Differences in forest plant functional trait distributions across land-use and productivity gradients

Stochastic disturbance regimes alter patterns of ecosystem variability and recovery

Altered ecosystem variability is an important ecological response to disturbance yet understanding of how various attributes of disturbance regimes affect ecosystem variability is limited. To improve the framework for understanding the disturbance regime attributes that affect ecosystem variability, we examine how the introduction of stochasticity to disturbance parameters (frequency, severity and extent) alters simulated recovery when compared to deterministic outcomes from a spatially explicit simulation model. We also examine the agreement between results from empirical studies and deterministic and stochastic configurations of the model. We find that stochasticity in disturbance frequency and spatial extent leads to the greatest increase in the variance of simulated dynamics, although stochastic severity also contributes to departures from the deterministic case. The incorporation of stochasticity in disturbance attributes improves agreement between empirical and simulated responses, with 71% of empirical responses correctly classified by stochastic configurations of the model as compared to 47% using the purely deterministic model. By comparison, only 2% of empirical responses were correctly classified by the deterministic model and misclassified by stochastic configurations of the model. These results indicate that stochasticity in the attributes of a disturbance regime alters the patterns and classification of ecosystem variability, suggesting altered recovery dynamics. Incorporating stochastic disturbance processes into models may thus be critical for anticipating the ecological resilience of ecosystems.

Forest bees are replaced in agricultural and urban landscapes by native species with different phenologies and life-history traits

Anthropogenic landscapes are associated with biodiversity loss and large shifts in species composition and traits. These changes predict the identities of winners and losers of future global change, and also reveal which environmental variables drive a taxon's response to land use change. We explored how the biodiversity of native bee species changes across forested, agricultural, and urban landscapes. We collected bee community data from 36 sites across a 75,000 km² region, and analyzed bee abundance, species richness, composition, and life-history traits. Season-long bee abundance and richness were not detectably different between natural and anthropogenic landscapes, but community phenologies differed strongly, with an early spring peak followed by decline in forests, and a more extended summer season in agricultural and urban habitats. Bee community composition differed significantly between all three land use types, as did phylogenetic composition. Anthropogenic land use had negative effects on the persistence of several life-history strategies, including early spring flight season and brood parasitism, which may indicate adaptation to conditions in forest habitat. Overall, anthropogenic communities are not diminished subsets of contemporary natural communities. Rather, forest species do not persist in anthropogenic habitats, but are replaced by different native species and phylogenetic lineages preadapted to open habitats. Characterizing compositional and functional differences is crucial for understanding land use as a global change driver across large regional scales.

Functional importance of sacred forest patches in the altered landscape of Palakkad region, Kerala, India

The role of sacred forest patches in maintaining biodiversity and offering ecosystem services is well established, though the functional aspects are understated. This study aims to understand the functional diversity of tree reproductive traits of sacred forest patches in an altered landscape. Twenty-five sacred groves in Palakkad region, Kerala, India, were chosen to assess the distribution of five reproductive traits – pollination mechanism, fruit size, seed number, seed size and dispersal mechanism – among the tree populations. The data matrix was analysed for overall trait-state distribution, functional diversity assessment and its relation to environmental parameters and disturbance in the area. A total of 87 woody species was documented with a fairly homogenized distribution of fruit and seed characters, with ≥50% of the recorded trait states in each grove in comparison to control plot. Pollination and dispersal mechanisms are dominated by a single guild. e.g. insects and birds, often generalist in nature. Functional richness had a strong correlation with Shannon's index and disturbance, but evenness and divergence were weakly related with others. Comparative assessment with null model showed no significant deviations from expected results indicating apparent lack of habitat filtering or resource competition among sacred groves. The trait homogenization and overall simplification of the grove biota is perhaps an outcome of rapid land-use change and its consequences on specialist members. This study shows sacred groves are important for maintaining a plethora of functional traits in the altered landscape. However, the prevalence of generalist mediators indicates maintenance of basic ecological functions in the landscape without support for specialist ones.

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits

Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height. We tested our capacity to perform out-of-sample prediction of growth trajectories between ecosystems using species functional traits. We found strong trait-growth relationships in one of the datasets; whereby species with low SLA achieved the greatest asymptotic heights, species with high leaf-nitrogen content achieved relatively fast growth rates, and species with low seed mass reached their time of maximum growth early. However these same growth-trait relationships did not hold across the two other datasets, making accurate prediction from one dataset to another unachievable. We believe there is evidence to suggest that growth trajectories themselves may be fundamentally different between ecosystems and that trait-height-growth relationships may change over environmental gradients.

Scaling up functional traits for ecosystem services with remote sensing: concepts and methods

Ecosystem service‐based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot‐level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community‐weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.

Land-use intensification effects on functional properties in tropical plant communities

There is consensus that plant diversity and ecosystem processes are negatively affected by land-use intensification (LUI), but, at the same time, there is empirical evidence that a large heterogeneity can be found in the responses. This heterogeneity is especially poorly understood in tropical ecosystems. We evaluated changes in community functional properties across five common land-use types in the wet tropics with different land-use intensity: mature forest, logged forest, secondary forest, agricultural land, and pastureland, located in the lowlands of Bolivia. For the dominant plant species, we measured 12 functional response traits related to their life history, acquisition and conservation of resources, plant domestication, and breeding. We used three single-trait metrics to describe community functional properties: community abundance-weighted mean (CWM) traits values, coefficient of variation, and kurtosis of distribution. The CWM of all 12 traits clearly responded to LUI. Overall, we found that an increase in LUI resulted in communities dominated by plants with acquisitive leaf trait values. However, contrary to our expectations, secondary forests had more conservative trait values (i.e., lower specific leaf area) than mature and logged forest, probably because they were dominated by palm species. Functional variation peaked at intermediate land-use intensity (high coefficient of variation and low kurtosis), which included secondary forest but, unexpectedly, also agricultural land, which is an intensely managed system. The high functional variation of these systems is due to a combination of how response traits (and species) are filtered out by biophysical filters and how management practices introduced a range of exotic species and their trait values into the local species pool. Our results showed that, at local scales and depending on prevailing environmental and management practices, LUI does not necessarily result in communities with more acquisitive trait values or with less functional variation. Instead of the widely expected negative impacts of LUI on plant diversity, we found varying responses of functional variation, with possible repercussions on many ecosystem services. These findings provide a background for actively mitigating negative effects of LUI while meeting the needs of local communities that rely mainly on provisioning ecosystem services for their livelihoods.

Global effects of land use on local terrestrial biodiversity

Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

Identifying priority areas for conservation and management in diverse tropical forests

The high concentration of the world’s species in tropical forests endows these systems with particular importance for retaining global biodiversity, yet it also presents significant challenges for ecology and conservation science. The vast number of rare and yet to be discovered species restricts the applicability of species-level modelling for tropical forests, while the capacity of community classification approaches to identify priorities for conservation and management is also limited. Here we assessed the degree to which macroecological modelling can overcome shortfalls in our knowledge of biodiversity in tropical forests and help identify priority areas for their conservation and management. We used 527 plant community survey plots in the Australian Wet Tropics to generate models and predictions of species richness, compositional dissimilarity, and community composition for all the 4,313 vascular plant species recorded across the region (>1.3 million communities (grid cells)). We then applied these predictions to identify areas of tropical forest likely to contain the greatest concentration of species, rare species, endemic species and primitive angiosperm families. Synthesising these alternative attributes of diversity into a single index of conservation value, we identified two areas within the Australian wet tropics that should be a high priority for future conservation actions: the Atherton Tablelands and Daintree rainforest. Our findings demonstrate the value of macroecological modelling in identifying priority areas for conservation and management actions within highly diverse systems, such as tropical forests.

Botany and a changing world: introduction to the special issue on global biological change

The impacts of global change have heightened the need to understand how organisms respond to and influence these changes. Can we forecast how change at the global scale may lead to biological change? Can we identify systems, processes, and organisms that are most vulnerable to global changes? Can we use this understanding to enhance resilience to global changes? This special issue on global biological change emphasizes the integration of botanical information at different biological levels to gain perspective on the direct and indirect effects of global change. Contributions span a range of spatial scales and include both ecological and evolutionary timescales and highlight work across levels of organization, including cellular and physiological processes, individuals, populations, and ecosystems. Integrative botanical approaches to global change are critical for the ecological and evolutionary insights they provide and for the implications these studies have for species conservation and ecosystem management.