Altitudinal gradients of tree species diversity and above-ground biomass on a small montane of Atlantic Central Africa

Tropical forests are both important carbon sinks and among the most biodiverse ecosystems on the earth. Patterns in aboveground biomass (AGB) and their relationship with species diversity of tropical forests over short altitudinal gradients are poorly known and the few previous studies on the subject have yielded variable results. Here, focusing on old-growth forests in Atlantic central Africa, we investigated how AGB varies with altitude, and how this variation is related to altitudinal changes in floristic composition and/or forest structure. We also investigate the relationship between AGB and species diversity along the altitudinal gradient. We inventoried all trees with a diameter (dbh) ≥ 10 cm in fifteen 1 ha permanent plots (100 m x 100 m) established along a transect from lowland (200 m) to submontane forests (900 m) in the Ngovayang Massif, southwestern Cameroon. Our data show a negative relationship between AGB and tree species richness, related to the elevation gradient. Forest AGB varied two-fold along this gradient, decreasing from 500-600 Mg ha-1 in lowland plots to less than 300 Mg ha-1 at the highest altitudes, while diversity increased, from 35.4 to 54.6 (Fisher's alpha index). The decreasing trend in AGB was mainly due to large trees (dbh ≥ 70 cm) whose contribution to AGB significantly decreased with altitude while the contribution from smaller trees was constant. Tree height and basal area also decreased significantly with increasing altitude, whereas stem density increased. While maximum potential tree height significantly decreased, wood specific gravity displayed no trend along the gradient. In particular, we showed that AGB variation was mainly determined by shift in species composition because large tree species were filtered out in the highest altitudes. Hence, our work further highlight the need for studying the drivers of large tree species distribution to better understand forest carbon stock variations in tropical forests. At the regional level, the Ngovayang massif was among the richest sites with highest level of biomass. Our results have strong implications in decisions on balancing carbon sequestration strategies with biodiversity conservation ones. Policy consequences are particularly relevant in forest management and land use planning.(Texte intégral

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Production properties of K*(892) vector mesons and their spin alignment as measured in the NOMAD experiment

First measurements of K*(892) mesons production properties and their spin alignment in nu_mu charged current (CC) and neutral current (NC) interactions are presented. The analysis of the full data sample of the NOMAD experiment is performed in different kinematic regions. For K*+ and K*- mesons produced in nu_mu CC interactions and decaying into K0 pi+/- we have found the following yields per event: (2.6 +/- 0.2 (stat.) +/- 0.2 (syst.))% and (1.6 +/- 0.1 (stat.) +/- 0.1 (syst.))% respectively, while for the K*+ and K*- mesons produced in nu NC interactions the corresponding yields per event are: (2.5 +/- 0.3 (stat.) +/- 0.3 (syst.))% and (1.0 +/- 0.3 (stat.) +/- 0.2 (syst.))%. The results obtained for the rho00 parameter, 0.40 +/- 0.06 (stat) +/- 0.03 (syst) and 0.28 +/- 0.07 (stat) +/- 0.03 (syst) for K*+ and K*- produced in nu_mu CC interactions, are compared to theoretical predictions tuned on LEP measurements in e+e- annihilation at the Z0 pole. For K*+ mesons produced in nu NC interactions the measured rho00 parameter is 0.66 +/- 0.10 (stat) +/- 0.05 (syst).Comment: 20 p

A study of strange particle production in νμ\nu_\mu charged current interactions in the NOMAD experiment

NeutrinosA study of strange particle production in $\nu_\mu$ charged current interactions has been performed using the data from the NOMAD experiment. Yields of neutral strange particles (\ko, \lam, \alam) have been measured. Mean multiplicities are reported as a function of the event kinematic variables $E_\nu$, $W^2$ and $Q^2$ as well as of the variables describing particle behaviour within a hadronic jet: $x_F$, $z$ and $p_T^2$. Decays of resonances and heavy hyperons with identified \ko and \lam in the final state have been analyzed. Clear signals corresponding to $\rm {K^\star}^\pm$ $\rm {\Sigma^\star}^\pm$, $\rm \Xi^-$ and $\rm \Sigma^0$ have been observed

Search for a new gauge boson in pi(0) decays

A search was made for a new light gauge boson X which might be produced in pi(0) -->, gamma + X decay from neutral pions generated by 450 GeV protons in the CERN SPS neutrino target. The X's would penetrate the downstream shielding and be observed in the NOMAD detector via the Primakoff effect, in the process of X --> pi(0) conversion in the external Coulomb field of a nucleus. With 1.45 x 10(18) protons on target, 20 candidate events with energy between 8 and 140 GeV were found from the analysis of neutrino data. This number is in agreement with the expectation of 18.1 +/- 2.8 background events from standard neutrino processes. A new 90% C.L. upper limit on the branching ratio Br(pi(0) --> Y + X)< (3.3 to 1.9)X 10(-5) for X masses ranging from 0 to 120 MeV/c(2) is obtained

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+. Though broad scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass (AGB) at spatial grains ranging from 5 to 250m (0.025–6.25 ha), and we evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that the spatial sampling error in AGB is large for standard plot sizes, averaging 46.3% for 0.1 ha subplots and 16.6% for 1 ha subplots. Topographically heterogeneous sites showed positive spatial autocorrelation in AGB at scales of 100m and above; at smaller scales, most study sites showed negative or nonexistent spatial autocorrelation in AGB. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGB leads to a substantial “dilution” bias in calibration parameters, a bias that cannot be removed with current statistical methods. Overall, our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

Large range sizes link fast life histories with high species richness across wet tropical tree floras

Understanding how the traits, of lineages are related to diversification is key for elucidating the origin of variation in species richness. Here, we test whether traits are related to species richness among lineages of trees from all major biogeographical settings of the lowland wet tropics. We explore whether variation in mortality rate, breeding system and maximum diameter are related to species richness, either directly or via associations with range size, among 463 genera that contain wet tropical forest trees. For Amazonian genera, we also explore whether traits are related to species richness via variation in mean species-level range size within genera. Lineages with higher mortality rates - faster life-history strategies - have larger ranges in all biogeographic settings and have higher mean species-level range sizes in Amazonia. These lineages also have smaller maximum diameters and, in the Americas, contain dioecious species. In turn, lineages with greater overall range size have higher species richness. Our results show that fast life-history strategies influence species richness in all biogeographic settings because lineages with these strategies have greater range sizes. These links suggest that dispersal has been a key process in the evolution of the tropical forest flora

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives