Phytodiversity is associated with habitat heterogeneity from Eurasia to the Hengduan Mountains

The geographic distribution of plant diversity matches the gradient of habitat heterogeneity from lowlands to mountain regions. However, little is known about how much this relationship is conserved across scales. Using the World Checklist of Vascular Plants and high-resolution biodiversity maps developed by species distribution models, we investigated the associations between species richness and habitat heterogeneity at the scales of Eurasia and the Hengduan Mountains (HDM) in China. Habitat heterogeneity explains seed plant species richness across Eurasia, but the plant species richness of 41/97 HDM families is even higher than expected from fitted statistical relationships. A habitat heterogeneity index combining growing degree days, site water balance, and bedrock type performs better than heterogeneity based on single variables in explaining species richness. In the HDM, the association between heterogeneity and species richness is stronger at larger scales. Our findings suggest that high environmental heterogeneity provides suitable conditions for the diversification of lineages in the HDM. Nevertheless, habitat heterogeneity alone cannot fully explain the distribution of species richness in the HDM, especially in the western HDM, and complementary mechanisms, such as the complex geological history of the region, may have contributed to shaping this exceptional biodiversity hotspot.

Plant chemical traits define functional and phylogenetic axes of plant biodiversity

To determine which types of plant traits might better explain ecosystem functioning and plant evolutionary histories, we compiled 42 traits for each of 15 perennial species in a biodiversity experiment. We used every possible combination of three traits to cluster species. Across these 11,480 combinations, clusters generated using tissue %Ca, %N and %K best mapped onto phylogeny. Moreover, for the 15 best combinations of three traits, 82% of traits were chemical, 16% morphological and 2% metabolic. The diversity-dependence of ecosystem productivity was better explained by the %Ca, %N and %K clusters: compared to adding a new species at random, adding a species from an absent cluster/clade better-explained gains in productivity. Species number impacted productivity only when all clusters were present. Our results suggest that tissue elemental chemistry might be more phylogenetically conserved and more strongly related to ecosystem functioning than commonly measured morphological and physiological traits, a possibility that merits exploration.

Scale-sensitivity in the measurement and interpretation of environmental niches

Species environmental niches are central to ecology, evolution, and global change research, but their characterization and interpretation depend on the spatial scale (specifically, the spatial grain) of their measurement. We find that the spatial grain of niche measurement is usually uninformed by ecological processes and varies by orders of magnitude. We illustrate the consequences of this variation for the volume, position, and shape of niche estimates, and discuss how it interacts with geographic range size, habitat specialization, and environmental heterogeneity. Spatial grain significantly affects the study of niche breadth, environmental suitability, niche evolution, niche tracking, and climate change effects. These and other fields will benefit from a more mechanism-informed choice of spatial grain and cross-grain evaluations that integrate different data sources.

Functional trait space and redundancy of plant communities decrease toward cold temperature at high altitudes in Southwest China

Plant communities in mountainous areas shift gradually as climatic conditions change with altitude. How trait structure in multivariate space adapts to these varying climates in natural forest stands is unclear. Studying the multivariate functional trait structure and redundancy of tree communities along altitude gradients is crucial to understanding how temperature change affects natural forest stands. In this study, the leaf area, specific leaf area, leaf carbon, nitrogen, and phosphorous content from 1,590 trees were collected and used to construct the functional trait space of 12 plant communities at altitudes ranging from 800 m to 3,800 m across three mountains. Hypervolume overlap was calculated to quantify species trait redundancy per community. First, hypervolumes of species exclusion and full species set were calculated, respectively. Second, the overlap between these two volumes was calculated to obtain hypervolume overlap. Results showed that the functional trait space significantly increased with mean annual temperature toward lower altitudes within and across three mountains, whereas species trait redundancy had different patterns between mountains. Thus, warming can widen functional trait space and alter the redundancy in plant communities. The inconsistent patterns of redundancy between mountains suggest that warming exerts varying influences on different ecosystems. Identification of climate-vulnerable ecosystems is important in the face of global warming.

High dimensionality of stoichiometric niches in soil fauna

The ecological niche is a fundamental concept to understand species coexistence in natural communities. The recently developed framework of the multidimensional stoichiometric niche (MSN) characterizes species niches using chemical elements in living organisms. Despite the fact that living organisms are composed by multiple elements, stoichiometric studies have so far mostly focused on carbon (C), nitrogen (N), and phosphorus (P), and therefore a quantitative analysis of the dimensionality of the MSN in living organisms is still lacking, particularly for animals. Here we quantified ten elements composing the biomass of nine soil animal taxa (958 individuals) from three trophic groups. We found that all ten elements exhibited large variation among taxa, which was partially explained by their phylogeny. Overlaps of MSNs among the nine soil animal taxa were relatively smaller based on ten elements, compared with those based on only C, N, and P. Discriminant analysis using all ten elements successfully differentiated among the nine taxa (accuracy: 90%), whereas that using only C, N, and P resulted in a lower accuracy (60%). Our findings provide new evidence for MSN differentiation in soil fauna and demonstrate the high dimensionality of organismal stoichiometric niches beyond C, N, and P.

A Landscape Epidemiological Approach for Predicting Chronic Wasting Disease: A Case Study in Virginia, US

Many infectious diseases in wildlife occur under quantifiable landscape ecological patterns useful in facilitating epidemiological surveillance and management, though little is known about prion diseases. Chronic wasting disease (CWD), a fatal prion disease of the deer family Cervidae, currently affects white-tailed deer (Odocoileus virginianus) populations in the Mid-Atlantic United States (US) and challenges wildlife veterinarians and disease ecologists from its unclear mechanisms and associations within landscapes, particularly in early phases of an outbreak when CWD detections are sparse. We aimed to provide guidance for wildlife disease management by identifying the extent to which CWD-positive cases can be reliably predicted from landscape conditions. Using the CWD outbreak in Virginia, US from 2009 to early 2020 as a case study system, we used diverse algorithms (e.g., principal components analysis, support vector machines, kernel density estimation) and data partitioning methods to quantify remotely sensed landscape conditions associated with CWD cases. We used various model evaluation tools (e.g., AUC ratios, cumulative binomial testing, Jaccard similarity) to assess predictions of disease transmission risk using independent CWD data. We further examined model variation in the context of uncertainty. We provided significant support that vegetation phenology data representing landscape conditions can predict and map CWD transmission risk. Model predictions improved when incorporating inferred home ranges instead of raw hunter-reported coordinates. Different data availability scenarios identified variation among models. By showing that CWD could be predicted and mapped, our project adds to the available tools for understanding the landscape ecology of CWD transmission risk in free-ranging populations and natural conditions. Our modeling framework and use of widely available landscape data foster replicability for other wildlife diseases and study areas.

The dimensionality and structure of species trait spaces

Trait-based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade-off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.

Leveraging multidimensional heterogeneity in resource selection to define movement tactics of animals

Increasing interest in the complexity, variation and drivers of movement-related behaviours promise new insight into fundamental components of ecology. Resolving the multidimensionality of spatially explicit behaviour remains a challenge for investigating tactics and their relation to niche construction, but high-resolution movement data are providing unprecedented understanding of the diversity of spatially explicit behaviours. We introduce a framework for investigating individual variation in movement-defined resource selection that integrates the behavioural and ecological niche concepts. We apply it to long-term tracking data of 115 African elephants (Loxodonta africana), illustrating how a behavioural hypervolume can be defined based on differences between individuals and their ecological settings, and applied to explore population heterogeneity. While normative movement behaviour is frequently used to characterise population behaviour, we demonstrate the value of leveraging heterogeneity in the behaviour to gain greater insight into population structure and the mechanisms driving space-use tactics.

Leveraging multidimensional heterogeneity in resource selection to define movement tactics of animals

Increasing interest in the complexity, variation and drivers of movement-related behaviours promise new insight into fundamental components of ecology. Resolving the multidimensionality of spatially explicit behaviour remains a challenge for investigating tactics and their relation to niche construction, but high-resolution movement data are providing unprecedented understanding of the diversity of spatially explicit behaviours. We introduce a framework for investigating individual variation in movement-defined resource selection that integrates the behavioural and ecological niche concepts. We apply it to long-term tracking data of 115 African elephants (Loxodonta africana), illustrating how a behavioural hypervolume can be defined based on differences between individuals and their ecological settings, and applied to explore population heterogeneity. While normative movement behaviour is frequently used to characterise population behaviour, we demonstrate the value of leveraging heterogeneity in the behaviour to gain greater insight into population structure and the mechanisms driving space-use tactics.

What makes a weed a weed? A large-scale evaluation of arable weeds through a functional lens

PREMISE OF THE STUDY

Despite long-term research efforts, a comprehensive perspective on the ecological and functional properties determining plant weediness is still lacking. We investigated here key functional attributes of arable weeds compared to non-weed plants, at large spatial scale.

METHODS

We used an intensive survey of plant communities in cultivated and non-cultivated habitats to define a pool of plants occurring in arable fields (weeds) and one of plants occurring only in open non-arable habitats (non-weeds) in France. We compared the two pools based on nine functional traits and three functional spaces (LHS, reproductive and resource requirement hypervolumes). Within the weed pool, we quantified the trait variation of weeds along a continuum of specialization to arable fields.

KEY RESULTS

Weeds were mostly therophytes and had higher specific leaf area, earlier and longer flowering, and higher affinity for nutrient-rich, sunny and dry environments compared to non-weeds, although functional spaces of weeds and non-weeds largely overlapped. When fidelity to arable fields increased, the spectrum of weed ecological strategies decreased as did the overlap with non-weeds, especially for the resource requirement hypervolume.

CONCLUSIONS

Arable weeds constitute a delimited pool defined by a trait syndrome providing tolerance to the ecological filters of arable fields (notably, regular soil disturbances and fertilization). The identification of such a syndrome is of great interest to predict the weedy potential of newly established alien plants. An important reservoir of plants may also become weeds after changes in agricultural practices, considering the large overlap between weeds and non-weeds.

How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison

The hypervolume indicator has frequently been used for comparing evolutionary multi-objective optimization (EMO) algorithms. A reference point is needed for hypervolume calculation. However, its specification has not been discussed in detail from a viewpoint of fair performance comparison. A slightly worse point than the nadir point is usually used for hypervolume calculation in the EMO community. In this paper, we propose a reference point specification method for fair performance comparison of EMO algorithms. First, we discuss the relation between the reference point specification and the optimal distribution of solutions for hypervolume maximization. It is demonstrated that the optimal distribution of solutions strongly depends on the location of the reference point when a multi-objective problem has an inverted triangular Pareto front. Next, we propose a reference point specification method based on theoretical discussions on the optimal distribution of solutions. The basic idea is to specify the reference point so that a set of well-distributed solutions over the entire linear Pareto front has a large hypervolume and all solutions in such a solution set have similar hypervolume contributions. Then, we examine whether the proposed method can appropriately specify the reference point through computational experiments on various test problems. Finally, we examine the usefulness of the proposed method in a hypervolume-based EMO algorithm. Our discussions and experimental results clearly show that a slightly worse point than the nadir point is not always appropriate for performance comparison of EMO algorithms.

Biogeochemical and Ecomorphological Niche Segregation of Mediterranean Woody Species along a Local Gradient

According with niche theory the species are specialized in different ecological niches, being able to coexist as result of a differential use of resources. In this context, the biogeochemical niche hypothesis proposes that species have an optimal elemental composition which results from the link between the chemical and morphological traits for the optimum plant functioning. Thus, and attending to the limiting similarity concept, different elemental composition and plant structure among co-occurring species may reduce competition, promoting different functional niches. Different functional habits associated with leaf life-span or growth forms are associated with different strategies for resource uptake, which could promote niche partitioning. In the present study, based on the biogeochemical niche concept and the use of resources in different proportions, we have focused on leaf traits (morphological and chemical) associated with resource uptake, and explored the niche partitioning among functional habits: leaf life-span (deciduous, evergreen, and semideciduous) and growth (tree, shrub, and arborescent-shrub). To this end, we have quantified the hypervolume of the leaf functional trait space (both structure and chemical composition) in a sample of 45 Mediterranean woody species from Sierra Morena Mountains (Spain) growing along a local soil resource gradient. Our results show consistent variation in functional space for woody communities distributed along the environmental gradient. Thus, communities dominated by deciduous trees with faster growth and a predominant acquisitive strategy were characteristic of bottom forests and showed highest leaf biogeochemical space. While semideciduous shrubs and evergreen (arborescent, trees) species, characterized by a conservative strategy, dominated ridge forests and showed smaller functional space. In addition, within each topographical zone or environment type, the foliar biogeochemical niche partitioning would underlie the species ability to coexist by diverging on leaf nutrient composition and resource uptake. Lower niche overlap among functional habits were found, which support that different growth forms and leaf life-habits may facilitate the coexistence of the woody species and niche partitioning along and within the gradient.

Hypervolume Subset Selection in Two Dimensions: Formulations and Algorithms

The hypervolume subset selection problem consists of finding a subset, with a given cardinality k, of a set of nondominated points that maximizes the hypervolume indicator. This problem arises in selection procedures of evolutionary algorithms for multiobjective optimization, for which practically efficient algorithms are required. In this article, two new formulations are provided for the two-dimensional variant of this problem. The first is a (linear) integer programming formulation that can be solved by solving its linear programming relaxation. The second formulation is a k-link shortest path formulation on a special digraph with the Monge property that can be solved by dynamic programming in [Formula: see text] time. This improves upon the result of [Formula: see text] in Bader ( 2009 ), and slightly improves upon the result of [Formula: see text] in Bringmann et al. ( 2014b ), which was developed independently from this work using different techniques. Numerical results are shown for several values of n and k.