Takehiro Okuda

Latitudinal gradient of species diversity: multi-scale variability in rocky intertidal sessile assemblages along the Northwestern Pacific coast

This study examined the latitudinal gradient of species diversity of rocky intertidal sessile assemblages on the slopes of rocks along the Northwestern Pacific coast of Japan, located between 31°N and 43°N, by explicitly incorporating an hierarchical spatial scale into the monitoring design. The specific questions were to examine: (1) whether there is a latitudinal gradient of regional diversity, (2) how spatial components of the regional diversity (local diversity and turnover diversity) vary with latitude depending on spatial scale, and (3) whether the latitudinal gradient differs between different measures of species diversity, i.e. species richness and Simpson’s diversity index. We measured coverage and the presence or absence of all sessile organisms in a total of 150 census plots established at five shores in each of six regions. The results showed that there were clear latitudinal gradients in regional species richness and in species turnover among shores. However, these patterns were not reflected in smaller-scale local species richness. For Simpson’s diversity index, there was no evidence of latitudinal clines either in regional diversity or in spatial components. These results suggest that relative abundance of common species does not vary along latitude, while the number of rare species increases with decreasing latitude.

Seasonality in the strength and spatial scale of processes determining intertidal barnacle population growth

1. Population growth rate is determined by both density-dependent and density-independent processes. In the temperate zone, the strength and spatial scale of these processes are likely to differ seasonally, but such differences have rarely been quantitatively examined. 2. Coverage, the area occupied by organisms, is a measure of resource use in sessile marine populations. Population models used for density-based studies should be able to characterize effectively fluctuations in coverage, but few have tried to apply such models to sessile populations. 3. We observed coverage of the intertidal barnacle Chthamalus challengeri at 20 plots on four shores along the Pacific coast of Japan over 8 years. We then fitted a population model that incorporated both a density-dependent process (strength of density dependence) and density-independent processes (intrinsic growth rate and stochastic fluctuation at different spatial scales) to these data to analyse the seasonal variation of these processes and answer the following two questions: (i) How do the effects of density-dependent and density-independent processes on population growth vary seasonally? (ii) At what spatial scale, regional (tens of kilometres), shore (hundreds of metres), or rock (tens of centimetres), does density-independent stochastic fluctuation most strongly affect population size changes? 4. Barnacle population size tended to decrease in summer, when population dynamics were characterized by a relatively lower intrinsic growth rate, weaker density dependence and stronger stochastic fluctuation. In contrast, population size tended to increase in winter, reflecting a higher intrinsic growth rate, strong density dependence and weak stochastic fluctuation. 5. In summer, population growth rate was strongly affected by regional-scale stochastic fluctuation, whereas in winter it was affected more by rock-scale stochastic fluctuation, suggesting that populations were strongly affected by regional-scale processes in summer but not in winter. 6. These results indicate that seasonally variable density-dependent and density-independent processes determine the population dynamics of C. challengeri. Therefore, to understand fluctuation patterns of populations of this species, seasonality should be taken into account. Moreover, this study demonstrates that population models commonly used for density-based studies are also applicable to coverage-based population studies.

Variable processes that determine population growth and an invariant mean‐variance relationship of intertidal barnacles

Although researchers recognize that population dynamics can vary in space and time as a result of differences in biotic and abiotic conditions, spatial and temporal variability in the patterns and processes of population dynamics have not been well documented on a seasonal time frame. We quantified seasonal changes in the coverage of intertidal barnacles, Chthamalus spp., with data collected for as many as 9 years at 88 plots in five regions located along more than 1800 km of the Pacific coastline of Japan from 31° N to 43° N. To examine how seasonal changes and the spatial heterogeneity of environments can interact to influence patterns and processes of population dynamics, we analyzed the data with two models of population variability: a population dynamics model, which provides knowledge about processes that determine population growth rates; and Taylors power law, which summarizes the relationship between the temporal mean and variance of the size of a population (temporal mean-variance relationship). We found that seasonal differences were prevalent in population growth rates, as well as in the strength and spatial scales of processes that determine population growth rates. In addition, the seasonality of these rates and processes varied between habitats at different spatial scales ranging from the scale of among-rocks within a shore to that of among-regions located in different latitudes, suggesting that the effects of seasonal environmental fluctuations on population growth can depend on the spatial heterogeneity of biotic and abiotic conditions that vary at multiple spatial scales. In contrast, the evidence for spatiotemporal differences in temporal mean-variance relationships was weak. Unlike theoretical expectations, spatiotemporal differences in the variability of population size were best explained by a unique power law, despite remarkable regional and seasonal differences in the processes that determine population growth rates. These results suggest that spatiotemporal environmental variability can affect population dynamics at multiple spatial scales but do not necessarily alter the scaling law of population size variability.

Distance decay of community dynamics in rocky intertidal sessile assemblages evaluated by transition matrix models

It is well known that the similarity in species composition between two communities decays with the geographic distance that separates them. It is thus likely that the similarity in the dynamics of two communities also decays with distance, because the distance–decay relationship is fundamental in nature. However, the distance–decay relationships of community dynamics have not yet been revealed. We used transition matrix models to evaluate distance–decay relationships of seasonal community dynamics (from spring to summer) in rocky intertidal sessile assemblages along the Pacific coast of Japan between 31°N and 43°N. We evaluated the distance–decay relationships of whole-community dynamics and of three dynamics-related components—recruitment, disturbance, and species interaction (competition and facilitation)—for communities separated by distances ranging from several meters to thousands of kilometers. The similarity of the recruitment dynamics among communities declined rapidly with distance within the fine spatial scale, but only moderately within larger scales. The similarity of the disturbance dynamics was independent of distance, and the similarity of species interaction declined slightly with increasing distance. The similarity of whole-community dynamics declined rapidly with distance at a fine spatial scale and moderately at larger scales. The fact that the distance–decay relationship of whole-community dynamics was similar to that of recruitment may suggest that recruitment processes are the most important determinant of spatial variability of community dynamics at our study sites during the study period.

Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range

Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylors power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species.

Latitudinal gradients in species richness in assemblages of sessile animals in rocky intertidal zone: mechanisms determining scale‐dependent variability

1. Although latitudinal gradients in species richness within a region are observed in a range of taxa and habitats, little is known about variability in its scale dependence or causal processes. The scale-dependent variability of latitudinal gradients in species richness can be affected by latitudinal differences in (i) the regional relative abundance distribution, and (ii) the degree of aggregated distribution (i.e., intraspecific aggregation and interspecific segregation; henceforth, the degree of aggregation) reflecting differences in ecological processes among regions, which are not mutually exclusive. 2. In rocky intertidal sessile animal assemblages along Japans Pacific coast (between 31 degrees N and 43 degrees N), scale-dependent variability of the latitudinal gradient in species richness and its causal mechanisms were examined by explicitly incorporating three hierarchical spatial scales into the monitoring design: plots (50 x 100 cm), shores (78 to 235 m), and regions (16.7 to 42.5 km). 3. To evaluate latitudinal differences in the degree of aggregation, the degree of intraspecific aggregation at each spatial scale in each region was examined using the standardized Morishita index. Furthermore, the observed species richness was compared with the species richness expected by random sampling from the regional species pool using randomization tests. 4. Latitudinal gradients in species richness were observed at all spatial scales, but the gradients became steadily more moderate with decreasing spatial scale. The slope of the relative abundance distribution decreased with decreasing latitude. 5. Tests of an index of intraspecific aggregation and randomization tests indicated that although species richness at smaller scales differed significantly from species richness expected based on a random distribution, the degree of aggregation did not vary with latitude. Although some ecological processes (possibly species sorting) may have played a role in determining species richness at small spatial scales, the importance of these processes did not vary with latitude. 6. Thus, scale-dependent variability in the latitudinal gradient of species richness appears to be explained mainly by latitudinal differences in the regional relative abundance distribution by imposing statistical constraint caused by decreasing grain size.

A multistate dynamic site occupancy model for spatially aggregated sessile communities

Markov community models have been applied to sessile organisms because such models facilitate estimation of transition probabilities by tracking species occupancy at many fixed observation points over multiple periods of time. Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e., a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations. In this study, we developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error. By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real dataset of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account. Our approach can even accommodate an anisotropic spatial correlation of species composition, and may serve as a basis for inferring complex nonlinear ecological dynamics.