Showing papers by "Guy F. Midgley published in 2008"
TL;DR: This review proposes two main avenues to progress the understanding and prediction of the different processes occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena and concludes with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world.
Abstract: Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species' range shifts, changes in phenology and species' extinctions, accurate projections of species' responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species' responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species' distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the "trailing edge" of shifting populations, species' interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes A occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species' migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species' distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world. (c) 2007 Rubel Foundation, ETH Zurich. Published by Elsevier GrnbH. All rights reserved.
1,134 citations
TL;DR: A novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
Abstract: Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
626 citations
01 Jan 2008
TL;DR: Invasive alien plant species pose significant challenges to managing and maintaining indigenous biodiversity in natural ecosystems as mentioned in this paper and the question of how climate change will interact in this global process of ecosystem modification is becoming highly relevant for natural resource management.
Abstract: Invasive alien plant species pose significant challenges to managing and maintaining indigenous biodiversity in natural ecosystems. Invasive plants can transform ecosystems by establishing viable populations with growth rates high enough to displace elements of the native biota (Rejmánek 1999) or to modify disturbance regimes (Brooks et al. 2004), thereby potentially transforming ecosystem structure and functioning (Dukes and Mooney 2004). Because the numbers of invasive plant species and the extent of invasions are increasing rapidly in many regions, concern has grown about the stability of these novel, emerging ecosystems (Hobbs et al. 2006). The question of how climate change will interact in this global process of ecosystem modification is becoming highly relevant for natural resource management. Although many studies have addressed the potential threats to ecosystems from invasive alien plants and climate change separately, few studies have considered the interactive and potentially synergistic impacts of these two factors on ecosystems (but see Ziska 2003). Climatic and landscape features set the ultimate limits to the geographic distribution of species and determine the seasonal conditions for establishment, recruitment, growth and survival (Rejmánek and Richardson 1996; Thuiller et al. 2006b). Human-induced climate change is therefore a pervasive element of the multiple forcing functions which maintain, generate and threaten natural biodiversity. A widely stated view is that climate change is likely to enhance the capacity of alien species to invade new areas, while simultaneously decreasing the resistance to invasion of natural communities by disturbing the dynamic equilibrium maintaining them. Links between invasion dynamics and climate change are, nevertheless, particularly difficult to conceptualize (Fig. 12.1). The determinants of plant invasiveness per se are extremely complex (Rejmánek et al. 2005). Consequently, efforts to combat plant invasions
200 citations
TL;DR: It is proved that the given planning goals cannot be achieved with a smaller area, given the modeling assumptions and data, so an alternate formalization of a minimum range size moving through time is proposed and used to achieve the revised goals, again with the smallest possible newly protected area.
Abstract: We introduce a new way of measuring and optimizing connectivity in conservation landscapes through time, accounting for both the biological needs of multiple species and the social and financial constraint of minimizing land area requiring additional protection. Our method is based on the concept of network flow; we demonstrate its use by optimizing protected areas in the Western Cape of South Africa to facilitate autogenic species shifts in geographic range under climate change for a family of endemic plants, the Cape Proteaceae. In 2005, P. Williams and colleagues introduced a novel framework for this protected area design task. To ensure population viability, they assumed each species should have a range size of at least 100 km 2 of predicted suitable conditions contained in protected areas at all times between 2000 and 2050. The goal was to design multiple dispersal corridors for each species, connecting suitable conditions between time periods, subject to each species' limited dispersal ability, and minimizing the total area requiring additional protection. We show that both minimum range size and limited dispersal abilities can be naturally modeled using the concept of network flow. This allows us to apply well-established tools from operations research and computer science for solving network flow problems. Using the same data and this novel modeling approach, we reduce the area requiring additional protection by a third compared to previous methods, from 4593 km 2 to 3062 km 2 , while still achieving the same conservation planning goals. We prove that this is the best solution mathematically possible: the given planning goals cannot be achieved with a smaller area, given our modeling assumptions and data. Our method allows for flexibility and refinement of the underlying climate-change, species-habitat-suitability, and dispersal models. In particular, we propose an alternate formalization of a minimum range size moving through time and use network flow to achieve the revised goals, again with the smallest possible newly protected area (2850 km 2 ). We show how to relate total dispersal distance to probability of successful dispersal, and compute a trade-off curve between this quantity and the total amount of extra land that must be protected.
160 citations
TL;DR: In this paper, the authors developed a habitat model to aid in the identification of isolated populations, offer opportunities for re-introduction or introduction, and guide future conservation efforts by assessing the possible impacts of global change.
30 citations
TL;DR: In this paper, the authors provide a description of plant diversity patterns, growth form composition and species turnover across the gradient and the results of four years of climate monitoring at selected points along the altitudinal gradient.
Abstract: A temperature and moisture gradient on the equator-facing slope of Jonaskop on the Riviersonderend Mountain. Westem Cape has been selected as an important gradient for monitoring the effects of climate change on fynbos and the Fynbos- Succulent Karoo ecotone. This study provides a description of plant diversity patterns, growth form composition and species turnover across the gradient and the results of four years of climate monitoring at selected points along the altitudinal gradient.The aim o f this study is to provide data for a focused monitoring strategy for the early detection of climate change-related shifts in species’ ranges, as well as gaining a better understanding of the role of climate variability in shaping species growth responses, their distributions, and other ecosystem processes.
20 citations
TL;DR: The recently concluded EU funded project MACIS as discussed by the authors reviewed observed and projected climate change impacts on biodiversity and developed methods to assess future impacts of climate change on biodiversity including the identification of policy options to prevent and minimise these impacts.
Abstract: The recently finished EU funded project MACIS reviewed observed and projected climate change impacts on biodiversity. It assessed mitigation and adaptation options. It also reviewed and developed methods to assess future impacts of climate change on biodiversity including the identification of policy options to prevent and minimise these impacts.
16 citations
01 Jan 2008
TL;DR: In this paper, the authors used frequency counts to deal with species presence data, then used the recently developed partial differential equation motivated regression (PDEMR) model to predict the unknown locations, and finally combine these data to produce a kriging prediction map.
Abstract: Ecological data is very costly and difficult to collect, and quite often the sampled data are insufficient for further spatial analysis. Today, we as spatial modellers are often presented with the situation whereby a set of data is collected already, although from the viewpoint of spatial analysis the data is insufficient, but re-sampling is impossible because of the cost and time limits. In this paper, we are dealing with a two spatial problems whereby: the data is just species presence only and no numerical data; and also the data sampling is not well spread over the study area. These are two very common problems that spatial modellers face everyday, and in this paper we provide some simple techniques to deal with these problems. We firstly use frequency counts to deal with species presence data, then use the recently developed partial differential equation motivated regression (PDEMR) model to predict the unknown locations, and finally combine these data to produce a kriging prediction map. These techniques are fairly new, but very effective in dealing with ecological data problems. For illustration, Protea rare species ( i.e., the population size of 10 to 100), in the Cape Floristic Region, from 1992 to 2002, South Africa, are used.
6 citations
01 Jan 2008
TL;DR: In this article, the authors developed a bivariate partial differential equation associated regression (PDEAR) model for investigating the impacts from rainfall and temperature on the Protea species in the Cape Floristic Region, South Africa.
Abstract: One of the major concerns today is global warming and climate change impacts, and how they are changing the distribution and behaviour of the plant species. For example, Proteas species in the Cape Floristic Region, South Africa, are very sensitive to climate change. In this paper, we first arguing and the random fuzzy error structure for spatial modelling accuracy and then we are focusing on the population category of rare Proteas that has an estimated population size from 1 to 10 per sample site, which is very small. We develop a bivariate partial differential equation associated regression (PDEAR) model for investigating the impacts from rainfall and temperature on the Protea species. Under same the average biodiversity structure assumptions, we explore the future spatial change patterns of Protea species with future (average) predicted rainfall and temperature. Our investigation shows that the global climate change impacts on distributional patterns of the endangered Protea species are significant.
2 citations
21 Dec 2008
TL;DR: In this article, the authors examined and compared two South African Acacia tree species: Acacia gerrardii and Acacia tortilis subsp. Heteracantha, and look at how they change in terms of distribution in the future (2100).
Abstract: Global climate changes are changing our ecosystem and therefore changing the spatial distributional pattern of plants and trees. In this paper, we examine and compare the two South African Acacia tree species: Acacia gerrardii var. gerrardii and Acacia tortilis subsp. Heteracantha, and look at how they change in terms of distribution in the future (2100). We used the PDEAR (partial differential equation associated regression) model to analyze the tree species future spatial pattern changes. The spatial distribution and patterns are clearly will help us to understand global climate changing impacts upon endangered species.