Academic literature on the topic 'Extinction of species'

Species invasion and range shifts are widely reported and facilitate novel interactions among potential competitors in plant and animal communities worldwide. However, predicting which novel interactions will result in the extirpation of subordinate competitors is challenging. Coexistence versus extinction as alternative outcomes of competition between resident and colonizing species may arise due to (1) variation in interaction strength, (2) change in other demographic drivers more influential than those linked to competition, or (3) differences in the extent to which resources are equitably partitioned between competitors, which may in turn depend on the spatial scale examined. To date, however, empirical studies suggest these factors rarely align to cause the competitive exclusion of native species. I used a combination of field experiments and demographic analyses to test the hypothesis that colonizing fox sparrows (Passerella iliaca) have caused the 0.6% per year decline of a song sparrow (Melospiza melodia) population resident on Mandarte Island, BC, Canada. Several lines of evidence indicate that interspecific competition for winter food has: a) reduced survival in juvenile song sparrows after colonization by fox sparrows in 1975, b) led to an inverse relationship between juvenile song sparrow survival and fox sparrow population size, c) excluded song sparrows from high-quality foraging sites in winter via consistent behavioural dominance by fox sparrows and complete overlap of fox and song sparrow preference for local seeds, despite d) no evidence of competition for breeding territories or nesting habitat. My results suggest that in the absence of rapid ecological or evolutionary shifts in niche dimension, song sparrows will likely be extirpated from Mandarte Is., thus demonstrating that competitive exclusion of native species can occur when interactions are strong and resources are not easily partitioned.<br>Forestry, Faculty of<br>Graduate

This thesis explains the decline of biological diversity as the result of a particular form of dynamic externality inherent within the global development process. Agricultural technology and learning have become embedded within particular species, by reason of species-specific investments, and the diffusion of these technologies has implied the adoption of these particular species as well. The decline of biological diversity has been the consequence of this development process, which carries with it the by-product of a homogenised biosphere. This theory has important implications for the regulation of diverse biological resources, and especially their extinction. It implies that the fundamental force driving extinctions is relative underinvestment in these non-specialised resources and in their ancillary resources: base resources (land) and management requirements. When particular species do not attract investment, they are subject to disinvestment by reason of "mining" (for investment of rents elsewhere), "land use conversions" (for investment of base resources elsewhere), or "overexploitation" (for investment of management resources elsewhere). Decisions concerning the conversion of diverse resources made by individual states are necessarily suboptimal. The mere existence of a range of diversity in biological resources confers global benefits, specifically insurance and informational services. No single state will take these global benefits into consideration when making its disinvestment decisions. The internalisation of these benefits, through international environmental agreements to that effect, is the means by which the decline of biological diversity might be controlled. The international regulation of extinction may take three distinct forms: 1) the creation of dynamically consistent transfer systems to compensate for reduced rates of conversion of diverse resources ("international franchise agreements"); 2) the creation of rent enhancement systems to render nonconversion a more profitable alternative ("international wildlife trade regimes"); or, 3) the creation of appropriation mechanisms that render the nonappriable appropriable ("international intellectual property right regimes").

The potential impacts of climate change on many species worldwide remains unknown, especially in those tropical regions that are centers of endemism and are highly biodiverse. This thesis provides an insight into the extinction risk of selected tree species using different species distribution modelling techniques and reviewing the current conservation status on montane forest in the Tropical Andes. Starting with a global analysis, the potential impacts of climate change on montane ecoregions is investigated, by identifying those that are more vulnerable to the expected changes in temperature and precipitation, from global predictions under different climate change scenarios. It then gives an insight on the current and potential threats to biodiversity in the Andean region, including the identification of those that are most likely to be responsible for increasing the extinction risk of the species. With the use of the IUCN Red List Categories and Criteria, selected tree species were assessed to identify their extinction risk. Information on the species’ current distribution was collated and used to estimate their potential distribution under climate change, by using different modelling techniques. These results were used to reassess the species using the IUCN Red List and establish the changes in Red List Category. Lastly, it provides a discussion that integrates all the results obtained throughout the thesis, to explore the implications for conservation, in order to highlight the overriding importance of including threatened tree species to target conservation efforts in the region, while considering the uncertainties that surround predictions under climate change scenarios, modelling techniques and the use of the IUCN Red List.

Aim MaxEnt, a very popular species distribution modelling technique, has been used extensively to relate species’ geographic distributions to environmental variables and to predict changes in species’ distributions in response to environmental change. Here, we test its predictive ability through time (rather than through space, as is commonly done) by modeling colonizations and extinctions. Location Continental U.S. and southern Canada. Time period 1979-2009 Major taxa studied Twenty-one species of passerine birds. Methods We used MaxEnt to relate species’ geographic distributions to the variation in environmental conditions across North America. We then modelled site-specific colonizations and extinctions between 1979 and 2009 as functions of MaxEnt-estimated previous habitat suitability and inter- annual change in habitat suitability and neighborhood occupancy. We evaluated whether the effects were in the expected direction, we partitioned model’s explained deviance, and we compared colonization and extinction model’s accuracy to MaxEnt’s AUC. Results IV Colonization and extinction probabilities both varied as functions of previous habitat suitability, change in habitat suitability, and neighborhood occupancy, in the expected direction. Change in habitat suitability explained very little deviance compared to other predictors. Neighborhood occupancy accounted for more explained deviance in colonization models than in extinction models. MaxEnt AUC correlates with extinction models’ predictive ability, but not with that of colonization models. Main conclusions MaxEnt appears to sometime capture a real effect of the environment on species’ distributions since a statistical effect of habitat suitability is detected through both time and space. However, change in habitat suitability (which is much smaller through time than through space) is a poor predictor of change in occupancy. Over short time scales, proximity of sites occupied by conspecifics predicts changes in occupancy just as well as MaxEnt. The ability of MaxEnt models to predict spatial variation in occupancy (as measured by AUC) gives little indication of transferability through time. Thus, the predictive value of species distribution models may be overestimated when evaluated through space only. Future prediction of species’ responses to climate change should make a distinction between colonization and extinction, recognizing that the two processes are not equally well predicted by SDMs.

Cost-effective reduction in the uncertainty surrounding global indicators of biodiversity change is a central goal of conservation. In this thesis, I identify and resolve the effects of IUCN Data Deficient species on the estimation of global patterns and levels of extinction risk. I show that gaps in our knowledge of species' conservation status are primarily driven by spatial patterns of ecological research (Chapter 2). Large numbers of species are extremely poorly known, highlighting the importance of basic taxonomic and natural history information in conservation assessments. Using sensitivity analyses (Chapter 3), I show that Data Deficient species contribute to considerable uncertainty in patterns of extinction risk in freshwater invertebrates, limiting our understanding of the factors influencing extinction risks and our capacity to design reliable conservation schemes. To determine the likely conservation status of Data Deficient species, I develop seven machine learning models based on species' life-history traits, niche and threat exposure (Chapter 4). I find that machine learning models accurately predict species conservation status and geographical patterns of threatened species richness. I predict 64% of Data Deficient mammals to be at risk of extinction, increasing the estimated proportion of threatened mammals from 22% to 27% globally. Finally, I use sampling theory to compare the cost-effectiveness of predictive models and IUCN Red List assessments in mammals, amphibians, reptiles and crayfish (Chapter 5). Double sampling with predictive models reduces the cost of determining the proportion of Data Deficient species at risk of extinction by up to 69%, and can be used to reduce the impact of uncertainty in the Red List and Red List Index. My thesis demonstrates how predictive models and decision theory can strengthen indicators of biodiversity change to monitor progress towards international biodiversity targets.

Loss of biodiversity is one of the most severe threats to the ecosystems of the world. The major causes behind the high population and species extinction rates are anthropogenic activities such as overharvesting of natural populations, pollution, climate change and destruction and fragmentation of natural habitats. There is an urgent need of understanding how these species losses affect the ecological structure and functioning of our ecosystems. Ecological communities exist in a landscape but the spatial aspects of community dynamics have until recently to large extent been ignored. However, the community’s response to species losses is likely to depend on both the structure of the local community as well as its interactions with surrounding communities. Also the characteristics of the species going extinct do affect how the community can cope with species loss. The overall goal of the present work has been to investigate how both local and regional processes affect ecosystem stability, in the context of preserved biodiversity and maintained ecosystem functioning. The focus is particularly on how these processes effects ecosystem’s response to species loss. To accomplish this goal I have formulated and analyzed mathematical models of ecological communities. We start by analyzing the local processes (Paper I and II) and continue by adding the regional processes (Paper III, IV and V). In Paper I we analyze dynamical models of ecological communities of different complexity (connectance) to investigate how the structure of the communities affects their resistance to species loss. We also investigate how the resistance is affected by the characteristics, like trophic level and connectivity, of the initially lost species. We find that complex communities are more resistant to species loss than simple communities. The loss of species at low trophic levels and/or with high connectivity (many links to other species) triggers, on average, the highest number of secondary extinctions. We also investigate the structure of the post-extinction community. Moreover, we compare our dynamical analysis with results from topological analysis to evaluate the importance of incorporating dynamics when assessing the risk and extent of cascading extinctions. The characteristics of a species, like its trophic position and connectivity (number of ingoing and outgoing trophic links) will affect the consequences of its loss as well as its own vulnerability to secondary extinction. In Paper II we characterize the species according to their trophic/ecological uniqueness, a new measure of species characteristic we develop in this paper. A species that has no prey or predators in common with any other species in the community will have a high tropic uniqueness. Here we examine the effect of secondary extinctions on an ecological community’s trophic diversity, the range of different trophic roles played by the species in a community. We find that secondary extinctions cause loss of trophic diversity greater than expected from chance. This occurs because more tropically unique species are more vulnerable to secondary extinctions. In Paper III, IV and V we expand the analysis to also include the spatial dimension. Paper III is a book chapter discussing spatial aspects of food webs. In Paper IV we analyze how metacommunities (a set of local communities in the landscape connected by species dispersal) respond to species loss and how this response is affected by the structure of the local communities and the number of patches in the metacommunity. We find that the inclusion of space reduces the risk of global and local extinctions and that lowly connected communities are more sensitive to species loss. In Paper V we investigate how the trophic structure of the local communities, the spatial structure of the landscape and the dispersal patterns of species affect the risk of local extinctions in the metacommunity. We find that the pattern of dispersal can have large effects on local diversity. Dispersal rate as well as dispersal distance are important: low dispersal rates and localized dispersal decrease the risk of local and global extinctions while high dispersal rates and global dispersal increase the risk. We also show that the structure of the local communities plays a significant role for the effects of dispersal on the dynamics of the metacommunity. The species that are most affected by the introduction of the spatial dimension are the top predators.