3D-imaging technologies provide measurements of terrestrial and aquatic ecosystems’ structure, key for biodiversity studies. However, the practical use of these observations globally faces practical ...challenges. First, available 3D data are geographically biased, with significant gaps in the tropics. Second, no data source provides, by itself, global coverage at a suitable temporal recurrence. Thus, global monitoring initiatives, such as assessment of essential biodiversity variables (EBVs), will necessarily have to involve the combination of disparate data sets. We propose a standardized framework of ecosystem morphological traits – height, cover, and structural complexity – that could enable monitoring of globally consistent EBVs at regional scales, by flexibly integrating different information sources – satellites, aircrafts, drones, or ground data – allowing global biodiversity targets relating to ecosystem structure to be monitored and regularly reported.
3D-imaging data acquired from a variety of platforms have become critical for ecological and environmental management. However, the use of disparate information sources to produce comprehensive and standardized global products is hindered by a lack of harmonization and terminology around ecosystem structure.We propose a sensor- and platform-independent framework which effectively distils the wealth of 3D information into concise ecosystem morphological traits – height, cover, and structural complexity – easy to conceptualize by ecologists and conservation stakeholders lacking remote sensing background.The conceptual disaggregation of ecosystem structure would contribute to defining and monitoring essential biodiversity variables obtained from 3D imaging that can be used to inform progress towards the UN 2030 Sustainable Development Goals and other international policy targets.
Light is widely considered to be the most important factor limiting the performance of plants on the floors of forests and woodlands, but the roles of nutrient availability and water supply remain ...poorly defined. We seek to predict the types of forest in which root competition affects seedling performance, and the types of plants that respond most strongly to release from root competition. We then test our predictions by reviewing experiments in which tree seedlings and forest herbs are released from belowground competition, usually by cutting trenches to sever the roots of surrounding trees. First, we provide a worldwide review of changes in canopy form and fine-root mass along gradients of soil fertility and seasonal drought, keeping in mind the stages of forest development. Our review shows that penetration of light is least in forests on moist soils providing large amounts of major nutrients. The changes are far more complex than those considered by allocation models. Dry woodlands typically allow 20 times as much light to penetrate as do wet forests, but there is surprisingly little evidence that they have greater fine-root densities in the topsoil. Tropical rain forests on highly infertile soils have only slightly more open canopies than those on fertile soils, but much greater fine-root densities. Northern temperate forests on highly acidic peats and sandy soils are often dominated by early-successional, open-canopied conifers (generally pines), mostly as a result of recurrent fires, and transmit about five times as much light as surrounding deciduous forests. A review of trenching experiments shows that light alone limits seedling growth in forests on moist, nutrient-rich soils, but competition for belowground resources becomes important on infertile soils and in drier regions. Secondly, we consider how root competition alters species' shade tolerances. Shade-house experiments demonstrate that species differ markedly in the minimum irradiance at which they respond to nutrient addition, but there generally tends to be a sizable response at >5% daylight and little response in <2% daylight. There is some evidence that species that have high potential growth rates and that respond markedly to increased irradiance are also most responsive to nutrient addition in 2-3% daylight. T. Smith and M. Huston have hypothesized that species cannot tolerate both shade and drought; this appears to be the case for species that tolerate shade chiefly by maximizing leaf area. However, many shade-tolerant woody plants in tropical and mediterranean-climate forests have thick, tough, long-lived leaves and a relatively high allocation to roots, and these species are much more drought tolerant. A few studies indicate that root trenching allows species to persist in deeper shade than that in which they are normally found and allows species from mesic sites to invade more xeric sites. Usually, the impact of trenching on growth rate is much greater in gaps than in the understory. Finally, we discuss the ways in which life-form composition and population structure of plant communities are shaped by reduced water supply and reduced nutrient availability, emphasizing the inadequacy of models that consider the impact of "belowground resource availability" in a generic sense. Competition in a dry climate leads to widely spaced dominants, a lack of interstitial plants, high rates of seedling mortality in the understory, and a restriction of regeneration to patches where established matrix-forming plants have died. In contrast, vegetation on moist, infertile sites is characterized by closely packed, slender dominants, miniaturized interstitial plants, and slow rates of seedling growth in the understory, combined with relatively low rates of seedling mortality. Consequently, there is a continuum of sizes among the individuals of the dominant species, and a lack of reliance on gaps for establishment.
European forests have a prominent role in the global carbon cycle and an increase in carbon storage has been consistently reported during the twentieth century. Any further increase in forest carbon ...storage, however, could be hampered by increases in aridity and extreme climatic events. Here, we use forest inventory data to identify the relative importance of stand structure (stand basal area and mean d.b.h.), mean climate (water availability), and recent climate change (temperature and precipitation anomalies) on forest basal area change during the late twentieth century in three major European biomes. Using linear mixed-effects models we observed that stand structure, mean climate, and recent climatic change strongly interact to modulate basal area change. Although we observed a net increment in stand basal area during the late twentieth century, we found the highest basal area increments in forests with medium stand basal areas and small to medium-sized trees. Stand basal area increases correlated positively with water availability and were enhanced in warmer areas. Recent climatic warming caused an increase in stand basal area, but this increase was offset by water availability. Based on recent trends in basal area change, we conclude that the potential rate of aboveground carbon accumulation in European forests strongly depends on both stand structure and concomitant climate warming, adding weight to suggestions that European carbon stocks may saturate in the near future.
Boreal forest soils play an important role in the global carbon cycle by functioning as a large terrestrial carbon sink or source, and the alteration of fire regime through global change phenomena ...may influence this role. We studied a system of forested lake islands in the boreal zone of Sweden for which fire frequency increases with increasing island size. Large islands supported higher plant productivity and litter decomposition rates than did smaller ones, and, with increasing time since fire, litter decomposition rates were suppressed sooner than was ecosystem productivity. This contributes to greater carbon storage with increasing time since fire; for every century without a major fire, an additional 0.5 kilograms per square meter of carbon becomes stored in the humus.
Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations. Our ability to understand and predict changes in the forest ...carbon cycle--particularly net primary productivity and carbon storage--increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level and stand-level productivity can be explained, respectively, by increases in a tree's total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to undertand and model forest carbon dynamics, and have additional implications for theories of resource allocation and plant senescence.
Forest canopy structure is strongly influenced by environmental factors and disturbance, and in turn influences key ecosystem processes including productivity, evapotranspiration and habitat ...availability. In tropical forests increasingly modified by human activities, the interplay between environmental factors and disturbance legacies on forest canopy structure across landscapes is practically unexplored. We used airborne laser scanning (ALS) data to measure the canopy of old-growth and selectively logged peat swamp forest across a peat dome in Central Kalimantan, Indonesia, and quantified how canopy structure metrics varied with peat depth and under logging. Several million canopy gaps in different height cross-sections of the canopy were measured in 100 plots of 1 km2 spanning the peat dome, allowing us to describe canopy structure with seven metrics. Old-growth forest became shorter and had simpler vertical canopy profiles on deeper peat, consistent with previous work linking deep peat to stunted tree growth. Gap size frequency distributions (GSFDs) indicated fewer and smaller canopy gaps on the deeper peat (i.e. the scaling exponent of Pareto functions increased from 1.76 to 3.76 with peat depth). Areas subjected to concessionary logging until 2000, and illegal logging since then, had the same canopy top height as old-growth forest, indicating the persistence of some large trees, but mean canopy height was significantly reduced. With logging, the total area of canopy gaps increased and the GSFD scaling exponent was reduced. Logging effects were most evident on the deepest peat, where nutrient depletion and waterlogged conditions restrain tree growth and recovery. A tight relationship exists between canopy structure and peat depth gradient within the old-growth tropical peat swamp forest. This relationship breaks down after selective logging, with canopy structural recovery, as observed by ALS, modulated by environmental conditions. These findings improve our understanding of tropical peat swamp ecology and provide important insights for managers aiming to restore degraded forests.
•Flawed models may seem reliable if assessing MD, RMSD and R2 alone.•We promote using hypothesis tests in evaluating observed vs. predicted scatterplots.•Overfitting must be included in model ...evaluation and variable selection algorithms.•Assessing overfitting with cross-validation: better compare squares sums than R2.
The evaluation of accuracy is essential for assuring the reliability of ecological models. Usually, the accuracy of above-ground biomass (AGB) predictions obtained from remote sensing is assessed by the mean differences (MD), the root mean squared differences (RMSD), and the coefficient of determination (R2) between observed and predicted values. In this article we propose a more thorough analysis of accuracy, including a hypothesis test to evaluate the agreement between observed and predicted values, and an assessment of the degree of overfitting to the sample employed for model training. Using the estimation of forest AGB from LIDAR and spectral sensors as a case study, we compared alternative prediction and variable selection methods using several statistical measures to evaluate their accuracy. We showed that the hypothesis tests provide an objective method to infer the statistical significance of agreement. We also observed that overfitting can be assessed by comparing the inflation in residual sums of squares experienced when carrying out a cross-validation. Our results suggest that this method may be more effective than analysing the deflation in R2. We proved that overfitting needs to be specifically addressed since, in light of MD, RMSD and R2 alone, predictions may apparently seem reliable even in clearly unrealistic circumstances, for instance when including too many predictor variables. Moreover, Theil’s partial inequality coefficients, which are employed to resolve the proportions of the total errors due to the unexplained variance, the slope and the bias, may become useful to detect averaging effects common in remote sensing predictions of AGB. We concluded that statistical measures of accuracy, precision and agreement are necessary but insufficient for model evaluation. We therefore advocate for incorporating evaluation measures specifically devoted to testing observed-versus-predicted fit, and to assessing the degree of overfitting.
El Niño events generate periods of relatively low precipitation, low cloud cover and high temperature over the rainforests of Southeast Asia, but their impact on tree physiology remains poorly ...understood. Here we use remote sensing and functional trait approaches-commonly used to understand plant acclimation to environmental fluctuations-to evaluate rainforest responses to an El Niño event at a site in northern Borneo. Spaceborne measurements (i.e. normalised difference vegetation index calculated from Moderate Resolution Imaging Spectroradiometer data) show the rainforest canopy greened throughout 2015, coinciding with a strengthening of the El Niño event in Sabah, Malaysia, then lost greenness in early 2016, when the El Niño was at its peak. Leaf chemical and structural traits measured for mature leaves of 65 species (104 branches from 99 tree canopies), during and after this El Niño event revealed that chlorophyll and carotenoid concentrations were 35% higher in mid 2015 than in mid 2016. Foliar concentrations of the nutrients N, P, K and Mg did not vary, suggesting the mineralisation and transportation processes were unaffected by the El Niño event. Leaves contained more phenolics, tannins and cellulose but less Ca and lignin during the El Niño event, with concentration shifts varying strongly among species. These changes in functional traits were also apparent in hyperspectral reflectance data collected using a field spectrometer, particularly in the shortwave infrared region. Leaf-level acclimation and leaf turnover could have driven the trait changes observed. We argue that trees were not water limited in the initial phase of the El Niño event, and responded by flushing new leaves, seen in the canopy greening trend and higher pigment concentrations (associated with young leaves); we argue that high evaporative demand and depleted soil water eventually caused leaves to drop in 2016. However, further studies are needed to confirm these ideas. Time-series of vegetation dynamics obtained from space can only be understood if changes in functional traits, as well as the quantity of leaves in canopies, are monitored on the ground.
1 Angiosperm trees often dominate forests growing in resource-rich habitats, whereas conifers are generally restricted to less productive habitats. It has been suggested that conifers may be ...displaced by angiosperms except where competition is less intense, because conifer seedlings are inherently slow growing, and are outpaced by faster-growing angiosperm species. Here we investigate whether competition with ferns and deeply shading trees also contributes to a failure of conifers to regenerate in resource-rich habitats. 2 We examined how changes in soil nutrient availability and drainage affected vegetation along the retrogressive stages of a soil chronosequence in southern New Zealand. Vegetation composition shifted from angiosperm-tree dominance on 'recent' alluvial terraces (< 24 ky), via coniferous-tree dominance on older marine terraces (79-121 ky), to coniferous-shrub dominance on the oldest marine terraces (291 ky). Soil drainage deteriorated along the sequence, and N : P(leaves) and N : P(soil) indicate increasing P-limitation. Conifer species appear to be adapted to persistence on infertile and poorly drained soils. 3 The floor of the relatively fertile alluvial forests was deeply shaded (approximately 1% light transmission) by dense groves of tree-ferns and ground-ferns, and by large-leaved subcanopy trees. Few seedlings of any type were found on the forest floor, even in tree-fall gaps, and establishment was restricted to rotting logs and tree-fern trunks. Angiosperms were particularly successful at colonizing these raised surfaces. 4 Less shade was cast by the conifer-dominated forests on infertile marine terraces (approximately 5% light transmission), which lacked tall ferns. There were many opportunities for conifer establishment, with high seedling densities recorded on the forest floor and on logs. By contrast, angiosperm seedlings were mainly restricted to logs. 5 Our results suggest that several mechanisms act in concert to reduce regeneration opportunities for conifers in productive habitats. In particular, we suggest that tall ferns and deep shade are responsible for a restriction of regeneration opportunities in relatively productive forests in New Zealand, diminishing the opportunities for conifers to escape the competitive effects of fast-growing angiosperms. Thus 'crocodiles' may alter the outcome of the race between 'hares' and 'tortoises'.
The juvenile life stage is a crucial determinant of forest dynamics and a first indicator of changes to species' ranges under climate change. However, paucity of detailed re‐measurement data of ...seedlings, saplings and small trees means that their demography is not well understood at large scales, and rarely represented in forest models in detail. In this study we quantify the effects of climate and density dependence on recruitment and juvenile growth and mortality rates of thirteen species measured in the Spanish Forest Inventory. Single‐census sapling count data is used to constrain demographic parameters of a simple forest juvenile dynamics model based on the perfect plasticity approximation model (PPA) within a likelihood‐free parameterisation method, Approximate Bayesian Computation. Our results highlight marked differences between species, and the important role of climate and stand structure, in controlling juvenile dynamics. Recruitment had a hump‐shaped relationship with conspecific density, and for most species conspecific competition had a stronger negative effect than heterospecific competition. Mediterranean species showed on average higher mortality and lower growth rates than temperate species, and in low density stands recruitment and mortality rates were positively correlated. Under climate change our model predicted declines in recruitment rates for almost all species. Reliable predictive models of forest dynamics should include realistic representation of critical early life‐stage processes and our approach demonstrates that existing coarse count data can be used to parameterise such models. Approximate Bayesian Computation may have wide application in many fields of ecology to unlock information about past processes from single survey observations.
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