Composition Of Ecological Communities Research Articles

The role of shade in influencing dung deposition and nutrient transfer by kangaroos (Macropus spp.) in an arid landscape

Where they occur at high densities, herbivores are likely to impact ecosystems by functioning as nutrient vectors that shift nutrients from areas where they graze to other locations. Such lateral shifts in nutrients are important to understand as they can alter the balance of species interactions and composition of ecological communities. In arid Australia, kangaroo (Macropus spp.) populations have irrupted due to suppression of their chief predator and their presence can have marked impacts on vegetation and soils in areas where they graze. Kangaroos are hypothesised to facilitate the transport of nutrients by ingesting organic material and depositing it in the form of faecal matter and urine under the shade of trees where they rest during the day. Here, we investigate the role that kangaroos and shade play as nutrient vectors and nutrient sinks, respectively. We compared kangaroo visitation and soil nutrients under experimental shades with unshaded areas in an arid landscape with little natural shade. Kangaroo visitation was greatest at shaded plots. Dung accumulation was greater at shaded plots than unshaded plots. Total carbon (TC) was greater in soils within shaded plots than control plots; however, there was no difference in TC between shaded plots and procedural control plots. There was no difference in total nitrogen and plant available phosphorus between shaded, control and procedural control plots. Our findings demonstrate that the presence of shade in an arid landscape influences the microhabitat choice of kangaroos, but only partially supports the hypothesis that nutrients concentrate within the soil under shade.

Chaotic turnover of rare and abundant species in a strongly interacting model community

The composition of ecological communities varies not only between different locations but also in time. Understanding the fundamental processes that drive species toward rarity or abundance is crucial to assessing ecosystem resilience and adaptation to changing environmental conditions. In plankton communities in particular, large temporal fluctuations in species abundances have been associated with chaotic dynamics. On the other hand, microbial diversity is overwhelmingly sustained by a "rare biosphere" of species with very low abundances. We consider here the possibility that interactions within a species-rich community can relate both phenomena. We use a Lotka-Volterra model with weak immigration and strong, disordered, and mostly competitive interactions between hundreds of species to bridge single-species temporal fluctuations and abundance distribution patterns. We highlight a generic chaotic regime where a few species at a time achieve dominance but are continuously overturned by the invasion of formerly rare species. We derive a focal-species model that captures the intermittent boom-and-bust dynamics that every species undergoes. Although species cannot be treated as effectively uncorrelated in their abundances, the community's effect on a focal species can nonetheless be described by a time-correlated noise characterized by a few effective parameters that can be estimated from time series. The model predicts a nonunitary exponent of the power-law abundance decay, which varies weakly with ecological parameters, consistent with observation in marine protist communities. The chaotic turnover regime is thus poised to capture relevant ecological features of species-rich microbial communities.

Disturbance intensification is altering the trait composition of Caribbean reefs, locking them into a low functioning state

Anthropogenic climate change is intensifying natural disturbance regimes, which negatively affects some species, while benefiting others. This could alter the trait composition of ecological communities and influence resilience to disturbance. We investigated how the frequency and intensification of the regional storm regime (and likely other disturbances) is altering coral species composition and in turn resistance and recovery. We developed regional databases of coral cover and composition (3144 reef locations from 1970 to 2017) and of the path and strength of cyclonic storms in the region (including 10,058 unique storm-reef intersections). We found that total living coral cover declined steadily through 2017 (the median annual loss rate was ~ 0.25% per year). Our results also indicate that despite the observed increase in the intensity of Atlantic cyclonic storms, their effect on coral cover has decreased markedly. This could be due in part to selection for disturbance-resistant taxa in response to the intensifying disturbance regime. We found that storms accelerated the loss of threatened acroporid corals but had no measurable effect on the cover of more resilient “weedy” corals, thereby increasing their relative cover. Although resistance to disturbance has increased, recovery rates have slowed due to the dominance of small, slow-growing species. This feedback loop is locking coral communities into a low-functioning state dominated by weedy species with limited ecological or societal value.

The effect of selective logging on microclimates, arthropod abundance and the foraging behaviour of Eastern Himalayan birds

Selective logging—the practice of removing a subset of commercially important trees from a forest—is a globally pervasive form of forest degradation. Selective logging alters both the structure and function of forests and the composition of ecological communities. Tropical insectivorous birds are highly vulnerable to microhabitat alterations in logged forest. Such altered microhabitats might affect the foraging of forest birds by altering (a) resource availability, and (b) foraging behaviour. We investigated the effect of selective logging on microclimates, prey availability, foraging behaviour and the foraging success of eastern Himalayan birds in the breeding season. Selective logging alters temperature-humidity microclimates and the composition of arthropod communities, both of which are likely to then collectively alter foraging behaviour by birds. We show that birds spent a lower proportion of their time foraging in primary compared with logged forest. Further, selective logging interacts with species traits such as body mass, preferred foraging stratum (understorey, midstorey or canopy) and foraging manoeuvre to influence foraging success. Gleaners generally foraged more successfully in primary forest and salliers in logged forest, although these patterns were modified by body mass and foraging stratum. Synthesis and applications: Our study shows how altered microclimates in anthropogenically modified habitats can influence resource availability and have downstream impacts on the behaviour of species at higher trophic levels.

Colonization order of bacterial isolates on treefrog embryos impacts microbiome structure in tadpoles.

Priority effects, or impacts of colonization order, may have lasting influence on ecological community composition. The embryonic microbiome is subject to stochasticity in colonization order of bacteria. Stochasticity may be especially impactful for embryos developing in bacteria-rich environments, such as the embryos of many amphibians. To determine if priority effects experienced as embryos impacted bacterial community composition in newly hatched tadpoles, we selectively inoculated the embryos of laboratory-raised hourglass treefrogs, Dendropsophus ebraccatus, with bacteria initially isolated from the skin of wild D. ebraccatus adults over 2 days. First, embryos were inoculated with two bacteria in alternating sequences. Next, we evaluated the outcomes of priority effects in an in vitro co-culture assay absent of host factors. We then performed a second embryo experiment, inoculating embryos with one of three bacteria on the first day and a community of five target bacteria on the second. Through 16S rRNA gene amplicon sequencing, we observed relative abundance shifts in tadpole bacteria communities due to priority effects. Our results suggest that the initial bacterial source pools of embryos shape bacterial communities at later life stages; however, the magnitude of those changes is dependent on the host environment and the identity of bacterial colonists.

Animal functional traits: Towards a trait‐based ecology for whole ecosystems

Abstract Functional traits and associated trait‐based concepts have driven rapid innovation in ecology over recent years, with most progress based on insights from plants. However, plants are almost entirely restricted to a single trophic level, and an over‐reliance on plant traits therefore neglects the complexity and importance of biotic interactions across trophic levels. The need to expand the focus of trait‐based ecology to account for trophic complexity has led to an upsurge in attention on animal functional traits and the emergence of new concepts relevant to community ecology, macroecology and ecosystem science. Recent progress in the compilation of global trait datasets for some animal taxa has opened up new possibilities for testing ecological theory. In this Special Focus, we explore how trait‐based ecology can expand the scope of investigation from single to multiple trophic levels, how insights from these investigations can be used to upscale understanding from local communities to biogeographical patterns and how this can ultimately help to predict the impacts of global change on ecosystem functions. To address these key questions, we showcase studies on diverse animal taxa ranging in size from springtails to crocodiles and spanning multiple trophic levels from primary consumers to apex predators. This collection of studies shows how precise measurements of morphological or physiological traits can increase mechanistic understanding of community assembly across trophic levels, particularly of the mechanisms underpinning large‐scale biodiversity patterns. Furthermore, a clearer picture is emerging of systematic animal responses to environmental change that shape the trait composition of ecological communities and affect ecosystem functioning. The articles in this volume highlight the need to move trait‐based ecology beyond the limits of taxonomic boundaries. The integration of trait data and concepts across trophic levels opens up new possibilities for identifying general ecological mechanisms that shape patterns and processes operating at different scales. The identification of key functional traits and their interplay across trophic levels can underpin the development of a trait‐based ecology for whole ecosystems, which could eventually enable predictions of the ecosystem‐level consequences of biodiversity loss. Read the free Plain Language Summary for this article on the Journal blog.

Modelling ecological communities when composition is manipulated experimentally

Abstract In an experimental setting, the composition of ecological communities can be manipulated directly. Starting from a pool of species, it is possible to co‐culture species in different combinations, ranging from monocultures, to pairs, and all the way up to the full species pool. Leveraging datasets with this experimental design, we advance methods to infer species interactions using density measurements taken at a single time point across a variety of distinct community compositions. First, we introduce a fast and robust algorithm to estimate parameters for simple statistical models describing these data, which can be combined with likelihood maximization approaches. Second, we derive from consumer–resource dynamics a family of statistical models with few parameters, which can be applied to study systems where only a small fraction of the potential community compositions have been observed. Third, we show how a Weighted Least Squares framework can be used to account for the fact that species abundances often display a strong relationship between means and variances. To illustrate our approach, we analyse datasets spanning plant, bacteria and phytoplankton communities, as well as simulations, consistently recovering a good fit to the data and demonstrating the ability of our methods to predict equilibrium densities in out‐of‐sample communities. By combining more robust model structures and fitting procedures along with a more flexible error model, we greatly extend the applicability of recently proposed methods to model community composition from experimental data, opening the door for the analysis of larger pools of species using sparser and noisier datasets than was previously possible.

Factors at multiple scales drive parasite community structure.

Understanding how ecological communities are assembled remains a key goal of ecosystem ecology. Because communities are hierarchical, factors acting at multiple scales can contribute to patterns of community structure. Parasites provide a natural system to explore this idea, as they exist as discrete communities within host individuals, which are themselves part of a community and metacommunity. We aimed to understand the relative contribution of multi-scale drivers in parasite community assembly and assess how patterns at one level may mask those occurring at another. Specifically, we wanted to disentangle patterns caused by passive sampling from those determined by ecological drivers, and how these vary with scale. We applied a Markov Random Fields model and assessed measures of β-diversity and nestedness for 420 replicate parasite infracommunities (parasite assemblages in host individuals) across two freshwater mussel host species, three sites and two time periods, comparing our results to simulations from four different ecologically relevant null models. We showed that β-diversity between sites (explaining 25% of variation in parasite distribution) and host species (41%) is greater than expected, and β-diversity between individual hosts is smaller than expected, even after accounting for parasite prevalence and characteristics of host individuals. Furthermore, parasite communities were significantly less nested than expected once parasite prevalence and host characteristics were both accounted for, but more nested than expected otherwise, suggesting a degree of modularity at the within-host level that is masked if underlying host and parasite characteristics are not taken into account. The Markov Random Fields model provided evidence for possible competitive within-host parasite interactions, providing a mechanism for the observed infracommunity modularity. An integrative approach that examines factors at multiple scales is necessary to understand the composition of ecological communities. Furthermore, patterns at one level can alter the interpretation of ecologically important drivers at another if variation at higher scales is not accounted for.

Community‐wide trait adaptation, but not plasticity, explains ant community structure in extreme environments

Abstract Quantifying trait–environment associations can help elucidate the processes underpinning the structure of species assemblages. However, most work has focused on trait variation across rather than within species, meaning that processes operating at the intraspecific levels cannot be detected. Incorporating intraspecific trait variation in community‐wide analyses can provide valuable insights about the role of morphological adaptation and plasticity on species persistence and the composition of ecological communities. Here, we assessed geographical variation in the direction (i.e. adaptation) and strength of selection, and the magnitude of plasticity, by examining community‐wide trait variation in ant communities along an environmental gradient spanning 9° latitude in Quebec, Canada. Specifically, we measured 9 morphological traits related to foraging strategies, resource use and thermal regulation at 20 locations across temperate and boreal forests. We then examined how the mean and variance of these traits varied along temperature and precipitation gradients. Moreover, we examined how these trait–environment relationships varied across levels of organization, from individual workers (intraspecific) to colonies (intraspecific) and species (interspecific). We observed changes in mean trait values along environmental gradients, but very little change in variance. Specifically, we observed a decrease in the mean length of antennae and an increase in the mean eye length from mild (warm and wet) to more extreme environments (cold and dry). These shifts in trait means were mostly coordinated across organizational levels (i.e. worker, colony and species). We also observed a general increase in trait variance from mild to extreme environments, but only at the species level. Our findings suggest that stressful environmental conditions exert a strong selection pressure on ant morphology causing shifts in optimal trait values. These adaptations may enable persistence at the northern edge of the boreal forest and therefore influence the composition of these ant communities. Specifically, ants with large eyes and short antennae are overrepresented at the transition zone between the boreal forest and the tundra, possibly representing an adaptation to these more open habitats. Our study demonstrates that combining spatial and community‐wide intraspecific functional trait data provides a promising way forward to gain new insights on trait adaptations and processes underpinning community structure along environmental gradients. Read the free Plain Language Summary for this article on the Journal blog.

The effect of resource availability on interspecific competition between a native and an invasive ant.

Interspecific competition influences the composition of ecological communities. Species may differ in their needs for different resources, therefore resource availability may determine the outcome of interspecific interactions. Species often compete over food, shelter or both. When more than one resource is limited, different species may prioritize different resources. To determine the impact of resource availability on the competitive relationship between an invasive and a native species, we examined interactions between groups of the invasive Argentine ant (Linepithema humile) and the native odorous ant (Tapinoma sessile) over (1) food, (2) shelter or (3) both simultaneously. We further examined the mechanisms underlying the competitive relationship, asking whether aggressive interactions, exploratory behaviour or the order of arrival at a resource explained resource use. Shelter was preferred by both species when no competitors were present. In a competitive setting, L. humile groups controlled shelter through aggressive displacement but lost control over food due to investment of workers in the control of shelter. Thus, there are tradeoffs when competing over multiple resources and aggressive interactions allow invasive species to displace native species from a preferred resource.This article is part of the theme issue ‘Intergroup conflict across taxa’.

Contributions of mean temperature and temperature variation to population stability and community diversity.

Future climate changes are predicted to not only increase global temperatures but also alter temporal variation in temperature. As thermal tolerances form an important component of a species’ niche, changes to the temperature regime have the capacity to negatively impact species, and therefore, the diversity of the communities they inhabit. In this study, we used protist microcosms to assess how mean temperature, as well as temporal variation in temperature, affected diversity. Communities consisted of seven species in a multitrophic food web. Each ecosystem was inoculated with the same abundances of each species at the start of the experiment, and species densities, Hill's numbers (based on Shannon diversity), the number of extinctions, and the probability the microcosm contained predators were all calculated at the end of the experiment. To assess how mean temperature and temperature fluctuations affect stability, we also measured population densities through time. We found that increased temporal variation in temperature increased final densities, increased Hill's numbers (at low mean temperatures), decreased rates of extinctions, and increased the probability that predators survived till the end of the experiment. Mean temperatures did not significantly affect either the number of extinctions or the probability of predators, but did reduce the positive effect of increased temporal variation in temperature on overall diversity. Our results indicate that climatic changes have the potential to impact the composition of ecological communities by altering multiple components of temperature regimes. However, given that some climate forecasts are predicting increased mean temperatures and reduced variability, our finding that increased mean temperature and reduced temporal variation are both generally associated with negative consequences is somewhat concerning.

Idea paper: Improving forecasts of community composition with lightweight biodiversity monitoring across ecological and anthropogenic disturbance gradients

AbstractAccurate and up‐to‐date biodiversity forecasts enable robust planning for environmental management and conservation of landscapes under a wide range of uses. Future predictions of the species composition of ecological communities complement more frequently reported species richness estimates to better characterize the different dimensions of biodiversity. The models that make community composition forecasts are calibrated with data on species' geographic patterns for the present, which may not be good proxies for future patterns. The future establishment of novel communities represents data on species interactions unaccounted for by these models. However, detecting them in a systematic way presents challenges due to the lack of monitoring data for landscapes with high environmental turnover, where such communities are likely to establish. Here, we propose lightweight monitoring over both ecological and anthropogenic disturbance gradients using passive sensors (i.e., those that operate continuously without much human input) to detect novel communities with the aim of updating models that make community composition forecasts. Monitoring over these two gradients should maximize detection of novel communities and improve understanding of relationships between community composition and environmental change. Further, barriers regarding cost and effort are reduced by using relatively few sensors requiring minimal upkeep. Ongoing updates to community composition forecasts based on novel community data and better understanding of the associated uncertainty should improve future decision‐making for both resource management and conservation efforts.

Present and historical landscape structure shapes current species richness in Central European grasslands

ContextCurrent diversity and species composition of ecological communities can often not exclusively be explained by present land use and landscape structure. Historical land use may have considerably influenced ecosystems and their properties for decades and centuries.ObjectivesWe analysed the effects of present and historical landscape structure on plant and arthropod species richness in temperate grasslands, using data from comprehensive plant and arthropod assessments across three regions in Germany and maps of current and historical land cover from three time periods between 1820 and 2016.MethodsWe calculated local, grassland class and landscape scale metrics for 150 grassland plots. Class and landscape scale metrics were calculated in buffer zones of 100 to 2000 m around the plots. We considered effects on total species richness as well as on the richness of species subsets determined by taxonomy and functional traits related to habitat use, dispersal and feeding.ResultsOverall, models containing a combination of present and historical landscape metrics showed the best fit for several functional groups. Comparing three historical time periods, data from the 1820/50s was among the most frequent significant time periods in our models (29.7% of all significant variables).ConclusionsOur results suggest that the historical landscape structure is an important predictor of current species richness across different taxa and functional groups. This needs to be considered to better identify priority sites for conservation and to design biodiversity-friendly land use practices that will affect landscape structure in the future.

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble.

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models.

Metagenomics Analysis Reveals Compositional and Functional Differences in the Gut Microbiota of Red Swamp Crayfish, Procambarus clarkii, Grown on Two Different Culture Environments.

The structure and function of intestinal microorganisms are closely related to host metabolism, development, physiology, and health. The red swamp crayfish, Procambarus clarkii, is an important farmed aquatic species in China, which is grown in aquaculture ponds and rice paddy fields. Since these are two distinct cultivation environments with important differences in nutrient input and ecological community composition, we hypothesized that they may have different effects on the gut microbiota of the crayfish. Here, we sought to examine this hypothesis. To that aim, metagenomics analyses were applied to unveil the taxonomic composition and functional diversity of the microbiota in the intestines of red swamp crayfish grown in aquaculture ponds and rice-crayfish cultivation environments. The results showed that Firmicutes and Proteobacteria were the two most abundant microbial components. In addition, the relative abundance of bacterial and archaeal communities, but not that of fungal and viral communities, significantly differed between the two environments. The abundance of genes involved in pathways related to genetic information processing and human diseases was lower in the guts of red swamp crayfish grown in rice-crayfish cultivation environments. In particular, the abundance of two gene sets, K13730 and K08303, which are related to epithelial cell invasion by Listeria monocytogenes and Helicobacter pylori, respectively, decreased in this culture environment. In addition, the samples from rice-crayfish cultivation environments tended to have lower relative abundance of glycosyltransferases (GTs), which were the most abundant carbohydrate-active enzymes in the samples from both groups, higher abundance of glycoside hydrolases, and lower abundance of GT2.

Population genetic structure in a rapidly expanding mesocarnivore: golden jackals in the Dinaric-Pannonian region

Species range expansions and (re)colonization of landscapes variously dominated by humans occur on a global scale. Understanding such range enlargements and subsequent changes in the composition of ecological communities is important for conservation management, and the golden jackal (Canis aureus) can be considered a model species for regional and continental range expansion. Although this mesopredator has been known from the Adriatic Coast of southeastern Europe for over 500 years, the species is a recent arrival further north, including in Slovenia where jackals were first confirmed in the 1950s. Research from eastern Italy found jackals with ancestry from the Dalmatian region on the Adriatic Coast and the Pannonian region further east. We predicted similar ancestry for Slovenian jackals, and examined samples from Croatia, including Dalmatia and interior regions, Serbia, Hungary, and Slovenia with 25 microsatellite markers to determine population genetic structure. We detected two distinct genetic clusters, representing the Dalmatian and Balkan-Pannonian (Pannonian) jackal populations (FST = 0.157, 95% CI: 0.112–0.209). Contrary to expectations, only few individuals in Slovenia exhibited signs of Dalmatian ancestry, and none appeared to be direct immigrants. Some results suggested a third cluster centered in northern Hungary. These divergent profiles might indicate immigration from outside the study area, and samples from regions further east are required for additional resolution. Based on our results, we hypothesize that Dalmatia has not been a substantial source for recent range expansion of the species, which has likely occurred from the east. Further investigation can help resolve the ancestry and current distribution of the Dalmatian and Pannonian populations, and the ecological relationships resulting from progressively overlapping distributions of canid species. Finally, genomic research could illuminate whether genetic variants from eastern areas might have facilitated jackal expansion into regions characterized by a colder climate, the presence of snow, and extensive forest cover; habitats seemingly avoided by the jackals occupying the Adriatic Coast and surrounding areas in southeastern Europe.

What evidence exists on the impact of specific ecosystem components and functions on infectious diseases? A systematic map

BackgroundThe control and prevention of vector-borne and zoonotic diseases is often based on the reduction of host or vector populations, involving but not limited to preventative culling and use of insecticides. Yet, destructive interventions such as these have shown several limitations including ineffectiveness on arthropods and negative impacts on ecosystems. An alternative strategy would be to rely on the natural ecosystem functions and their careful management to regulate such diseases. The goal of our work was to evaluate existing scientific evidence on potential links between ecosystem components/functions and 14 vector-borne and zoonotic diseases impacting human health and answer the question: “What evidence exists on the impact of specific ecosystem components and functions on infectious diseases?”.MethodsWe searched for scientific articles published in English and French and screened them in a 3-round process (title, abstract and full-text). Articles were retained, without any geographical limitation, if they matched the following eligibility criteria: an exposure/intervention linked to changes in biological communities, habitats, or landscapes; an outcome consisting of any measure of infection in vector, animal or human hosts; and the presence of a comparator, in time and/or in space. The results are presented as a systematic map, followed by a narrative review where the amount of papers allowed for synthesis.ResultsSearches in 5 scientific publication databases allowed to retrieve 9723 unique articles, among which 207 were retained after the screening process. The amount of relevant literature was highly variable depending on diseases, and the types of exposures also varied greatly among studies focusing on the same disease. A hundred articles presented in the map were unique in their “disease x exposure” combination and thus not eligible for further narrative description. The remaining 107 articles were organized in 34 “disease x exposure” groups, encompassing 9 out of the 14 initial diseases. The groups were composed of 2 to 16 articles and were examined to provide a description of the current state of knowledge for those diseases.ConclusionStudies investigating the interaction between infectious diseases and ecosystems components and functions are still very scarce, and certain diseases are much more studied than others. Out of 14 diseases, 8 generated less than 10 relevant articles, while 2 diseases (Lyme disease and West Nile disease) represented 44% of all relevant studies. Although several vector-borne diseases included in the review represent a major health issue in the world, such as malaria or dengue, they have been exclusively studied under the prism of land-use, and we were unable to find relevant studies that tested the regulatory role of animal biodiversity-related functions. The role of predation in the regulation of vector and host populations has rarely been studied, with the exception of schistosomiasis. The dilution and amplification effects were addressed in several studies focusing on the composition of ecological communities. This map is a first step and could be upgraded in order to guide future research projects with the aim to conduct meta-analysis and build a robust evidence base to inform decision-making.

The role of deterministic succession during forest development within a southern African savanna

AbstractWoody encroachment can lead to a switch from open savannas to dense woodlands or forests. This has implications for both the composition of ecological communities and the provision of ecosystem services such as nutrient cycling and grazing capacity. The patterns and underlying drivers responsible for woody encroachment are not fully understood. Here, we investigate the underlying determinants of bush clump formation (a form of encroachment) in a South African savanna and explore whether bush clump succession is driven by deterministic (i.e., predictable changes in species composition) or stochastic (i.e., random) processes. Specifically, we test (1) whether the similarity in species composition of saplings and trees differs among small and large clumps, (2) which environmental factors are driving succession, and (3) whether forest specialization of tree and sapling species within bush clumps increases with the successional gradient. Similarity in species composition between saplings in small clumps and trees in large clumps was higher than similarity between trees in small clumps and trees in large clumps. Furthermore, temperature, soil moisture, relative humidity, and light intensity were related to changes in species composition along the successional gradient. As expected, forest specialization of trees increased with increasing clump area indicating that late‐successional bush clumps have more forest‐type species. The directional changes of species found along the successional gradient suggest a deterministic process of succession driven by changes in local environmental conditions during clump formation.

The influence of nutrient enrichment on riverine food web function and stability.

Nutrient enrichment of rivers and lakes has been increasing rapidly over the past few decades, primarily because of agricultural intensification. Although nutrient enrichment is known to drive excessive algal and microbial growth, which can directly and indirectly change the ecological community composition, the resulting changes in food web emergent properties are poorly understood. We used ecological network analysis (ENA) to examine the emergent properties of 12 riverine food webs across a nutrient enrichment gradient in the Manawatu, New Zealand. We also derive Keystone Sensitivity Indices to explore whether nutrients change the trophic importance of species in a way that alters the resilience of the communities to further nutrient enrichment or floods. Nutrient enrichment resulted in communities composed of energy inefficient species with high community (excluding microbes) respiration. Community respiration was several times greater in enriched communities, and this may drive hypoxic conditions even without concomitant changes in microbial respiration. Enriched communities exhibited weaker trophic cascades, which may yield greater robustness to energy flow loss. Interestingly, enriched communities were also more structurally and functionally affected by species sensitive to flow disturbance making these communities more vulnerable to floods.

Generalized Linear Models outperform commonly used canonical analysis in estimating spatial structure of presence/absence data.

BackgroundEcological communities tend to be spatially structured due to environmental gradients and/or spatially contagious processes such as growth, dispersion and species interactions. Data transformation followed by usage of algorithms such as Redundancy Analysis (RDA) is a fairly common approach in studies searching for spatial structure in ecological communities, despite recent suggestions advocating the use of Generalized Linear Models (GLMs). Here, we compared the performance of GLMs and RDA in describing spatial structure in ecological community composition data. We simulated realistic presence/absence data typical of many β-diversity studies. For model selection we used standard methods commonly used in most studies involving RDA and GLMs.MethodsWe simulated communities with known spatial structure, based on three real spatial community presence/absence datasets (one terrestrial, one marine and one freshwater). We used spatial eigenvectors as explanatory variables. We varied the number of non-zero coefficients of the spatial variables, and the spatial scales with which these coefficients were associated and then compared the performance of GLMs and RDA frameworks to correctly retrieve the spatial patterns contained in the simulated communities. We used two different methods for model selection, Forward Selection (FW) for RDA and the Akaike Information Criterion (AIC) for GLMs. The performance of each method was assessed by scoring overall accuracy as the proportion of variables whose inclusion/exclusion status was correct, and by distinguishing which kind of error was observed for each method. We also assessed whether errors in variable selection could affect the interpretation of spatial structure.ResultsOverall GLM with AIC-based model selection (GLM/AIC) performed better than RDA/FW in selecting spatial explanatory variables, although under some simulations the methods performed similarly. In general, RDA/FW performed unpredictably, often retaining too many explanatory variables and selecting variables associated with incorrect spatial scales. The spatial scale of the pattern had a negligible effect on GLM/AIC performance but consistently affected RDA’s error rates under almost all scenarios.ConclusionWe encourage the use of GLM/AIC for studies searching for spatial drivers of species presence/absence patterns, since this framework outperformed RDA/FW in situations most likely to be found in natural communities. It is likely that such recommendations might extend to other types of explanatory variables.