A. Salim, A. R. Kassim, M. Keller, J. Kemp, D. A. King, J. C. Lovett, B. S. Marimon, B. H. Marimon-Junior, E. Lenza, A. R. Marshall, D. J. Metcalfe, E. T. A. Mitchard, E. F. Moran, B.W. Nelson, R. Nilus, E. M. Nogueira, M. Palace, S. Patino, K. S.-H. Peh, M. T. Raventos, J. M. Reitsma, G. Saiz, F. Schrodt, B. Sonke, H. E. Taedoumg, S. Tan, H. Woll, and J. Lloy

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Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (<i>H</i>). We estimate the effect of incorporating <i>H</i> on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 <i>H</i> and diameter measurements and harvested trees from 20 sites to answer the following questions: <br><br> 1. What is the best <i>H</i>-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? <br><br> 2. To what extent does including <i>H</i> estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? <br><br> 3. What effect does accounting for <i>H</i> have on plot- and continental-scale forest biomass estimates? <br><br> The mean relative error in biomass estimates of destructively harvested trees when including <i>H</i> (mean 0.06), was half that when excluding <i>H</i> (mean 0.13). Power- and Weibull-<i>H</i> models provided the greatest reduction in uncertainty, with regional Weibull-<i>H</i> models preferred because they reduce uncertainty in smaller-diameter classes (&le;40 cm <i>D</i>) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including <i>H</i> reduces errors from 41.8 Mg ha⁻¹ (range 6.6 to 112.4) to 8.0 Mg ha⁻¹ (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha⁻¹ (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including <i>H</i> estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to <i>H</i>. After accounting for variation in <i>H</i>, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km² and store 285 Pg C (estimate including <i>H</i>), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if <i>H</i> is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height ...

We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha−1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha−1) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha−1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity.

Summary1. Calibrating indices of animal abundance to true densities is critical in wildlife studies especially when direct density estimations are precluded by high costs, lack of required data or model parameters, elusiveness and rarity of target species. For studies deploying camera traps, the use of photographic rate (photographs per sampling time) as an index of abundance potentially applies to the majority of terrestrial mammals where individual recognition, and hence capture-recapture analysis, are unfeasible. The very few studies addressing this method have either been limited by lack of independence between trapping rates and density estimations, or because they combined different species, thus introducing potential bias in camera trap detection rates. This study uses a single model species from several sites to analyse calibration of trapping rates to independently derived estimations of density. The study also makes the first field test of the method by Rowcliffe et al. (2008) for density derivation from camera trapping rates based on modelling animal-camera contacts. 2. We deployed camera traps along line transects at six sites in the Udzungwa Mountains of Tanzania and correlated trapping rates of Harvey's duiker Cephalophus harveyi with densities estimated from counts made along the same transects. 3. We found a strong, linear relationship (R 2 = 0AE90) between trapping rate and density. Sampling precision analysis indicates that camera trapping rates reach satisfactory precision when trapping effort amounts to 250-300 camera days. Density estimates using Rowcliffe et al.'s (2008) gas model conversion are higher than from transect censuses; we discuss the possible reasons and stress the need for more field tests. 4. Synthesis and applications. Subject to rigorous and periodic calibration, and standardization of sampling procedures in time and over different sites, camera trapping rate is shown to be, in this study, a valid index of density in the target species. Comparative data indicate that this may also apply to forest ungulates in general. The method has great potential for standardizing monitoring programmes and reducing the costs of wildlife surveys, especially in remote areas.