Occupancy frequency distributions: patterns,artefacts and mechanisms

Numerous hypotheses have been proposed to explain the shape of occupancy frequency distributions (distributions of the numbers of species occupying different numbers of areas). Artefactual effects include sampling characteristics, whereas biological mechanisms include organismal, niche-based and meta-population models. To date, there has been little testing of these models. In addition, although empirically derived occupancy distributions encompass an array of taxa and spatial scales, comparisons between them are often not possible because of differences in sampling protocol and method of construction. In this paper, the effects of sampling protocol (grain, sample number, extent, sampling coverage and intensity) on the shape of occupancy distributions are examined, and approaches for minimising artefactual effects recommended. Evidence for proposed biological determinants of the shape of occupancy distributions is then examined. Good support exists for some mechanisms (habitat and environmental heterogeneity), little for others (dispersal ability), while some hypotheses remain untested (landscape productivity, position in geographic range, range size frequency distributions), or are unlikely to be useful explanations for the shape of occupancy distributions 'species specificity and adaptation to habitat, extinction-colonization dynamics). The presence of a core (class containing species with the highest occupancy) mode in occupancy distributions is most likely to be associated with larger sample units, and small homogenous sampling areas positioned well within and towards the range centers of a sufficient proportion of the species in the assemblage. Satellite (class with species with the lowest occupancy) modes are associated with sampling large, heterogeneous areas that incorporate a large proportion of the assemblage range. However, satellite modes commonly also occur in the presence of a core mode, and rare species effects are likely to contribute to the presence of a satellite mode at most sampling scales. In most proposed hypotheses, spatial scale is an important determinant of the shape of the observed occupancy distribution. Because the attributes of the mechanisms associated with these hypotheses change with spatial scale, their predictions for the shape of occupancy distributions also change. To understand occupancy distributions and the mechanisms underlying them, a synthesis of pattern documentation and model testing across scales is thus needed. The development of null models, comparisons of occupancy distributions across spatial scales and taxa, documentation of the movement of individual species between occupancy classes with changes in spatial scale, as well as further testing of biological mechanisms are all necessary for an improved understanding of the distribution of species and assemblages within their geographic ranges.     

The Co-Occurrence of Species and the Co-Diversity of Sites in Neutral Models of Biodiversity

Patterns of co-occurrence of species are widely used to assess the fit of ecological neutral models to empirical patterns. The mathematically equivalent patterns of co-diversity of sites, in contrast, have been considered only indirectly and analyses normally are focused on the spatial distribution of species richness, rather than on the patterns of species sharing. Here we use two analytical tools (range-diversity plots and rank plots) to assess the predictions of simple neutral models in relation to patterns of co-occurrence and co-diversity. Whereas a fully stochastic null model predicts zero average among species and among sites, neutral models generate systems with low levels of covariance among species and high levels of positive covariance among sites. These patterns vary with different combinations of dispersal and speciation rates, but are always linked to the shape, symmetry, and spread of the range-size and species-richness frequency distributions. Non-homogeneous patterns of diversity and distribution arise in neutral models because of the spatial arrangement of sites and their concomitant similarity, which is reflected also in the spread of the range-size frequency distribution. The nearly null covariance among species, in contrast, implies low variance in species richness of sites and very slim frequency distributions. In real world assemblages of Mexican volant and non-volant mammals, patterns of range-size and species-richness frequency distribution are similar to those generated by neutral models. However, when the comparison includes the covariance both for species (co-occurrence) and for sites (co-diversity), empirical patterns differ significantly from the predictions of neutral models. Because of the mathematical links between the covariance in the distribution of species and the variance of species-richness values and between the covariance in species sharing among sites and the variance of range-size values, a full understanding of patterns of diversity calls for the simultaneous analysis of co-occurrence and co-diversity.     

Modeling species distributions by breaking the assumption of self-similarity

Species distributions are commonly measured as the number of sites, or geographic grid cells occupied. These data may then be used to model species distributions and to examine patterns in both intraspecific and interspecific distributions. Harte et al. (1999) used a model based on a bisection rule and assuming self-similarity in species distributions to do so. However, this approach has also been criticized for several reasons. Here we show that the self-similarity in species distributions breaks down according to a power relationship with spatial scales, and we therefore adopt a power-scaling assumption for modeling species occupancy distributions. The outcomes of models based on these two assumptions (self-similar and power-scaling) have not previously been compared. Based on Harte's bisection method and an occupancy probability transition model under these two assumptions (self-similar and power-scaling), we compared the scaling pattern of occupancy (also known as the area-of-occupancy) and the spatial distribution of species. The two assumptions of species distribution lead to a relatively similar interspecific occupancy frequency distribution pattern, although the spatial distribution of individual species and the scaling pattern of occupancy differ significantly. The bimodality in occupancy frequency distributions that is common in species communities, is confirmed to a result for certain mathematical and statistical properties of the probability distribution of occupancy. The results thus demonstrate that the use of the bisection method in combination with a power-scaling assumption is more appropriate for modeling species distributions than the use of a self-similarity assumption, particularly at fine scales.     

Temporally stable abundance–occupancy relationships and occupancy frequency patterns in stream insects

The interspecific relationship between local abundance and regional distribution, as well as the occupancy frequency distribution, are widely studied topics in macroecology. A positive abundance-occupancy relationship has been found in a majority of studies, and satellite species modes are typically dominant in occupancy frequency distributions. However, there are a number of exceptions to these "general" findings, and only a few studies have examined these patterns and their temporal variability in stream organisms. I examined both abundance-occupancy relationships and occupancy frequency distributions in stream insects in a boreal drainage system over six consecutive years. I found that the positive interspecific abundance-occupancy relationship was highly stable temporally, with coefficients of determination ranging from 0.25 to 0.47 over the years. There were no strong differences in the strength and slope of the abundance-occupancy relationship between non-predatory and predatory insect species in each year. Temporally stable abundance-occupancy relationships were paralleled by among-year patterns in both abundance and occupancy, with locally abundant and widely distributed species remaining locally abundant and widely distributed over the years, while locally uncommon and regionally rare species showed the opposite. Occupancy frequency distributions were strongly right-skewed, mirroring the dominance of the left-most satellite mode of regionally rare species. That the abundance-occupancy relationship, species' abundances and distributions, as well as the dominance of satellite species in occupancy frequency distribution were temporally stable suggest that niche-based models are strong candidates for explaining these patterns in stream insects. By contrast, metapopulation-based models that predict clear temporal variability in species' abundance and occupancy, as well as bimodal occupancy frequency distributions, are less plausible candidates for explaining the observed patterns. The present findings are the opposite to those in some terrestrial studies, but they are in agreement with other terrestrial studies and with a few previous studies on stream organisms.     

ARE RANGE‐SIZE DISTRIBUTIONS CONSISTENT WITH SPECIES‐LEVEL HERITABILITY?

The concept of species-level heritability is widely contested. Because it is most likely to apply to emergent, species-level traits, one of the central discussions has focused on the potential heritability of geographic range size. However, a central argument against range-size heritability has been that it is not compatible with the observed shape of present-day species range-size distributions (SRDs), a claim that has never been tested. To assess this claim, we used forward simulation of range-size evolution in clades with varying degrees of range-size heritability, and compared the output of three different models to the range-size distribution of the South American avifauna. Although there were differences among the models, a moderate-to-high degree of range-size heritability consistently leads to SRDs that were similar to empirical data. These results suggest that range-size heritability can generate realistic SRDs, and may play an important role in shaping observed patterns of range sizes.     

Disentangling scale dependencies in species environmental niches and distributions

Understanding species’ responses to environmental conditions, and how these ­species–environment associations shape spatial distributions, are longstanding goals in ecology and biogeography. However, an essential component of species–environment relationships – the spatial unit, or grain, at which they operate – remains unresolved. We identify three components of scale‐dependence in analyses of species–environment associations: 1) response grain, the grain at which species respond most strongly to their environment; 2) environment spatial structure, the pattern of spatial autocorrelation intrinsic to an environmental factor; and 3) analysis grain, the grain at which analyses are conducted and ecological inferences are made. We introduce a novel conceptual framework that defines these scale components in the context of analyzing species–environment relationships, and provide theoretical examples of their interactions for species with various ecological attributes. We then use a virtual species approach to investigate the impacts of each component on common methods of measuring and predicting species–environment relationships. We find that environment spatial structure has a substantial impact on the ability of even simple, univariate species distribution models (SDMs) to recover known species–­environment associations at coarse analysis grains. For simulated environments with ‘fine’ and ‘intermediate’ spatial structure, model explanatory power, and the frequency with which simple SDMs correctly estimated a virtual species’ response to the simulated environment, dramatically declined as analysis grain increased. Informed by these results, we use a scaling analysis to identify maximum analysis grains for individual environmental factors, and a scale optimization procedure to determine the grain of maximum predictive accuracy. Implementing these analysis grain thresholds and model performance standards in an example east African study system yields more accurate distribution predictions, compared to SDMs independently constructed at arbitrary analysis grains. Finally, we integrate our conceptual framework with virtual and empirical results to provide practical recommendations for researchers asking common questions about species–environment relationships.     

Range size in mid-domain models of species diversity

Geographical patterns of species diversity have been examined using mid-domain null models, in which the ranges of individual species are simulated by randomly arranging them on a bounded one- or two-dimensional continent. These models have shown that structured patterns in the geographical distribution of biodiversity can arise even under a fully stochastic procedure. In particular, mid-domain models have demonstrated that the random generation of ranges of different sizes and locations can produce a gradient of species diversity similar to the one found in real assemblages, with a peak at the middle of a continent. A less explored feature of mid-domain models is the pattern of range-size frequency distribution. Numerical simulations have provided some insights about the geographic pattern of average range size, but no exploration of the shape of range-size frequency distributions has been carried out. Here I present analytical and numerical models that generate explicit predictions for patterns of range size under the assumptions of mid-domain models of species diversity. Some generalizations include: (1) Mid-domain models predict no geographic gradient of average range size; the mean range size of species occurring at any point on a continent is constant (0.5 of the extent of the continent in the one-dimensional model, 0.25 of the area of the continent in the two-dimensional case); (2) Variance in range size is lowest at the middle of a continent and highest near the corners of a square-shaped continent; (3) The range-size frequency distribution is highly right-skewed at any point of a continent, but the skewness is highest near the corners. Despite their alleged weaknesses, mid-domain models are adequate null models against which real-world patterns can be contrasted.     

Odonate species occupancy frequency distribution and abundance–occupancy relationship patterns in temporal and permanent water bodies in a subtropical area

This paper investigates species richness and species occupancy frequency distributions (SOFD) as well as patterns of abundance–occupancy relationship (SAOR) in Odonata (dragonflies and damselflies) in a subtropical area. A total of 82 species and 1983 individuals were noted from 73 permanent and temporal water bodies (lakes and ponds) in the Pampa biome in southern Brazil. Odonate species occupancy ranged from 1 to 54. There were few widely distributed generalist species and several specialist species with a restricted distribution. About 70% of the species occurred in <10% of the water bodies, yielding a surprisingly high number of rare species, often making up the majority of the communities. No difference in species richness was found between temporal and permanent water bodies. Both temporal and permanent water bodies had odonate assemblages that fitted best with the unimodal satellite SOFD pattern. It seems that unimodal satellite SOFD pattern frequently occurred in the aquatic habitats. The SAOR pattern was positive and did not differ between permanent and temporal water bodies. Our results are consistent with a niche‐based model rather than a metapopulation dynamic model.     

Ranked species occupancy curves reveal common patterns among diverse metacommunities

Aim Community ecologists often compare assemblages. Alternatively, one may compare species distributions among assemblages for macroecological comparisons of species niche traits and dispersal abilities, which are consistent with metacommunity theory and a regional community concept. The aim of this meta‐analysis is to use regressions of ranked species occupancy curves (RSOCs) among diverse metacommunities and to consider the common patterns observed. Location Diverse data sets from four continents are analysed. Methods Six regression models were translated from traditional occupancy frequency distributions (OFDs) and are distributed among four equation families. Each regression model was fitted to each of 24 data sets and compared using the Akaike information criterion. The analysed data sets encompass a wide range of spatial scales (5 cm–50 km grain, 2–7000 km extent), study scales (11–590 species, 6–5114 sites) and taxa. Observed RSOC regressions were tested for the differences in scale and taxa. Results Three RSOC models within two equation families (exponential and sigmoidal) are required to describe the very different data sets. This result is generally consistent with OFD research, but unlike OFD‐based expectations the simple RSOC patterns are not related to spatial scale or other factors. Species occupancy in diverse metacommunities is efficiently summarized with RSOCs, and multi‐model inference reliably distinguishes among alternative RSOCs. Main conclusions RSOCs are simple to generate and analyse and clearly identified surprisingly similar patterns among very different metacommunities. Species‐specific hypotheses (e.g. niche‐based factors and dispersal abilities) that depend on spatial scale may not translate to diverse metacommunities that sample regional communities. A novel set of three metacommunity succession and disturbance hypotheses potentially explain RSOC patterns and should be tested in subsequent research. RSOCs are an operational approach to the regional community concept and should be useful in macroecology and metacommunity ecology.     

A dynamic multi‐scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species

Distribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi‐scale model is currently unpublished. We extended multi‐scale models to account for the dynamic processes governing species distributions, while concurrently modeling local‐scale availability. We fit the model to data for lark buntings and chestnut‐collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine‐scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.     

Are there latitudinal and altidudinal Rapoport effects in the geographic ranges of Andean passerine birds?

We analysed the range-sizes of 835 Andean passerine species (including 414 endemics and 421 non-endemics) to test for latitudinal and altitudinal Rapoport effects (LRE and ARE). We tested for positive range-size: latitude/altitude correlations using three different methods: (i) Rohde's mid-point method, (ii) species sorted out by altitude, and (iii) a phylogenetic comparative method (CAIC). Using Rohde's mid-point method, the mean latitudinal extent of species does not follow a Rapoport pattern, but the mean latitudinal occupancy of all passerines and non-endemics do increase with latitude. The latitudinal ranges of endemics sorted out by altitude follow a reverse Rapoport effect, but non-endemics support the pattern. CAIC confirms the latitudinal increase in the occupancy of non-endemics, but regressions have low coefficients of determination. The ARE is supported by the mean altitudinal extent of species, but the trend vanishes when controlling for geometric effects. Low-altitude species occupy about the same proportion of the available altitudinal space as do high-altitude ones. Our analyses suggest that latitude and altitude have low explanatory power for understanding the spatial variation in range-sizes at a continental scale. We show how different patterns can emerge from applying different criteria to the analysis of data.     

Hierarchical multi-scale occupancy estimation for monitoring wildlife populations

Occupancy estimation is an effective analytic framework, but requires repeated surveys of a sample unit to estimate the probability of detection. Detection rates can be estimated from spatially replicated rather than temporally replicated surveys, but this may violate the closure assumption and result in biased estimates of occupancy. We present a new application of a multi-scale occupancy model that permits the simultaneous use of presence–absence data collected at 2 spatial scales and uses a removal design to estimate the probability of detection. Occupancy at the small scale corresponds to local territory occupancy, whereas occupancy at the large scale corresponds to regional occupancy of the sample units. Small-scale occupancy also corresponds to a spatial availability or coverage parameter where a species may be unavailable for sampling at a fraction of the survey stations. We applied the multi-scale occupancy model to a hierarchical sample design for 2 bird species in the Black Hills National Forest: brown creeper (Certhia americana) and lark sparrow (Chondestes grammacus). Our application of the multi-scale occupancy model is particularly well suited for hierarchical sample designs, such as spatially replicated survey stations within sample units that are typical of avian monitoring programs. The model appropriately accounts for the non-independence of the spatially replicated survey stations, addresses the closure assumption for the spatially replicated survey stations, and is useful for decomposing the observation process into detection and availability parameters. This analytic approach is likely to be useful for monitoring at local and regional scales, modeling multi-scale habitat relationships, and estimating population state variables for rare species of conservation concern. © 2011 The Wildlife Society.     

Relationships between distribution and abundance vary with spatial scale and ecological group in stream bryophytes

1. We examined whether the local abundance of stream bryophytes in a boreal drainage basin (Koutajoki system in northeastern Finland) correlated with their: (i) regional occupancy; (ii) provincial distribution in northwestern Europe; and (iii) global range size. We specifically tested whether aquatic and semi‐aquatic species differ in their distribution–abundance relationships. We also analysed the frequency distributions of occupancy at two spatial scales: within the focal drainage system and across provinces of northwestern Europe. 2. Regional occupancy and mean local abundance of stream bryophytes were positively correlated, and the relationship was rather strong in aquatic species but very weak in semi‐aquatic species. Local abundance was related neither to provincial distribution nor global distribution. 3. Species frequency distributions differed between regional occupancy and provincial distribution. While most species were rare with regard to their regional occupancy within the focal drainage system, most of the same set of species were common and occurred in most provinces in northwestern Europe. 4. The results indicate the presence of dominants (core species) and transients/subordinates (satellite species) among stream bryophytes, highlighting marked differentiation in life‐history strategies and growth form. The observed abundance–occupancy relationships suggest that dispersal limitation and metapopulation processes may govern the dynamics of obligatory aquatic stream bryophytes. In semi‐aquatic species, however, habitat availability may be more important in contributing to regional occupancy.     

How are tree species distributed in climatic space? A simple and general pattern

Aim Although many factors undoubtedly affect species geographic distributions, can a single, simple model nonetheless capture most of the spatial variation in the probability of presence/absence in a large set of species? For 482 North American tree species that occur east of the Rocky Mountains, we investigated the shape(s) of the relationship between the probability of occupancy of a given location and macroclimate, and its consistency among species and regions. Location North America. Methods Using Little's tree range maps, we tested four hypothetical shapes of response relating occupancy to climate: (1) high occupancy of all suitable climates; (2) threshold response (i.e. unsuitable climates exclude species, but within the thresholds, species presence is independent of climate); (3) occupancy is a bivariate normal function of annual temperature and precipitation; and (4) asymmetric limitation (i.e. abiotic factors set abrupt range limits in stressful climates only). Finally, we compared observed climatic niches with the occupancy of similar climates on off‐shore islands as well as west of the Rockies. Results (a) Species' distributions in climatic space do not have strong thresholds, nor are they systematically skewed towards less stressful climates. (b) Occupancy can generally be described by a bivariate normal function of temperature and precipitation, with little or no interaction between the two variables. This model, averaged over all species, accounts for 82% of the spatial variation in the probability of occupancy of a given area. (c) Occupied geographic ranges are typically ringed by unoccupied, but climatically suitable areas. (d) Observed climatic niche positions are largely conserved between regions. Main conclusions We conclude that, despite the complexities of species histories and biologies, to a first approximation most of the variation in their geographic distributions relates to climate, in similar ways for nearly all species.     

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.     

Shared or distinct responses between intermediate and satellite stream fish species in an altered Amazonian River?

Environmental and spatial variables can distinctly influence the occupancy frequency distributions in stream fish. From a metacommunity context, we tested the following hypothesis, intermediate species are governed by dispersal and niche-based processes; in contrast, satellite species are governed by niche-based processes. To test this, we separately analyzed three data sets, the entire metacommunity, the intermediate species and the satellite species, using a forward selection of explanatory variables, and a partial Redundancy Distance Analysis. The fish and 31 variables of 52 stream reaches of a Brazilian river basin in the Western Amazon were collected during the dry period of 2012. The results for all of the data set revealed two different patterns: on one side, satellite species revealed that niche and dispersal-based processes were the most important; on the other side, for intermediate species and for all of the species set, only dispersal-based processes were the most important. For the data set including all of the species and the intermediate species, the variance was explained mainly by landscape scale variables. By contrast, the variance within the satellite species set was explained by local scale variables. Management efforts for intermediate species should be taking at larger scale, but they are usually less critical for the maintenance of aquatic biodiversity; on the other hand, management efforts for satellite species should be taken at smaller scale and based on specific biological and ecological information for the focal species.     

Scale dependency of diversity components estimated from primary biodiversity data and distribution maps

Different sources of information about biodiversity may lead to unrealistic or biased estimation of its components, with different patterns according to the scale of analysis. In this study, we analyse patterns of species richness at the local (average alpha) and regional (gamma) scales, and the relationship between them (Whittaker's beta), in central Mexico, using as a source of data for the species' distributions: (1) museum specimen occurrence data for birds, and (2) distribution maps based on ecological niche models developed and refined by experts. We performed analyses at five spatial resolutions (1/32°−1/2°). Scale changes (grain and extent) affected significantly the estimates of average alpha, gamma, and beta. Use of raw occurrence data vs. distribution maps yielded contrasting results, with raw data underestimating alpha and overestimating beta, as functions of area. As regards species–area relationships, our results suggest a natural decomposition of factors into an area-invariant component (related to alpha), and an area dependent factor (related to beta). Most of our results are maintained in a null model that randomizes occurrences without changing observed range-size distributions. From this result we argue that average alpha and Whittaker's beta capture little information about the spatial covariation of species distribution patterns.     

Spatial and temporal changes in occupancy frequency distribution patterns of freshwater macrophytes in Finland

A useful method for characterizing biological numerous assemblages at regional scales is the species occupancy frequency distribution (SOFD). An SOFD shows the number or proportion of study sites each species occurred. Species that occur at only a few sites are termed satellite species, while species that occur at many sites are termed core species.This study is the first to document and assess SOFD patterns in aquatic macrophytes. It characterizes SOFD patterns of freshwater macrophyte assemblages in Finland at two spatial and two temporal scales. For this, I analyzed three published datasets on freshwater macrophyte distributions: two from studies conducted at a local scale and the third from large national surveys. One local study and the national study also included data on temporal variation in species occupancy frequencies.In the national study, the number of core and satellite species varied slightly between the older and the newer survey, respectively. Among the 113 waterbodies surveyed as part of the national study, the SOFD followed a unimodal satellite pattern. However, for the older dataset (from the 1930s), a bimodal symmetric pattern also fit the SOFD data well. At the local scale, I observed geographical variation in SOFD patterns. The dataset from southern Finland followed a unimodal satellite SOFD pattern; data from central Finland instead displayed a bimodal symmetric SOFD pattern, although they also fit equally well with a bimodal truncated pattern. Moreover, temporal patterns in central Finland seemed to demonstrate a shift from a bimodal symmetric to a bimodal asymmetric SOFD probably.Geographical variation in the SOFD pattern may be due to variation in the regional species pool. The temporal changes in SOFD pattern may be due to lake eutrophication and anthropogenic disturbance around waterbodies, which may increase number of macrophyte species.