Using climatically based random forests to downscale coarse‐grained potential natural vegetation maps in tropical Mexico

Questions: Can the accuracy of coarse resolution potential vegetation maps be improved through downscaling to finer resolution climatic grids? Can output from random forests produce new insight into the climatic characteristics that are associated with the structural characteristics of the vegetation? Location: Southern Mexico. Methods: A potential vegetation map (National Atlas of Mexico) at a 1:4 000 000 scale, was downscaled to a 1 km² grid resolution using climatically based random forests models. The resulting map was then evaluated against 256 inventory plots sampled at the transition between different vegetation types in Southern Mexico. Results: Downscaling increased accuracy up to 0.40, as measured by the Kappa Index of Agreement. Multivariate analysis of the results allowed the association between Rzedowski's classification and climatic variation to be explored. This confirmed that many of the structural aspects of the vegetation that are used by the Rzedowski classification are closely associated with climate, but it also revealed weaknesses in the underlying basis of this classification system. Conclusions: Rzedowski's scheme for vegetation classification may require further modification in order to be an effective tool for research into vegetation–climate relationships.     

Drier tropical forests are susceptible to functional changes in response to a long‐term drought

Climatic changes have profound effects on the distribution of biodiversity, but untangling the links between climatic change and ecosystem functioning is challenging, particularly in high diversity systems such as tropical forests. Tropical forests may also show different responses to a changing climate, with baseline climatic conditions potentially inducing differences in the strength and timing of responses to droughts. Trait‐based approaches provide an opportunity to link functional composition, ecosystem function and environmental changes. We demonstrate the power of such approaches by presenting a novel analysis of long‐term responses of different tropical forest to climatic changes along a rainfall gradient. We explore how key ecosystem's biogeochemical properties have shifted over time as a consequence of multi‐decadal drying. Notably, we find that drier tropical forests have increased their deciduous species abundance and generally changed more functionally than forests growing in wetter conditions, suggesting an enhanced ability to adapt ecologically to a drying environment.     

南四湖沉水植物物种多样性和功能多样性对水深梯度的响应

从物种多样性和功能多样性探讨沉水植物群落对水深的响应可深刻揭示水深对群落构建的影响机制。以南四湖不同水深沉水植物群落为研究对象,对比分析了群落的9个加权功能性状（株高、茎分支数、茎节数、茎直径、根长、根围直径、生物量分配比、比叶面积、植物体磷含量）、5个物种多样性指数（Berger-Parker生态优势度指数、Margalef丰富度指数、Simpson多样性指数、Shannon-Wiener多样性指数和Pielou均匀度指数）和5个功能多样性指数（功能丰富度FRic指数、功能均匀度FEve指数、功能离散度FDiv指数、功能分散度FDis指数和二次熵Rao指数）以及物种多样性和功能多样性关系对水深的响应规律。研究结果表明：（1）水深可显著改变群落株高、根长、根围直径、比叶面积、生物量分配比和植物体磷含量6个加权功能性状;群落茎分支数、茎节数和茎直径3个加权功能性状对水深变化无显著响应;（2）水深可显著影响群落物种多样性和功能多样性,中等水深处沉水植物群落具有较高的Margalef丰富度指数、Shannon-Wiener多样性指数、Berger-Parker生态优势度指数、Pielou均匀度指数以及功能丰富度FRic指数、功能均匀度FEve指数、功能离散度FDis指数、二次熵Rao指数;（3）水深可改变5个物种多样性指数与功能丰富度FRic指数、功能均匀度FEve指数、功能离散度FDiv指数3个功能多样性指数间的相关关系,但对5个物种多样性指数与功能离散度FDis指数、二次熵Rao指数2个功能多样性指数间的相关关系无显著影响。研究结论为：群落不同测度的物种多样性和功能多样性指数及其相关关系对水深变化的响应迥异,在探讨水深对沉水植物群落构建的影响机制时应从多个方面综合考量。     

A large‐scale field assessment of carbon stocks in human‐modified tropical forests

Tropical rainforests store enormous amounts of carbon, the protection of which represents a vital component of efforts to mitigate global climate change. Currently, tropical forest conservation, science, policies, and climate mitigation actions focus predominantly on reducing carbon emissions from deforestation alone. However, every year vast areas of the humid tropics are disturbed by selective logging, understory fires, and habitat fragmentation. There is an urgent need to understand the effect of such disturbances on carbon stocks, and how stocks in disturbed forests compare to those found in undisturbed primary forests as well as in regenerating secondary forests. Here, we present the results of the largest field study to date on the impacts of human disturbances on above and belowground carbon stocks in tropical forests. Live vegetation, the largest carbon pool, was extremely sensitive to disturbance: forests that experienced both selective logging and understory fires stored, on average, 40% less aboveground carbon than undisturbed forests and were structurally similar to secondary forests. Edge effects also played an important role in explaining variability in aboveground carbon stocks of disturbed forests. Results indicate a potential rapid recovery of the dead wood and litter carbon pools, while soil stocks (0–30 cm) appeared to be resistant to the effects of logging and fire. Carbon loss and subsequent emissions due to human disturbances remain largely unaccounted for in greenhouse gas inventories, but by comparing our estimates of depleted carbon stocks in disturbed forests with Brazilian government assessments of the total forest area annually disturbed in the Amazon, we show that these emissions could represent up to 40% of the carbon loss from deforestation in the region. We conclude that conservation programs aiming to ensure the long‐term permanence of forest carbon stocks, such as REDD+, will remain limited in their success unless they effectively avoid degradation as well as deforestation.     

Recovery of mammal diversity in tropical forests: a functional approach to measuring restoration

Ecological restoration is increasingly applied in tropical forests to mitigate biodiversity loss and recover ecosystem functions. In restoration ecology, functional richness, rather than species richness, often determines community assembly, and measures of functional diversity provide a mechanistic link between diversity and ecological functioning of restored habitat. Vertebrate animals are important for ecosystem functioning. Here, we examine the functional diversity of small‐to‐medium sized mammals to evaluate the diversity and functional recovery of tropical rainforest. We assess how mammal species diversity and composition and functional diversity and composition, vary along a restoration chronosequence from degraded pasture to “old‐growth” tropical rainforest in the Wet Tropics of Australia. Species richness, diversity, evenness, and abundance did not vary, but total mammal biomass and mean species body mass increased with restoration age. Species composition in restoration forests converged on the composition of old‐growth rainforest and diverged from pasture with increasing restoration age. Functional metrics provided a clearer pattern of recovery than traditional species metrics, with most functional metrics significantly increasing with restoration age when taxonomic‐based metrics did not. Functional evenness and dispersion increased significantly with restoration age, suggesting that niche complementarity enhances species' abundances in restored sites. The change in community composition represented a functional shift from invasive, herbivorous, terrestrial habitat generalists and open environment specialists in pasture and young restoration sites, to predominantly endemic, folivorous, arboreal, and fossorial forest species in older restoration sites. This shift has positive implications for conservation and demonstrates the potential of tropical forest restoration to recover rainforest‐like, diverse faunal communities.     

Groundwater drawdown drives ecophysiological adjustments of woody vegetation in a semi‐arid coastal ecosystem

Predicted droughts and anthropogenic water use will increase groundwater lowering rates and intensify groundwater limitation, particularly for Mediterranean semi‐arid ecosystems. These hydrological changes may be expected to elicit differential functional responses of vegetation either belowground or aboveground. Yet, our ability to predict the impacts of groundwater changes on these ecosystems is still poor. Thus, we sought to better understand the impact of falling water table on the physiology of woody vegetation. We specifically ask (a) how is woody vegetation ecophysiological performance affected by water table depth during the dry season? and (b) does the vegetation response to increasing depth to groundwater differ among water‐use functional types? We examined a suite of physiological parameters and water‐uptake depths of the dominant, functionally distinct woody vegetation along a water‐table depth gradient in a Mediterranean semi‐arid coastal ecosystem that is currently experiencing anthropogenic groundwater extraction pressure. We found that groundwater drawdown did negatively affect the ecophysiological performance of the woody vegetation. Across all studied environmental factors, depth to groundwater was the most important driver of ecophysiological adjustments. Plant functional types, independent of groundwater dependence, showed consistent declines in water content and generally reduced C and N acquisition with increasing depths to groundwater. Functional types showed distinct operating physiological ranges, but common physiological sensitivity to greater water table depth. Thus, although differences in water‐source use exist, a physiological convergence appeared to happen among different functional types. These results strongly suggest that hydrological drought has an important impact on fundamental physiological processes, constraining the performance of woody vegetation under semi‐arid conditions. By disentangling the functional responses and vulnerability of woody vegetation to groundwater limitation, our study establishes the basis for predicting the physiological responses of woody vegetation in semi‐arid coastal ecosystems to groundwater drawdown.     

Monitoring LITT thermal penetration depth using real‐time analysis of backscattered light

Real‐time monitoring of the thermal penetration depth (TPD) is essential in various clinical procedures, such as Laser Interstitial Thermal Therapy (LITT). MRI is commonly used to this end, though bulky and expensive. In this paper, we present an alternative novel method for an optical feedback system based on changes in the diffused reflection from the tissue during treatment. Monte‐Carlo simulation was used to deduce the relations between the backscattered pattern and the TPD. Several methods of image analysis are developed for TPD estimation. Each yields a set of parameters which are linearly dependent on the TPD. In order to test these experimentally, tissue samples were monitored in‐vitro during treatment at multiple wavelengths. The SNR and coefficient of determination were used to compare the various methods and wavelengths and to determine the preferred method. Such system and algorithms may be used for real‐time in‐vivo control during laser thermotherapy and other clinical procedures. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The effects of plantation practice on soil properties based on the comparison between natural and planted forests: a meta‐analysis

Aim The effects of planted forests on soils are of great concern in the context of the increasing demands for timber production and atmospheric CO₂ sequestration. However, the effects of plantations on soil properties have not well been quantified. We determined the effects of plantation practice on soil properties based on a comparison between natural forests and plantations. Locations All the continents except for Antarctica. Methods The meta‐analysis approach was used to examine the differences in 14 soil variables in the mineral layer, including pH, bulk density, C, N, P, K, Ca, Mg, Na and Al concentrations, C/N ratio, cation exchangeable capacity, base saturation, and moisture between plantations and their adjacent natural forests from 73 published studies. Results Plantations did not differ from natural forests in soil pH or soil Na and Al concentrations. Soil bulk density below plantations increased by 12.5%, and soil C and N concentrations decreased by 36.0% and 26.5%, respectively, relative to natural forests. The other eight variables were 8.4–30.6% lower in plantations than in natural forests. The general patterns also held true for planted trees from the genus Pinus and for study regions in China. The patterns for soil bulk density and C and N concentrations were not different between the two groups in relation to various factors: stand age (< 25 years versus ≥ 25 years), leaf form (broadleaved versus coniferous) and leaf seasonality (deciduous versus evergreen), tree species origin (native versus exotic), land‐use history (afforestation versus reforestation) and site preparation for plantations (burnt versus un‐burnt treatment), and biogeographic zone (tropical versus temperate). Main conclusions Our results suggest that the level of soil fertility in plantations is unlikely to restore to the level in natural forests, implying that the replacement of natural forests by plantations may be a practice best avoided to maintain the ecosystem sustainability.     

Predicting alpha diversity of African rain forests: models based on climate and satellite‐derived data do not perform better than a purely spatial model

Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods Alpha diversity estimates were compiled for trees with diameter at breast height ≥ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well‐sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances > 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity.     

Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis

The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite‐derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green‐up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green‐up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green‐up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green‐up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green‐up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature.     

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient

One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait‐spectra and individual‐based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon‐Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi‐mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale.     

Applying trait‐based models to achieve functional targets for theory‐driven ecological restoration

Manipulating community assemblages to achieve functional targets is a key component of restoring degraded ecosystems. The response‐and‐effect trait framework provides a conceptual foundation for translating restoration goals into functional trait targets, but a quantitative framework has been lacking for translating trait targets into assemblages of species that practitioners can actually manipulate. This study describes new trait‐based models that can be used to generate ranges of species abundances to test theories about which traits, which trait values and which species assemblages are most effective for achieving functional outcomes. These models are generalisable, flexible tools that can be widely applied across many terrestrial ecosystems. Examples illustrate how the framework generates assemblages of indigenous species to (1) achieve desired community responses by applying the theories of environmental filtering, limiting similarity and competitive hierarchies, or (2) achieve desired effects on ecosystem functions by applying the theories of mass ratios and niche complementarity. Experimental applications of this framework will advance our understanding of how to set functional trait targets to achieve the desired restoration goals. A trait‐based framework provides restoration ecology with a robust scaffold on which to apply fundamental ecological theory to maintain resilient and functioning ecosystems in a rapidly changing world.     

Predicting shifts in the functional composition of tropical forests under increased drought and CO2 from trade‐offs among plant hydraulic traits

Tropical forest responses are an important feedback on global change, but changes in forest composition with projected increases in CO₂ and drought are highly uncertain. Here we determine shifts in the most competitive plant hydraulic strategy (the evolutionary stable strategy or ESS) from changes in CO₂ and drought frequency and intensity. Hydraulic strategies were defined along a spectrum from drought avoidance to tolerance by physiology traits. Drought impacted competition more than CO₂, with elevated CO₂ reducing but not reversing drought‐induced shifts in the ESS towards more tolerant strategies. Trait plasticity and/or adaptation intensified these shifts by increasing the competitive ability of the drought tolerant relative to the avoidant strategies. These findings predict losses of drought avoidant evergreens from tropical forests under global change, and point to the importance of changes in precipitation during the dry season and constraints on plasticity and adaptation in xylem traits to forest responses.     

Plant functional diversity enhances associations of soil fungal diversity with vegetation and soil in the restoration of semiarid sandy grassland

The trait‐based approach shows that plant functional diversity strongly affects ecosystem properties. However, few empirical studies show the relationship between soil fungal diversity and plant functional diversity in natural ecosystems. We investigated soil fungal diversity along a restoration gradient of sandy grassland (mobile dune, semifixed dune, fixed dune, and grassland) in Horqin Sand Land, northern China, using the denaturing gradient gel electrophoresis of 18S rRNA and gene sequencing. We also examined associations of soil fungal diversity with plant functional diversity reflected by the dominant species' traits in community (community‐weighted mean, CWM) and the dispersion of functional trait values (FD_is). We further used the structure equation model (SEM) to evaluate how plant richness, biomass, functional diversity, and soil properties affect soil fungal diversity in sandy grassland restoration. Soil fungal richness in mobile dune and semifixed dune was markedly lower than those of fixed dune and grassland (P < 0.05). Soil fungal richness was positively associated with plant richness, biomass, CWM plant height, and soil gradient aggregated from the principal component analysis, but SEM results showed that plant richness and CWM plant height determined by soil properties were the main factors exerting direct effects. Soil gradient increased fungal richness through indirect effect on vegetation rather than direct effect. The negative indirect effect of FDis on soil fungal richness was through its effect on plant biomass. Our final SEM model based on plant functional diversity explained nearly 70% variances of soil fungal richness. Strong association of soil fungal richness with the dominant species in the community supported the mass ratio hypothesis. Our results clearly highlight the role of plant functional diversity in enhancing associations of soil fungal diversity with community structure and soil properties in sandy grassland ecosystems.