Species abundance distributions (SADs) follow one of ecology's oldest and most universal laws - every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just ...a few common species. Here, we review theoretical, empirical and statistical developments in the study of SADs. Several key points emerge. (i) Literally dozens of models have been proposed to explain the hollow curve. Unfortunately, very few models are ever rejected, primarily because few theories make any predictions beyond the hollow-curve SAD itself. (ii) Interesting work has been performed both empirically and theoretically, which goes beyond the hollow-curve prediction to provide a rich variety of information about how SADs behave. These include the study of SADs along environmental gradients and theories that integrate SADs with other biodiversity patterns. Central to this body of work is an effort to move beyond treating the SAD in isolation and to integrate the SAD into its ecological context to enable making many predictions. (iii) Moving forward will entail understanding how sampling and scale affect SADs and developing statistical tools for describing and comparing SADs. We are optimistic that SADs can provide significant insights into basic and applied ecological science.
Distribution models are used to predict the likelihood of occurrence or abundance of a species at locations where census data are not available. An integral part of modelling is the testing of model ...performance. We compared different schemes and measures for testing model performance using 79 species from the North American Breeding Bird Survey. The four testing schemes we compared featured increasing independence between test and training data: resubstitution, random data hold-out and two spatially segregated data hold-out designs. The different testing measures also addressed different levels of information content in the dependent variable: regression R² for absolute abundance, squared correlation coefficient r² for relative abundance and AUC/Somer s D for presence/absence. We found that higher levels of independence between test and training data lead to lower assessments of prediction accuracy. Even for data collected independently, spatial autocorrelation leads to dependence between random hold-out test data and training data, and thus to inflated measures of model performance. While there is a general awareness of the importance of autocorrelation to model building and hypothesis testing, its consequences via violation of independence between training and testing data have not been addressed systematically and comprehensively before. Furthermore, increasing information content (from correctly classifying presence/absence, to predicting relative abundance, to predicting absolute abundance) leads to decreasing predictive performance. The current tests for presence/absence distribution models are typically overly optimistic because a) the test and training data are not independent and b) the correct classification of presence/absence has a relatively low information content and thus capability to address ecological and conservation questions compared to a prediction of abundance. Meaningful evaluation of model performance requires testing on spatially independent data, if the intended application of the model is to predict into new geographic or climatic space, which arguably is the case for most applications of distribution models.
Premise of the Study
General relationships among functional traits have been identified across species, but the forces shaping these relationships remain largely unknown. Adopting an approach from ...evolutionary biology, we studied similarities and differences in intrapopulation trait correlations among locally co‐occurring tree species to assess the roles of constraints, phylogeny, and the environmental niche in shaping multivariate phenotypes. We tested the hypotheses (1) that intrapopulation correlations among functional traits are largely shaped by fundamental trade‐offs or constraints and (2) that differences among species reflect adaptation to their environmental niches.
Methods
We compared pairwise correlations and correlation matrices of 17 key functional traits within and among temperate tree species. These traits describe three well‐established trade‐off dimensions characterizing interspecific relationships among physiological functions: resource acquisition and conservation; sap transport and mechanical support; and branch architecture.
Key Results
Six trait pairs are consistently correlated within populations. Of these, only one involves dimensionally independent traits: LMA‐δ13C. For all other traits, intrapopulation functional trait correlations are weak, are species‐specific, and differ from interspecific correlations. Species intrapopulation correlation matrices are related to neither phylogeny nor environmental niche.
Conclusions
The results (1) suggest that the functional design of these species is centered on efficient water use, (2) highlight flexibility in plant functional design across species, and (3) suggest that intrapopulation, local interspecific, and global interspecific correlations are shaped by processes acting at each of these scales.
The what, how and why of doing macroecology McGill, Brian J.; Algar, Adam
Global ecology and biogeography,
January 2019, 2019-01-00, 20190101, Letnik:
28, Številka:
1
Journal Article
Recenzirano
Macroecology is a growing and important subdiscipline of ecology, but it is becoming increasingly diffuse, without an organizing principle that is widely agreed upon. I highlight two main current ...views of macroecology: as the study of large‐scale systems and as the study of emergent systems. I trace the history of both these views through the writings of the founders of macroecology. I also highlight the transmutation principle that identifies serious limitations to the study of large‐scale systems with reductionist approaches. And I suggest that much of the underlying goal of macroecology is the pursuit of general principles and the escape from contingency. I highlight that there are many intertwined aspects of macroecology, with a number of resulting implications. I propose that returning to a focus on studying assemblages of a large number of particles is a helpful view. I propose defining macroecology as “the study at the aggregate level of aggregate ecological entities made up of large numbers of particles for the purposes of pursuing generality”.
Ecology Letters (2010) 13: 838-848 Despite the increasing importance of functional traits for the study of plant ecology, we do not know how variation in a given trait changes across ecological ...scales, which prevents us from assessing potential scale-dependent aspects of trait variation. To address this deficiency, we partitioned the variance in two key functional traits (leaf mass area and leaf dry matter content) across six nested ecological scales (site, plot, species, tree, strata and leaf) in lowland tropical rainforests. In both traits, the plot level shows virtually no variance despite high species turnover among plots and the size of within-species variation (leaf + strata + tree) is comparable with that of species level variation. The lack of variance at the plot level brings substantial support to the idea that trait-based environmental filtering plays a central role in plant community assembly. These results and the finding that the amount of within-species variation is comparable with interspecific variation support a shift of focus from species-based to trait-based ecology.
•There are extensive human-caused impacts on the biosphere and we consider their effect on biodiversity.•Different human impacts have opposite results, and assessments to date have found ...contradictory results.•We suggest that this is due to the need to unpack biodiversity trends by scale and type of biodiversity.•We identify 15 distinct biodiversity trends and summarize what is and is not known about them to date.•We also show that community trends contain high variability in outcome for individual species.
Humans are transforming the biosphere in unprecedented ways, raising the important question of how these impacts are changing biodiversity. Here we argue that our understanding of biodiversity trends in the Anthropocene, and our ability to protect the natural world, is impeded by a failure to consider different types of biodiversity measured at different spatial scales. We propose that ecologists should recognize and assess 15 distinct categories of biodiversity trend. We summarize what is known about each of these 15 categories, identify major gaps in our current knowledge, and recommend the next steps required for better understanding of trends in biodiversity.
Because biodiversity is multidimensional and scale‐dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale‐dependence matters for empirical studies, and (2) if ...it does matter, how exactly we should quantify biodiversity change. To address the first question, we analysed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity – species richness – was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale‐dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi‐dimensional and multi‐scale perspective informs the responses of biodiversity to ecological drivers.
One of the key hypothesized drivers of gradients in species richness is environmental filtering, where environmental stress limits which species from a larger species pool gain membership in a local ...community owing to their traits. Whereas most studies focus on small-scale variation in functional traits along environmental gradient, the effect of large-scale environmental filtering is less well understood. Furthermore, it has been rarely tested whether the factors that constrain the niche space limit the total number of coexisting species. We assessed the role of environmental filtering in shaping tree assemblages across North America north of Mexico by testing the hypothesis that colder, drier, or seasonal environments (stressful conditions for most plants) constrain tree trait diversity and thereby limit species richness. We assessed geographic patterns in trait filtering and their relationships to species richness pattern using a comprehensive set of tree range maps. We focused on four key plant functional traits reflecting major life history axes (maximum height, specific leaf area, seed mass, and wood density) and four climatic variables (annual mean and seasonality of temperature and precipitation). We tested for significant spatial shifts in trait means and variances using a null model approach. While we found significant shifts in mean species' trait values at most grid cells, trait variances at most grid cells did not deviate from the null expectation. Measures of environmental harshness (cold, dry, seasonal climates) and lower species richness were weakly associated with a reduction in variance of seed mass and specific leaf area. The pattern in variance of height and wood density was, however, opposite. These findings do not support the hypothesis that more stressful conditions universally limit species and trait diversity in North America. Environmental filtering does, however, structure assemblage composition, by selecting for certain optimum trait values under a given set of conditions.
While human activities are known to elicit rapid turnover in species composition through time, the properties of the species that increase or decrease their spatial occupancy underlying this turnover ...are less clear. Here, we used an extensive dataset of 238 metacommunity time series of multiple taxa spread across the globe to evaluate whether species that are more widespread (large-ranged species) differed in how they changed their site occupancy over the 10-90 years the metacommunities were monitored relative to species that are more narrowly distributed (small-ranged species). We found that on average, large-ranged species tended to increase in occupancy through time, whereas small-ranged species tended to decrease. These relationships were stronger in marine than in terrestrial and freshwater realms. However, in terrestrial regions, the directional changes in occupancy were less extreme in protected areas. Our findings provide evidence for systematic decreases in occupancy of small-ranged species, and that habitat protection could mitigate these losses in the face of environmental change.
One of the fundamental questions of ecology is what controls biodiversity. Recent theory suggests that biodiversity is controlled predominantly by neutral drift of species abundances. This theory has ...generated considerable controversy, because it claims that many mechanisms that have long been studied by ecologists (such as niches) have little involvement in structuring communities. The theory predicts that the species abundance distribution within a community should follow a zero-sum multinomial distribution (ZSM), but this has not, so far, been rigorously tested. Specifically, it remains to be shown that the ZSM fits the data significantly better than reasonable null models. Here I test whether the ZSM fits several empirical data sets better than the lognormal distribution. It does not. Not only does the ZSM fail to fit empirical data better than the lognormal distribution 95% of the time, it also fails to fit empirical data better even a majority of the time. This means that there is no evidence that the ZSM predicts abundances better than the much more parsimonious null hypothesis.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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