Bayesian classification of catchments using spatial data: a first step to improved modelling of catchment effects on stream ecological condition

A major challenge facing freshwater ecologists and managers is the development of models that link stream ecological condition to catchment scale effects, such as land use. Previous attempts to make such models have followed two general approaches. The bottom-up approach employs mechanistic models, which can quickly become too complex to be useful. The top-down approach employs empirical models derived from large data sets, and has often suffered from large amounts of unexplained variation in stream condition.

We believe that the lack of success of both modelling approaches may be at least partly explained by scientists considering too wide a breadth of catchment type. Thus, we believe that by stratifying large sets of catchments into groups of similar types prior to modelling, both types of models may be improved. This paper describes preliminary work using a Bayesian classification software package, ‘Autoclass’ (Cheeseman and Stutz 1996) to create classes of catchments within the Murray Darling Basin based on physiographic data.

Autoclass uses a model-based classification method that employs finite mixture modelling and trades off model fit versus complexity, leading to a parsimonious solution. The software provides information on the posterior probability that the classification is ‘correct’ and also probabilities for alternative classifications. The importance of each attribute in defining the individual classes is calculated and presented, assisting description of the classes. Each case is ‘assigned’ to a class based on membership probability, but the probability of membership of other classes is also provided. This feature deals very well with cases that do not fit neatly into a larger class. Lastly, Autoclass requires the user to specify the measurement error of continuous variables.

Catchments were derived from the Australian digital elevation model. Physiographic data werederived from national spatial data sets. There was very little information on measurement errors for the spatial data, and so a conservative error of 5% of data range was adopted for all continuous attributes. The incorporation of uncertainty into spatial data sets remains a research challenge.

The results of the classification were very encouraging. The software found nine classes of catchments in the Murray Darling Basin. The classes grouped together geographically, and followed altitude and latitude gradients, despite the fact that these variables were not included in the classification. Descriptions of the classes reveal very different physiographic environments, ranging from dry and flat catchments (i.e. lowlands), through to wet and hilly catchments (i.e. mountainous areas). Rainfall and slope were two important discriminators between classes. These two attributes, in particular, will affect the ways in which the stream interacts with the catchment, and can thus be expected to modify the effects of land use change on ecological condition. Thus, realistic models of the effects of land use change on streams would differ between the different types of catchments, and sound management practices will differ.

A small number of catchments were assigned to their primary class with relatively low probability. These catchments lie on the boundaries of groups of catchments, with the second most likely class being an adjacent group. The locations of these ‘uncertain’ catchments show that the Bayesian classification dealt well with cases that do not fit neatly into larger classes.

Although the results are intuitive, we cannot yet assess whether the classifications described in this paper would assist the modelling of catchment scale effects on stream ecological condition. It is most likely that catchment classification and modelling will be an iterative process, where the needs of the model are used to guide classification, and the results of classifications used to suggest further refinements to models.

Spatial and temporal variation in the breeding of Masked Lapwings (Vanellus miles) in Australia

Spatial and temporal variation in the breeding of Masked Lapwings (Vanellus miles) in Australia were examined using data from Birds Australia’s Nest Record Scheme (NRS; 1957–2002), the Atlas of Australian Birds (1998–2006), and climatic data (1952–2006). Breeding in north-western Australia was concentrated in summer, while in other regions the peak of breeding occurred during spring. Breeding success varied between regions and years but was generally highest in Tasmania. Clutch-size (mean 3.57 eggs ± 0.033 s.e., n = 549 clutches) did not vary regionally or temporally. In the north-east, breeding became earlier over time (~1.9 days per year, NRS), while in the south-east, breeding became later (~0.9 days per year); in other regions temporal trends were not evident. Only Tasmania showed a significant temporal change in breeding success (decrease of ~1.5% per year). All regions experienced warming climates, and annual rainfall increased in north-western regions and decreased in eastern regions. There were weak or no relationships between the amount or success of breeding, clutch-size and the climatic variables considered (with the possible exception of Tasmania), suggesting either that data limitations precluded us from detecting subtle effects or that Masked Lapwings have been little influenced or are resilient to changes in climate over most of their range.

Assessment of spatiotemporal varying relationships between rainfall, land cover and surface water area using geographically weighted regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R 2 and lower corrected Akaike information criterion (AICC). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R 2 and lower AICC. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.

Temporal and spatial variability of breeding in Australian birds and the potential implications of climate change

Climate change has profound implications for biodiversity worldwide. To understand its effects on Australia's avifauna, we need to evaluate the effects of annual climatic variability and geographical climate gradients. Here, we use national datasets to examine variation in breeding of 16 species of common and widespread Australian landbirds, in relation to four variables: altitude, latitude, year and the Southern Oscillation Index. Analysis of 30 years of nesting records confirmed that breeding was generally later in colder altitudes and latitudes (geographic variation), but was not consistently related to year or the Southern Oscillation Index (temporal variation). However, power to detect expected temporal effects was low. The timing of breeding became significantly earlier with year only in south-eastern Australia. In contrast, an index of breeding activity (the proportion of atlas records for a species for which breeding was reported) increased with increasing winter values of the Southern Oscillation Index (generally wetter conditions) for all 16 species across Australia. This suggests that annual fluctuations in rainfall can have dramatic and immediate effects on breeding, even for largely sedentary, seasonally breeding species. If, as expected, climate change creates drier conditions over much of Australia, we predict a marked negative effect on bird breeding.

Spatial and temporal distribution of tadpole assemblages (Amphibia, Anura) in a seasonal dry tropical forest of southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

Reproductive Strategies of Brazilian Lizards of the Genus Tropidurus Rodrigues, 1987 (Squamata, Tropiduridae) in the Temporal and Spatial

Reproductive strategy is the set of adaptations that promote the most efficient way that the species will survive under the particular conditions of a determined environment. Understanding these adaptations is important and can help pinpoint populations indicator of environmental changes. Spermatogenesis is a measurable biological process of these adaptations in spatial and temporal scales. We analyzed the morphology of the testes and oviducts of the lizard species that comprise the genus Tropidurus, taking into account the geographical distribution and sympatric relations. For the analysis and the testes were removed from the middle part of the oviducts from Tropidurus etheridge, T oreadicus, T itambere, T spinulosus and T Guarani species, collected in different places in the Mato Grosso state, Brazil. The reproductive period is synchronous for males and females and occurs in September, October and November. Reproductive males were characterized. In the testes are seminiferous tubules with germ cells at different stages of spermatogenesis, with a high epithelium, at present light, free spermatozoa in the lumen and reduction of interstitial tissue. For females, the reproduction peak occurs when the oviduct epithelium is high with secretions and basal nucleus. These months are characterized in the sampled areas over a period of heavy rain and high temperatures. The decline of reproductive period was observed in both sexes, between April and August. Low reproduction in males is characterized by ample light, absence of sperm, only germ cells in the early stages of spermatogenesis are observed (a few spermatogonia and spermatocytes) and interstitial tissue wide. In females, the period of reproductive decline is marked by the absence of unicellular glands in the oviduct epithelium, with higher affinity with the dye. This period corresponds to low rainfall periods and lower temperatures. We propose an analysis of zoological samples; this is a proposal to facilitate the work of many researchers through access to the species, especially rare species.

Effect of atypical rainfall on lotic zooplankton: comparing downstream of a reservoir and tributaries with free stretches

To contribute to the knowledge of lotic zooplankton from dammed and free stretches, we tested the hypothesis that the ecological attributes are different between these environments, which are subjected to several effects caused by different hydrological conditions. The study was carried out in the low Iguacu river, a large hydrographic basin in the south of Brasil. Two samplings were performed, one in the dry period (April/04) and the other in the atypical rainy period (July/04), in five stations downstream a large reservoir, and other 12 stations in four tributaries representing the upper, intermediate and low regions of each river. The observations suggest a clear spatial distribution of zooplankton in lotic stretches subjected or not to damming, mainly due to the effects of physical, chemical and biological variables. Furthermore, the atypical rainfall promoted alterations in community structure when compared to the dry period.

Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Temporal and spatial distribution of the commercial shrimp Litopenaeus schmitti (Dendrobranchiata: Penaeidae) in the south-eastern Brazilian coast

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On the spatial and temporal dependence of CO2 emission on soil properties in sugarcane (Saccharum spp.) production

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatial distribution of the daily precipitation concentration index in Algeria

In this paper, the spatial and temporal distribution of the daily precipitation concentration index (CI) in Algeria (south Mediterranean Sea) has been assessed. CI is an index related to the rainfall intensity and erosive capacity; therefore, this index is of great interest for studies on torrential rainfall and floods. Forty-two daily rainfall series based on high-quality and fairly regular rainfall records for the period from 1970 to 2008 were used. The daily precipitation CI results allowed the identification of three climate zones: the northern country, characterized by coastal regions with CI values between 0.59 and 0.63; the highlands, with values between 0.57 and 0.62, except for the region of Biskra (CI = 0.70); and the southern region of the country, with high rainfall concentrations with values between 0.62 and 0.69.

Spatial distribution of runoff depth from a watershed located in a cuesta relief area of São Paulo State, Brazil

This study was undertaken in a 1566 ha drainage basin situated in an area with cuesta relief in the state of São Paulo, Brazil. The objectives were: 1) to map the maximum potential soil water retention capacity, and 2) to simulate the depth of surface runoff in each geographical position of the area based on a typical rainfall event. The database required for the development of this research was generated in the environment of the geographical information system ArcInfo v.10.1. Undeformed soil samples were collected at 69 points. The ordinary kriging method was used in the interpolation of the values of soil density and maximum potential soil water retention capacity. The spherical model allowed for better adjustment of the semivariograms corresponding to the two soil attributes for the depth of 0 to 20 cm, while the Gaussian model enabled a better fit of the spatial behavior of the two variables for the depth of 20 to 40 cm. The simulation of the spatial distribution revealed a gradual increase in the depth of surface runoff for the rainfall event taken as example (25 mm) from the reverse to the peripheral depression of the cuesta (from west to east). There is a positive aspect observed in the gradient, since the sites of highest declivity, especially those at the front of the cuesta, are closer to the western boundary of the watershed where the lowest depths of runoff occur. This behavior, in conjunction with certain values of erodibility and depending on the land use and cover, can help mitigate the soil erosion processes in these areas.

Scaling properties of rainfall and desert dust in the Canary Islands

[EN] Precipitation and desert dust event occurrence time series measured in the Canary Islands region are examined with the primary intention of exploring their scaling characteristics as well as their spatial variability in terms of the islands topography and geographical orientation. In particular, the desert dust intrusion regime in the islands is studied in terms of its relationship with visibility. Analysis of dust and rainfall events over the archipelago exhibits distributions in time that obey power laws. Results show that the rain process presents a high clustering and irregular pattern on short timescales and a more scattered structure for long ones. In contrast, dustiness presents a more uniform and dense structure and, consequently, a more persistent behaviour on short timescales. It was observed that the fractal dimension of rainfall events shows an important spatial variability, which increases with altitude, as well as towards northern latitudes and western longitudes.

Species Richness-Environment Relationships of European Arthropods at Two Spatial Grains: Habitats and Countries

We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area.