Nadja Rüger

The global spectrum of plant form and function

Earth is home to a remarkable diversity of plant forms and life histories, yet comparatively few essential trait combinations have proved evolutionarily viable in today’s terrestrial biosphere. By analysing worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled, we found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs. Three-quarters of trait variation is captured in a two-dimensional global spectrum of plant form and function. One major dimension within this plane reflects the size of whole plants and their parts; the other represents the leaf economics spectrum, which balances leaf construction costs against growth potential. The global plant trait spectrum provides a backdrop for elucidating constraints on evolution, for functionally qualifying species and ecosystems, and for improving models that predict future vegetation based on continuous variation in plant form and function.

Rate of tree carbon accumulation increases continuously with tree size

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.

Functional traits explain light and size response of growth rates in tropical tree species

Relationships between functional traits and average or potential demographic rates have provided insight into the functional constraints and trade-offs underlying life-history strategies of tropical tree species. We have extended this framework by decomposing growth rates of -130 000 trees of 171 Neotropical tree species into intrinsic growth and the response of growth to light and size. We related these growth characteristics to multiple functional traits (wood density, adult stature, seed mass, leaf traits) in a hierarchical Bayesian model that accounted for measurement error and intraspecific variability of functional traits. Wood density was the most important trait determining all three growth characteristics. Intrinsic growth rates were additionally strongly related to adult stature, while all traits contributed to light response. Our analysis yielded a predictive model that allows estimation of growth characteristics for rare species on the basis of a few easily measurable morphological traits.

Toward Integrated Analysis of Human Impacts on Forest Biodiversity: Lessons from Latin America

Although sustainable forest management (SFM) has been widely adopted as a policy and management goal, high rates of forest loss and degradation are still occurring in many areas. Human activities such as logging, livestock husbandry, crop cultivation, infrastructural development, and use of fire are causing widespread loss of biodiversity, restricting progress toward SFM. In such situations, there is an urgent need for tools that can provide an integrated assessment of human impacts on forest biodiversity and that can support decision making related to forest use. This paper summarizes the experience gained by an international collaborative research effort spanning more than a decade, focusing on the tropical montane forests of Mexico and the temperate rain forests of southern South America, both of which are global conservation priorities. The lessons learned from this research are identified, specifically in relation to developing an integrated modeling framework for achieving SFM. Experience has highlighted a number of challenges that need to be overcome in such areas, including the lack of information regarding ecological processes and species characteristics and a lack of forest inventory data, which hinders model parameterization. Quantitative models are poorly developed for some ecological phenomena, such as edge effects and genetic diversity, limiting model integration. Establishment of participatory approaches to forest management is difficult, as a supportive institutional and policy environment is often lacking. However, experience to date suggests that the modeling toolkit approach suggested by Sturvetant et al. (2008) could be of value in such areas. Suggestions are made regarding desirable elements of such a toolkit to support participatory-research approaches in domains characterized by high uncertainty, including Bayesian Belief Networks, spatial multi-criteria analysis, and scenario planning.

Growth Strategies of Tropical Tree Species: Disentangling Light and Size Effects

An understanding of the drivers of tree growth at the species level is required to predict likely changes of carbon stocks and biodiversity when environmental conditions change. Especially in species-rich tropical forests, it is largely unknown how species differ in their response of growth to resource availability and individual size. We use a hierarchical Bayesian approach to quantify the impact of light availability and tree diameter on growth of 274 woody species in a 50-ha long-term forest census plot in Barro Colorado Island, Panama. Light reaching each individual tree was estimated from yearly vertical censuses of canopy density. The hierarchical Bayesian approach allowed accounting for different sources of error, such as negative growth observations, and including rare species correctly weighted by their abundance. All species grew faster at higher light. Exponents of a power function relating growth to light were mostly between 0 and 1. This indicates that nearly all species exhibit a decelerating increase of growth with light. In contrast, estimated growth rates at standardized conditions (5 cm dbh, 5% light) varied over a 9-fold range and reflect strong growth-strategy differentiation between the species. As a consequence, growth rankings of the species at low (2%) and high light (20%) were highly correlated. Rare species tended to grow faster and showed a greater sensitivity to light than abundant species. Overall, tree size was less important for growth than light and about half the species were predicted to grow faster in diameter when bigger or smaller, respectively. Together light availability and tree diameter only explained on average 12% of the variation in growth rates. Thus, other factors such as soil characteristics, herbivory, or pathogens may contribute considerably to shaping tree growth in the tropics.

Long-term impacts of fuelwood extraction on a tropical montane cloud forest.

Fuelwood extracted from natural forests serves as a principal energy source in rural regions of many tropical countries. Although fuelwood extraction (even low intensities) might strongly impact the structure and species composition of natural forests, long-term studies remain scarce. Here, we estimate the potential long-term impacts (over several hundred years) of such repeated harvesting of single trees on tropical montane cloud forest in central Veracruz, Mexico, by applying a process-based forest growth model. We simulate a wide range of possible harvesting scenarios differing in wood volume harvested and preferred tree species and sizes, and use a set of indicators to compare their impacts on forest size structure and community composition. Results showed that the overall impact on forest structure and community composition increased linearly with the amount of harvested wood volume. Even at low levels of harvesting, forest size structure became more homogeneous in the long term because large old trees disappeared from the forest, but these changes might take decades or even centuries. Although recruitment of harvested species benefited from harvesting, species composition shifted to tree species that are not used for fuelwood. Our results demonstrate that fuelwood extraction can have marked long-term impacts on tropical montane cloud forests. The results also offer the possibility to support the design of management strategies for the natural species-rich forests that achieve a balance between economic needs and ecological goals of the stakeholders.

Application of a GIS-based simulation tool to illustrate implications of uncertainties for water management in the Amudarya river delta

Abstract River basin management decisions have to be made under uncertainty. Relevant uncertainties especially in external driving forces can often not be sufficiently reduced. Rather than expecting to eliminate them, new management strategies should thus aim at taking them into account. Simulation tools can support a process of reasoning about the implications of uncertainties for the outcome of management policies in a specific river basin management context. Model supported scenario analysis of alternative strategies with authorities, managers and other stakeholders can assist in the development of new strategies. The tools provide factual knowledge on the outcome of policy options proposed as scenarios by the participants to the debate. The GIS-based simulation tool TUGAI has been developed to support assessment of the ecological effects of alternative water management strategies in the degraded Amudarya river delta. It combines a multi-objective water allocation model with simple models of landscape dynamics and a fuzzy based evaluation of habitat suitability for riverine Tugai forests. In this paper an example application of the tool for scenario analysis to illustrate the implications of uncertainty in future water supply to the delta area is demonstrated. Scenario analysis provides an assessment of the range and magnitude of the impact of those uncertainties on the ecological situation in the delta. The potential and limitations of applying simple simulation tools in participative settings for analysis and discussion of the potential impacts of uncertainties and development of cooping strategies are discussed.

Taking a closer look: disentangling effects of functional diversity on ecosystem functions with a trait-based model across hierarchy and time

Biodiversity and ecosystem functioning (BEF) research has progressed from the detection of relationships to elucidating their drivers and underlying mechanisms. In this context, replacing taxonomic predictors by trait-based measures of functional composition (FC)—bridging functions of species and of ecosystems—is a widely used approach. The inherent challenge of trait-based approaches is the multi-faceted, dynamic and hierarchical nature of trait influence: (i) traits may act via different facets of their distribution in a community, (ii) their influence may change over time and (iii) traits may influence processes at different levels of the natural hierarchy of organization. Here, we made use of the forest ecosystem model ‘LPJ-GUESS’ parametrized with empirical trait data, which creates output of individual performance, community assembly, stand-level states and processes. To address the three challenges, we resolved the dynamics of the top-level ecosystem function ‘annual biomass change’ hierarchically into its various component processes (growth, leaf and root turnover, recruitment and mortality) and states (stand structures, water stress) and traced the influence of different facets of FC along this hierarchy in a path analysis. We found an independent influence of functional richness, dissimilarity and identity on ecosystem states and processes and hence biomass change. Biodiversity effects were only positive during early succession and later turned negative. Unexpectedly, resource acquisition (growth, recruitment) and conservation (mortality, turnover) played an equally important role throughout the succession. These results add to a mechanistic understanding of biodiversity effects and place a caveat on simplistic approaches omitting hierarchical levels when analysing BEF relationships. They support the view that BEF relationships experience dramatic shifts over successional time that should be acknowledged in mechanistic theories.

Response of Demographic Rates of Tropical Trees to Light Availability: Can Position-Based Competition Indices Replace Information from Canopy Census Data?

For trees in tropical forests, competition for light is thought to be a central process that offers opportunities for niche differentiation through light gradient partitioning. In previous studies, a canopy index based on three-dimensional canopy census data has been shown to be a good predictor of species-specific demographic rates across the entire tree community on Barro Colorado Island, Panama, and has allowed quantifying between-species variation in light response. However, almost all other forest census plots lack data on the canopy structure. Hence, this study aims at assessing whether position-based neighborhood competition indices can replace information from canopy census data and produce similar estimates of the interspecific variation of light responses. We used inventory data from the census plot at Barro Colorado Island and calculated neighborhood competition indices with varying relative effects of the size and distance of neighboring trees. Among these indices, we selected the one that was most strongly correlated with the canopy index. We then compared outcomes of hierarchical Bayesian models for species-specific recruitment and growth rates including either the canopy index or the selected neighborhood competition index as predictor. Mean posterior estimates of light response parameters were highly correlated between models (r>0.85) and indicated that most species regenerate and grow better in higher light. Both light estimation approaches consistently found that the interspecific variation of light response was larger for recruitment than for growth rates. However, the classification of species into different groups of light response, e.g. weaker than linear (decelerating) vs. stronger than linear (accelerating) differed between approaches. These results imply that while the classification into light response groups might be biased when using neighborhood competition indices, they may be useful for determining species rankings and between-species variation of light response and therefore enable large comparative studies between different forest census plots.

Towards global data products of Essential Biodiversity Variables on species traits

Essential Biodiversity Variables (EBVs) allow observation and reporting of global biodiversity change, but a detailed framework for the empirical derivation of specific EBVs has yet to be developed. Here, we re-examine and refine the previous candidate set of species traits EBVs and show how traits related to phenology, morphology, reproduction, physiology and movement can contribute to EBV operationalization. The selected EBVs express intra-specific trait variation and allow monitoring of how organisms respond to global change. We evaluate the societal relevance of species traits EBVs for policy targets and demonstrate how open, interoperable and machine-readable trait data enable the building of EBV data products. We outline collection methods, meta(data) standardization, reproducible workflows, semantic tools and licence requirements for producing species traits EBVs. An operationalization is critical for assessing progress towards biodiversity conservation and sustainable development goals and has wide implications for data-intensive science in ecology, biogeography, conservation and Earth observation.Essential Biodiversity Variables (EBVs) are intended to provide standardized measurements for reporting biodiversity change. Here, the authors outline the conceptual and empirical basis for the use of EBVs based on species traits, and highlight tools necessary for creating comprehensive EBV data products.