The importance of rare species: a trait‐based assessment of rare species contributions to functional diversity and possible ecosystem function in tall‐grass prairies

The majority of species in ecosystems are rare, but the ecosystem consequences of losing rare species are poorly known. To understand how rare species may influence ecosystem functioning, this study quantifies the contribution of species based on their relative level of rarity to community functional diversity using a trait‐based approach. Given that rarity can be defined in several different ways, we use four different definitions of rarity: abundance (mean and maximum), geographic range, and habitat specificity. We find that rarer species contribute to functional diversity when rarity is defined by maximum abundance, geographic range, and habitat specificity. However, rarer species are functionally redundant when rarity is defined by mean abundance. Furthermore, when using abundance‐weighted analyses, we find that rare species typically contribute significantly less to functional diversity than common species due to their low abundances. These results suggest that rare species have the potential to play an important role in ecosystem functioning, either by offering novel contributions to functional diversity or via functional redundancy depending on how rare species are defined. Yet, these contributions are likely to be greatest if the abundance of rare species increases due to environmental change. We argue that given the paucity of data on rare species, understanding the contribution of rare species to community functional diversity is an important first step to understanding the potential role of rare species in ecosystem functioning.     

Quantifying the effects of ecological constraints on trait expression using novel trait‐gradient analysis parameters

Complex processes related to biotic and abiotic forces can impose limitations to assembly and composition of plant communities. Quantifying the effects of these constraints on plant functional traits across environmental gradients, and among communities, remains challenging. We define ecological constraint (C_i) as the combined, limiting effect of biotic interactions and environmental filtering on trait expression (i.e., the mean value and range of functional traits). Here, we propose a set of novel parameters to quantify this constraint by extending the trait‐gradient analysis (TGA) methodology. The key parameter is ecological constraint, which is dimensionless and can be measured at various scales, for example, on population and community levels. It facilitates comparing the effects of ecological constraints on trait expressions across environmental gradients, as well as within and among communities. We illustrate the implementation of the proposed parameters using the bark thickness of 14 woody species along an aridity gradient on granite outcrops in southwestern Australia. We found a positive correlation between increasing environmental stress and strength of ecological constraint on bark thickness expression. Also, plants from more stressful habitats (shrublands on shallow soils and in sun‐exposed locations) displayed higher ecological constraint for bark thickness than plants in more benign habitats (woodlands on deep soils and in sheltered locations). The relative ease of calculation and dimensionless nature of C_i allow it to be readily implemented at various scales and make it widely applicable. It therefore has the potential to advance the mechanistic understanding of the ecological processes shaping trait expression. Some future applications of the new parameters could be investigating the patterns of ecological constraints (1) among communities from different regions, (2) on different traits across similar environmental gradients, and (3) for the same trait across different gradient types.     

A trait‐based approach reveals the feeding selectivity of a small endangered Mediterranean fish

Functional traits are growing in popularity in modern ecology, but feeding studies remain primarily rooted in a taxonomic‐based perspective. However, consumers do not have any reason to select their prey using a taxonomic criterion, and prey assemblages are variable in space and time, which makes taxon‐based studies assemblage‐specific. To illustrate the benefits of the trait‐based approach to assessing food choice, we studied the feeding ecology of the endangered freshwater fish Barbus meridionalis. We hypothesized that B. meridionalis is a selective predator which food choice depends on several prey morphological and behavioral traits, and thus, its top‐down pressure may lead to changes in the functional composition of in‐stream macroinvertebrate communities. Feeding selectivity was inferred by comparing taxonomic and functional composition (13 traits) between ingested and free‐living potential prey using the Jacob's electivity index. Our results showed that the fish diet was influenced by 10 of the 13 traits tested. Barbus meridionalis preferred prey with a potential size of 5–10 mm, with a medium–high drift tendency, and that drift during daylight. Potential prey with no body flexibility, conical shape, concealment traits (presence of nets and/or cases, or patterned coloration), and high aggregation tendency had a low predation risk. Similarly, surface swimmers and interstitial taxa were low vulnerable to predation. Feeding selectivity altered the functional composition of the macroinvertebrate communities. Fish absence favored taxa with weak aggregation tendency, weak flexibility, and a relatively large size (10–20 mm of potential size). Besides, predatory invertebrates may increase in fish absence. In conclusion, our study shows that the incorporation of the trait‐based approach in diet studies is a promising avenue to improve our mechanistic understanding of predator–prey interactions and to help predict the ecological outcomes of predator invasions and extinctions.     

Different roles of elevational and local environmental factors on abundance‐based beta diversity of the soil Enchytraeidae on the Changbai Mountain

The elevational alpha biodiversity gradient in mountain regions is one of the well‐known ecological patterns, but its beta diversity pattern remains poorly known. Examining the beta diversity and its components could enhance the understanding of community assembly mechanism. We studied the beta diversity pattern of the soil enchytraeids along a distinct elevational gradient (705–2,280 m) on the Changbai Mountain, the best‐preserved mountain in northeastern China. The overall abundance‐based community dissimilarity was relatively high (ca. 0.70), largely due to the balanced‐variation component (85%). The overall dissimilarity and its balanced‐variation (substitution) component were related to both local environmental heterogeneity and elevational distance, with the environmental relationships being stronger. In contrast, the abundance‐gradient (subsets) component was not related to the two gradients. The same important spatial and environmental variables were detected in structuring overall dissimilarity and substitution component, different from that in subsets component. Variation partitioning analysis showed that environmental control played a more important role than spatial (vertical and horizontal) factors in structuring the patterns of overall beta diversity and its two components. The predictive power of multivariate analysis was higher for the substitution component (nearly 50%) and overall dissimilarity (35%), but much lower for subsets components (<4%). These findings implied that abundance‐based beta diversity patterns of the soil enchytraeids were the results of different ecological processes (e.g., environmental sorting and dispersal limitation), operating in the two antithetic components. Our study showed the substitution and loss of individuals reflecting different ecological processes and highlights the importance of partitioning beta diversity in assessing biodiversity patterns and their causes.     

A new type of 3‐D peripheral ultrastructure in Glaucocystis (Glaucocystales,Glaucophyta) as revealed by ultra‐high voltage electron microscopy

The coccoid glaucophyte genus Glaucocystis is characterized by having a thick cell wall, which has to date prohibited examination of the native ultrastructural features of the protoplast periphery. Recently, however, the three‐dimensional (3‐D) ultrastructure of the protoplast periphery was revealed in two divergent Glaucocystis species, with the world's most powerful ultra‐high voltage electron microscope (UHVEM). The two species exhibit morphological diversity in terms of their 3‐D ultrastructural features. However, these two types do not seem to encompass actual ultrastructural diversity in the genetically diverse genus Glaucocystis. Here, we report a new type of peripheral 3‐D ultrastructure resolved in “G. incrassata” SAG 229‐2 cells by 3‐D modeling based on UHVEM tomography using high‐pressure freezing and freeze‐substitution fixation. The plasma membrane and underlying flattened vesicles in “G. incrassata” SAG 229‐2 exhibited grooves at intervals of 200–600 nm, and the flattened vesicles often overlapped one another at the protoplast periphery. This 3‐D ultrastructure differs from those of the two types previously reported in other species of Glaucocystis. The possibility of classification of Glaucocystis species based on the 3‐D ultrastructure of the protoplast periphery is discussed.     

An approach based on the total‐species accumulation curve and higher taxon richness to estimate realistic upper limits in regional species richness

Most of accumulation curves tend to underestimate species richness, as they do not consider spatial heterogeneity in species distribution, or are structured to provide lower bound estimates and limited extrapolations. The total‐species (T–S) curve allows extrapolations over large areas while taking into account spatial heterogeneity, making this estimator more prone to attempt upper bound estimates of regional species richness. However, the T–S curve may overestimate species richness due to (1) the mismatch among the spatial units used in the accumulation model and the actual units of variation in β‐diversity across the region, (2) small‐scale patchiness, and/or (3) patterns of rarity of species. We propose a new framework allowing the T–S curve to limit overestimation and give an application to a large dataset of marine mollusks spanning over 11 km² of subtidal bottom (W Mediterranean). As accumulation patterns are closely related across the taxonomic hierarchy up to family level, improvements of the T–S curve leading to more realistic estimates of family richness, that is, not exceeding the maximum number of known families potentially present in the area, can be considered as conducive to more realistic estimates of species richness. Results on real data showed that improvements of the T–S curve to accounts for true variations in β‐diversity within the sampled areas, small‐scale patchiness, and rarity of families led to the most plausible richness when all aspects were considered in the model. Data on simulated communities indicated that in the presence of high heterogeneity, and when the proportion of rare species was not excessive (>2/3), the procedure led to almost unbiased estimates. Our findings highlighted the central role of variations in β‐diversity within the region when attempting to estimate species richness, providing a general framework exploiting the properties of the T–S curve and known family richness to estimate plausible upper bounds in γ‐diversity.     

What does species richness tell us about functional trait diversity? Predictions and evidence for responses of species and functional trait diversity to land‐use change

In the conservation literature on land‐use change, it is often assumed that land‐use intensification drives species loss, driving a loss of functional trait diversity and ecosystem function. Modern research, however, does not support this cascade of loss for all natural systems. In this paper we explore the errors in this assumption and present a conceptual model taking a more mechanistic approach to the species–functional trait association in a context of land‐use change. We provide empirical support for our model's predictions demonstrating that the association of species and functional trait diversity follows various trajectories in response to land‐use change. The central premise of our model is that land‐use change impacts upon processes of community assembly, not species per se. From the model, it is clear that community context (i.e. type of disturbance, species pool size) will affect the response trajectory of the relationship between species and functional trait diversity in communities undergoing land‐use change. The maintenance of ecosystem function and of species diversity in the face of increasing land‐use change are complementary goals. The use of a more ecologically realistic model of responses of species and functional traits will improve our ability to make wise management decisions to achieve both aims in specific at‐risk systems.     

Invasive plants in Minnesota are “joining the locals”: A trait‐based analysis

Questions

Predicting which newly arrived species will establish and become invasive is a problem that has long vexed researchers. In a study of cold temperate oak forest stands, we examined two contrasting hypotheses regarding plant functional traits to explain the success of certain non‐native species. Under the “join the locals” hypothesis, successful invaders are expected to share traits with resident species because they employ successful growth strategies under light‐limited understorey conditions. Instead, under the “try harder” hypothesis, successful invaders are expected to have traits different from native species in order to take advantage of unused niche space.

Location

Minnesota, USA.

Methods

We examined these two theories using 109 native and 11 non‐native plants in 68 oak forest stands. We focused on traits related to plant establishment and growth, including specific leaf area (SLA), leaf carbon‐to‐nitrogen ratio (C:N), wood density, plant maximum height, mycorrhizal type, seed mass and growth form. We compared traits of native and non‐native species using ordinations in multidimensional trait space and compared community‐weighted mean (CWM) trait values across sites.

Results

We found few differences between trait spaces occupied by native and non‐native species. Non‐native species occupied smaller areas of trait space than natives, yet were within that of the native species, indicating similar growth strategies. We observed a higher proportion of non‐native species in sites with higher native woody species CWM SLA and lower CWM C:N. Higher woody CWM SLA was observed in sites with higher soil pH, while lower CWM C:N was found in sites with higher light levels.

Conclusions

Non‐native plants in this system have functional traits similar to natives and are therefore “joining the locals.” However, non‐native plants may possess traits toward the acquisitive end of the native plant trait range, as evidenced by higher non‐native plant abundance in high‐resource environments.

     

A compound‐based computational approach for the accurate determination of hot spots

A plethora of both experimental and computational methods have been proposed in the past 20 years for the identification of hot spots at a protein–protein interface. The experimental determination of a protein–protein complex followed by alanine scanning mutagenesis, though able to determine hot spots with much precision, is expensive and has no guarantee of success while the accuracy of the current computational methods for hot‐spot identification remains low. Here, we present a novel structure‐based computational approach that accurately determines hot spots through docking into a set of proteins homologous to only one of the two interacting partners of a compound capable of disrupting the protein–protein interaction (PPI). This approach has been applied to identify the hot spots of human activin receptor type II (ActRII) critical for its binding toward Cripto‐I. The subsequent experimental confirmation of the computationally identified hot spots portends a potentially accurate method for hot‐spot determination in silico given a compound capable of disrupting the PPI in question. The hot spots of human ActRII first reported here may well become the focal points for the design of small molecule drugs that target the PPI. The determination of their interface may have significant biological implications in that it suggests that Cripto‐I plays an important role in both activin and nodal signal pathways.