12. Theories of Simplification and Scaling of Spatially Distributed Processes

Patterns and functioning of communities, which are determined by a set of processes operating at a large variety of spatial and temporal scales, exhibit quite high context‐dependency and low predictability at the fine spatial scales at which recent studies have concentrated. More attention to broader scale and across‐scale phenomena may be useful to search for general patterns and rules in communities. In this context, it is effective to incorporate hierarchical spatial scale explicitly into the experimental and sampling design of field studies, an approach referred to here as the spatial hierarchical approach, focusing on a particular assemblage in which biological interaction and species life history are well known. The spatial hierarchical approach can provide insight into the effects of scale in operating processes and answers to a number of important questions in community ecology such as: (1) detection of patterns and processes in spatiotemporal variability in communities, including how to explain the partitioning of pattern information of species diversity at a broad scale into finer scales, and the pattern of spatial variability of community properties at the finest spatial scale; (2) evaluation of changes in patterns observed in macroecology at finer scales; (3) testing of models explaining the coexistence of competing species; and (4) detection of latitudinal patterns in spatiotemporal variability in communities and their causal processes.

We questioned the different interpretations of ecological sexual segregation from a novel perspective, i.e., by carrying out diverse temporal and spatial scale analyses within a long-term study (1984–2003). Thus we combined spatial (small/large) and temporal (small/large) scale analyses to identify the factors generating sexual segregation in fallow deer in San Rossore, Italy. The study site was divided into an eastern sector characterized by human disturbance (DS) and a western undisturbed sector (US). According to census data, human presence increased in DS from 1984, and while females gradually abandoned it, males remained—thus supporting the predation risk hypothesis (large spatial and temporal scale)—and actually increased their presence in DS, where they seemingly benefited from a lower female density. This supported the indirect competition hypothesis. The analysis of data on a large temporal and small spatial scale confirmed that intersexual competition, in particular for grass, was higher in a crowded pasture in US. Observations by means of radio-telemetry of 23 adult females and 25 adult males (1997–2001, reduced temporal and large spatial scale) showed that large scale segregation was relevant during the day and disappeared at night, when disturbance was absent and also the females reached DS. This also supported the predation risk hypothesis. Moreover, sexes showed different habitat choices inside DS at night, thus supporting the forage selection hypothesis (small spatial and temporal scale). In conclusion, failure to address the whole set of combinations of spatial and temporal scale analyses would have led to monocausal explanations of ecological sexual segregation.

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature (SST) from remote sensing during August to October of 2003–2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales (0.5°, 1° and 2°), four longitude scales (0.5°, 1°, 2° and 4°), and three temporal scales (week, fortnight, and month). The coefficients of variation (CV) of the weekly, biweekly and monthly suitability index (SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

Habitat fragmentation continues to occur despite increasing evidence of its adverse effects on ecosystems. One of the major detrimental effects of roads and traffic is the creation of barriers or filters to the movement of wildlife, ultimately disconnecting some populations. The authors' understanding of the extent to which roads reduce the movement of biota is mostly based on field-based observational methods of inferring animal movement, and to a much smaller extent, on allele frequency-based genetic analyses. Field-based methods, as it is typically feasible to apply them, tend to be informative at fine temporal and spatial scales. Allele frequency-based genetic methods are informative at broad geographic scales but at timescales usually greater than recent disturbance events. Contemporary analyses based on genotypes of individual organisms (called “genotypic” approaches herein) can augment these other approaches. They can be informative at fine spatial and temporal scales, are readily scaled up, and are complementary to the other field-based approaches. In genotypic analyses, every capture can be effectively a recapture, relieving a major limitation in sample size. They can evaluate the influence of even recently constructed roads on movements and their emergent effects on important population processes at the spatial and temporal scales of interest to wildlife and infrastructure managers. Information derived from genetic and field-based methods can be used to model the viability of populations influenced by roads and to evaluate and monitor mitigation efforts. Despite some excellent examples, the authors suggest that such applications are still rare relative to their potential. This paper emphasizes some of the detailed inferences that can be made using different types of genetic analyses, and suggests paths by which researchers in road ecology can incorporate genetic approaches. The authors recommend that the proven capacities of genetic techniques be routinely explored as approaches to quantify the diverse influences of roads on wildlife populations. With appropriate expertise, molecular ecology can be done extremely inexpensively. It is conducted within the same funding frameworks as field-based approaches and, in budgeting funding applications, molecular ecology maintenance costs are about 20–30% of payroll, in line with other disciplines and approaches. This and other common arguments against application of genetic approaches are often based on misconceptions, or limitations that no longer apply.

A whole-lake acoustic telemetry array was utilized to monitor the three-dimensional position of 20 largemouth bass (Micropterus salmoides). Code division multiple access (CDMA) technology enabled the simultaneous monitoring of the 20 transmitters (equipped with pressure and temperature sensors) at 15 s intervals with sub-meter accuracy. Fish were monitored between November 2003 and April 2004 to evaluate the behaviour of fish across different temporal and spatial scales. The distance moved by largemouth bass, assessed both on a daily and hourly basis, varied by season and was positively correlated with water temperature. For example, daily movement rates were 2.69 ± 1.45 km/day in mid November (average daily water temperature 5.9°C), 2.24 ± 0.73 km/day in early January (5.1°C), and 7.28 ± 2.62 km/day in mid April (7.7°C). Interestingly, daily movement rates varied by as much as 25 fold among individual fish. Visualization of fish swimming paths revealed that whereas some fish occupied discrete areas and made only localized movements, other individuals made lengthier journeys covering much of the lake in periods of as little as one day. Analysis of fish behaviour at a finer temporal scale revealed that during the winter, fish spend more than 95% of their time swimming at speeds less than 0.1 m/s (0.07 ± 0.24 m/s). During late fall, and especially in spring, swimming speeds were higher with mean swimming speeds of 0.11 ± 0.27 m/s and 0.19 ± 0.29 m/s, respectively. When the telemetry dataset was queried to simulate 24 h manual tracking intervals, it was clear that manual tracking data would not have been representative of actual daily movement rates, underestimating daily movement and swimming speeds by at least 75 fold. This study identifies the importance of evaluating fish activity at multiple spatial (whole lake to sub-meter position) and temporal (seasonal to seconds) scales and illustrates the potential of CDMA telemetry to yield such data.

Ecosystem monitoring for ecosystem‐based management: using a polycentric approach to balance information trade‐offs

The assumption that the description of any system depends on spatial and temporal scale has moved researchers to incorporate scale as another factor in determining the mechanisms explaining species diversity and distribution. Although most researchers agree that processes that occur at different spatial and temporal scales affect ecological communities, empirical support is still scarce. In this paper, we seek to discern whether the relationship between abundance, biomass, and species diversity, on the one hand, and habitat heterogeneity, on the other, holds across temporal and spatial scales. Moreover, we analyse whether the pattern/variation found depends on the taxonomic level, and the diversity index used. To answer these questions, we sampled arthropod assemblages across three nested temporal and spatial scales. In general, we found variability in the responses to habitat heterogeneity across scales according to the assemblage descriptor, the taxonomic level selected, and the diversity index used. Our results suggest that generalization is difficult and extrapolation should be made with caution. Moreover, the use of more than one diversity index would provide additional and complementary information about species‐distribution patterns and the mechanisms generating these patterns.

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 401:221-232 (2010) - DOI: https://doi.org/10.3354/meps08422 Population genetic structure of the Japanese eel Anguilla japonica: panmixia at spatial and temporal scales Yu-San Han1,2,*, Chia-Ling Hung2, Yi-Fen Liao2, Wann-Nian Tzeng1,2 1Department of Life Science and 2Institute of Fisheries Science, College of Life Science, National Taiwan University, Taipei 106, Taiwan *Email: yshan@ntu.edu.tw ABSTRACT: Since the 1970s, the population of the Japanese eel Anguilla japonica has dramatically declined in East Asia. Consequently, conservation and resource management of this species are urgently required. However, the population genetic structure of this species, in temporal and spatial scales, is still poorly understood. We used 8 polymorphic microsatellite DNA loci to investigate its genetic composition. For cohort analysis, juvenile (glass) eels were collected yearly between 1986 and 2007 from the Danshui River, Taiwan; for arrival wave analysis, glass eels were collected monthly from Fulong Estuary, Taiwan; and for spatial analysis, glass eels were collected from Taiwan, China, Korea and Japan. Genetic differentiation among annual cohorts, arrival waves and spatial samples was very low; a significant difference was observed among annual cohorts and spatial samples, but not among arrival waves. However, specific temporal or spatial scale patterns were not seen in either pairwise genetic comparisons or the phylogenetic tree of all samples. Occasional genetic variations among samples occurred randomly, but a stable lasting genetic structure could not be formed. The isolation by distance (IBD) test showed no evidence of genetic structuring at the spatial scale, and the results of the isolation by time (IBT) test were insignificant among arrival waves. Genetic heterogeneity over a 21 yr time scale showed marginal significance, potentially reflecting a genetic drift in the Japanese eel. Our results suggest the existence of a single panmictic population of Japanese eel in East Asia. Therefore, the Japanese eel should be considered as a single management unit for conservation. KEY WORDS: Genetic differentiation · Japanese eel · Anguilla japonica · Microsatellite DNA · Panmixia · Isolation by time · IBT · Isolation by distance · IBD Full text in pdf format PreviousNextCite this article as: Han YS, Hung CL, Liao YF, Tzeng WN (2010) Population genetic structure of the Japanese eel Anguilla japonica: panmixia at spatial and temporal scales. Mar Ecol Prog Ser 401:221-232. https://doi.org/10.3354/meps08422 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 401. Online publication date: February 22, 2010 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2010 Inter-Research.

Relative importance of spatial and temporal scales in a patchy environment

Hierarchies and spatial scale in process geomorphology: a review

Animals interact with their environment at multiple spatial, temporal, and behavioral scales. Few studies of selection for latrine sites by river otters (Lontra canadensis) have considered spatial scale, and no studies have integrated scales of behavior. We used an information theoretic model comparison approach to identify elements of otter habitat that influence the presence, consistency, and intensity of latrine-site activity at 2 spatial scales. We identified and monitored 73 latrine sites in central British Columbia, Canada, during the open-water season in 2007 and 2008. We inventoried latrines and randomly selected sites along the adjacent shoreline, and used those data in the form of a binary resource selection function to model fine-scale selection of latrine sites. At the scale of the landscape, we used a resource selection function and data from geographic information systems to model coarse-scale selection of latrine sites. Drawing on those same data, we used binary and count models to quantify factors that contributed to the consistency (high versus low use) and intensity (number of scats) of otter activity at latrine sites. Fine-scale habitat characteristics were better at predicting the presence of latrine sites when compared to coarse-scale geographic information system data. In general, the presence, consistency, and intensity of latrine activity at the fine scale were influenced by visual obscurity, larger trees, and characteristics of conifer trees. The presence of latrine sites at the coarse scale could not be accurately described by any of the models. The consistency and intensity of activity of otters at latrine sites at the coarse scale, however, was best predicted by habitat characteristics beneficial to fish. These results provide insight into the spatial and behavioral scales of latrine-site activity by river otters that can be incorporated into management, monitoring, and conservation strategies.

Numerical modeling of saturated subsurface flow and transport has been widely used inthe past using different numerical schemes such as finite difference and finite element methods.Such modeling often involves discretization of the problem in spatial and temporal scales. The choiceof the spatial and temporal scales for a modeling scenario is often not straightforward. For example,a basin-scale saturated flow and transport analysis demands larger spatial and temporal scales thana meso-scale study, which in turn has larger scales compared to a pore-scale study. The choice ofspatial-scale is often dictated by the computational capabilities of the modeler as well as the availability of fine-scale data. In this study, we analyze the impact of different spatial scales andscaling procedures on saturated subsurface flow and transport simulations.

Shihezi Reclamation Area is located at the southern edge of the Junggar Basin, with natural, soil, and climatic conditions unique to the production of peaches. In turn, peach orchards have accumulated rich microbial resources. As an important taxon of soil fungi, the diversity and community structure changes of yeast in the soil of peach orchards on spatial and temporal scales are still unknown. Here, we aimed to investigate the changes in yeast diversity and community structure in non-rhizosphere and rhizosphere soils of peach trees of different ages in the peach orchard and the factors affecting them, as well as the changes in the yeast co-occurrence network in the peach orchard at spatial and temporal scales. High-through put sequencing results showed that a total of 114 yeast genera were detected in all soil samples, belonging to Ascomycota (60 genera) and Basidiomycota (54 genera). The most dominant genus, Cryptococcus, was present in greater than 10% abundance in each sample. Overall, the differences in yeast diversity between non-rhizosphere and rhizosphere soil of peach trees at 3, 8 and 15 years were not significant. Principal coordinate analysis (PCoA) showed that differences in yeast community structure were more pronounced at the temporal scale compared to the spatial scale. The results of soil physical and chemical analysis showed that the 15-year-old peach rhizosphere soil had the lowest pH, while the OM, TN, and TP contents increased significantly. Redundancy analysis showed that soil pH and CO were key factors contributing to changes in soil yeast community structure in the peach orchard at both spatial and temporal scales. The results of co-occurrence network analysis showed that the peach orchard soil yeast network showed synergistic effects as a whole, and the degree of interactions and connection tightness of the 15-year-old peach orchard soil yeast network were significantly higher than the 3- and 8-year-old ones on the time scale. The results reveal the distribution pattern and mechanism of action of yeast communities in peach orchard soils, which can help to develop effective soil management strategies and improve the stability of soil microecology, thus promoting crop growth.

Appropriate temporal and spatial scales are important prerequisites for obtaining reliable results in studies of wildlife activity patterns and interspecific interactions. The spread of camera-trap technology has increased interest in and feasibility of studying the activity patterns and interspecific interactions of wildlife. However, such studies are often conducted at arbitrary spatial and temporal scales, and the methods used impose scale on the study rather than determining how activity and species interactions change with spatial scale. In this study, we used a wavelet-based approach to determine the temporal and spatial scales for activity patterns and interspecific interactions on Amur leopard and their ungulate prey species that were recorded using camera traps in the main Amur leopard occurrence region in northeast China. Wavelets identified that Amur leopards were more active in spring and fall than summer, and fluctuated with periodicities of 9 and 17 days, respectively. Synchronous relationships between leopards and their prey commonly occurred in spring and fall, with a periodicity of about 20 days, indicating the appropriate seasons and temporal scales for interspecific interaction research. The influence of human activities on the activity patterns of Amur leopard or prey species often occurred over longer time periods (60-64 days). Two-dimensional wavelet analyses showed that interactions between leopard and prey were more significant at spatial scales of 1 km2 . Overall, our study provides a feasible approach to studying the temporal and spatial scales for wildlife activity patterns and interspecific interaction research using camera trap data.

At different temporal and spatial scales, the impact factors and the response patterns of vegetation are different and correspond to different research methods (Liu and Yin 2013). For the issue of forest migration, it is necessary to conduct research at the long-term scale (e.g., the millennium scale), and the corresponding research methods are mainly the analysis of macrofossils and palynology (Fig. 6.1). This book focuses on relatively large spatial and temporal scales. We conduct research on local forest dynamics at temporal scales of hundreds or thousands of years and on millennial-scale forest migration patterns that have occurred since the LGM. At the spatial scale, we focus on not only the local inland lake basin but also the evolution of vegetation patterns across northern China. In addition to palynological evidence, we combine phylogeography and species distribution models. The comprehensive utilization of the combination of different spatiotemporal scales and different research methods provides a more reliable scientific basis for intensive studies on forest migration patterns, reflecting the differences in response patterns and driving factors at different spatial and temporal scales (Pearson and Dawson 2003).