Population structure of Araucaria angustifolia under distinct forest protection status:implications for management and conservation

Araucaria angustifolia is the dominant coniferous species in Brazil,a long-lived pioneer species and a supplier of valuable timber and non-timber products,which gives it key-species status.This study examines how A.angustifolia population structure affects the stand structure,and whether these relationships differ between protected and unprotected areas.The study was carried out on two protection status forests(national forest and urban forest)in a region of Atlantic mixed forest in ParanáState,southern Brazil.Skewness coefficient and the Weibull shape parameter described the population structure and its effects on species diversity and biomass stock.Population diameter distribution differed significantly between forests,with unbalanced structure in both,although regeneration was more abundant in the protected area.Skewness positively affected aboveground biomass whereas shape negatively affected it and species diversity.These relationships differed between protected and unprotected stands.The effect of A.angustifolia populations on stand structure was conditioned on protection status.Old-growth populations may have lower diversity and biomass stock even supporting large trees.Consequently,old-growth forests,can lead to wood loss through mortality,senescence,and declining populations,representing the waste of a valuable timber resource.These findings provide useful knowledge for forest management,species conservation,and the carbon market.

Plant growth and metabolism of exotic and native Crotalaria species for mine land rehabilitation in the Amazon

Despite its enormous benefits,mining is respon-sible for intense changes to vegetation and soil properties.Thus,after extraction,it is necessary to rehabilitate the mined areas,creating better conditions for the establishment of plant species which is challenging.This study evaluated mineral and organic fertilization on the growth,and carbon and nitrogen(N)metabolism of two Crotalaria species[Cro-talaria spectabilis(exotic species)and Crotalaria maypu-rensis(native species from Carajás Mineral Province(CMP)]established on a waste pile from an iron mine in CMP.A control(without fertilizer application)and six fertilization mixtures were tested(i=NPK;ii=NPK+micronutrients;iii=NPK+micronutrients+organic compost;iv=PK;v=PK+micronutrients;vi=PK+micronutrients+organic compost).Fertilization contributed to increased growth of both species,and treatments with NPK and micronutrients had the best results(up to 257%cf.controls),while organic fertilization did not show differences.Exotic Crotalaria had a greater number of nodules,higher nodule dry mass,chlorophyll a and b contents and showed free ammonium as the predominant N form,reflecting greater increments in biomass compared to native species.Although having lower growth,the use of this native species in the rehabilitation of mining areas should be considered,mainly because it has good development and meets current government legislation as an opportunity to restore local biodiversity.

Species-specific biomass allometric models and expansion factors for indigenous and planted forests of the Mozambique highlands

Secondary Miombo woodlands and forest plantations occupy increasing areas in Mozambique,the former due to anthropogenic activities.Plantations,mainly species of Eucalyptus and Pinus,are being established on sites previously covered by secondary Miombo woodlands.This affects the evolution,cycle and spatiotemporal patterns of carbon(C)storage and stocks in forest ecosystems.The estimation of C storage,which is indispensable for formulating climate change policies on sequestrating CO_(2),requires tools such as biomass models and biomass conversion and expansion factors(BCEF).In Mozambique,these tools are needed for both indigenous forests and plantations.The objective of this study is to fit species-specific allometric biomass models and BCEF for exotic and indigenous tree species.To incorporate efficient inter-species variability,biomass equations were fitted using nonlinear mixed-effects models.All tree component biomass models had good predictability;however,better predictive accuracy and ability was observed for the 2-predictors biomass model with tree height as a second predictor.The majority of the variability in BCEF was explained by the variation in tree species.Miombo species had larger crown biomass per unit of stem diameter and stored larger amounts of biomass per stem volume.However,due to relatively rapid growth,larger stem diameters,heights,and stand density,the plantations stored more biomass per tree and per unit area.

Live above-and belowground biomass of a Mozambican evergreen forest:a comparison of estimates based on regression equations and biomass expansion factors

Background： Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors （BEFs）. Yet, national and regional biomass estimates are generally calculated based on BEFs, especially when using national forest inventory data. Comparison of regression equations based and BEF-based biomass estimates are scarce. Thus, this study was intended to compare these two commonly used methods for estimating tree and forest biomass with regard to errors and biases. Methods： The data were collected in 2012 and 2014. In 2012, a two-phase sampling design was used to fit tree component biomass regression models and determine tree BEFs. In 2014, additional trees were felled outside sampling plots to estimate the biases associated with regression equation based and BEF-based biomass estimates; those estimates were then compared in terms of the following sources of error： plot selection and variability, biomass model, model parameter estimates, and residual variability around model prediction. Results： The regression equation based below-, aboveground and whole tree biomass stocks were, approximately, 7.7, 8.5 and 8.3 % larger than the BEF-based ones. For the whole tree biomass stock, the percentage of the total error attributed to first phase （random plot selection and variability） was 90 and 88 % for regression- and BEF-based estimates, respectively, being the remaining attributed to biomass models （regression and BEF models, respectively）. The percent bias of regression equation based and BEF-based biomass estimates for the whole tree biomass stock were -2.7 and 5.4 %, respectively. The errors due to model parameter estimates, those due to residual variability around model prediction, and the percentage of the total error attributed to biomass model were larger for BEF models （than for regression models）, except for stem and stem wood components. Conclusions＂ The regression equation based biomass stocks were found to be slightly larger, associated with relatively smaller errors and least biased than the BEF-based ones. For stem and stem wood, the percentages of their total errors （as total variance） attributed to BEF model were considerably smaller than those attributed to biomass regression equations.

Cloning and characterization of gene-resistant analogs(RGAs)involved in rust(Puccinia psidii) resistance in Eucalyptus grandis

Disease-resistant genes play an important role in defending against a variety of pathogens and insect pests in plants. Most of the disease-resistant genes encode pro- teins with conserved leucine rich repeat and nucleotide binding site domains. In this study, we cloned and char- acterized gene-resistant analogs （RGAs） from Eucalyptus grandis using degenerate PCR, with primers specifically targeting these two domains. The amplified fragments were cloned into the pGEM-T vector and transformed into Escherichia coli. Among the 90 clones obtained, 13 were sequenced and compared with each other and with previ- ously identified gene-resistant diseases. A BLASTX search in GenBank revealed high similarities among the con- served domains of these cloned genes with RGA genes. Some clones, however, showed no significant similarity with DNA sequences in GenBank. Southern blotting ana- lysis identified several polymorphic RFLP loci between distinct genotypes. However, none of them co-segregated with the Puccinia psidii Winter resistance gene 1 （Ppr1） in a population study.

Mixed-Species Allometric Equations to Quantify Stem Volume and Tree Biomass in Dry Afromontane Forest of Ethiopia

Volume and biomass equations are essential tools to determine forest productivity and enable forest managers to make informed decisions. However, volume and biomass estimation equations are scarce for Afromontane forests in Africa in general and Ethiopia in particular. This limits our knowledge of the standing volume of wood, biomass, and carbon stock of the forests therein. In this study, we developed a new mixed-species volume and biomass equations for Afromontane forests and compared them with generic pantropical and local models. A total of 193 sampled trees from seven dominant tree species were used to develop the equations. Various volume and biomass equations were fitted using robust linear and nonlinear regression. Model comparison indicated that the best model to estimate stem volume was ln(v)=-9.909+ 0.954*ln(d2h), whereas the best model to estimate biomass was ln(b)=-2.983+ 0.949*ln(ρd2h) . These equations explained over 85% of the variations in the stem volume and biomass measurements. The mean density and basal area of trees in the forest with d ≥ 2 cm was 631.5 stems·ha-1 and 24.4 m2·ha-1. Based on the newly developed equations, the forest has on average 303.0 m3·ha-1 standing volume of wood and 283.8 Mg·ha-1 biomass stock. The newly developed allometric equations derived from this study can be used to accurately determine the stem volume, biomass, and carbon storage in the Afromontane forests in Ethiopia and elsewhere with similar stand characteristics and ecological conditions. By contrast, the generic pan-tropical and other local models appear to provide biased estimates and are not suitable for dry Afromontane forests in Ethiopia. The estimated stem biomass and carbon stock in the Chilimo forest are comparable with the estimates from various tropical forests and woodlands elsewhere in Africa, indicating the importance of dry Afromontane forest for climate change mitigation.

Estimation of Tree Biomass,Carbon Stocks,and Error Propagation in Mecrusse Woodlands

We performed a biomass inventory using two-phase sampling to estimate biomass and carbon stocks for mecrusse woodlands and to quantify errors in the estimates. The first sampling phase involved measurement of auxiliary variables of living Androstachys johnsonii trees;in the second phase, we performed destructive biomass measurements on a randomly selected subset of trees from the first phase. The second-phase data were used to fit regression models to estimate below and aboveground biomass. These models were then applied to the first-phase data to estimate biomass stock. The estimated forest biomass and carbon stocks were 167.05 and 82.73 Mg·ha-1, respectively. The percent error resulting from plot selection and allometric equations for whole tree biomass stock was 4.55% and 1.53%, respectively, yielding a total error of 4.80%. Among individual variables in the first sampling phase, diameter at breast height (DBH) measurement was the largest source of error, and tree-height estimates contributed substantially to the error. Almost none of the error was attributable to plot variability. For the second sampling phase, DBH measurements were the largest source of error, followed by height measurements and stem-wood density estimates. Of the total error (as total variance) of the sampling process, 90% was attributed to plot selection and 10% to the allometric biomass model. The total error of our measurements was very low, which indicated that the two-phase sampling approach and sample size were effective for capturing and predicting biomass of this forest type.

Efects of topographic variability and forest attributes on fne-scale soil fertility in late-secondary succession of Atlantic Forest

Background:Understanding how soil fertility changes due to topographical conditions and forest attributes is an essential premise for local-scale forest management practices.We evaluated the efects of topographic variables and forest attributes on soil fertility along a local topographical gradient in a Brazilian Atlantic Forest.We hypothesised that soil fertility is positively afected by topographic variability and forest attributes(structure and diversity).We used tree species richness,composition,abundance,and aboveground biomass as forest attributes.We analysed two 1-ha for‑est patches with contrasting topographical conditions.We used diferent linear mixed efects models(LMMs)to test the main efects of diferent forest attributes and topography variables on soil fertility.Results:The results showed that higher topographic variability determines soil fertility along a fne-scale gradient.The frst two axes of the PCA explained 66.8%of the variation in soil data,with the frst axis(PCA_(1))explaining 49.6%of the variation in soil data and positively correlating with fertility-related soil properties.The second axis(PCA_(2))explained 17.2%of the variation in topographical data and positively correlated with convexity(the elevation of a plot minus the average elevation of all immediate neighbour plots)and elevation.Our best models showed that topo‑graphic variables(elevation and convexity)are the main predictors that afect fne-scale soil fertility.Conclusions:Our study demonstrates that the topographic variability,mainly elevation and convexity,determines fne-scale soil fertility in an Atlantic Forest.These results advance our understanding that context-dependent condi‑tions based on topography and soil properties have a high variability at a fne scale,which can infuence variations in forest attributes(i.e.,species distribution,diversity and structure of tree communities).In addition,the information generated in this research may be important for planning forest restoration activities(passive and active)based on the high variability of environmental variables at a fne scale.

Contrasting soil fungal communities in Mediterranean pine forests subjected to different wildfire frequencies

Mediterranean forest ecosystems are characterized by various vascular plant groups with their associated mycor-rhizae and free living soil fungi with various ecological functions.Fire plays a major role in Mediterranean ecosystem dynamics and impacts both above-and below-ground community structure and functioning.However,studies on the effects induced by altered disturbance regimes(associated with recent land use and climate extremes)on fire ecology and especially on its below-ground impacts are few.The objectives of this study were to evaluate the effects of different wildfire regimes on soil fungal community structure using two different molecular methods.We investigated the long-term effects of wildfire on soil fungal communities associated with Pinus pinaster forests in central Portugal,by comparing the results of denaturing gradient gel electrophoresis(DGGE)-based profiling with those obtained with 454 pyrosequencing.Four forest stands with differing fire history and fire return interval,and vegetation cover(mature forest,early successional stage of pine regeneration,and forest converted to scrubland)were sampled 6 years after the last fire event.The pyrosequencing-based approach indicated ca.eight-fold higher numbers of taxa than DGGE.However,fungal community fingerprinting data obtained for the different study stands with DGGE were congruent with those obtained with pyrosequencing.Both short(7.6 years)and long(24 years)fire return intervals(indicated by the presence of ericaceous shrubs in the understorey)induced a decrease in the abun-dance ratio between basidiomycetes and ascomycetes and appeared to reduce the frequency of ectomycorrhizal fungal species and saprophytes.Wildfire significantly reduced the frequency of late stage successional taxa(e.g.Atheliaceae and Cantharellales)and known or putative saprophytes belonging to the Clavulinaceae and the Archaeorhizomycetaceae.Conversely,early successional fungal species belonging to the Thelephoraceae were favoured by both fire return inter-vals,while the abundance of Cortinarius and Hebeloma,which include several Cistus-specific species,increased with short wildfire return intervals.This last finding highlights the relationship between postfire vegetation composition and cover(vegetation successional stage),and fungal symbionts.We hypothesise that these changes could,in the long term,exhaust the resilience of Mediterranean pine forest vegetation and associated soil fungal communities by preventing pine regeneration.