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Soil health has been defined as the soil's capacity to support crop growth without becoming degraded. Yet, soil health is under threat by overuse, climate change, salinization, erosion, compaction, nutrient depletion, contamination with toxic heavy metals or pesticides, overgrazing, and human assisted migration of soil-borne pests. Many agricultural practices that are proposed to be sustainable provide relatively small improvements and merely slow down the rate of degradation, which means that soils remain endangered. Thus, not only improvements in soil quality and fertility, but also a restoration of the soil food web, locking-up carbon in soil organic matter, improving water holding capacity, and diminishing soilborne pest outbreaks need to be addressed. To establish a representative database of soil factors changes induced by various agriculture management as well as factors reflecting local soil conditions and climate, seven long term experiments were sampled for physical, chemical and biological soil characteristics. Those include also the community composition and quantity of microorganisms, namely bacteria, archaea and fungi, which seem to be the most promising soil bioindicators. Thus, the main goal of the study was to combine the soil factors representing soil management and relate them to soil microbial communities for estimation of changes in microbial phylogenetic and functional diversity, which will be proposed as indicators of soil health. Since some management practices are replicated within our data set, the selected indicators will be determined using one set of sites and confirmed using another set of sites. The experiment is part of the EJP Soil – MINOTAUR project and covers different regions of Europe, so we anticipate proposing those indicators for agriculture practices as a measure of changes in soil quality and prediction of future soil development.

23 Pág., Purpose: Owing to their topographic location and nutrient rich soils, riparian forests are often converted to pastures for grazing. In recent decades, remnant riparian forests cleared for grazing pastures have been restored with native species. The impacts of such land-use changes on soil fungal communities are unclear, despite the central roles that soil fungi play in key ecosystem processes. We investigated how soil fungal taxonomic and functional composition are affected by land-use change at different depths, and if variation in soil fungal communities is related to edaphic properties and extant vegetation. Methods: The study was conducted in six waterways in south-eastern Australia, each comprising three land-use types: remnant riparian forest, cleared forest converted to pasture, and pastures restored with native plants. We surveyed three strata of vegetation and sampled top-soil and sub-soil to characterise physicochemical properties and soil fungal communities. ITS1 region sequences were used to assign soil fungal taxonomic and functional composition. Results: Fungal taxonomic and functional composition infrequently varied with land-use change or soil depth. Overall, environmental properties (soil and vegetation) explained 35–36% of variation in both fungal taxonomic and functional composition. Soil fungal taxonomic composition was related to soil fertility (N, P, K, pH and Ca) and ground cover characteristics, whereas functional composition was related to clay content, sub-canopy cover and tree basal area. Conclusion: Across the six studied waterways, fungal taxonomic and functional composition were more strongly associated with land-use mediated changes in site-scale soil physicochemical properties and vegetation structure than broad-scale classes of land-use type., Open Access funding enabled and organized by CAUL and its Member Institutions This study was funded by Holsworth Wildlife Research Endowment from the Ecological Society of Australia, Melbourne Water, and the Madeleine Selwyn Smith Memorial Scholarship. . Sabine Kasel is supported by the Integrated Forest Ecosystem Research Program funded by the Victorian Government Department of Environment, Land, Water and Planning. We would like to acknowledge the contributions of the Biomes of Australian Soil Environments (BASE) and Australian Microbiome consortiums for the generation of genetic data for this study. The Australian Microbiome initiative is supported by funding from Bioplatforms Australia and the Integrated Marine Observing System (IMOS) through the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS), Parks Australia through the Bush Blitz program funded by the Australian Government and BHP, and CSIRO.

Forest fire severity influences post-fire fuel structure and thus the behaviour of subsequent fires. Understanding such interactions is critical to improving predictions of fire risk and emergency management, yet few studies have quantified fire severity effects on fuel attributes. We quantify fuel structure of a fire-tolerant eucalypt forest 7 years after a landscape-scale wildfire in south-eastern Australia. We used high-density airborne lidar data to estimate understorey fuel metrics in three strata representing horizontal and vertical connectivity in 1084 plots (0.06 ha) representing four wildfire severities (unburnt, low, moderate, high). Fuel structure was changed by high-severity fire, which significantly increased the cover and horizontal connectivity of the elevated and midstorey strata and decreased space between the understorey and canopy relative to other severity types. Random Forest models indicated that understorey fuel metrics were most influenced by wildfire severity, pre-fire values of each metric, and post-fire canopy cover, and least influenced by climatic and topographic variables. Our study provides evidence of positive feedbacks to flammability by high-severity wildfire in fire-tolerant eucalypt forests through increased horizontal and vertical fuel connectivity. It demonstrates the utility of airborne lidar data for quantifying fuel structure in complex forests and providing critical data for fire risk assessments.

OBJECTIVE To determine the influence of plating systems on the clinical outcomes in dogs treated for ilial fractures. DESIGN Retrospective study. ANIMALS Fifty-nine dogs (63 hemipelves). METHODS Radiographs and medical records of dogs with ilial fractures presented to Iowa State University between 2003 and 2019 were reviewed. After fracture reduction, fractures were fixed with a locking plate system (LPS) or non-locking plate system (NLS). Perioperative, long-term complications, and follow-up data were recorded. The frequency of implant failure and pelvic collapse were compared using a logistic and linear regression analysis, respectively. Where the univariate test was statistically significant, a multivariate analysis across categories was performed to identify statistically different categories. RESULTS LPS and NLS implants were used in 25/63 and 38/63 hemipelves, respectively. Median follow-up time was 8 weeks (3-624 weeks). Implant failure occurred in 18/63 (29%) of fracture repairs, consisting of 17 with NLS and 1 with LPS. Revision surgery was recommended in five cases of implant failure, all with NLS. The probability of implant failure was higher when fractures were fixed with NLS (p = .0056). All other variables evaluated did not seem to influence outcome measures. CONCLUSION The variable with the most influence on the outcomes of dogs treated for ilial fractures consisted of the fixation method (NLS vs. LPS). Fractures repaired with NLS were nearly 20 times more likely to fail than those repaired with LPS. CLINICAL RELEVANCE Surgeons should consider repairing ilial body fractures in dogs with LPS to reduce the risk of short-term implant failure.

Riparian ecosystems are among the most degraded worldwide as they are subject to a range of human-mediated disturbances at different scales. As riparian vegetation plays a key role in maintaining waterway and landscape health, restoration often focuses on promoting riparian vegetation re-establishment. The role of below-ground processes and agents in the process of revegetation is often overlooked even though agents like mycorrhizal fungi enhance seedling establishment and plant growth. In this study we aimed to understand whether colonisation by local mycorrhizal fungi can be advantageous to the early phases of plant establishment during revegetation, whether revegetation technique influences the extent of this potential colonisation, and has the potential to enhance revegetation outcomes. We examined mycorrhizal colonisation rate and species composition of root fungal communities in direct seeded and tube-stock plants and compared them with local native vegetation in a retarding basin in Victoria, Australia, then modelled the relationship between root fungal community attributes and plant size. Results indicate that revegetation technique influenced the colonisation rate, diversity and composition of root fungal communities. Moreover, greater fungal diversity and greater similarity of fungal communities to the mycobiota of native vegetation were positively related with growth of seeded plants but showed negative or little relationship to size of tube-stock plants. High colonisation rates of plant species studied, and relationships between fungal community characteristics and plant growth of seeded plants provide the first evidence of the potential importance of mycorrhizal associations for these plant species in a revegetation context.

Understanding the extent of heterogeneity in soil microbial community structure and function at different scales within vegetation communities is critical to designing appropriate sampling protocols. Environmental factors (e.g. disturbance) make sampling in the riparian zone particularly challenging as vegetation communities are highly heterogeneous. To assess whether heterogeneity in soil and vegetation factors is reflected in microbial communities, a study was conducted in a riparian area in southern Australia. Nine quadrats were established encompassing different environmental conditions. Within quadrats physical, chemical and biological soil properties were analysed at two depths (top-soil = 0–10 cm and sub-soil = 20–30 cm), and floristic composition of ground cover, sub-canopy and canopy vegetation assessed. Soil biological analyses included microbial community composition (genetic analysis using ITS and 16S regions), and function (microbial metabolic activity using EcoPlates). Variation in soil microbial communities (fungi, bacteria, archaea) was related to differences in vegetation factors, particularly sub-canopy, and to a lesser extent, soil chemical properties. Relationships between variation in microbial communities and vegetation composition were stronger in top-soil than sub-soil. These observations were consistent for fungal communities excluding the phylum Glomeromycota, where the relationship was stronger with ground cover and only for top-soil. Variation in soil microbial community function was not related to variation in microbial community composition, soil physicochemical properties or vegetation factors. Our findings suggest there is little variation in the composition of soil microbial communities within areas with similar vegetation, and a small sampling effort would be needed to adequately describe the characteristics of such soil communities.

Aim: Forest carbon storage is the result of a multitude of interactions among biotic and abiotic factors. Our aim was to use an integrative approach to elucidate mechanistic relationships of carbon storage with biotic and abiotic factors in the natural forests of temperate Australia, a region that has been overlooked in global analyses of carbon-biodiversity relations. Location: South-eastern Australia. Time period: 2010–2015. Major taxa studied: Forest trees in 732 plots. Methods: We used the most comprehensive forest inventory database available for south-eastern Australia and structural equation models to assess carbon-storage relationships with biotic factors (species or functional diversity, community-weighted mean (CWM) trait values, structural diversity) and abiotic factors (climate, soil, fire history). To assess the consistency of relationships at different environmental scales, our analyses involved three levels of data aggregation: six forest types, two forest groups (representing different growth environments), and all forests combined. Results: Structural diversity was consistently the strongest independent predictor of carbon storage at all levels of data aggregation, whereas relationships with species- and functional-diversity indices were comparatively weak. CWMs of maximum height and wood density were also significant independent predictors of carbon storage in most cases. In comparison, climate, soil, and fire history had only minor and mainly indirect effects via biotic factors on carbon storage. Main conclusions: Our results indicate that carbon storage in our temperate forests was underpinned by tree structural diversity (representing efficient utilisation of space) and by CWM trait values (representing selection effects) more so than by tree species richness or functional diversity. Abiotic effects were comparatively weak and mostly indirect via biotic factors irrespective of the environmental range. Our study highlights the importance of managing forests for functionally important species and to maintain and enhance their structural complexity in order to support carbon storage.

18 Päg. Departamento de Medio Ambiente y Agronomía​, The structure and functioning of temperate forests are shifting due to changes in climate. Foreseeing the trajectory of such changes is critical to implementing adequate management practices and defining long-term strategies. This study investigated future shifts in temperate forest species composition and abundance expected to occur due to climate change. It also identified the ecological mechanisms underpinning such changes. Using an altitudinal gradient in the Romanian Carpathian temperate forests encompassing several vegetation types, we explored forest change using the Landis-II landscape model coupled with the PnET ecophysiological process model. We specifically assessed the change in biomass, forest production, species composition and natural disturbance impacts under three climate change scenarios, namely, RCP 2.6, 4.5 and 8.5. The results show that, over the short term (15 years), biomass across all forest types in the altitudinal gradient will increase, and species composition will remain unaltered. In contrast, over the medium and long terms (after 2040), changes in species composition will accelerate, with some species spreading (e.g., Abies alba Mill.) and others declining (e.g., Fagus sylvatica L.), particularly under the most extreme climate change scenario. Some forest types (e.g., Picea abies (L.) karst forests) in the Southern Carpathians will notably increase their standing biomass due to climate change, compared to other types, such as Quercus forests. Our findings suggest that climate change will alter the forest composition and species abundance, with some forests being particularly vulnerable to climate change, e.g., F. sylvatica forests. As far as productivity and forest composition changes are concerned, management practices should accommodate the new conditions in order to mitigate climate change impacts., This work was supported financially by EO-ROFORMON project, ID P_37_651/SMIS 105058 and PN 19070101

La acción COST NNEXT ha financiado el coste para publicar este artículo en abierto, por lo que aparece en la web de la revista como acceso abierto: https://onlinelibrary.wiley.com/doi/full/10.1111/brv.12511, Non-native tree (NNT) species have been transported worldwide to create or enhance services that are fundamental for human well-being, such as timber provision, erosion control or ornamental value; yet NNTs can also produce undesired effects, such as fire proneness or pollen allergenicity. Despite the variety of effects that NNTs have on multiple ecosystem services, a global quantitative assessment of their costs and benefits is still lacking. Such information is critical for decision-making, management and sustainable exploitation of NNTs. We present here a global assessment of NNT effects on the three main categories of ecosystem services, including regulating (RES), provisioning (PES) and cultural services (CES), and on an ecosystem disservice (EDS), i.e. pollen allergenicity. By searching the scientific literature, country forestry reports, and social media, we compiled a global data set of 1683 case studies from over 125 NNT species, covering 44 countries, all continents but Antarctica, and seven biomes. Using different meta-analysis techniques, we found that, while NNTs increase most RES (e.g. climate regulation, soil erosion control, fertility and formation), they decrease PES (e.g. NNTs contribute less than native trees to global timber provision). Also, they have different effects on CES (e.g. increase aesthetic values but decrease scientific interest), and no effect on the EDS considered. NNT effects on each ecosystem (dis)service showed a strong context dependency, varying across NNT types, biomes and socio-economic conditions. For instance, some RES are increased more by NNTs able to fix atmospheric nitrogen, and when the ecosystem is located in low-latitude biomes; some CES are increased more by NNTs in less-wealthy countries or in countries with higher gross domestic products. The effects of NNTs on several ecosystem (dis)services exhibited some synergies (e.g. among soil fertility, soil formation and climate regulation or between aesthetic values and pollen allergenicity), but also trade-offs (e.g. between fire regulation and soil erosion control). Our analyses provide a quantitative understanding of the complex synergies, trade-offs and context dependencies involved for the effects of NNTs that is essential for attaining a sustained provision of ecosystem services., Ministerio de Ciencia y Competitividad, Comunidad de Madrid

14 Pág. Departamento de Medio Ambiente y Agronomía​, Dead wood, including dead standing trees (DST) and coarse woody debris (CWD), is a critical component of forest ecosystems that provides habitat and refugia for fauna, flora, and microbial communities and plays a key role in carbon and nutrient cycling. However, few studies have modelled the long-term dynamics of dead wood, limiting our ability to predict how the abundance and composition of dead wood may change with climate change or altered fire regimes. Here we analyse DST and CWD data in 884 plots encompassing multiple field campaigns and forest types of varying canopy cover and species composition across the State of Victoria in temperate south-eastern Australia. We use boosted regression tree modelling to examine the relative influence of disturbance history and tree functional traits on dead wood biomass while accounting for the influence of environmental and climatic factors and stand attributes across a broad productivity gradient. We modelled absolute and relative dead wood biomass by size (‘small’ 100 < 200 mm diameter, ‘medium’ 200 < 500 mm diameter, ‘large’ ≥ 500 mm diameter) and decay classes (sound to advanced decay) to evaluate the consistency of predictor effects among different components of dead wood. We found that live tree basal area and mean annual precipitation were influential predictors of both DST and CWD biomass, indicating an over-arching effect of forest productivity on dead wood biomass. Fire history was also an important predictor, with DST biomass decreasing and CWD biomass increasing with time since last wildfire. The proportion of large DST biomass increased with increased tree mortality as a result of fire interval and time in drought. DST biomass also increased and CWD biomass decreased with increasing wood density, and this was relatively more important than the other functional traits we examined (heartwood nitrogen content and bark type). Our study suggests that forest productivity, fire history, drought and wood density are important determinants of dead wood, as they influence dead wood inputs and outputs. Our study reveals the broad-scale drivers of dead wood biomass, and the potential for altered fire regimes and changing climate to influence live- to dead wood dynamics and associated ecosystem functions., This research was undertaken with approval by the Victorian Department of Environmental, Land, Water and Planning (DELWP) under Research Permit Numbers 10006440, 10006488, 10006691, 10007105, and the Forests Act 1958 (FS/14/3694/1/3). The work was funded by the Victorian DELWP through the Integrated Forest Ecosystem Research Program, with additional support from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) former Sustainable Agriculture Flagship program. For their contributions to data collection, we thank: Helen Vickers, Julio Najera-Umana and Benjamin Smith from The University of Melbourne, Australia; Michele Kohout, Matthew Bruce, and colleagues from Arthur Rylah Institute for Environmental Research, Australia; Elizabeth Pryde and colleagues from Arthur Rylah Institute for Environmental Research, Australia; and Sue Baker from the University of Tasmania, Australia. The study benefited from the TRY database on plant traits (http://www.try.db.org), which is hosted, developed and maintained by J. Kattge and G. Bönisch (Max Planck Institute for Biogeochemistry, Jena, Germany). TRY is currently supported by DIVERSITAS/Future Earth and the German Centre for Integrative Biodiversity Research (iDiv).

Wildfires have increased in size and frequency in recent decades in many biomes, but have they also become more severe? This question remains under-examined despite fire severity being a critical aspect of fire regimes that indicates fire impacts on ecosystem attributes and associated post-fire recovery. We conducted a retrospective analysis of wildfires larger than 1000 ha in south-eastern Australia to examine the extent and spatial pattern of high-severity burned areas between 1987 and 2017. High-severity maps were generated from Landsat remote sensing imagery. Total and proportional high-severity burned area increased through time. The number of high-severity patches per year remained unchanged but variability in patch size increased, and patches became more aggregated and more irregular in shape. Our results confirm that wildfires in southern Australia have become more severe. This shift in fire regime may have critical consequences for ecosystem dynamics, as fire-adapted temperate forests are more likely to be burned at high severities relative to historical ranges, a trend that seems set to continue under projections of a hotter, drier climate in south-eastern Australia.

Wildfires worldwide are becoming more frequent but are they also becoming more severe? Here we used remotely sensed burn-severity data from wildfires in Victoria, southeastern Australia to address that question. We selected 162 wildfires of more than 1000 ha that occurred over the past 30 years across a wide range of forest types. Spectral indices derived from Landsat pre- and post- fire imagery were used to map fire severity. Our results show a significant increase in the absolute and proportional area burnt by high-severity fire over the last three decades. This study demonstrates that wildfires in the temperate forests of southern Australia are becoming more severe. Such change in fire regimes may have critical consequences for the sustainability and resilience of the studied forests.

According to the competitive exclusion principle, species with low competitive abilities should be excluded by more efficient competitors; yet, they generally remain as rare species. Here, we describe the positive and negative spatial association networks of 326 disparate assemblages, showing a general organization pattern that simultaneously supports the primacy of competition and the persistence of rare species. Abundant species monopolize negative associations in about 90% of the assemblages. On the other hand, rare species are mostly involved in positive associations, forming small network modules. Simulations suggest that positive interactions among rare species and microhabitat preferences are the most probable mechanisms underpinning this pattern and rare species persistence. The consistent results across taxa and geography suggest a general explanation for the maintenance of biodiversity in competitive environments., J.C. is supported by the Carl Tryggers Foundation for Scientific Research (no. CTS 16:384). E.A. is supported by a postdoctoral grant (no. CT39/17) funded by the Universidad Complutense de Madrid. C.J.M. is supported by the Swiss National Science Foundation (grant no. SNSF-31003A-144162). R.B.-M. is supported by the Spanish Ministry of Science and Innovation predoctoral fellowship no. BES-2013-065753. M.S., J.A.B.-C. and J.M.-G. acknowledge support from the University of Geneva (project: C-CIA; no. 309354). X.A. is supported by a Ramón y Cajal research contract by the Spanish Ministry of Economy and Competitiveness (MINECO, no. RYC-2015-18448). M.R. is supported by the Swedish Research Council grant no. 2016-00796. J.A.N. was supported by a Colombian COLCIENCIAS doctoral scholarship (no. 617-2013). F.A.-M. is grateful to CAPES for a doctoral scholarship (no. 120147/2016-01). A.L., P.F. and J.M.-G. were funded by the AGORA Project (MINECO, no. CGL2016-77417-P). C.M.-M. was supported by an IdEx Bordeaux Postdoctoral Fellowship (VECLIMED project). A.H. was supported by the University of Alcalá own research programme 2018 postdoctoral grant and Basque Country Government funding support to FisioClimaCO2 (IT1022-16) research group. L.J. received productivity grants from of CNPq (process no. 307597/2016-4).

More tree species can increase the carbon storage capacity of forests (here referred to as the more species hypothesis) through increased tree productivity and tree abundance resulting from complementarity, but they can also be the consequence of increased tree abundance through increased available energy (more individuals hypothesis). To test these two contrasting hypotheses, we analyse the most plausible pathways in the richness-abundance relationship and its stability along global climatic gradients. We show that positive effect of species richness on tree abundance only prevails in eight of the twenty-three forest regions considered in this study. In the other forest regions, any benefit from having more species is just as likely (9 regions) or even less likely (6 regions) than the effects of having more individuals. We demonstrate that diversity effects prevail in the most productive environments, and abundance effects become dominant towards the most limiting conditions. These findings can contribute to refining cost-effective mitigation strategies based on fostering carbon storage through increased tree diversity. Specifically, in less productive environments, mitigation measures should promote abundance of locally adapted and stress tolerant tree species instead of increasing species richness., Correlations between tree species diversity and tree abundance are well established, but the direction of the relationship is unresolved. Here the authors use path models to estimate plausible causal pathways in the diversity-abundance relationship across 23 global forests regions, finding a lack of general support for a positive diversity-abundance relationship, which is prevalent in the most productive lands on Earth only

Biochar, produced from biosolids using microwave pyrolysis technology, is energetically a more efficient alternative to that produced with conventional convective heating. However the potential of microwave generated biochar as a growing media amendment has not been sufficiently explored. Here we produced biochar from biosolids using microwave energy. The pyrolysis expeiments were conducted in two stages, initially using a custom built single mode chamber to explore the energetics and product distribution of the pyrolysis process at different temperatures and secondly in a 1 m3 6 kW multi-mode chamber, to explore potential scale-up of the process. The second phase of the pyrolysis experiments was focused on biochar generation for use in the remainder of this research. Microwave pyrolyzed biochar (MB) was characterised for its chemcal and physical properties. Then, we conducted a greenhouse experiment, where we compared the ability of four growing media mixes that combined pine bark with (i) sphagnum peat and fertilizers; (ii) 20% MB and fertilizers; (iii) 60% MB and fertilizers; and (iv) 60% MB and no fertilizers, to promote plant growth and nutrient uptake and to minimise leaching losses. MB had high mesoporosity (average pore width of 4.46 nm), moderate surface area (75 m2 g−1), elevated nutrient content and low heavy metal concentrations as compared to other biosolids biochars reprted in literatures. Substitution of peat with 60% MB on volume basis reduced leaching loss of nitrate and phosphate from the media but increased leaching loss of ammonium. Addition of MB in conjunction with fertilizer increased plant growth and plant nitrogen and phosphorus use efficiency. Our study has shown microwave pyrolysis as a promising technology for pyrolyzing biosolids and also has demonstrated the synergistic interaction of MB and fertilizer which results in greater plant growth and nutrient uptake and use efficiency.

16 Pág. Departamento de Medio Ambiente y Agronomía​, While products generated at global levels provide easy access to information on forest growing stock volume (GSV), their use at regional to national levels is limited by temporal frequency, spatial resolution, or unknown local errors that may be overcome through locally calibrated products. This study assessed the need, and utility, of developing locally calibrated GSV products for the Romanian forests. To this end, we used national forest inventory (NFI) permanent sampling plots with largely concurrent SAR datasets acquired at C-and L-bands to train and validate a machine learning algorithm. Different configurations of independent variables were evaluated to assess potential synergies between C-and L-band. The results show that GSV estimation errors at C-and L-band were rather similar, relative root mean squared errors (RelRMSE) around 55% for forests averaging over 450 m3 ha−1, while synergies between the two wavelengths were limited. Locally calibrated models improved GSV estimation by 14% when compared to values obtained from global datasets. However, even the locally calibrated models showed particularly large errors over low GSV intervals. Aggregating the results over larger areas considerably reduced (down to 25%) the relative estimation errors., This research was funded by the Romanian National Authority for Scientific Research and Innovation and the European Regional Development Fund through the project “Prototyping an Earth-Observation based monitoring and forecasting system for the Romanian forests” (EO-ROFORMON, grant P_37_651/105058).

Australia’s temperate forest landscapes encompass broad topographic and edaphic ranges, and are regularly disturbed by fire. Nonetheless, relative contributions of environmental heterogeneity, disturbance regimes, and dispersal limitations to plant species turnover remain poorly understood. To evaluate the relative influences of deterministic (environmental, disturbance), and stochastic (spatial) processes on plant species turnover [beta-diversity (β diversity)] in natural forest landscapes, and how such influences vary among plant functional types and vegetation strata. We assessed the environment and species composition of 81 forest stands, representing a range of structures and fire histories across contiguous landscapes in south-eastern Australia, and examined the potential to explain β diversity using variance partitioning and distance-decay analyses. Explanatory variables accounted for 34–55% of β diversity of multiple plant functional types, with environmental heterogeneity explaining the greatest proportion (10–25%). Stand structural variables (e.g., leaf area index, height coefficient of variation) accounted for 8–14% of β diversity in understorey life forms and 5% in canopy species, far greater than a single direct descriptor of disturbance history such as time-since-fire which explained just 2% of tree and shrub β diversity. β Diversity increased with increasing geographic distance for all functional types. Dispersal limitation accounted for 5–11% of β diversity, and distance-decay rates varied among plant functional types. Landscape-scale conservation of forest biodiversity will require representation of a broad environmental range as well as metrics that fully capture site disturbance histories, including stand structural complexity as a potential proxy for fire regimes.

Aim In boreal forest ecosystems plant productivity is typically constrained by mineral nutrient availability. In some boreal regions changes in nutrient availability have led to limited changes in productivity but large changes in plant composition. To determine the impact that a change in nutrient availability has on the plant communities it is important to understand how species use nutrients. Here we explore how plant species and functional types in a cold-dry boreal forest community use available nutrients by quantifying their respective nutrient utilization and response efficiency. Location Boreal forests in the southwest corner of the Yukon Territory, Canada. Methods We collected soil samples and total plant biomass from 29 plots from nine locations subjected to fire, harvesting or bark beetle disturbances. Nutrient analysis of all vegetation and soil samples were conducted to determine the concentration of macro- and micronutrients from both plant biomass and soils collected. Nutrient pools between stands with different disturbance histories are compared. Nutrient uptake, use and response efficiencies were then calculated and nutrient response profiles were developed for each species/functional type. Results We found few differences between nutrient pools in plots with different disturbance histories. A clear separation of species and functional groups in elemental hyperspace suggesting divergent nutrient use in co-occurring species was identified. The use efficiency analysis highlighted that the species with the highest uptake efficiency have lowest use efficiency and vice versa. Species showed either a monotonic or constant relationship between nutrient response efficiency and N, P, K, reflecting a lack of relationship between plant productivity and resource availability or a linear increase in productivity with increasing nutrient availability, respectively. Conclusions Our findings indicate that species are maximizing nutrient use along different parts of the resource gradient, which has implications for understanding how species respond to changes in nutrient availability. Our findings also show that nutrient use by some species may be governed more by uptake efficiency than use efficiency, allowing them to respond to increases in resource availability by increasing uptake rather than use.

Functional diversity and composition of soil bacterial communities affect important soil biogeochemical processes. In natural and semi-natural ecosystems, variations in habitat complexity have been shown to significantly impact both litter and soil bacterial communities. However, this remains largely untested in urban ecosystems, where human management can lead to habitat complexity combinations unobserved in rural ecosystems. We established 10 research plots in low-complexity park, high-complexity park, and high-complexity remnant habitat types (n = 30) in Melbourne, Australia. The use of organic carbon substrates by soil and litter bacteria was measured using EcoPlates to investigate the effects of habitat complexity upon metabolic functional diversity and functional composition of bacterial communities of i) soil and ii) one-year old litter. Direct and indirect effects of habitat complexity, microclimate and decomposition status upon litter microbial functional diversity and composition were also modelled using path analysis. Soil bacterial communities had significantly higher functional diversity compared to litter bacterial communities, but no significant effect of habitat complexity was apparent. The functional composition of soil bacterial communities was not affected by habitat complexity. In contrast, the functional composition of litter bacterial communities in high complexity parks and remnants was significantly different from that in low-complexity parks. The functional composition of litter bacterial communities, but not their diversity, was directly affected by habitat complexity and microclimate as well as their indirect effects upon the decomposition status of litter. Human management of urban habitat complexity can alter the functional composition of litter and soil bacterial communities without affecting their functional diversity. While this can have significant impacts on bacteria-regulated processes and ecosystem services, it also suggests that urban bacterial communities might be able to adjust to further environmental and climatic changes affecting urban ecosystems.

Mixed-species eucalypt forests of temperate Australia are assumed tolerant of most fire regimes based on the impressive capacity of the dominant eucalypts to resprout. However, empirical data to test this assumption are rare, limiting capacity to predict forest tolerance to emerging fire regimes including more frequent severe wildfires and extensive use of prescribed fire. We quantified tree mortality and regeneration in mixed-species eucalypt forests five years after an extensive wildfire that burnt under extreme fire weather. To examine combined site-level effects of wildfire and prescribed fire, our study included factorial replications of three wildfire severities, assessed as crown scorch and understorey consumption shortly after the wildfire (Unburnt, Low, High), and two times since last preceding fire ( 30 years since any fire). Our data indicate that while most trees survived low-severity wildfire through epicormic resprouting, this capacity was tested by high-severity wildfire. Five years after the wildfire, percentage mortalities of eucalypts in all size intervals from 10 to >70 cm diameter were significantly greater at High severity than Unburnt or Low severity sites, and included the near loss of the 10–20 cm cohort (93% mortality). Prolific seedling regeneration at High severity sites, and unreliable basal resprouting, indicated the importance of seedling recruitment to the resilience of these fire-tolerant forests. Recent prescribed fire had no clear effect on forest resistance (as tree survival) to wildfire, but decreased site-level resilience (as recruitment) by increasing mortalities of small stems. Our study indicates that high-severity wildfire has the potential to cause transitions to more open, simplified stand structures through increased tree mortality, including disproportionate losses in some size cohorts. Dependence on seedling recruitment could increase vulnerabilities to subsequent fires and future climates, potentially requiring direct management interventions to bolster forest resilience.

Machine learning and spectral index (SI) thresholding approaches have been tested for fire-severity mapping from local to regional scales in a range of forest types worldwide. While index thresholding can be easily implemented, its operational utility over large areas is limited as the optimum index may vary with forest type and fire regimes. In contrast, machine learning algorithms allow for multivariate fire classifications. This study compared the accuracy of fire-severity classifications from SI thresholding with those from Random Forests (RF). Reference data were from 3730 plots within the boundaries of eight major wildfires across the six temperate forest �functional' groups of Victoria, south-eastern Australia. The reference plots were randomly divided into training and validation datasets (60/40) for each fire-severity class (unburnt, low, moderate, high) and forest functional group. SI fire-severity classifications were conducted using thresholds derived in a previous study based on the same datasets. A RF classification algorithm was trained to derive fire-severity levels based on appropriate spectral indices and their temporal difference. The RF classification outperformed the SI thresholding approach in most cases, increasing overall accuracy by 11% on a forest-group basis, and 16% on an individual wildfire basis. Adding more predictor variables into the RF algorithm did not improve classification accuracy. Greater overall accuracies (by 12% on average) were achieved when in situ data (rather than data from other fires) were used to train the RF algorithm. Our study shows the utility of Random Forest algorithms for streamlining fire-severity mapping across heterogeneous forested landscapes.

Natural and anthropogenic disturbances pose a significant threat to forest condition. Continuous, reliable and accurate forest monitoring systems are needed to provide early warning of potential declines in forest condition. To address that need, state-of-the-art simulations models were used to evaluate the utility of C-, L- and P-band synthetic aperture radar (SAR) sensors within an integrated Earth-Observation monitoring system for beech, oak and coniferous forests in Romania. The electromagnetic simulations showed differentiated sensitivity to vegetation water content, leaf area index, and forest disturbance depending on SAR wavelength and forest structure. C-band data was largely influenced by foliage volume and therefore may be useful for monitoring defoliation. Changes in water content modulated the C-band signal by

Cork oaks (Quercus suber L.) are key tree species at Doñana Biological Reserve (DBR), Huelva, Spain. Sampling was conducted on a total of 13 trees exhibiting symptoms of decline (foliar wilting and defoliation, branch dieback, and root necrosis).

Departamento de Medio Ambiente y Agronomía​ (INIA), Riparian forests were frequently cleared and converted to agricultural pastures, but in recent times these pastures are often revegetated in an effort to return riparian forest structure and function. We tested if there is a change in the soil bacterial taxonomy and function in areas of riparian forest cleared for agricultural pasture then revegetated, and if soil bacterial taxonomy and function is related to vegetation and soil physicochemical properties. The study was conducted in six riparian areas in south‐eastern Australia, each comprising of three land‐use types: remnant riparian forest, cleared forest converted to pasture, and revegetated pastures. We surveyed three strata of vegetation and sampled surface soil and subsoil to characterize physicochemical properties. Taxonomic and functional composition of soil bacterial communities were assessed using 16S rRNA gene sequences and community level physiological profiles, respectively. Few soil physiochemical properties differed with land use despite distinct vegetation in pasture relative to remnant and revegetated areas. Overall bacterial taxonomic and functional composition of remnant forest and revegetated soils were distinct from pasture soil. Land‐use differences were not consistent for all bacterial phyla, as Acidobacteria were more abundant in remnant soils; conversely, Actinobacteria were more abundant in pasture soils. Overall, bacterial metabolic activity and soil carbon and nitrogen content decreased with soil depth, while bacterial metabolic diversity and evenness increased with soil depth. Soil bacterial taxonomic composition was related to soil texture and soil fertility, but functional composition was only related to soil texture. Our results suggest that the conversion of riparian forests to pasture is associated with significant changes in the soil bacterial community, and that revegetation contributes to reversing such changes. Nevertheless, the observed changes in bacterial community composition (taxonomic and functional) were not directly related to changes in vegetation but were more closely related to soil attributes., This research was funded by Holsworth Wildlife Research Endowment from the Ecological Society of Australia, Melbourne Water, and the Madeleine Selwyn Smith Memorial Scholarship. Vicky Waymouth was a recipient of a Research Training Program Scholarship. Cybec Foundation supported Rebecca Miller during her lectureship at Melbourne University. We would like to acknowledge the contributions of the Biomes of Australian Soil Environments (BASE) and Australian Microbiome consortiums to the generation of genetic data for this study. The Australian Microbiome initiative is supported by funding from Bioplatforms Australia and the Integrated Marine Observing System (IMOS) through the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS), Parks Australia through the Bush Blitz program funded by the Australian Government and BHP, and CSIRO. Soil collection and field sampling was conducted under Parks Victoria permit number 10008494., 24 Pág. This article belongs to the Special Issue Restoring Forest Landscapes: Impact on Soil Properties and Functions

Management strategies such as planned burning for fuel reduction can help mitigate the effects of wildfires. The amount of biomass consumed is of interest to fire managers as reduction of fuel loads is imperative to reducing the risk and extent of a wildfire event. Biomass regeneration is also of importance for ecosystem recovery and resilience. Pyrogenic carbon (PyC), a product of combustion during both planned and unplanned fires, plays a key role in global carbon stores and balances. A three-year study of planned burning practices examined fires in Lowland temperate Eucalypt forest of south eastern Australia. We collected data on overstorey, understorey, coarse woody debris, fine litter, PyC and soil across nine sites to determine biomass consumption, PyC production and changes in ecosystem carbon during planned burning. Lowland forest showed significant recovery of combustible biomass (fine litter and understorey) one year after planned fire. Across our sites, PyC was produced at a rate of approximately 5% of the biomass consumed. The PyC produced is destined to become part of soil and litter carbon and contributes to long-term carbon storage. Planned burning had a short-term (

Fires affect wide areas and their effects can be successfully estimated from a range of remote sensing sensors, with synthetic aperture radars (SAR) being of particular interest due to their sensitivity to forest vertical structure, global availability and independence of cloud cover or solar elevation. Previous studies have demonstrated the sensitivity to fire effects of L-band SAR sensors using post-fire datasets and empirical modeling. This study proposed an innovative method for estimating fire severity by combining pre- and post-fire SAR datasets within a change detection framework to compute a novel index, the Radar Burn Ratio (RBR). More importantly, a standardized RBR was developed and tested over seven temperate forest types located on three continents with above ground biomass values ranging from 30 to over 500 t ha− 1. RBR standardization allowed for common thresholds to be defined and subsequently used for estimating the Composite Burn Index (CBI, a measure of fire impact) without the need for a priori information (i.e., in situ data) on local post-fire conditions. The estimation accuracy of the standardized RBR was compared to locally-calibrated empirical models based on field CBI data. The results showed similar estimation errors and a strong agreement with the reference in situ data (i.e., Cohen's weighted kappa > 0.61). The RBR index most sensitive to fire severity was based on the cross-polarized channel applied under dry environmental conditions. Under wet conditions the estimation accuracy was considerably lower. The methods proposed in this study are particularly valuable for rapid fire severity assessments at regional to global scales, requiring only that RBR thresholds be calibrated for a range of environments and that CBI scores be related to fuel consumption for each forest type.

Wildfires can influence the canopy structure of resprouter forests in multiple ways including crown scorching and consumption, tree damage and mortality, and changes in resources available for recovery. Few studies have quantified post-fire changes in the canopy structure of fire-tolerant eucalypt forests, which limits understanding of the extent and persistence of fire effects on ecosystem processes including interactions with environment. In this study, we assess the impacts of a landscape-scale wildfire on the canopy structure of fire-tolerant eucalypt forests in temperate Australia using metrics derived from airborne lidar data. Our assessment, made seven years after the wildfire, encompassed four fire severities (unburnt, low, moderate, high) and involved 1084 lidar plots (0.06 ha, including validation using 51 field plots) across an area of ~30,000 ha in a single forest type. We used Random Forest models to examine the relative importance of fire severity, pre-fire canopy metrics, climate and topography to the prediction of seven post-fire metrics representing the horizontal and vertical structure of the full canopy, the dominant and sub-dominant strata. Canopy cover at seven years post-fire was significantly reduced in moderate- and particularly high-severity plots (mean decrease of 30%). High-severity fire also decreased mean canopy height and led to changes in the canopy relief ratio and rumple index consistent with a dominant stratum that was more heterogeneous and fragmented. In addition to fire severity, the pre-fire values of each metric were important to their post-fire prediction, suggesting that canopy structural recovery after this fire could have been influenced by any lingering effects of previous fires. Topographic and climatic variables were of comparatively minor importance to the prediction of post-fire canopy metrics, although relationships with the forest drought stress index indicated that canopy recovery was slowest at the driest sites. Our study provides quantitative evidence of significant changes in the canopy structure of fire-tolerant eucalypt forests that persisted for at least seven years after high-severity wildfire. Recent trends in southern Australia of shortened wildfire intervals and a drier climate will likely narrow the windows for canopy recovery of fire-tolerant forests, realizing predictions of a gradual opening and fragmentation of forest canopies in temperate Australia and associated changes in multiple ecosystem processes.

Soil organic carbon (SOC) stocks in Australia’s temperate forests have been overlooked in national soil databases and in global SOC analyses of natural ecosystems despite the importance of temperate forests to the global terrestrial carbon balance. This limits the potential to both predict change in SOC stocks in temperate Australia and to identify where and how SOC stocks can be managed to mitigate climate change. Based on data from 707 sites, we examine variations in SOC concentrations and stocks across a range of natural temperate broadleaf forests in south-eastern Australia. Comparisons with current Australia-wide databases highlight previous under-estimation of forest SOC concentrations, leading to substantial underprediction of SOC stocks in the most productive forests (e.g. this study’s mean of 207 Mg C ha−1 compared with a database mean estimate of 141 Mg C ha−1 for Tall open-forests to 30-cm soil depth). Random Forest models involving 27 environmental variables (representing climate, terrain, parent material, soil attributes, vegetation, and fire history) explained up to 79% of the variation in SOC concentrations and 77% of the variation in SOC stocks to 30-cm depth. Climate variables (precipitation, temperature) were of greatest importance to the prediction of both SOC concentrations and SOC stocks, tending to override the importance of terrain and fire-history variables at this study’s regional scale. While patterns in SOC concentrations and stocks were correlated, SOC concentrations were not a reliable proxy for SOC stocks to 10-cm depth, reiterating the importance of mass equivalent measures (i.e. soil bulk density) to assessing changes in soil carbon storage. Our study provides a timely check of the model-based estimates of SOC concentrations and stocks in Australia’s temperate forests that are currently available in nation-wide databases and improves the available information for defining benchmarks, and for identifying potential areas of SOC loss and gain, in programs that aim to mitigate climate change.

Spectral indices derived from optical remote sensing data have been widely used for fire-severity classification in forests from local to global scales. However, comparative analyses of multiple indices across diverse forest types are few. This represents an information gap for fire management agencies in areas like temperate south-eastern Australia, which is characterised by a diversity of natural forests that vary in structure, and in the fire-regeneration strategies of the dominant trees. We evaluate 10 spectral indices across eight areas burnt by wildfires in 1998, 2006, 2007, and 2009 in south-eastern Australia. These wildfire areas encompass 13 forest types, which represent 86% of the 7.9M ha region’s forest area. Forest types were aggregated into six forest groups based on their fire-regeneration strategies (seeders, resprouters) and structure (tree height and canopy cover). Index performance was evaluated for each forest type and forest group by examining its sensitivity to four fire-severity classes (unburnt, low, moderate, high) using three independent methods (anova, separability, and optimality). For the best-performing indices, we calculated index-specific thresholds (by forest types and groups) to separate between the four severity classes, and evaluated the accuracy of fire-severity classification on independent samples. Our results indicated that the best-performing indices of fire severity varied with forest type and group. Overall accuracy for the best-performing indices ranged from 0.50 to 0.78, and kappa values ranged from 0.33 (fair agreement) to 0.77 (substantial agreement), depending on the forest group and index. Fire severity in resprouter open forests and woodlands was most accurately mapped using the delta Normalised Burnt ratio (dNBR). In contrast, dNDVI (delta Normalised difference vegetation index) performed best for open forests with mixed fire responses (resprouters and seeders), and dNDWI (delta Normalised difference water index) was the most accurate for obligate seeder closed forests. Our analysis highlighted the low sensitivity of all indices to fire impacts in Rainforest. We conclude that the optimal spectral index for quantifying fire severity varies with forest type, but that there is scope to group forests by structure and fire-regeneration strategy to simplify fire-severity classification in heterogeneous forest landscapes.

The carbon stability of fire-tolerant forests is often assumed but less frequently assessed, limiting potential to anticipate threats to forest carbon posed by predicted increases in forest fire activity. Assessing the carbon stability of fire-tolerant forests requires multi-indicator approaches that recognise the myriad of ways that fires influence the carbon balance including combustion, deposition of pyrogenic material, and tree death, post-fire decomposition, recruitment, and growth. Five years after a large-scale wildfire in south-eastern Australia, we assessed the impacts of low- and high-severity wildfire, with and without prescribed fire (≤ 10 years before), on carbon stocks in multiple pools, and on carbon stability indicators (carbon stock percentages in live trees and in small trees, and carbon stocks in char and fuels) in fire-tolerant eucalypt forests. Relative to unburnt forest, high-severity wildfire decreased short-term (five-year) carbon stability by significantly decreasing live tree carbon stocks and percentage stocks in live standing trees (reflecting elevated tree mortality), by increasing the percentage of live tree carbon in small trees (those vulnerable to the next fire), and by potentially increasing the probability of another fire through increased elevated fine fuel loads. In contrast, low-severity wildfire enhanced carbon stability by having negligible effects on above-ground stocks and indicators, and by significantly increasing carbon stocks in char and, in particular, soils, indicating pyrogenic carbon accumulation. Overall, recent preceding prescribed fire did not markedly influence wildfire effects on short-term carbon stability at stand scales. Despite wide confidence intervals around mean stock differences – indicating uncertainty about the magnitude of fire effects in these natural forests – our assessment highlights the need for active management of carbon assets in fire-tolerant eucalypt forests under contemporary fire regimes. Decreased live tree carbon and increased reliance on younger cohorts for carbon recovery after high-severity wildfire, could increase vulnerabilities to imminent fires, leading to decisions about interventions to maintain the productivity of some stands. Our multi-indicator assessment also highlights the importance of considering all carbon pools, particularly pyrogenic reservoirs like soils, when evaluating the potential for prescribed fire regimes to mitigate the carbon costs of wildfires in fire-prone landscapes. This article is protected by copyright. All rights reserved.

Prescribed fires are a common management practice in the temperate forests of Australia, but effects on total forest carbon (C) of long-term prescribed fire regimes, involving multiple repeat fires, remain under-examined. This study quantified C stocks in multiple pools after 27 years of a long-term prescribed fire experiment in a mixed-species eucalypt forest in south-eastern Australia. The experimental design included five replications of each of five treatments – a long-unburnt Control, plus a factorial combination of two fire frequencies (c. 3-yearly ‘High’, c. 10-yearly ‘Low’), and two fire seasons (Spring, Autumn) – encompassing up to 7 low-intensity repeat fires over the 27 years. Overall, total C stocks (the sum of all pools: Above-ground biomass, Dead wood, Litter, and Soil) were significantly greater in Control than Fire treatments. Mean total C stock differences (Control minus Fire) were 36 Mg ha−1, and increased with both fire frequency (46 Mg ha−1, Control versus High frequency treatments) and fires in autumn rather than spring (42 Mg ha−1, Control versus Autumn treatments). Mean differences had wide 95% confidence intervals (e.g. 4–67 Mg C ha−1, Control versus Fire), indicating considerable uncertainty about the magnitude of effects of prescribed fire regimes on total C in these native forests. Weighted averaging of linear multiple regression models was used to identify the most important variables for explaining proportional C stock differences ((Control–Fire)/Control), and involved consideration of 85 explanatory variables including measures of fire intensity, fire severity, fuel, pre- and post-fire rainfall, fire weather, and topography. The best regression model explained 80% of variation in total C stock differences between Control and Fire treatments. Consistently important explanatory variables were those representing or associated with fire intensity (flame angle, wind speed, Forest Fire Danger Index), and number of prescribed fires. Measures of fuel load, pre- and post-fire rainfall, and, in particular, fire severity, were less important explanatory variables. The study provides indications of management options for minimising C stock decreases associated with prescribed fire regimes in temperate eucalypt forests; notably, wide fire intervals (closer to 10 than 3 years), and utilising strategies to minimise mean fire intensity, including burning in moist (spring) rather than dry (autumn) conditions.

Previous studies have found negligible effects of single prescribed fires on coarse woody debris (CWD), but the cumulative effects of repeated low-intensity prescribed fires are unknown. This represents a knowledge gap for environmental management because repeated prescribed fires are a key tool for mitigating wildfire risk, and because CWD is recognized as critical to forest biodiversity and functioning. We examined the effects of repeated low-intensity prescribed fires on the attributes and stocks of (fallen) CWD in a mixed-species eucalypt forest of temperate Australia. Prescribed fire treatments were a factorial combination of two seasons (Autumn, Spring) and two frequencies (three yearly High, 10 yearly Low), were replicated over five study areas, and involved two to seven low-intensity fires over 27 years. Charring due to prescribed fires variously changed carbon and nitrogen concentrations and C to N ratios of CWD pieces depending on decay class, but did not affect mean wood density. CWD biomass and C and N stocks were significantly less in Fire than Control treatments. Decreases in total CWD C stocks of -8 Mg/ha in Fire treatments were not balanced by minor increases in pyrogenic (char) C (-0.3 Mg/ha). Effects of prescribed fire frequency and season included significantly less C and N stocks in rotten CWD in High than Low frequency treatments, and in the largest CWD pieces in Autumn than Spring treatments. Our study demonstrates that repeated low-intensity prescribed fires have the potential to significantly decrease CWD stocks, in pieces of all sizes and particularly decayed pieces, and to change CWD chemical attributes. CWD is at best a minor stock of pyrogenic C under such fire regimes. These findings suggest a potential trade-off in the management of temperate eucalypt forests between sustained reduction of wildfire risk, and the consequences of decreased CWD C stocks, and of changes in CWD as a habitat and biogeochemical substrate. Nonetheless, negative impacts on CWD of repeated low-intensity prescribed fires could be lessened by fire intervals of 10 rather than three years (to decrease losses of decayed CWD), and fires in moist rather than dry conditions (to conserve large CWD).

16 páginas.-- 5 figuras.-- 3 tablas.-- 75 referencias.-- Tiene un archivo de material suplementario., Aims The extent to which the spatial and temporal patterns of soil microbial and available nutrient pools hold across different Mediterranean forest types is unclear impeding the generalization needed to consolidate our understanding on Mediterranean ecosystems functioning. Methods We explored the response of soil microbial, total, organic and inorganic extractable nutrient pools (C, N and P) to common sources of variability, namely habitat (tree cover), soil depth and season (summer drought), in three contrasting Mediterranean forest types: a Quercus ilex open woodland, a mixed Q. suber and Q. canariensis woodland and a Pinus sylvestris forest. Results Soil microbial and available nutrient pools were larger beneath tree cover than in open areas in both oak woodlands whereas the opposite trend was found in the pine forest. The greatest differences in soil properties between habitat types were found in the open woodland. Season (drought effect) was the main driver of variability in the pine forest and was related to a loss of microbial nutrients (up to 75 % loss of Nmic and Pmic) and an increase in microbial ratios (Cmic/Nmic, Cmic/Pmic) from Spring to Summer in all sites. Nutrient pools consistently decreased with soil depth, with microbial C, N and P in the top soil being up to 208 %, 215 % and 274 % larger than in the deeper soil respectively. Conclusions Similar patterns of variation emerged in relation to season and soil depth across the three forest types whereas the direction and magnitude of the habitat (tree cover) effect was site-dependent, possibly related to the differences in tree species composition and forest structure, and thus in the quality and distribution of the litter input., This study was supported by the coordinated Spanish MEC Projects DINAMED (CGL2005-05830-C03), INTERBOS (CGL2008- 4503-C03-01), and DIVERBOS (CGL2011-30285- C02), the Andalusian Projects GESBOME (P06-RNM-1890) and ANASINQUE (PE2010-RNM5782), the Life + Biodehesa project (11/BIO/ES/000726), three FPI-MEC predoctoral fellowships to CA, LM and VGR, the Subprograma de Técnicos de Apoyo MICINN (PTA2009-1782-I), a MECD postdoctoral grant E-28- 2012-0934030 to CA and a EU Marie Curie fellowship (FP7- 2011-IEF-300825) to LM.

This letter evaluates the biomass-retrieval error in pine-dominated stands when using high-spatial-resolution airborne measurements from fully polarimetric L-band radar and airborne laser scanning sensors. Information on total above-ground biomass was estimated through allometric relationships from plot-level field measurements. Multiple-linear-regression models were developed to model relationships between biomass and radar/lidar data. Overall, lidar data provided lower estimation errors (17.2 t·ha-1, 28% relative) when compared with radar data (30.3 t·ha-1, 61% relative). However, for the 30-100 t·ha-1 biomass range, the relative error from radar-based models was only 9% higher than that from lidar-based models. This suggests that high-spatial-resolution radar data could provide fundamentally similar results to lidar for some biomass intervals. This is an important finding for large-scale biomass estimation that needs to rely upon satellite data, as there are no lidar satellites planned for the foreseeable future.

Fully polarimetric C- and L-band synthetic aperture radar (SAR) data have been investigated to determine the relationship between polarimetric target decomposition components and forest burn severity over two sites located in a Mediterranean environment. The dependence of the polarimetric decomposition metrics on SAR acquisition geometry and environmental conditions was also analyzed at C-band. Multiple linear regression models with interactions (i.e., the incidence angle was included as a predictor variable and its interaction with the radar metrics was accounted for as a multiplicative effect) were used to quantify burn severity retrieval accuracy. According to our experiment, we found that for steep SAR acquisition geometries C-band polarimetric components related to surface scattering mechanisms had increased sensitivity to burn severity levels, while for datasets acquired with more grazing geometries the polarimetric components related to volume scattering and dihedral scattering mechanisms were more correlated with burn severity levels. At L-band only volume and dihedral scattering related decomposition components provided significant relationships with burn severity levels. Relatively low burn severity estimation errors (less than 20% of burn severity range) were obtained for all datasets, with L-band data presenting the highest sensitivity to fire effects. Using a single regression model provided sufficient accuracy for burn severity estimation when taking into account the local incidence angle. The use of fully polarimetric data improved the estimation accuracy of forest burn severity with respect to backscatter intensities by a small margin for our study sites. However, since backscatter intensity metrics already provide high retrieval accuracies, whatever improvement was bound to be low.