205 resultados para 770503 Living resources (flora and fauna)


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The thelastomatoid fauna of Macropanesthia rhinoceros was examined from 13 localities across its range in Queensland, Australia. Nine species of thelastomatoids, including two representing new genera, Geoscaphenema megaovum n. g., n. sp. and Jaidenema rhinoceratum n. g., n. sp., were found. Macropanesthia rhinoceros is reported as a new host for seven species previously recorded from Panesthia cribrata (Blaberidae: Panesthiinae) and P. tryoni tryoni, viz, Blattophila sphaerolaima, Leidynemella fusiformis, Cordonicola gibsoni, Travassosinema jaidenae, Coronostoma australiae, Hammerschmidtiella hochi and Desmicola ornata. Overall estimated richness for the system ranged from 10.1-13.5 species. The high degree of parasite faunal overlap between M. rhinoceros and the two Panesthia species is surprising given the disparate ecological niches that they occupy; P. cribrata and P. tryoni tryoni burrow in, and feed upon, moist decaying wood and require a climate that is moist all year round, whereas M. rhinoceros burrows in loose soil, feeds on fallen leaf litter and is tolerant of much drier environments.

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Traditional sensitivity and elasticity analyses of matrix population models have been used to p inform management decisions, but they ignore the economic costs of manipulating vital rates. For exam le, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously, These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency.

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Deforestation often occurs as temporal waves and in localized fronts termed 'deforestation hotspots' driven by economic pulses and population pressure. Of particular concern for conservation planning are 'biodiversity hotspots' where high concentrations of endemic species undergo rapid loss and fragmentation of habitat. We investigate the deforestation process in Caqueta, a biodiversity hotspot and major colonization front of the Colombian Amazon using multi-temporal satellite imagery of the periods 1989-1996-1999-2002. The probabilities of deforestation and regeneration were modeled against soil fertility, accessibility and neighborhood terms, using logistic regression analysis. Deforestation and regeneration patterns and rates were highly variable across the colonization front. The regional average annual deforestation rate was 2.6%, but varied locally between -1.8% (regeneration) and 5.3%, with maximum rates in landscapes with 40-60% forest cover and highest edge densities, showing an analogous pattern to the spread of disease. Soil fertility and forest and secondary vegetation neighbors showed positive and significant relationships with the probability of deforestation. For forest regeneration, soil fertility had a significant negative effect while the other parameters were marginally significant. The logistic regression models across all periods showed a high level of discrimination power for both deforestation and forest regeneration, with ROC values > 0.80. We document the effect of policies and institutional changes on the land clearing process, such as the failed peace process between government and guerillas in 1999-2002, which redirected the spread of deforestation and increased forest regeneration. The implications for conservation in biologically rich areas, such as Caqueta are discussed. (c) 2005 Elsevier B.V All rights reserved.

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Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south-east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (< 1 ha), patch level (100 ha) and landscape level (100-1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.

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Effective detection of population trend is crucial for managing threatened species. Little theory exists, however, to assist managers in choosing the most cost-effective monitoring techniques for diagnosing trend. We present a framework for determining the optimal monitoring strategy by simulating a manager collecting data on a declining species, the Chestnut-rumped Hylacola (Hylacola pyrrhopygia parkeri), to determine whether the species should be listed under the IUCN (World Conservation Union) Red List. We compared the efficiencies of two strategies for detecting trend, abundance, and presence-absence surveys, underfinancial constraints. One might expect the abundance surveys to be superior under all circumstances because more information is collected at each site. Nevertheless, the presence-absence data can be collected at more sites because the surveyor is not obliged to spend a fixed amount of time at each site. The optimal strategy for monitoring was very dependent on the budget available. Under some circumstances, presence-absence surveys outperformed abundance surveys for diagnosing the IUCN Red List categories cost-effectively. Abundance surveys were best if the species was expected to be recorded more than 16 times/year; otherwise, presence-absence surveys were best. The relationship between the strategies we investigated is likely to be relevant for many comparisons of presence-absence or abundance data. Managers of any cryptic or low-density species who hope to maximize their success of estimating trend should find an application for our results.

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A number of systematic conservation planning tools are available to aid in making land use decisions. Given the increasing worldwide use and application of reserve design tools, including measures of site irreplaceability, it is essential that methodological differences and their potential effect on conservation planning outcomes are understood. We compared the irreplaceability of sites for protecting ecosystems within the Brigalow Belt Bioregion, Queensland, Australia, using two alternative reserve system design tools, Marxan and C-Plan. We set Marxan to generate multiple reserve systems that met targets with minimal area; the first scenario ignored spatial objectives, while the second selected compact groups of areas. Marxan calculates the irreplaceability of each site as the proportion of solutions in which it occurs for each of these set scenarios. In contrast, C-Plan uses a statistical estimate of irreplaceability as the likelihood that each site is needed in all combinations of sites that satisfy the targets. We found that sites containing rare ecosystems are almost always irreplaceable regardless of the method. Importantly, Marxan and C-Plan gave similar outcomes when spatial objectives were ignored. Marxan with a compactness objective defined twice as much area as irreplaceable, including many sites with relatively common ecosystems. However, targets for all ecosystems were met using a similar amount of area in C-Plan and Marxan, even with compactness. The importance of differences in the outcomes of using the two methods will depend on the question being addressed; in general, the use of two or more complementary tools is beneficial.

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The Centre for Native Floriculture (CNF) commenced in May 2003 at The University of Queensland, Gatton. The CNF is a joint initiative with the Queensland State Government, with funding for an initial 3-year period. The phase-out of bush-picking under the South East Queensland Forests Agreement was a catalyst for the Centres establishment. The CNF vision is: ‘to help create an internationally competitive and environmentally sustainable native floriculture industry that provides significant employment opportunities in Queensland’. The Centre is comprised of three research, development and extension programs. The Value Chain Program assists native floriculture industry groups in developing efficient consumer-orientated production, handling and marketing systems for select high potential species. These value chain systems will serve as models for realizing the market potential of and regional fiscal returns on other native ornamental species identified as crop ideotypes that are sought after by end-users (e.g. florists). The Floriculture Program supports the value chain by working to enhance germplasm for the native floriculture industry through selection and breeding, optimize cultivation protocols and overcome any technical barriers that arise. Such barriers include propagation constraints, disease problems and post-harvest limitations. The Capacity Building Program operates to transfer technology and other skills (e.g. value chain management principles) to industry members, train operatives for the industry and promote native floriculture. Conservation of native flora is encouraged through cultivation and community engagement. Protection of biodiversity is advocated via regional production systems that spare natural areas and educate the public as to the biological, floricultural and aesthetic values of native flora. Eco-agricultural tourism focused on wildflowers both in nature and in cultivation is also advocated by the CNF.

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A review of the current conservation status of Australian amphibians was recently completed as part of a World Conservation Union (IUCN) sponsored Global Amphibian Assessment (GAA). Fifty of 216 amphibian species (23%) in Australia are now recognized as threatened or extinct in accord with IUCN Red List Categories and Criteria. Here we report on the categories and criteria under which individual species qualified for listing and provide a summary of supporting information pertaining to population and distribution declines. Major threatening processes contributing to listing of species are also reviewed.

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