An evaluation of the role and impacts of alien finfish in Asian inland aquaculture

Asia dominates global aquaculture production accounting for over 80% of the total and the mainstay in Asian aquaculture is finfish. Over the years, Asia has experienced a number of inter-continental and intra-continental transfers/introductions/translocation of finfish species, between nations and watersheds, beyond their natural range of distribution, primarily for aquaculture development. In this article all such species are referred to as alien species. An attempt is made to evaluate the importance of the production of alien species in selected Asian nations, using statistics of the Food and Agriculture Organization. Also, negative effects, if any, based on literature surveys, of alien species in relation to displacement of indigenous species, and on biodiversity and/or genetic diversity together with associated pathogen transfers are evaluated. The major alien species, based on their significance to Asian inland aquaculture considered, are the tilapias, catfish, Chinese and Indian major carps and common carp. It is estimated that currently alien species account for nearly 12% of the cultured finfish production (2.6 million tonnes) in Asia, valued at US$ 2.59 billion, and the contribution exceeds 40% when Asian countries excluding China are taken into consideration. Inland finfish aquaculture in some Asian nations, such as Indonesia and the Philippines, is predominated by alien species, and in some others, e.g. Bangladesh and India, the contribution from alien species has been increasing steadily. It is suggested that overall alien finfish species have done little ecological harm to native flora and fauna. However, in the wake of increasing anthropogenic development taking place in watersheds the resulting environments are often made unconducive to indigenous species but not to some alien species, thereby potentially and indirectly making the latter invasive.

Water, land use change and 'new forests': what are the challenges for South-Western Victoria?

Land use change has occurred rapidly in southwestern Victoria over the last decade and is expected to continue, albeit at a slower pace. One of these changes has been the development of 'new forests', that is industrial and farm forestry plantations and environmental plantings. Some of the challenges that these land use changes pose for water and natural resource managers are discussed. Land use change is expected to substantially reduce potential water yield in four of the region's seven drainage basins (A).

Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Clustering of multivariate data is a commonly used technique in ecology, and many approaches to clustering are available. The results from a clustering algorithm are uncertain, but few clustering approaches explicitly acknowledge this uncertainty. One exception is Bayesian mixture modelling, which treats all results probabilistically, and allows comparison of multiple plausible classifications of the same data set. We used this method, implemented in the AutoClass program, to classify catchments (watersheds) in the Murray Darling Basin (MDB), Australia, based on their physiographic characteristics (e.g. slope, rainfall, lithology). The most likely classification found nine classes of catchments. Members of each class were aggregated geographically within the MDB. Rainfall and slope were the two most important variables that defined classes. The second-most likely classification was very similar to the first, but had one fewer class. Increasing the nominal uncertainty of continuous data resulted in a most likely classification with five classes, which were again aggregated geographically. Membership probabilities suggested that a small number of cases could be members of either of two classes. Such cases were located on the edges of groups of catchments that belonged to one class, with a group belonging to the second-most likely class adjacent. A comparison of the Bayesian approach to a distance-based deterministic method showed that the Bayesian mixture model produced solutions that were more spatially cohesive and intuitively appealing. The probabilistic presentation of results from the Bayesian classification allows richer interpretation, including decisions on how to treat cases that are intermediate between two or more classes, and whether to consider more than one classification. The explicit consideration and presentation of uncertainty makes this approach useful for ecological investigations, where both data and expectations are often highly uncertain.

Hydrologic response of a tropical watershed to urbanization

 Urbanization has profound influence on the hydrologic response of landscapes. Urban transformation affects the storages and processes that determine the generation of hydrologic fluxes. It also changes the time-scales associated with hydrologic processes. Shifts in hydrologic response of the watershed unit due to urban transformation may be more complex than the simple linear mixing (weighted sum) of responses from the urbanized and non-urbanized fractions of the landscape. This may especially be the case for tropical watersheds where the precipitation forcing of the watershed is frequent and intense - interacting with the shifting time-scales and changing storages with increasing urbanization. In this study, a fully distributed hydrological model (MOBIDIC) that captures hydrologic dynamics during storms and interstorms is applied in order to characterize the potentially nonlinear response of a tropical watershed to urban transformation. Indices that quantify the departures from linear response are introduced and used to test the effects of urbanization on different hydrologic processes and fluxes in a mixed (urban and non-urban) watershed. The tropical Kranji watershed in Singapore is used in this study. Fortunately two sub-watersheds within Kranji that have streamflow gaging stations are well-suited for the calibration of the model. One sub-watershed is nearly fully urbanized and another is pristine (non-urban). As a result the contrasting components (urban and non-urban) can be calibrated in the model. The simulation system is then used to assess the hydrologic response due to changing levels of urbanization. For some fluxes and storages, the hydrologic response due to changing urban fraction cannot be simply predicted from a linear mixing model.

Balancing the environmental benefits of reforestation in agricultural regions

Reforestation is an important tool for reducing or reversing biodiversity loss and mitigating climate change. However, there are many potential compromises between the structural (biodiversity) and functional (carbon sequestration and water yield) effects of reforestation, which can be affected by decisions on spatial design and establishment of plantings. We review the environmental responses to reforestation and show that manipulating the configuration of plantings (location, size, species mix and tree density) increases a range of environmental benefits. More extensive tree plantings (>10. ha) provide more habitat, and greater improvements to carbon and water cycling. Planting a mixture of native trees and shrubs is best for biodiversity, while traditional plantation species, generally non-native species, sequester C faster. Tree density can be manipulated at planting or during early development to accelerate structural maturity and to manage water yields. A diversity of habitats will be created by planting in a variety of landscape positions and by emulating the patchy distribution of forest types, which characterized many regions prior to extensive landscape transformation. Areas with shallow aquifers can be planted to reduce water pollution or avoided to maintain water yields. Reforestation should be used to build forest networks that are surrounded by low-intensity land use and that provide links within regions and between biomes. While there are adequate models for C sequestration and changes in water yields after reforestation, the quantitative understanding of changes in habitat resources and species composition is more limited. Development of spatial and temporal modelling platforms based on empirical models of structural and functional outcomes of reforestation is essential for deciding how to reconfigure agricultural regions. To build such platforms, we must quantify: (a) the influence of previous land uses, establishment methods, species mixes and interactions with adjacent land uses on environmental (particularly biodiversity) outcomes of reforestation and (b) the ways in which responses measured at the level of individual plantings scale up to watersheds and regions. Models based on this information will help widespread reforestation for carbon sequestration to improve native biodiversity, nutrient cycling and water balance at regional scales.