Landscape Connectivity & Metapopulation Dynamics

Transcription

1 Shelby Southworth 509: Concepts in GIS & RS December 6 th, 2012 Landscape Connectivity & Metapopulation Dynamics The natural world is growing increasingly fragmented due to human activities, and once expansive habitats that supported wildlife populations have been divided and truncated over time. As the human population grows, so too does the impact that human society has on the landscape. Wildlife populations are now more likely to be small in individual numbers, restricted in range/ distribution, and increasingly isolated from other local populations of the same species. Based on this trending pattern in wildlife populations, and in part due to new, sophisticated, theoretical developments, ecologists began stressing the importance of spatial context in relation to large scale studies such as those on the population, community and ecosystem levels. The field of spatial ecology then emerged, where spatial variation and complexity is included in ecological analysis, as well as changes in spatiality over time. Spatial ecology has been defined by two distinct approaches: landscape ecology, and metapopulation ecology (Rockwood 2011). Founded by community and ecosystem oriented ecologists, landscape ecology explicitly recognizes the heterogeneity of an environment, and addresses the importance of spatial configuration (landscape pattern) in ecological processes. The larger geographic scale of landscape ecology studies enable the description of physical structures in patchy environments, as well as the movement of individuals/ resources across the landscape mosaic. While landscape ecologists do not generally work on population dynamic studies, much of the work done by landscape ecologists is relevant to metapopulation ecology. A metapopulation (regional assemblage) is a collective of many local populations within a landscape, where each local population is influenced by immigration and emigration, as well as by birth and death processes. On the scale of the metapopulation, local populations are connected by migration, and commonly undergo local extinction within a species defined metapopulation range. The metapopulation analysis operates within this region, delineating suitable habitat for a target species (patch), and the unsuitable remainder of the landscape (matrix). The size of a patch in the matrix, and the isolation of a patch from other patches, can influence population density and colonization/ extinction rates. In effect, metapopulation ecology seeks to underscore the importance of the spatial structure of a habitat on population processes at a regional scale. With the effects of habitat fragmentation becoming more widely accepted during the 1990s, and the long term survival of a species being considered at the regional level, the metapopulation approach became standard in the world of conservation biology (Rockwood 2011). The dependence of metapopulation ecology on landscape ecology within the field of spatial ecology (specifically how connectivity of a landscape can affect metapopulation

2 dynamics), and the technologies used to derive spatial data for analysis, are the focal points of this project. To provide real world perspective on the application of spatial technologies in a field tailored to the use of spatial data, I reviewed six different studies: two studies on carnivores (Ocelots Janeka et al. 2011; Jaguars Rabinowitz & Zeller 2010), two on large ungulates (Bighorn sheep DeCesare & Pletscher 2006; White tailed deer Walter et al. 2009), and two on small herbivores (Round tailed muskrats Schooley & Branch 2006; Quokkas Hayward et al. 2005). Each study targets a land based, terrestrial animal in order to hone in on basic spatial ecology studies, where more complex metapopulation types presented by plant, avian, aquatic and entomological species were avoided. In the studies reviewed, many different technologies were used to achieve varied, but similar goals. As I had expected, due to the size of the focal species in these papers, I found that radio telemetry techniques were very common only one of them did not employ such technology in their study (Rabinowitz & Zeller 2010), and another simply used radio telemetry data from previous studies (Janecka et al. 2011). The Animal Movement extension for ArcView 3.2 was another commonly used spatial technology which was used in four of my papers. This extension for ArcView 3.2 was designed for studies like these in mind, where the movement of tracked individuals can be coupled with theories about habitat selection, use and migration. The tie in of landscape connectivity and metapopulation dynamics with these technologies is that without them, showing the connection between fragmented habitats and the survival of a species is more difficult. A large amount of modeling has to be done to estimate a species behavior without these softwares, although as we saw in the case of Walter et al. (2009), sometimes radio telemetry data must be processed through different models to help us understand why changes in behavior occur at different spatial and temporal scales. Most of the studies also used common GIS vectors such as different components from the ArcGIS suite (ArcView 3.2, ArcGIS 9) combined with the Spatial Analyst extension package. In one study that was based in Australia (Hayward et al. 2005), ESRI software was not even used, but rather MapInfo Professional (v. 5.5). While this notable issue was not highlighted by more of my papers, it is worth bringing up the variety and extent of map making software suites like ArcGIS that are used professionally across the world and even just across the USA. When studying in the realm of spatial ecology, which is inherently dependent on these technologies, knowledge of different processing software is important. The next step in understanding the role and use of spatial technology in landscape/metapopulation combined studies is the need for classification methods such as TWINSPAN, which was used by Hayward et al. (2005) to describe the structural and floristic landscape characteristics of their study area. In a different study, the Patch Analyst extension used by ArcView was used to assess landscape configuration via indicies through an interface with FragStats a software designed to compute landscape metrics for categorical map patterns (Walter et al. 2009). Landscape analysis and delineation of habitat patches should take into account specific behavioral/perceptual responses of a species to the landscape structure (which is why the use of radio telemetry in these studies is so common). PatchMorph is an algorithm tool that can do this, and is meant to be used in conjunction with software such as ArcGIS or MapInfo Professional (Walter et al. 2009).

3 Radio telemetry data, landscape classification indicies, patch delineation tools, and geographic information system software has proved to be very important in this area of study, but that is mostly due to the nature of landscape and metapopulation ecology being spatiallyexplicit in nature. Modeling makes up a large portion of these studies, whether it be statistical modeling such as done with Statview in the paper by Hayward et al. (2005), or the grid based, least cost funcational connectivity spatial modeling done by Rabinowitz & Zeller (2010). There are numerous examples of models and modeling techniques that can be used in spatial ecology, and as such it is impossible to mention them all here. On a separate, final note I also found that data such as USGS NED, TIGER 2000 Census data, SILC3 Land cover Classification data that were explicitly referenced by DeCesare & Pletscher (2006), were also used in some form for most of the other projects such as the NLCD 2001 referenced in Walter et al. (2009). I did not see a huge number of explicitly mentioned uses of remote sensing via imagery in these studies although Rabinowitz & Zeller (2010), and Walter et al. (2009) did use satellite data for land cover delineation. Spatial ecology is a very young field compared to others in the biological science, and as a field it is still forming some of its theoretical and practical bases. In the future, I expect to see a much larger emphasis placed on spatial ecology vs. traditional ecology because of the spatially explicit information that it inherently takes into consideration, making data and inferences much stronger. I first discovered the field of spatial ecology during my undergraduate years while taking a basic, theoretical population ecology class. Spatial ecology was used to introduce a chapter on metapopulation ecology in that class, and while I align my interests more with landscape ecology, this project has helped me see the cross application of data from both of these aspects of spatial ecology. I came to URI for graduate school to study spatial ecology and to learn about the application of spatial technologies in a research setting. The inherent spatiality of this field indicated that GIS and RS is already used to a large degree; I expect to see greater GIS and RS presence in the field than their already is in the future especially in the area of remote sensing. As the theory behind this field solidifies, and technologies continue to advance, spatial ecology seems to be emerging as a new paradigm in ecology.

4 DeCesare NJ, Pletscher DH Movements, connectivity and resource selection of Rocky Mountain Bighorn Sheep. Journal of Mammalogy. 87(3): In this paper, DeCesare and Pletscher used an information theoretic approach to study the movement and habitat selection of bighorn sheep (Ovis canadensis) in western Montana, where habitat quality, connectivity and disease play a role in the viability of each local population. They used radio telemetry to track the movement of 3 herd populations through the landscape each of which colonized areas that were previously unoccupied by bighorn sheep in Montana. They used the Animal Movement 2.0 extension for ArcView 3.2a software for tracking. Herd movements are related to 3 biologically meaningful seasons (winter, lambing, autumn); resource selection is different in each season. They selected explanatory variables for resource selection modeling from literature, and compiled the spatial data for each into a GIS using ArcView3.2a and the Spatial Analyst extension examples include USGS NED, TIGER 2000 Census data, SILC3 Land Cover Classification Data. They generated 10 candidate models based on their lit review and field observations for each season; slope, distance to escape terrain and distance to cover type (open area vs. dense cover) were identified as important habitat selection factors in all 3 seasons. This study is a good example of habitat factors that can delineate selection of different habitat patches by a species this is a highly connected metapopulation so genetic diversity is great, but the extent of connectivity in their landscape can also spell disaster via disease vectors. Hayward MW, de Tores PJ, Banks PB Habitat use of the Quokka, Setonix brachyurus (Macropodidae: Marsupialia), in the Northern Jarrah Forest of Australia. Journal of Mammalogy. 86(4): In this paper by Haward et al., habitat use of the small marsupial Quokka in Western Australia was studied using radio telemetry techniques monitoring 58 individuals over 2 years, in 5 different local populations in the northern jarrah forest bioregion. They digitized aerial photographs of the study area using MapInfo Professional v. 5.5 and demarcated the habitats of each of the 5 field sites, describing landscape characteristics (structural, floristic) using the classificatioin method, TWINSPAN. They also used software such as Statview to perform statistical analysis on their data. They found that, in the norther jarrah forest there is a distinct preference of quokkas for Agonis swamp shrubland habitat types in the intermediate stages of ecological succession (fire damage; historically could be a result of Aboriginal burn hunting, currently low intensity control burns). Preference for intermediate succession swamp habitats potentially related to high nitrogen levels in new foliage growth, the inaccessibility of older growth resources to these land bound marsupials, high water requirements, and refuge from red fox predation. This study is a good example of how smaller mammals may not be subject to the pressures of the loss of ideal, continuous habitat the quokka is restricted to such discreet habitat patches because dispersal between patches no longer occurs (a huge concern for the persistence of the overall metapopulation.

5 Janecka JE, Tewes ME, Laack LL, Caso A, Grassman LI, Hains AM, Shindle DB, Davis BW, Murphy WJ, Honeycutt RL Reduced genetic diversity and isolation of remnant ocelot populations occupying a severely fragmented landscape in Southern Texas. Animal Conservation. 14(6): In this paper Janecka et al. used GIS to display information about the genetics of three distinct ocelot populations with blood samples from previous radio telemetry studies between 1986 and The viability of these populations is threatened by the disappearance of their habitat (dense, thornshrub communities), human caused mortality and demographic stochasticity (variable growth rates due to differences among individuals in survival and reproductive success). They found that the two populations in Texas were very different genetically even though they are relatively close to one another compared to the population in Mexico; both of these populations were significantly divergent from the population in Mexico. The absence of detectable gene flow implies that the human modified landscape acts as a strong barrier to ocelot movement disrupting metapopulation dynamics and contributing to genetic erosion. While this study did not use GIS analysis, it did use GIS to represent their genetic data on a spatial scale. Rabinowitz A, Zeller KA A range wide model of landscape connectivity and conservation for the jaguar, Panthera onca. Biological Conservation. 143(4): In this paper, Rabinowitz and Zeller use GIS to create a spatial model for jaguar conservation. Using the spatial data in their GIS, as well as the insight of jaguar experts, they created a dispersal cost surface. This generated raster helped to identify least cost corridors within their natural landscape that connect the 90 known jaguar populations across their range in South America. They used a grid based, least cost functional connectivity model because they require accounting for landscape structure and species response to the landscape. Estimates for movement through the gridded landscape were based on a permeability matrix; depending on the characteristics of each pixel, it was calculated how easy/hard it would be for an individual to move through that space. This is a step beyond simple landscape connectivity via suitable habitat, because unsuitable habitat in this case is not simply assigned a single value, but can range from safe, permeable unsuitable(low cost) to dangerous, non permeable unsuitable habitat (high cost). This paper is a good example of how landscape connectivity can account for metapopulation health especially in this case where we are looking at a large feline predator which requires much more suitable habitat than other animals when migrating through the matrix. Schooley RL, Branch LC Space use by Round tailed Muskrats in isolated wetlands. Journal of Mammalogy. 87(3): In this paper by Schooly and Branch, radio tracking data from 23 individuals in 2 different populations was used to study space use patterns and dispersal of round tailed muskrat

6 (Neofiber alleni). This metapopulation of muskrats thrives in small, geographically isolated, fresh water marsh patches, with habitat patches occurring at an average distance of 312m. They used the Animal Movement extension for the Spatial Analyst module of ArcView GIS v. 3.2 to conduct home range analyses using the radiotelemetry data collected. Cross species equations were used to predict dispersal distances based on average body mass because actual dispersal data is very difficult to obtain. Based on these extrapolated data, the authors hypothesized that good quality habitat with many available resources may result in smaller home ranges, where low quality habitat may produce significantly larger ranges. In a broad scale study being performed by these authors concurrently, recolonization of vacant wetlands by this species does occur, and they also exhibit metapopulation dynamics within the wetlands (although they are not a highly vagile species). This paper is a good example of how landscape quality can affect the ranges of round tailed muskrats, and relates how landscape connectivity of suitable habitat patches is important to this species metapopulation dynamics. Walter WD, VerCauteren KC, Campa H, Clark WR, Fischer JW, Hygnstrom SE, Mathews NE, Nielsen CK, Schauber EM, Van Deelen TR, Winterstein SR Regional assessment on influence of landscape configuration and connectivity on range size of white tailed deer. Landscape Ecology. 24(10): In this paper, Walter et al. investigated how the size of home ranges of deer populations in agro forested landscapes are influenced by characteristics of the landscape that fill habitat suitability needs. They used radio telemetry, and the original Animal Movement Extension of ArcView 3.2, in order to track the movement of individuals within the metapopulation, within the annual home range of the different populations studied. They used a GIS to compile spatial data including the NLCD 2001, as well as census block group data, and road infrastructure data from previous studies/ unnamed databases. Because the spatial arrangement of vegetation cover types can influence habitat use in deer, landscape configuration was assessed using landscape pattern indices calculated using the Patch Analyst Extension of the Fragstats Interface within ArcView. They also used the PatchMorph patch delineation algorithm to rank the suitability of habitats by first delineating patches at several different grain sizes, representing different levels of connectivity as perceived by white tailed deer. They then used 7 anthropogenic variables in their GIS, and 17 landscape pattern indices in Fragstats, to run their statistical analyses. They found that seasonal changes in forage affected deer ranges as natural forage declines with the end of the growing season, deer shift to forage in large agricultural fields with little variation in core edge ratio. This suggests that deer occupy cover types that are insular in structure (small patches with similar patches close together) during the growing period, preferring complex edge habitat. The connectivity and complexity of this preferred matrix of forest and agricultural land cover in a landscape is important to deer range sizes. This study is a good example of landscape connectivity and its role in selection of habitat by deer.

7 Other Sources: Rockwood LL. Introduction to Population Ecology Chapter 5: Metapopulation Ecology Blackwell Publishing Ltd. Malden, MA, USA.