Spatial variability of infiltration and its relationship to some physical properties

Water infiltration into soil is one of the basic factors for estimating irrigation intensity according to the plants' requirements; this is aimed at avoiding problems of surface run-off and degradation. The purpose of the present investigation was to determine the spatial variation of infiltration and its relationship to some physical properties of soil by means of geostatistical techniques in Typic Plinthaquult soils having average texture and flat relief. A 113 point mesh was designned, having a regular distance of 10 m between points, samples being taken from 0 to 0.20 meters depth. Sand, silt and clay content, bulk density, macroporosity, microporosity and total porosity were determined. Infiltration tests were carried out in the field by means of a 15 cm diameter ring. Descriptive statistics and geostatistics were used for analysing the data. Infiltration, silt and microporosity data did not fit a normal distribution curve. Infiltration had high variability, having an average 36.03 mm h(-1). Total porosity was 56.73%, this being the only property that did not show spatial dependency. The smallest ranges were observed for bulk density, macroporosity and microporosity, having values of less than 40 m. The smallest degrees of spatial dependence were observed for infiltration, silt and clay, evidence also being shown of the influence of silt and clay on infiltration rate. Contour maps were constructed; fitting them to the semivariogram models, together with studying the correlations, led to establishing relationships between the properties.

Spatial and temporal heterogeneity in the Jurumirim Reservoir, São Paulo, Brazil

Jurumirim is a large tropical reservoir with remarkable spatial gradients. This structure seems to be determined by a longitudinal gradient in the trophic conditions along the main axis of the reservoir. Nutrient-rich waters enter from the main tributary river, Paranapanema, and towards the dam there is a lacustrine zone that is deeper and more oligotrophic. Additional variability is derived from two important lateral components: the entrance of the Taquari River, the second largest tributary, bringing waters with higher pH and alkalinity; and the Ribeirão das Posses arm, a sheltered bay where the hydrodynamic conditions promote a high growth of phytoplankton. However, such a spatial pattern is not static. It can become either more defined, during the dry season (late autumn and winter), or less evident, during the expansion of the lotic conditions in the rainy period (late spring and summer). Seasonal processes of stratification/destratification determine the temporal changes in the lacustrine zone but, unlike the upstream regions, the dam zone of the reservoir seems to be little affected by periodic pulses of modifications produced by intensive rains. The presence of extensive wetlands and oxbow lagoons in the mouth zones of the main rivers also constitutes an important source of spatial variability and should be considered in the future.

Distribution of carabid beetles in agroecosystems across spatial scales - A review

The review focuses on the questions (1) how does the spatial heterogeneity of landscape influences carabid biodiversity, and (2) what are the main factors causing this biodiversity across nested spatial scales (study point - plant association - landscape level). The analysis of recent literature indicates that the spatial distribution of carabids differs at various spatial scales, and the factors responsible for the distribution are different. At the study point level most of the communities exhibit high variability of population density and diversity, which has no correlations with soil, and sometimes, vegetation, parameters. Most of the factors that contribute to formation of the communities are stochastic, simply because patches of a factor are much smaller than the size of a distinct carabid community. At the level of plant association, soil factors begin to play the role in driving the communities. At this level, litter depth, micro-climate and vegetation composition are the main factors. At the landscape level, geological factors, such as topography, landscape geochemistry, and history are playing important roles. As a conservation measure, spatial heterogeneity should be kept at all spatial scales at the same time to maintain carabid biodiversity in agricultural areas.

Spatial correlation between the composition of the clay fraction and contents of available phosphorus of an Oxisol at hillslope scale

Relief is regarded as the abiotic factor most strongly influencing pedogenic processes at a local scale. The spatial correlations between the composition of the clay fraction (iron - Fe and aluminum - Al oxides, kaolinite and organic matter - OM) and contents of available phosphorus (P) of an Oxisol were evaluated at hillslope scale under sugarcane cultivation. A total of 119 samples were collected at intersection points on a 100. ×. 100. m georeferenced grid of regularly spaced points 10. m apart in the 0.2-0.4. m depth in an area consisting of two landform components namely: component I (an area with a linear hillslope curvature), and component II (one with a concave-convex hillslope curvature). Soil OM and available P contents were subjected to descriptive statistics and geostatistical analyses in order to assess their variability and spatial dependence. All attributes studied were spatially dependent. Available phosphorus had positive spatial correlation with high crystalline goethite, hematite and gibbsite. Identifying small hillslope curvatures is useful with a view to better understanding their relationships with soil organic matter and available phosphorus, as well as kaolinite and Fe and Al oxide attributes. A simple correlation analysis by itself is inadequate to relate attributes, which requires a supplemental, geostatistical technique. © 2012 Elsevier B.V..

Spatiotemporal variation in life history traits of three small fishes in streams of south-eastern Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatial and temporal variability and ecological processes in the epibenthic assemblages of the northern Adriatic Sea

Several coralligenous reefs occur in the soft bottoms of the northern Adriatic continental shelf. Mediterranean coralligenous habitats are characterised by high species diversity and are intrinsically valuable for their biological diversity and for the ecological processes they support. The conservation and management of these habitats require quantifying spatial and temporal variability of their benthic assemblages. This PhD thesis aims to give a relevant contribution to the knowledge of the structure and dynamics of the epibenthic assemblages on the coralligenous subtidal reefs occurring in the northern Adriatic Sea. The epibenthic assemblages showed a spatial variation larger compared to temporal changes, with a temporal persistence of reef-forming organisms. Assemblages spatial heterogeneity has been related to morphological features and geographical location of the reefs, together with variation in the hydrological conditions. Manipulative experiments help to understand the ecological processes structuring the benthic assemblages and maintaining their diversity. In this regards a short and long term experiment on colonization patterns of artificial substrata over a 3-year period has been performed in three reefs, corresponding to the three main types of assemblages detected in the previous study. The first colonisers, largely depending by the different larval supply, played a key role in determining the heterogeneity of the assemblages in the early stage of colonisation. Lateral invasion, from the surrounding assemblages, was the driver in structuring the mature assemblages. These complex colonisation dynamics explained the high heterogeneity of the assemblages dwelling on the northern Adriatic biogenic reefs. The buildup of these coralligenous reefs mainly depends by the bioconstruction-erosion processes that has been analysed through a field experiment. Bioconstruction, largely due to serpulid polychaetes, prevailed on erosion processes and occurred at similar rates in all sites. Similarly, the total energy contents in the benthic communities do not differ among sites, despite being provided by different species. Therefore, we can hypothesise that both bioconstruction processes and energetic storage may be limited by the availability of resources. Finally the major contribution of the zoobenthos compared to the phytobenthos to the total energetic content of assemblages suggests that the energy flow in these benthic habitats is primarily supported by planktonic food web trough the filter feeding invertebrates.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Limitations of Remotely-sensed Aerosol as a Spatial Proxy for Fine Particulate Matter

Recent research highlights the promise of remotely-sensed aerosol optical depth (AOD) as a proxy for ground-level PM2.5. Particular interest lies in the information on spatial heterogeneity potentially provided by AOD, with important application to estimating and monitoring pollution exposure for public health purposes. Given the temporal and spatio-temporal correlations reported between AOD and PM2.5 , it is tempting to interpret the spatial patterns in AOD as reflecting patterns in PM2.5 . Here we find only limited spatial associations of AOD from three satellite retrievals with PM2.5 over the eastern U.S. at the daily and yearly levels in 2004. We then use statistical modeling to show that the patterns in monthly average AOD poorly reflect patterns in PM2.5 because of systematic, spatially-correlated error in AOD as a proxy for PM2.5 . Furthermore, when we include AOD as a predictor of monthly PM2.5 in a statistical prediction model, AOD provides little additional information to improve predictions of PM2.5 when included in a model that already accounts for land use, emission sources, meteorology and regional variability. These results suggest caution in using spatial variation in AOD to stand in for spatial variation in ground-level PM2.5 in epidemiological analyses and indicate that when PM2.5 monitoring is available, careful statistical modeling outperforms the use of AOD.

Geographical variation in shell morphology of juvenile snails (Concholepas concholepas) along the physical-chemical gradient of the Chilean coast

Changes in phenotypic traits, such as mollusc shells, are indicative of variations in selective pressure along environmental gradients. Recently, increased sea surface temperature (SST) and ocean acidification (OA) due to increased levels of carbon dioxide in the seawater have been described as selective agents that may affect the biological processes underlying shell formation in calcifying marine organisms. The benthic snail Concholepas concholepas (Muricidae) is widely distributed along the Chilean coast, and so is naturally exposed to a strong physical-chemical latitudinal gradient. In this study, based on elliptical Fourier analysis, we assess changes in shell morphology (outlines analysis) in juvenile C. concholepas collected at northern (23°S), central (33°S) and southern (39°S) locations off the Chilean coast. Shell morphology of individuals collected in northern and central regions correspond to extreme morphotypes, which is in agreement with both the observed regional differences in the shell apex outlines, the high reclassification success of individuals (discriminant function analysis) collected in these regions, and the scaling relationship in shell weight variability among regions. However, these extreme morphotypes showed similar patterns of mineralization of calcium carbonate forms (calcite and aragonite). Geographical variability in shell shape of C. concholepas described by discriminant functions was partially explained by environmental variables (pCO2, SST). This suggests the influence of corrosive waters, such as upwelling and freshwaters penetrating into the coastal ocean, upon spatial variation in shell morphology. Changes in the proportion of calcium carbonate forms precipitated by C. concholepas across their shells and its susceptibility to corrosive coastal waters are discussed.

On the spatial distribution of woody plant species in a tropical montane cloud forest

Abstract The cloud forest is a special type of forest ecosystem that depends on suitable conditions of humidity and temperature to exist; hence, it is a very fragile ecosystem. The cloud forest is also one of the richest ecosystems in terms of species diversity and rate of endemism. However, today, it is one of the most threatened ecosystems in the world. Little is known about tree species distribution and coexistence among cloud forest trees. Trees are essential to understanding ecosystem functioning and maintenance because they support the ecosystem in important ways. For this dissertation, an analysis of woody plant species distribution at a small scale in a north-Peruvian Andean cloud forest was performed, and some of the factors implicated in the observed patterns were identified. Towards that end, different natural factors acting on species distribution within the forest were investigated: (i) intra-specific arrangements, (ii) heterospecific spatial relationships and (iii) relationships with external environmental factors. These analyses were conducted first on standing woody plants and then on seedlings. The woody plants were found to be clumped in the forest, either considering all the species together or each species separately. However, each species presented a specific pattern and specific spatial relationship among different-age individuals. Dispersal mode, growth form and shade tolerance played roles in the final distribution of the species. Furthermore, spatial associations among species, either positive or negative, were observed. These associations were more numerous when considering individuals of the interacting species at different developmental stages, i.e., younger individuals from one species and older individuals from another. Accordingly, competition and facilitation are asymmetric processes and vary throughout the life of an individual. Moreover, some species appear to prefer certain habitat conditions and avoid other habitats. The habitat definition that best explains species distribution is that which includes both environmental and stand characteristics; thus, a combination of these factors is necessary to understanding species' niche preferences. Seedling distribution was also associated with habitat conditions, but these conditions explained less than the 30% of the spatial variation. The position of conspecific adult individuals also affected seedling distribution; although the seedlings of many tree species avoid the vicinity of conspecifics, a few species appeared to prefer the formation of cohorts around their parent trees. The importance of habitat conditions and distance dependence with conspecifics varied among regions within the forest as well as on the developmental stage of the stand. The results from this thesis suggest that different species can coexist within a given space, forming a “puzzle” of species as a result of the intra- and interspecific spatial relationships along with niche preferences and adaptations that operate at different scales. These factors not only affect each species in a different way, but specific preferences also vary throughout species' lifespans. Resumen Resumen El bosque de niebla es uno de los ecosistemas más amenazados del mundo además de ser uno de los más frágiles. Son formaciones azonales que dependen de la existencia de unas condiciones de humedad y temperatura que permitan la formación de nubes que cubran el bosque; lo que dificulta en gran medida su conservación. También es uno de los ecosistemas con mayor riqueza de especies además de tener uno de los mayores porcentajes de endemismos. Uno de los aspectos más importantes para entender el ecosistema, es identificar y entender los elementos que lo componen y los mecanismos que regulan las relaciones entre ellos. Los árboles son el soporte del ecosistema. Sin embargo, apenas hay información sobre la distribución y coexistencia de los árboles en los bosques de niebla. Esta tesis presenta un análisis de la distribución a pequeña escala de las plantas leñosas en un bosque de niebla situado en la cordillera andina del norte de Perú; así como el análisis de algunos de los factores que pueden estar implicados en que se origine la distribución observada. Para este propósito se estudia cómo influyen factores de diferente naturaleza en la distribución de las especies (i) organización intra-específica (ii) relaciones espaciales heterospecíficas y (iii) relación con factores ambientales externos. En estos análisis se estudiaron primero las plantas jóvenes y las adultas, y después las plántulas. Los árboles aparecieron agregados en el bosque, tanto considerando todos a la vez como cuando se estudió cada especie por separado. Sin embargo, cada especie mostró un patrón distinto así como una particular relación espacial entre individuos jóvenes y adultos. El modo de dispersión, la forma de vida y la tolerancia de la especies estuvieron relacionados con el patrón general observado. Se vio también que ciertas especies aparecían relacionadas con otras, tanto de forma positiva (compartiendo zonas) como negativa (apareciendo en áreas distintas). Las asociaciones fueron mucho más numerosas cuando se consideraron los pares de especies en diferente estado de desarrollo, es decir, individuos jóvenes de una especie e individuos mayores de la otra. Eso indicaría que los procesos de competencia y facilitación son asimétricos y además varían durante la vida de la planta. Por otro lado, algunas especies aparecen preferentemente bajo ciertas condiciones de hábitat y evitan otras. La definición de hábitat a la que mejor responden las especies es cuando se incluyen tanto variables ambientales como de masa; así que ambos tipos de variables son necesarias para entender la preferencia de las especies por ciertos nichos. La distribución de las plántulas también estuvo relacionada con condiciones de hábitat, pero eso sólo llegaba a explicar hasta un 30% de la variabilidad espacial. La posición de los adultos de la misma especie también afectó a la distribución de las plántulas. En bastantes especies las plántulas evitan la cercanía de adultos de su misma especie, padres potenciales, aunque algunas especies aisladas mostraron el patrón contrario y aparecieron preferentemente en las mismas áreas que sus padres. La importancia de las condiciones de hábitat y posición de los adultos en la disposición de las plántulas varía de una zona a otra del bosque y además también varía según el estado de desarrollo de la masa.

The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar

In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

Ross River virus disease clusters and spatial relationship with mosquito biting exposure in Redland Shire, southern Queensland, Australia

The spatial heterogeneity in the risk of Ross River virus (family Togaviridae, genus Alphavirus, RRV) disease, the most common mosquito-borne disease in Australia, was examined in Redland Shire in southern Queensland, Australia. Disease cases, complaints from residents of intense mosquito biting exposure, and human population data were mapped using a geographic information system. Surface maps of RRV disease age-sex standardized morbidity ratios and mosquito biting complaint morbidity ratios were created. To determine whether there was significant spatial variation in disease and complaint patterns, a spatial scan analysis method was used to test whether the number of cases and complaints was distributed according to underlying population at risk. Several noncontiguous areas in proximity to productive saline water habitats of Aedes vigilax (Skuse), a recognized vector of RRV, had higher than expected numbers of RRV disease cases and complaints. Disease rates in human populations in areas which had high numbers of adult Ae. vigilax in carbon dioxide- and octenol-baited light traps were up to 2.9 times those in areas that rarely had high numbers of mosquitoes. It was estimated that targeted control of adult Ae. vigilax in these high-risk areas could potentially reduce the RRV disease incidence by an average of 13.6%. Spatial correlation was found between RRV disease risk and complaints from residents of mosquito biting. Based on historical patterns of RRV transmission throughout Redland Shire and estimated future human population growth in areas with higher than average RRV disease incidence, it was estimated that RRV incidence rates will increase by 8% between 2001 and 2021. The use of arbitrary administrative areas that ranged in size from 4.6 to 318.3 km2, has the potential to mask any small scale heterogeneity in disease patterns. With the availability of georeferenced data sets and high-resolution imagery, it is becoming more feasible to undertake spatial analyses at relatively small scales.

The spatial distribution of self-employment in India:evidence from semi-parametric geoadditive models

The spatial distribution of self-employment in India: evidence from semiparametric geoadditive models, Regional Studies. The entrepreneurship literature has rarely considered spatial location as a micro-determinant of occupational choice. It has also ignored self-employment in developing countries. Using Bayesian semiparametric geoadditive techniques, this paper models spatial location as a micro-determinant of self-employment choice in India. The empirical results suggest the presence of spatial occupational neighbourhoods and a clear north–south divide in self-employment when the entire sample is considered; however, spatial variation in the non-agriculture sector disappears to a large extent when individual factors that influence self-employment choice are explicitly controlled. The results further suggest non-linear effects of age, education and wealth on self-employment.

Data to Decision in a Dynamic Ocean: Robust Species Distribution Models and Spatial Decision Frameworks

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Spatial Variations of the Methanogenic Communities in the Sediments of Tropical Mangroves

Methane production by methanogens in mangrove sediments is known to contribute significantly to global warming, but studies on the shift of methanogenic community in response to anthropogenic contaminations were still limited. In this study, the effect of anthropogenic activities in the mangrove sediments along the north and south coastlines of Singapore were investigated by pyrosequencing of the mcrA gene. Our results showed that hydrogenotrophic, acetoclastic and methylotrophic methanogens coexist in the sediments. The predominance of the methylotrophic Methanosarcinales reflects the potential for high methane production as well as the possible availability of low acetate and high methylated C-1 compounds as substrates. A decline in the number of acetoclastic/methylotrophic methanogens in favor of hydrogenotrophic methanogens was observed along a vertical profile in Sungei Changi, which was contaminated by heavy metals. The diversity of methanogens in the various contaminated stations was significantly different from that in a pristine St. John’s Island. The spatial variation in the methanogenic communities among the different stations was more distinct than those along the vertical profiles at each station. We suggest that the overall heterogeneity of the methanogenic communities residing in the tropical mangrove sediments might be due to the accumulated effects of temperature and concentrations of nitrate, cobalt, and nickel.