Statistical challenges in null model analysis.

This review identifies several important challenges in null model testing in ecology: 1) developing randomization algorithms that generate appropriate patterns for a specified null hypothesis; these randomization algorithms stake out a middle ground between formal Pearson-Neyman tests (which require a fully-specified null distribution) and specific process-based models (which require parameter values that cannot be easily and independently estimated); 2) developing metrics that specify a particular pattern in a matrix, but ideally exclude other, related patterns; 3) avoiding classification schemes based on idealized matrix patterns that may prove to be inconsistent or contradictory when tested with empirical matrices that do not have the idealized pattern; 4) testing the performance of proposed null models and metrics with artificial test matrices that contain specified levels of pattern and randomness; 5) moving beyond simple presence-absence matrices to incorporate species-level traits (such as abundance) and site-level traits (such as habitat suitability) into null model analysis; 6) creating null models that perform well with many sites, many species pairs, and varying degrees of spatial autocorrelation in species occurrence data. In spite of these challenges, the development and application of null models has continued to provide valuable insights in ecology, evolution, and biogeography for over 80 years. 'A null model is a pattern generating model that is based on randomization of ecological data or random sampling from a known or imagined distribution. The null model is designed with respect to some ecological or evolutionary process of interest'. (Gotelli and Graves 1996) From its origins in the analysis of species/genus ratios Hypothesis testing and constraints in null model analysis Classical Pearson-Neyman hypothesis testing The null hypothesis varies depending on the details of the test, but it is often a parsimonious expectation that the data are drawn from a single distribution, so that any patterns in the data arise only from random sampling processes. The alternative hypothesis is that patterns in the data are not the result of random variation generated by H 0 . Erroneous rejection of H 0 occurs with probability a and represents a type I statistical error. Conversely, erroneous acceptance of a false null hypothesis is a type II error and occurs with probability b. The quantity 1 -b is the power of the test, the probability of correctly rejecting H 0 given that it is false In ecological null model analysis, 'Null hypotheses entertain the possibility that nothing has happened, that a process has not occurred, or that change has not been produced by a cause of interest&apos

Anthropogenic Noise Changes Arthropod Abundances

Anthropogenic noise is a widespread and growing form of sensory pollution associated with the expansion of human infrastructure. One specific source of constant and intense noise is that produced by compressors used for the extraction and transportation of natural gas. Terrestrial arthropods play a central role in many ecosystems, and given that numerous species rely upon airborne sounds and substrate-borne vibrations in their life histories, we predicted that increased background sound levels or the presence of compressor noise would influence their distributions. In the second largest natural gas field in the United States (San Juan Basin, New Mexico, USA), we assessed differences in the abundances of terrestrial arthropod families and community structure as a function of compressor noise and background sound level. Using pitfall traps, we simultaneously sampled five sites adjacent to well pads that possessed operating compressors, and five alternate, quieter well pad sites that lacked compressors, but were otherwise similar. We found a negative association between sites with compressor noise or higher levels of background sound and the abundance of five arthropod families and one genus, a positive relationship between loud sites and the abundance of one family, and no relationship between noise level or compressor presence and abundance for six families and two genera. Despite these changes, we found no evidence of community turnover as a function of background sound level or site type (compressor and noncompressor). Our results indicate that anthropogenic noise differentially affects the abundances of some arthropod families. These preliminary findings point to a need to determine the direct and indirect mechanisms driving these observed responses. Given the diverse and important ecological functions provided by arthropods, changes in abundances could have ecological implications. Therefore, we recommend the consideration of arthropods in the environmental assessment of noise-producing infrastructure

Quantifying regional biodiversity in the tropics : a case study of freshwater fish in Trinidad and Tobago

Funding: European Research Council (AdG BioTIME 250189 and PoC BioCHANGE 727440) (AEM).Extinction rates are predicted to accelerate during the Anthropocene. Quantifying and mitigating these extinctions demands robust data on distributions of species and the diversity of taxa in regional biotas. However, many assemblages, particularly those in the tropics, are poorly characterized. Targeted surveys and historical museum collections are increasingly being used to meet the urgent need for accurate information, but the extent to which these contrasting data sources support meaningful inferences about biodiversity change in regional assemblages remains unclear. Here, we seek to elucidate uncertainty surrounding regional biodiversity estimates by evaluating the performance of these alternative methods in estimating the species richness and assemblage composition of the freshwater fish of Trinidad & Tobago. We compared estimates of regional species richness derived from two freshwater fish datasets: a targeted two year survey of Trinidad & Tobago rivers and historical museum collection records submitted to The University of the West Indies Zoology Museum. Richness was estimated using rarefaction and extrapolation, and assemblage composition was benchmarked against a recent literature review. Both datasets provided similar estimates of regional freshwater fish species richness (50 and 46 species, respectively), with a large overlap (85%) in species identities. Regional species richness estimates based on survey and museum data are thus comparable, and consistent in the species they include. Our results suggest that museum collection data are a viable option for setting reliable baselines in many tropical systems, thereby widening options for meaningful monitoring and evaluation of temporal trends.PostprintPeer reviewe

Difficulties in benchmarking ecological null models: an assessment of current methods

Identifying species interactions and detecting when ecological communities are structured by them is an important problem in ecology and biogeography. Ecologists have developed specialized statistical hypothesis tests to detect patterns indicative of community-wide processes in their field data. In this respect, null model approaches have proved particularly popular. The freedom allowed in choosing the null model and statistic to construct a hypothesis test leads to a proliferation of possible hypothesis tests from which ecologists can choose to detect these processes. Here, we point out some serious shortcomings of a popular approach to choosing the best hypothesis for the ecological problem at hand that involves benchmarking different hypothesis tests by assessing their performance on artificially constructed datasets. Terminological errors concerning the use of Type-I and Type-II errors that underlie these approaches are discussed. We argue that the key benchmarking methods proposed in the literature are not a sound guide for selecting null hypothesis tests, and further, that there is no simple way to benchmark null hypothesis tests. Surprisingly, the basic problems identified here do not appear to have been addressed previously, and these methods are still being used to develop and test new null models and summary statistics, from quantifying community structure (e.g., nestedness and modularity) to analyzing ecological networks

Temporal overlap and co-occurrence in a guild of sub-tropical tephritid fruit flies

Studies of community assembly have emphasized snapshot comparisons of spatially replicated samples from natural assemblages. Agro-ecosystems are characterized by relatively little habitat heterogeneity and no dispersal barriers for actively flying insects. Therefore, dynamic patterns of species segregation and aggregation are more likely to reflect the direct or indirect effects of species interactions. We studied the temporal organization of a guild of 21 congeneric species of Anastrepha that colonized fruit orchards in Monte Alegre do Sul, São Paulo, Brazil. This assemblage also included the introduced Mediterranean fruit fly Ceratitis capitata. One hundred six consecutive weekly censuses (11 Jan 2002-16 Jan 2004) of flies in guava, loquat, and peach orchards revealed a pattern of minimum abundance during the coldest months of each year (June and July) and a maximum abundance during periods of flowering and fruit ripening. Overall, phenological overlap was greater than expected by chance. However, conditioned on the pattern of seasonal abundances, temporal occurrence and abundance matrices exhibited patterns of significant species segregation and anti-nestedness. In each year, the 3 orchards contained a small number of species pairs that exhibited statistically significant temporal segregation or aggregation. Most aggregated and segregated pairs reflected seasonal shifts in species presences that were not related to variation in air temperature. Most of the significant pairwise associations involved C. capitata: 8 of the 11 segregated pairs and 2 of the 7 aggregated pairs. These results suggest that species interactions between introduced and native species can be an important determinant of species associations in agro-ecosystems

The Influence of Fire on a Rare Serpentine Plant Assemblage: A Five Year Study of Darlingtonia Fens

Premise of the study: Serpentine soils have attracted the attention of evolutionary biologists for decades due to their high number of rare and endemic taxa, though less is known about the ecological factors that govern the diversity and composition of serpentine communities. Theory suggests that vegetation on these low-productivity soils will be relatively resilient to fire, the most common natural disturbance in serpentine systems. Methods: We studied the recovery of vegetation in Darlingtonia fens, a unique habitat dominated by herbaceous perennials, from a major fire that burned ~202,000 hectares in California and Oregon’s Klamath Mountains in 2002. We established permanent plots in 8 unburned and 8 burned fens in 2003 and recorded percent cover of vascular plant species. We re-sampled plots each year through 2007. Key results: Burned fens had less plant cover than unburned fens for two years after the fire. Average species density was ~10% lower in burned fens one year after the fire but ~4-8% higher for the next four years. Burned fens exhibited greater evenness, but not until four years after the fire. Differences in community composition were detected between the two fen types, but species ranks were similar, and species neither were added to, nor removed from, the burned assemblages. Conclusions: Burning of Darlingtonia fens has detectable, albeit modest effects on serpentine communities. Because fens have little or no canopy cover, fire has little influence on light availability in this system. This relatively small resource change, combined with high soil moisture and well-developed underground organs of fen plants, produces a highly resilient assemblage.Organismic and Evolutionary BiologyOther Research Uni

Geographic differences in effects of experimental warming on ant species diversity and community composition

Ecological communities are being reshaped by climatic change. Losses and gains of species will alter community composition and diversity but these effects are likely to vary geographically and may be hard to predict from uncontrolled natural experiments . In this study, we used open-top warming chambers to simulate a range of warming scenarios for ground-nesting ant communities at a northern (Harvard Forest, MA) and southern (Duke Forest, NC) study site in the eastern US. After 2.5 years of experimental warming, we found no significant effects of accumulated growing degree days or soil moisture on ant diversity or community composition at the northern site, but a decrease in asymptotic species richness and changes in community composition at the southern site. However, fewer than 10% of the species at either site responded significantly to the warming treatments. Our results contrast with those of a comparable natural experiment conducted along a nearby elevational gradient, in which species richness and composition responded strongly to changes in temperature and other correlated variables. Together, our findings provide some support for the prediction that warming will have a larger negative effect on ecological communities in warmer locales at lower latitudes and suggest that predicted responses to warming may differ between controlled field experiments and unmanipulated thermal gradients. Key words: Ants; climate change; community; elevational gradient; Formicidae; geographic range; warming experiment

Lifting the veil: richness measurements fail to detect systematic biodiversity change over three decades

While there is widespread recognition of human involvement in biodiversity loss globally, at smaller spatial extents, the effects are less clear. One reason is that local effects are obscured by the use of summary biodiversity variables, such as species richness, that provide only limited insight into complex biodiversity change. Here, we use 30 yr of invertebrate data from a metacommunity of 10 streams in Wales, UK, combined with regional surveys, to examine temporal changes in multiple biodiversity measures at local, metacommunity, and regional scales. There was no change in taxonomic or functional a-diversity and spatial b-diversity metrics at any scale over the 30-yr time series, suggesting a relative stasis in the system and no evidence for on-going homogenization. However, temporal changes in mean species composition were evident. Two independent approaches to estimate species niche breadth showed that compositional changes were associated with a systematic decline in mean community specialization. Estimates of species-specific local extinction and immigration probabilities suggested that this decline was linked to lower recolonization rates of specialists, rather than greater local extinction rates. Our results reveal the need for caution in implying stasis from patterns in a-diversity and spatial b-diversity measures that might mask non-random biodiversity changes over time. We also show how different but complementary approaches to estimate niche breadth and functional distinctness of species can reveal long-term trends in community homogenization likely to be important to conservation and ecosystem function

A stochastic model for landscape patterns of biodiversity

Many factors have been proposed to affect biodiversity patterns across landscapes, including patch area, patch isolation, edge distances, and matrix quality, but existing models emphasize only one or two of these factors at a time. Here we introduce a synthetic but simple individual-based model that generates realistic patterns of species richness and density as a function of landscape structure. In this model, we simulated the stochastic placement of home ranges in landscapes, thus combining features of existing random placement and mid-domain effect models. As such, the model allows investigation of whether and how geometric constraints on home range placement of individuals scale up to affect species abundance and richness in landscapes. The model encompassed a gradient of possible landscapes, from a strictly homogeneous landscape to an archipelago of discrete patches. The model incorporated only variation in home range size of individuals of different species, with a simple suitability index that controlled home range spread into areas of habitat and areas of inter-habitat matrix. Demographic details of birth, death, and migration, as well as effects of species interactions were not included. Nevertheless, this simple model generated realistic patterns of biodiversity, including species-area curves and increases in diversity and abundance with decreasing isolation and increasing distance from patch edges. Species-area slopes (z values) generated by the model fell within the range observed in empirical studies on both true islands and habitat patches. Isolation and edge effects were stronger when the matrix was unsuitable, and became progressively weaker as matrix suitability increased, again in accordance with many empirical studies. When applied to a real data set on the abundance of 20 small mammal species sampled in forest patches in the Atlantic Forest of Brazil, the model predicted increases in abundance and richness with increasing patch size, consistent with the general pattern observed with field data. The ability of this simple model to reproduce realistic qualitative patterns of biodiversity suggests that such patterns may be driven, at least in part, by geometric constraints acting on the placement of individual ranges, which ultimately affect biodiversity patterns at the landscape level