Competitive intransitivity, population interaction structure, and strategy coexistence

Sherpa Romeo green journal. Permission to archive accepted author manuscriptIntransitive competition occurs when competing strategies cannot be listed in a hierarchy, but rather form loops – as in the game Rock-Paper-Scissors. Due to its cyclic competitive replacement, competitive intransitivity promotes strategy coexistence, both in Rock-Paper-Scissors and in higher-richness communities. Previous work has shown that this intransitivity-mediated coexistence is strongly influenced by spatially explicit interactions, compared to when populations are well mixed. Here, we extend and broaden this line of research and examine the impact on coexistence of intransitive competition taking place on a continuum of small-world networks linking spatial lattices and regular random graphs. We use simulations to show that the positive effect of competitive intransitivity on strategy coexistence holds when competition occurs on networks toward the spatial end of the continuum. However, in networks that are sufficiently disordered, increasingly violent fluctuations in strategy frequencies can lead to extinctions and the prevalence of monocultures. We further show that the degree of disorder that leads to the transition between these two regimes is positively dependent on population size; indeed for very large populations, intransitivity-mediated strategy coexistence may even be possible in regular graphs with completely random connections. Our results emphasize the importance of interaction structure in determining strategy dynamics and diversity

Opposing community assembly patterns for dominant and nondominant plant species in herbaceous ecosystems globally

Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co-dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (\u3c50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities

Multiple Facets of Biodiversity Drive the Diversity-Stability Relationship

A significant body of evidence has demonstrated that biodiversity stabilizes ecosystem functioning over time in grassland ecosystems. However, the relative importance of different facets of biodiversity underlying the diversity–stability relationship remains unclear. Here we used data from 39 biodiversity experiments and structural equation modeling to investigate the roles of species richness, phylogenetic diversity, and both the diversity and community-weighted mean of functional traits representing the ‘fast–slow’ leaf economics spectrum in driving the diversity–stability relationship. We found that high species richness and phylogenetic diversity stabilize biomass production via enhanced asynchrony. Contrary to our hypothesis, low phylogenetic diversity also enhances ecosystem stability directly, albeit weakly. While the diversity of fast–slow functional traits has a weak effect on ecosystem stability, communities dominated by slow species enhance ecosystem stability by increasing mean biomass production relative to the standard deviation of biomass over time. Our results demonstrate that biodiversity influences ecosystem stability via a variety of facets, thus highlighting a more multicausal relationship than has been previously acknowledged

Opposing community assembly patterns for dominant and jonnondominant plant species in herbaceous ecosystems globally

Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co-dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (<50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities.Fil: Arnillas, Carlos Alberto. University of Toronto Scarborough; CanadáFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Seabloom, Eric. University of Minnesota; Estados UnidosFil: Alberti, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Baez, Selene. Escuela Politécnica Nacional; EcuadorFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Boughton, Elizabeth H.. Archbold Biological Station; Estados UnidosFil: Buckley, Yvonne M.. Trinity College Dublin; IrlandaFil: Bugalho, Miguel Nuno. Universidad de Lisboa; PortugalFil: Donohue, Ian. Trinity College Dublin; IrlandaFil: Dwyer, John. University of Queensland; AustraliaFil: Firn, Jennifer. The University of Queensland; AustraliaFil: Gridzak, Riley. Queens University; CanadáFil: Hagenah, Nicole. University of Pretoria; SudáfricaFil: Hautier, Yann. Utrecht University; Países BajosFil: Helm, Aveliina. University of Tartu; EstoniaFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Knops, Johannes M. H.. Xi'an Jiaotong Liverpool University; China. University of Nebraska; Estados UnidosFil: Komatsu, Kimberly J.. Smithsonian Environmental Research Center; Estados UnidosFil: Laanisto, Lauri. Estonian University of Life Sciences; EstoniaFil: Laungani, Ramesh. Poly Prep Country Day School; Estados UnidosFil: McCulley, Rebecca. University of Kentucky; Estados UnidosFil: Moore, Joslin L.. Monash University; AustraliaFil: Morgan, John W.. La Trobe University; AustraliaFil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Sur. Estación Experimental Agropecuaria Santa Cruz. Agencia de Extensión Rural Río Gallegos; ArgentinaFil: Power, Sally A.. University of Western Sydney; AustraliaFil: Price, Jodi. Charles Sturt University; AustraliaFil: Sankaran, Mahesh. National Centre for Biological Sciences; IndiaFil: Schamp, Brandon. Algoma University; CanadáFil: Speziale, Karina Lilian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Standish, Rachel. Murdoch University; AustraliaFil: Virtanen, Risto. University of Oulu; FinlandiaFil: Cadotte, Marc W.. University of Toronto Scarborough; Canadá. University of Toronto; Canad

Mapping local and global variability in plant trait distributions

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means

Opposing community assembly patterns for dominant and nondominant plant species in herbaceous ecosystems globally

Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co-dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (<50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities.National Science Foundation; Natural Sciences and Engineering Research Council of Canada; Institute on the Environment, University of Minnesota and Portuguese Science Foundation.http://www.ecolevol.orghj2022Mammal Research InstituteZoology and Entomolog

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Species abundance of an old-field plant community in Sault Ste. Marie, Ontario

Three years of species abundance data for 75 control plots and 75 herbivore exclosure plots. Exclosure plots are identified as "cage" in the "treatment" column of tabs 2-4. The first tab ("SpeciesID") provides species names and abbreviations used in the abundance data. Tabs 2-4 contain species abundance data for 3 years (year indicated by tab name)

Data from: Calculating competitive intransitivity: computational challenges

Intransitive, or 'rock-paper-scissors' competition is compelling because it promotes species coexistence and because recent work suggests it may be common in natural systems. One class of intransitivity indices works by considering s, the minimum number of competitive reversals to convert a given competitive community (i.e., a 'tournament') to a hierarchy. The most straightforward example of such 'reversal-based' indices is Petraitis' index, t = 1 - s/M, where M is the maximum s across all possible n-species tournaments. Using exhaustive searches, we prove that Petraitis' formula for M (and, therefore, t) does not hold for n ≥ 7. Furthermore, the determination of s for even moderate values of n may prove difficult, as the equivalent graph-theoretical problem is NP-hard; there is no known computationally feasible way to compute an exact answer for anything but small values of n, let alone a closed-form solution. Petraitis' t is a valuable index of intransitivity; however, at present its use is limited to relatively species-poor systems. More broadly, reversal-based indices, while intuitive, may be problematic because of this computability issue

Canopy effects on abundance and leaf traits of a spring ephemeral: Erythronium americanum

Spring ephemerals take advantage of the high light levels available in the spring by completing the aboveground portion of their lifecycle before the canopy develops and while few other understory plant species are growing. The spring is marked by high resource availability, yet spring ephemerals are variably abundant throughout forests. Research indicates that canopy conditions can influence the growth of spring ephemerals; consequently, we tested whether the variation in canopy conditions predicted variation in the abundance of Erythronium americanum Ker Gawl. across 50 forest plots. We also tested whether the specific leaf area (SLA) of E. americanum in plots was predicted by variation in plot-level canopy conditions, reflecting E. americanum‘s ability to adapt to different canopy conditions. The abundance of E. americanum was significantly lower in the plots with greater hard canopy closure (i.e., permanent cover: tree architecture + evergreen leaf cover), and significantly higher under canopies that reached full development earlier. Canopies with greater hard canopy cover at the start of the growing season were associated with significantly higher SLA, quantifying local adaptation by E. americanum to variable canopy conditions. Erythronium americanum takes advantage of the high light levels available in the spring. It is unclear at this time why higher abundance of E. americanum is associated with canopies that close earlier.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author