Aggregation and interspecific abundance-occupancy relationships

Within-species relationship of patchiness to both abundance and occupancy, as exemplified by seagrass macrobenthos

For the first time, intraspecific relationships between the macroecological metrics patchiness (P) and both abundance (A) and occupancy (O) were investigated in a faunal assemblage. As a companion study to recent work on interspecific P, A and O patterns at the same localities, intraspecific patterns were documented within each of the more dominant invertebrates forming the seagrass macrobenthos of warm–temperate Knysna estuarine bay (South Africa) and of sub-tropical Moreton Bay (Australia). As displayed interspecifically, individual species showed strong A–O patterns (mean scaling coefficient − 0.76 and mean R² > 0.8). All P–O relations were negative and most (67%) were statistically significant, although weaker (mean R² 0.5) than A–O ones; most P–A ones were also negative but fewer (43%) achieved significance, and were even weaker (mean R² 0.4); 33% of species showed no significant interrelations of either O or A with P. No species showed only a significant P–A relationship. Compared with interspecific P–A–O data from the same assemblages, power–law scaling exponents were equivalent, but R² values were larger. Larviparous species comprised 70% of the total studied, but 94% of those displaying significant patchiness interrelationships; 5 of the 9 showing no P–A or P–O relationships, however, were also larviparous. At Knysna, though not in Moreton Bay, larviparous species also showed higher levels of occupancy than non-larviparous ones, whilst non-larviparous species showed higher levels of patchiness. Dominant Moreton Bay species, but not those at Knysna, exhibited homogeneously sloped P–O relationships.

Dietary habits of the black-necked swan Cygnus melancoryphus (Birds: Anatidae) and variability of the aquatic macrophyte cover in the Río Cruces wetland, southern Chile

The black-necked swan Cygnus melancoryphus is an aquatic herbivorous bird whose dietary habits depend on the dominance and accessibility of macrophyte banks in shallow areas of coastal and limnetic wetlands in southern South America. The swans from the Río Cruces wetland in southern Chile (ca. 39°S) feed mainly on the macrophyte Egeria densa from the water column between depths from less than 0,5 and 2,0 m. A micro- histological analysis of black-necked swan feces (N = 152) collected during six sampling occasions between 2012 and 2017 confirms the preferred consumption of E. densa and highlights the impact of temporal changes in the cover of these macrophytes on the swan's diet. The dietary composition of black-necked swans appears as a reliable proxy for temporal changes in the distribution of the most common aquatic macrophytes in the Río Cruces wetland. These results highlight the importance of preserving shallow wetlands as the habitat for aquatic macrophytes that provide the main food source for these herbivorous water birds.

An Empirical and Mechanistic Explanation of Abundance-Occupancy Relationships for a Critically Endangered Nomadic Migrant

The positive abundance-occupancy relationship (AOR) is a pervasive pattern in macroecology. Similarly, the association between occupancy (or probability of occurrence) and abundance is also usually assumed to be positive and in most cases constant. Examples of AORs for nomadic species with variable distributions are extremely rare. Here we examined temporal and spatial trends in the AOR over 7 years for a critically endangered nomadic migrant that relies on dynamic pulses in food availability to breed. We predicted a negative temporal relationship, where local mean abundances increase when the number of occupied sites decreases, and a positive relationship between local abundances and the probability of occurrence. We also predicted that these patterns are largely attributable to spatiotemporal variation in food abundance. The temporal AOR was significantly negative, and annual food availability was significantly positively correlated with the number of occupied sites but negatively correlated with abundance. Thus, as food availability decreased, local densities of birds increased, and vice versa. The abundance-probability of occurrence relationship was positive and nonlinear but varied between years due to differing degrees of spatial aggregation caused by changing food availability. Importantly, high abundance (or occupancy) did not necessarily equate to high-quality habitat and may be indicative of resource bottlenecks or exposure to other processes affecting vital rates. Our results provide a rare empirical example that highlights the complexity of AORs for species that target aggregated food resources in dynamic environments.

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship.

Exploration of Trends in Interspecific Abundance-Occupancy Relationships Using Empirically Derived Simulated Communities

The interspecific abundance-occupancy relationship (AOR) is a widely used tool that describes patterns of habitat utilization and, when evaluated over time, may be used to identify large-scale changes in community structure. Our primary goal for this research was to validate the utility of AORs as temporal indicators of community state. We used long-term survey data in four regions of the northwest Atlantic coastal shelf (NWACS) to estimate the diversity of spatial behaviors in each community, which we modeled with negative binomial (NB) distributions. NB parameters were used to generate time series data for simulated communities, from which AORs were then estimated and evaluated for temporal trends. We found that AORs from simulated communities were similar in year-to-year variation to empirical relationships. In order to further understand the role of spatial diversity in the generation of AOR trends, we did additional simulations where NB parameters were manually manipulated. In one instance, we ran simulations while holding species’ parameters constant over time. This treatment effectively removed trends, suggesting that temporal change in community relationships was the result of genuine variation in intraspecific spatial use. In another set of simulations, we conducted a case study to evaluate the impact of a select group of schooling and spatially aggregating species on an especially rapid shift in AORs in the Gulf of Maine from 1973 to 1983. Removals of these species reduced the magnitudes of most trends, demonstrating their importance to observed community changes. This research directly links variation in AORs to distribution and density-related processes and provides a potentially powerful framework to identify community-level change and to test ecological and mechanistic hypotheses.

A point-process model for variance-occupancy-abundance relationships

The relationship between species abundance, the variance of the number of individuals, and species occupancy is a fundamental ecological characteristic of a community. Moreover, this relationship varies across scales, and any model for the variance-occupancy-abundance (VOA) relationship has to address its scale dependency in a consistent way. In this study, point-process theory was used to define a multiscale model that jointly predicts the VOA relationship across scales in a consistent way. This provides a tool to jointly analyze data sets collected at different scales and to give insights into the biological processes underlying the VOA relationship. This model can also account for different types of individual spatial pattern (clustered, random, or regular). Three stand-mapping data sets of tree species in tropical rain forests were used to assess the relevance of this model. When compared with four existing models, the model based on point-process theory provided the best fit to the data and was the most often ranked as the model with the best predictive performance.

Causality of the relationship between geographic distribution and species abundance

The positive relationship between a species' geographic distribution and its abundance is one of ecology's most well-documented patterns, yet the causes behind this relationship remain unclear. Although many hypotheses have been proposed to account for distribution-abundance relationships none have attained unequivocal support. Accordingly, the positive association in distribution-abundance relationships is generally considered to be due to a combination of these proposed mechanisms acting in concert. In this review, we suggest that much of the disparity between these hypotheses stems from differences in terminology and ecological point of view. Realizing and accounting for these differences facilitates integration, so that the relative contributions of each mechanism may be evaluated. Here, we review all the mechanisms that have been proposed to account for distribution-abundance relationships, in a framework that facilitates a comparison between them. We identify and discuss the central factors governing the individual mechanisms, and elucidate their effect on empirical patterns.

Variations on a theme: sources of heterogeneity in the form of the interspecific relationship between abundance and distribution

1. A positive interspecific relationship between abundance and distribution is widely considered to be one of the most general patterns in ecology. However, the relationship appears to vary considerably across assemblages, from significant positive to significant negative correlations and all shades in between. 2. This variation has led to the suggestion that the abundance-distribution relationship has multiple forms, with the corollary that different patterns may inform about, or have different, causes. However, this variation has never been formally quantified, nor has it been determined whether the observed variation is indicative of sampling error in estimating a single effect or of real heterogeneity in such relationships. Here, we use the meta-analytical approach to assess variation in abundance-distribution relationships, and to test different hypotheses for it. 3. Analysis of 279 relationships found a mean effect size of 0.655, which was both highly significantly different from zero and indicative of a strong positive association between abundance and distribution. However, effect sizes were highly heterogeneous, supporting the contention that this relationship does indeed have multiple forms. 4. Most notably, relationships vary significantly in strength across realms, with the strongest in the marine and intertidal, intermediate relationships for terrestrial and parasitic assemblages, and the weakest relationships in freshwater systems. Effect sizes in all of the aquatic realms are homogeneous, suggesting that realm is an important source of the heterogeneity observed across all studies. We posit that this may be because the different spatial structure of the environment in each realm affects the opportunity for the dispersal of individuals between sites. 5. Some of the remaining heterogeneity in effect sizes for terrestrial assemblages could be explained by partitioning assemblages by habitat, scale, biogeographical region and taxon, but considerable heterogeneity in effect sizes for terrestrial and parasitic assemblages remained unexplained.

Distributions of habitat suitability and the abundance-occupancy relationship

Positive abundance-occupancy relationships (a relationship between the number of sites a species occupies and the average density of individuals in occupied sites) are widespread through a range of taxa. The simplest model for this is the "vital rates" model, which proposes that habitat suitability varies spatially; increasing average habitat quality thus leads to simultaneous increases in average densities within occupied areas, as well as the total area that is habitable. This model has not been tested. We develop a general analytical version of this model and show that it predicts that the skewness of population size or aggregation of individuals within sites should vary systematically with density and occupancy, depending on the distribution of habitat suitability, and that the variance in occupancy should be highest at low densities. We compare these predictions with data from the British Trust for Ornithology's Common Birds Census, and we find systematic changes in both variance and skewness of density, both intra- and interspecifically.

Negative density-distribution relationship in butterflies

BACKGROUND

Because "laws of nature" do not exist in ecology, much of the foundations of community ecology rely on broad statistical generalisations. One of the strongest generalisations is the positive relationship between density and distribution within a given taxonomic assemblage; that is, locally abundant species are more widespread than locally sparse species. Several mechanisms have been proposed to create this positive relationship, and the testing of these mechanisms is attracting increasing attention.

RESULTS

We report a strong, but counterintuitive, negative relationship between density and distribution in the butterfly fauna of Finland. With an exceptionally comprehensive data set (data includes all 95 resident species in Finland and over 1.5 million individuals), we have been able to submit several of the mechanisms to powerful direct empirical testing. Without exception, we failed to find evidence for the proposed mechanisms creating a positive density-distribution relationship. On the contrary, we found that many of the mechanisms are equally able to generate a negative relationship.

CONCLUSION

We suggest that one important determinant of density-distribution relationships is the geographical location of the study: on the edge of a distribution range, suitable habitat patches are likely to be more isolated than in the core of the range. In such a situation, only the largest and best quality patches are likely to be occupied, and these by definition can support a relatively dense population leading to a negative density-distribution relationship. Finally, we conclude that generalizations about the positive density-distribution relationship should be made more cautiously.