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The use of mobile laser scanning to survey forest ecosystems is a promising, scalable technology to describe the 3D structure of forests at a high resolution. We use a structurally complex, mixed-species Mediterranean forest to test the performance of a mobile Handheld Laser Scanning (HLS) system to estimate tree attributes within a forest patch in central Spain. We describe the different stages of the HLS approach: field position, ground data collection, scanning path design, point cloud processing, alignment between detected trees and measured reference trees, and finally, the assessment of main tree structural attributes diameter at breast height (DBH) and tree height considering species and tree size as control factors. We surveyed 418 reference trees to account for omission and commission error rates over a 1 ha plot divided into 16 sections and scanned using two different scanning paths. The HLS-based approach reached a high of 88 and 92% tree detection rate for the best combination of scanning path and point cloud processing modes for the HLS system. The root mean squared errors for DBH estimates varied between species: errors for Pinus pinaster were below 2 cm for Scan 02. Quercus pyrenaica, and Alnus glutinosa showed higher error rates. We observed good agreement between ALS and HLS estimates for tree height, highlighting differences to field measurements. Despite the complexity of the mixed forest area surveyed, our results show that HLS is highly efficient at detecting tree locations, estimating DBH, and supporting tree height measurements as confirmed with airborne laser data used for validation. This study is one of the first HLS-based studies conducted in the Mediterranean mixed forest region, where variability in tree allometries and spacing and the presence of natural regeneration pose challenges for the HLS approach. HLS is a feasible, time-efficient, scalable technology for tree mapping in mixed forests with potential to support forest monitoring programmes such as national forest inventories lacking three-dimensional, remote sensing data to support field measurements. [ABSTRACT FROM AUTHOR]

Adapting forests to climate change is a critical issue for forest management. It requires an understanding of climate effects on forest systems and the ability to forecast how these effects may change over time. We used Spanish Second National Forest Inventory data and the SIMANFOR platform to simulate the evolution of CO2 stock (CO2 Mg · ha−1) and accumulation rates (CO2 Mg · ha−1 · year−1) for the 2000–2100 period in pure and mixed stands managed under different Shared Socioeconomic Pathways (SSPs) in Spain. We hypothesized that (1) the more optimistic climate scenarios (SSP1 > > SSP5) would have higher CO2 stock and accumulation rates; (2) mixed stands would have higher CO2 stock and accumulation rates than pure stands; and (3) the behavior of both variables would vary based on forest composition (conifer–conifer vs. conifer–broadleaf). We focused on Pinus sylvestris L., and its main mixtures with Pinus nigra, Pinus pinaster, Fagus sylvatica and Quercus pyrenaica. The SSP scenarios had correlating CO2 stock values in which SSP1 > SSP2 > SSP3 > SSP5, ranging from the most optimistic (SSP1) to the most pessimistic (SSP5). Though pure stands had higher CO2 stock at the beginning, differences with regard to mixed stands were drastically reduced at the end of the simulation period. We also found an increase in the aboveground CO2 proportion compared to belowground in conifer–broadleaf mixtures, while the opposite trend occurred in conifer–conifer mixtures. Overall CO2 accumulation rates decreased significantly from the beginning to the end of the simulation period, but our results indicated that this decline would be less drastic in mixed stands than in pure ones. At the end of the simulation period, CO2 accumulation rates were higher in mixed stands than in pure stands for all mixtures, fractions (aboveground and belowground) and SSPs. Knowing the evolution of mixed forests in different climate scenarios is relevant for developing useful silvicultural guidelines in the Mediterranean region and optimizing forestry adaptation strategies. Better understanding can also inform the design of management measures for transitioning from pure stands to more resource efficient, resistant and resilient mixed stands, in efforts to reduce forest vulnerability in the face of climate change. This work highlights the importance and benefits of mixed stands in terms of CO2 accumulation, stand productivity and species diversity. [ABSTRACT FROM AUTHOR]

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While the impacts of forest management options on carbon (C) storage are well documented, the way they affect C distribution among ecosystem components remains poorly investigated. Yet, partitioning of total forest C stocks, particularly between aboveground woody biomass and the soil, greatly impacts the stability of C stocks against disturbances in forest ecosystems. This study assessed the impact of species composition and stand density on C storage in aboveground woody biomass (stem + branches), coarse roots, and soil, and their partitioning in pure and mixed forests in Europe. We used 21 triplets (5 beech-oak, 8 pine-beech, 8 pine-oak mixed stands, and their respective monocultures at the same sites) in seven European countries. We computed biomass C stocks from total stand inventories and species-specific allometric equations, and soil organic C data down to 40 cm depth. On average, the broadleaved species stored more C in aboveground woody biomass than soil, while C storage in pine was equally distributed between both components. Stand density had a strong effect on C storage in tree woody biomass but not in the soil. After controlling for stand basal area, the mixed stands had, on average, similar total C stocks (in aboveground woody biomass + coarse roots + soil) to the most performing monocultures. Although species composition and stand density affect total C stocks and its partitioning between aboveground woody biomass and soil, a large part of variability in soil C storage was unrelated to stand characteristics. [ABSTRACT FROM AUTHOR]

The impact of biodiversity loss on the functioning of forest ecosystems has become a central issue in ecology. Most reports of the positive effects of tree mixture on the biodiversity–productivity relationship focus on mixtures that combine tree species with contrasting traits. Nevertheless, little is known about how coniferous mixtures of the same genus affect forest productivity, what mechanisms are involved, and how the understory is affected. Here, we assessed the effect of mixed versus monospecific stands of Pinus sylvestris L. and P. pinaster Ait. on productivity, its impact on the understory, and its relationship with soil water and fertility, based on research with six triplets (6 triplets × 3 forest stands × 1 plot = 18 plots) in North-Central Spain. Each triplet consisted of two plots dominated either by P. sylvestris or P. pinaster and of one mixed plot that contained both species. Productivity, at the stand and neighborhood levels, and the understory richness, and soil water and fertility at the stand level were analyzed. A positive effect of pine mixture on productivity was observed at the smaller spatial scale, and it had no negative effect on the understory richness. The greater space-use efficiency (higher tree density and basal area) of both Pinus species in the admixtures was related to soil water and fertility niche complementarity. The fundamental role of scale in determining the relationship between species richness and ecosystem functioning in forests is highlighted. [ABSTRACT FROM AUTHOR]

Chilimo forest is one of the few remnants of dry afro-montane mixed uneven-aged natural forest located in Central Highlands of Ethiopia. Also it has been during the last century one of the most exploited and disturbed forest in the country. Stand density management diagram (SDMD) is a stand-level model that graphically illustrates the relationships between wood yield, density and mortality throughout all stages of stand development. SDMD is a useful tool for designing, displaying and evaluating alternative density management regimes for both even-aged and uneven-aged forest stands. However, information in this regard and other silvicultural management operations are lacking for most Ethiopian forests in general and Chilimo dry afro-montane forest in particular. The purpose of the study is to develop a SDMD model for the existing mixed natural forest using appropriate species proportion for Juniperus procera and Podocarpus falcatus. Two linear equations were simultaneously fitted to relate quadratic mean diameter with stand density and dominant height and relate it to total stand volume with quadratic mean diameter, stand density and dominant height. Moreover, dominant height and quadratic mean diameter were found to be the best endogenous variables for SDMD for Chilimo forest. The relationship between stand density, dominant height, quadratic mean diameter and stand volume is represented in the SDMD graph. Formulating SDMD using species proportion is better than treating each species independently. This SDMD is the first diagram model developed for mixed forest in Africa, and it can serve sustainable management of Chilimo dry afro-montane forest in particular and other dry afro-montane forests in general. [ABSTRACT FROM AUTHOR]

• This study presented new tree basal area increment models for 29 different mixtures along an aridity gradient in Spain. • Higher productivity in mixed than pure stands was found, suggesting that BAI values may increase with the increment of species diversity. • Competition was the most representative biological interaction in pine-pine forests; neutralism and facilitation in pine-oak and oak-oakones. • Tree productivity may be also significantly limited by aridity, finding higher values of basal area increment in more humid than arid conditions. • Models presented in this study can be used in the design of guidelines for Mediterranean mixed forests under future climate change scenarios. Competition plays a key role controlling tree growth in mixed forests. Contrary to monocultures, quantifying species mixing influence on tree growth suppose a challenge since the presence of two or more species requires to estimate the degree of intra- and inter-specific competition among trees. Moreover, it is well known that aridity can also influence tree growth, especially in the Mediterranean Basin. In the present context of climate change, it is essential to take into account species mixing and aridity uncertainty in the design of sustainable management guidelines for Mediterranean mixed forests. To achieve that, data from Spanish National Forest Inventory was used in this study to fit new mixed-effects basal area increment (BAI) models for 29 two-species compositions in Spain. A wide range of different competition structures (intra-specific, inter-specific, size-symmetric and size-asymmetric) and aridity conditions (in terms of the De Martonne Index) were included and tested into the BAI models. Parameter estimations were obtained for all possible species, mixtures and combinations by Maximum Likelihood (ML). Models with all the coefficients being significant (p < 0.05) were first selected. Among these models, we used Akaike Evidence Ratios for selecting the best one by species for each mixture. The best model for each species and mixture was used to analyze the competition and climatic influence on tree growth. Regarding competition influence, a common trend among mixtures was found with higher productivity in mixed than pure stands, suggesting that BAI values may increase with the increment of species diversity. Based on intra and inter-specific competition indexes, competition seemed to be the most representative biological interaction in conifer-conifer mixtures, since neutralism and facilitation may occur more frequently in conifer-broadleaved and broadleaved-broadleaved mixtures. Our findings also suggested that tree growth may be significantly limited by arid conditions, excepting for Pinus halepensis and Pinus pinea. Our rigorous modelling approach successfully uncovered not only possible mixing effect among various species but also help us to understand the effect of aridity on tree growth. Thus, models presented in this study can be used in the design and implementation of management and adaptation guidelines under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Estimating tree height is essential for modelling and managing both pure and mixed forest stands. Although height–diameter (H–D) relationships have been traditionally fitted for pure stands, attention must be paid when analyzing this relationship behavior in stands composed of more than one species. The present context of global change makes also necessary to analyze how this relationship is influenced by climate conditions. This study tends to cope these gaps, by fitting new H–D models for 13 different Mediterranean species in mixed forest stands under different mixing proportions along an aridity gradient in Spain. Using Spanish National Forest Inventory data, a total of 14 height–diameter equations were initially fitted in order to select the best base models for each pair species-mixture. Then, the best models were expanded including species proportion by area (mi) and the De Martonne Aridity Index (M). A general trend was found for coniferous species, with taller trees for the same diameter size in pure than in mixed stands, being this trend inverse for broadleaved species. Regarding aridity influence on H–D relationships, humid conditions seem to beneficiate tree height for almost all the analyzed species and species mixtures. These results may have a relevant importance for Mediterranean coppice stands, suggesting that introducing conifers in broadleaves forests could enhance height for coppice species. However, this practice only should be carried out in places with a low probability of drought. Models presented in our study can be used to predict height both in different pure and mixed forests at different spatio-temporal scales to take better sustainable management decisions under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Mixed forests make up the majority of natural forests, and they are conducive to improving the resilience and resistance of forest ecosystems. Moreover, it is in the crown of the trees where the effect of inter- and intra-specific interaction between them is evident. However, our knowledge of changes in crown morphology caused by density, competition, and mixture of specific species is still limited. Here, we provide insight on stand structural complexity based on the study of four response crown variables (Maximum Crown Width Height, MCWH; Crown Base Height, CBH; Crown Volume, CV; and Crown Projection Area, CPA) derived from multiple terrestrial laser scans. Data were obtained from six permanent plots in Northern Spain comprising of two widespread species across Europe; Scots pine (Pinus sylvestris L.) and sessile oak (Quercus petraea (Matt.) Liebl.). A total of 193 pines and 256 oaks were extracted from the point cloud. Correlation test were conducted (ρ ≥ 0.9) and finally eleven independent variables for each target tree were calculated and categorized into size, density, competition and mixture, which was included as a continuous variable. Linear and non-linear multiple regressions were used to fit models to the four crown variables and the best models were selected according to the lowest AIC Index and biological sense. Our results provide evidence for species plasticity to diverse neighborhoods and show complementarity between pines and oaks in mixtures, where pines have higher MCWH and CBH than oaks but lower CV and CPA, contrary to oaks. The species complementarity in crown variables confirm that mixtures can be used to increase above ground structural diversity. [ABSTRACT FROM AUTHOR]

Tree biomass and the diversity relationship in mixed forest have an impact on forest ecosystem services provisions. Tree biomass yield is driven by several aspects such as species identity, site condition, stand density, tree age and tree diversity expressed as species mingling and structural diversity. By comparing diverse degrees of tree mixtures in natural forests, we can gain insight into the ecosystem services provision level and dynamic. Two monitoring sites in the Castilian Northern Plateau (Spain) have been analyzed to disentangle the relationships between biodiversity levels and tree biomass yield. Two permanent one hectare (ha) squared plots were established at Llano de San Marugán and Valdepoza. In each plot, all individual trees were measured (diameter and height), georeferenced and its species identity defined. Tree species in the two sites were Pinus sylvestris, Pinus nigra, Pinus pinea, Quercus pyrenaica, Quercus ilex, Quercus faginea and Juniperus thurifera. From these datasets, ten diversity indices that fall in three categories (species richness indices, species compositional/mingling indices and vertical structural indices) were used as predictor variables to fit several candidate models. By merging the trees by site (without considering the species identity) selected models include individual tree basal area as an explanatory variable combining by addition or interaction with diversity indices. When species are analyzed independently, structural diversity impacts on biomass yield in combination (additive or multiplicative) with tree size is negative for Pinus nigra and positive for the other species. [ABSTRACT FROM AUTHOR]

• We investigated SOC storage in two-species forests and their corresponding monocultures in Europe. • Tree species identity was the main driver of SOC storage, compared with species mixing. • Tree species identity influenced SOC storage predominantly in the topsoil layers. • Species mixing effect on deep SOC storage was limited to pine-beech triplets. Mixed forests are usually associated with higher aboveground carbon storage compared to the corresponding monocultures but information on the impact of tree species mixing on soil organic carbon (SOC) is still limited. Yet, maximizing SOC storage is crucial for ecosystem C sequestration and many other ecosystem services. This study used a triplet approach (ie. two-species mixed stand and respective pure stands at the same site) to assess the impact of tree species identity and mixing on SOC storage in eight pine-oak, eight pine-beech and five beech-oak triplets in Europe. We sampled the forest floor (FF) and 0–40 cm in the mineral soil per 10 cm interval. For each triplet type, we fitted basal area (BA) proportion of one component species (for species identity) and a BA-based plot-level True Shannon Diversity index (for species mixing) as explanatory variables for SOC stocks in linear mixed effects models, which included stone content and plot BA as covariates, and site as a random intercept. Considering the total soil depth (FF + 0–40 cm), species identity effect on SOC stocks was only significant for pine-beech and pine-oak triplets but explained more variability in SOC stocks than species mixing across triplet types. Species mixing effect was not significant for any triplet type in the total soil depth. While species identity consistently drove SOC storage in the topsoil layers across triplet types, species mixing explained more variability in SOC stocks in the deeper soil layers except for pine-oak triplets. The results showed that species identity is a stronger driver of SOC storage than species mixing. While tree species identity effect was strongly related to a conifers vs broadleaves signature, the drivers behind mixing effects remained elusive. The results suggest that targeted selection of tree species could better enhance SOC storage in European forests than a mere increase in species richness. [ABSTRACT FROM AUTHOR]