Llauradó Harvey, Pedro (2022) Modelado de hábitats fragmentados mediante redes complejas en el marco de la ecología de la conservación / Modeling of fragmented habitats through complex networks in the framework of conservation ecology. Maestría en Ciencias Físicas, Universidad Nacional de Cuyo, Instituto Balseiro.
![[img]](/style/images/fileicons/application_pdf.png)
| PDF (Tesis) Español 22Mb |
Resumen en español
Se implementó un modelo metapoblacional espacialmente explícito para la simulación de un sistema depredador-presa inmerso en un hábitat fragmentado, compuesto por un conjunto de parches habitables conectados mediante enlaces de dispersión lenta. Un formalismo particularmente adecuado para describir este tipo de hábitats es el de la teoría de grafos. Específicamente, en este trabajo se implementaron Redes de Umbral Geográfico, cuyos nodos poseen coordenadas espaciales y donde las conexiones se establecen por proximidad. Para agregar un mayor nivel de detalle al modelo, se utilizaron multigrafos, por lo que cada especie posee su propio conjunto de aristas, de manera que la probabilidad de acceder a un parche dado es distinta para presas y depredadores. Se encontró una amplia región del espacio de fases en la cual la coexistencia entre ambas especies es posible. La exploración de la especificidad en la dieta del depredador y de la presión de depredación reveló una alta sensibilidad del sistema a los valores de los parámetros utilizados. Esto es relevante desde un punto de vista ecológico, ya que remarca el hecho de que ciertos ecosistemas pueden sufrir modificaciones sustanciales frente a pequeños cambios en la forma en la que las especies interactúan. Otro resultado destacable es que las presas presentan un efecto de refugio: el tiempo de vida medio es mayor en los parches donde el depredador tiene baja conectividad. Por ultimo, se estudió el impacto de diferentes estrategias para la destrucción y reconstrucción de parches. Se encontró que el sistema presenta histéresis, es decir, la densidad de ambas especies puede diferir para un mismo número de parches removidos según se esté ejecutando un proceso de destrucción o de restauración de la red. Esta diferencia está asociada a la fragmentación de la componente gigante en subgrafos pequeños, donde la supervivencia se ve dificultada ya que las fluctuaciones estocásticas se hacen comparables al tamaño del subsistema. La destrucción de nodos donde la presa posee grado elevado resultó la más perjudicial para el ecosistema en su conjunto, ya que la componente gigante de la presa se fragmenta mucho antes que la del depredador. De forma analogía, aquellas estrategias que priorizan la restauración de parches donde la presa tiene mayor grado son las más eficientes para la recuperación simultánea de ambas especies, ya que la presa percibe una rápida mejora en la conectividad. Este aumento en su colonización efectiva se traduce en un incremento en su densidad, beneficiando indirectamente a los depredadores. Por el contrario, si los parches que se restauran maximizan el flujo de depredadores en la red, el impacto sobre las presas es muy negativo, por lo que no es una estrategia recomendable si lo que se busca es una recuperación homogénea del ecosistema. Los hábitats fragmentados resultan ubicuos en la naturaleza. La destrucción de estos ecosistemas es considerada la mayor causa de la pérdida de biodiversidad actual. Estudiar el impacto que las diferentes estrategias de restauración pueden tener en la recuperación de estos hábitats es de vital importancia para la toma de decisiones en la gestión de los recursos naturales y para el desarrollo de políticas optimas de conservación.
Resumen en inglés
A spatially explicit metapopulation model was implemented to simulate a predatorprey system immersed in a fragmented habitat, composed of a set of habitable patches connected by slow dispersal links. A particularly suitable formalism to describe this type of habitat is that of graph theory. Specifically, in this work Geographic Threshold Networks were implemented, whose nodes have spatial coordinates and where connections are established by proximity. To add a higher level of detail to the model, multigraphs were used, where each species has its own set of edges, so the probability of accessing a given patch depends upon the species considered. A wide region of the phase space was found in which the coexistence between both species is possible. The exploration of the specificity in the predator’s diet and of the predation pressure revealed a high sensitivity of the system to the values of the parameters used. This is relevant from an ecological point of view, since it highlights the fact that certain ecosystems can undergo substantial modifications in the face of small changes in the way in which species interact. Another noteworthy result is that the prey presents a refuge effect: the mean lifetime is longer in patches where the predator has low connectivity. Finally, the impact of different strategies for the destruction and reconstruction of patches was studied. It was found that the system presents hysteresis, that is, the density of both species can differ for the same number of patches removed depending on whether a network destruction or restoration process is being executed. This difference is associated with the fragmentation of the giant component into small subgraphs, where survival is harder since stochastic fluctuations become comparable to the size of the subsystem. The destruction of nodes where the prey has a high degree was the most detrimental to the ecosystem as a whole, since the giant component of the prey fragments much earlier than that of the predator. Similarly, those strategies that prioritize the restoration of patches where the prey has a higher grade are the most efficient for the simultaneous recovery of both species, since the prey perceives a rapid improvement in connectivity. This increase in their effective colonization translates into an increase in their density, indirectly benefiting predators. On the contrary, if the patches that are restored maximize the flow of predators in the network, the impact on the prey is very negative, so it is not a recommended strategy if a homogeneous recovery of the ecosystem is sought. Fragmented habitats are ubiquitous in nature. The destruction of these ecosystems is considered the main cause of current biodiversity loss. Studying the impact that different restoration strategies can have on the recovery of these habitats is of vital importance for decision-making in the management of natural resources and for the development of optimal conservation policies.
| Tipo de objeto: | Tesis (Maestría en Ciencias Físicas) |
|---|---|
| Palabras Clave: | [Mathematical ecology; Ecología matemática; Metapopulations; Metapoblaciones; Predator-prey model; Modelo depredador-presa; Fragmented habitat; Habitat fragmentado; Complex Networks; Redes complejas; Patch destructions; Destrucción de parches] |
| Referencias: | [1] Spatial Ecology: The Role of Space in Population Dynamics and Interspecific Interactions (MPB-30). Princeton University Press, 1997. URL http://www.jstor.org/stable/j.ctv36zpzm. 1 [2] Volterra, V. Variations and fluctuations of the number of individuals in animal species living together. ICES Journal of Marine Science, 3 (1), 3–51, 1928. 1 [3] Gause, G. F. Experimental analysis of vito volterra’s mathematical theory of the struggle for existence. Science, 79 (2036), 16–17, 1934. 1 [4] Nicholson, A. J., Bailey, V. A. The balance of animal populations.—part i. En: Proceedings of the zoological society of London, tomo 105, pags. 551–598. Wiley Online Library, 1935. 2 [5] Debach, P., Smith, H. S. The effect of host density on the rate of reproduction of entomophagous parasites. Journal of Economic Entomology, 34 (6), 741–745, 1941. 2 [6] Huffaker, C., et al. Experimental studies on predation: dispersion factors and predator-prey oscillations. Hilgardia, 27 (14), 343–383, 1958. 2, 30 [7] Pimentel, D., Nagel, W., Madden, J. L. Space-time structure of the environment and the survival of parasite-host systems. The American Naturalist, 97 (894), 141–167, 1963. 2 [8] Andrewartha, H. G., Birch, L. C., et al. The distribution and abundance of animals. Ed 1. University of Chicago press, 1954. 2 [9] MacArthur, R., Wilson, E. 0. i967 the theory of island biogeography. Princeton, UP, New Jersey, 1944. 2, 4, 21, 26 [10] Glassman, S. I., Lubetkin, K. C., Chung, J. A., Bruns, T. D. The theory of island biogeography applies to ectomycorrhizal fungi in subalpine tree “islands” at a fine scale. Ecosphere, 8 (2), e01677, 2017. 3 [11] Bell, T., Ager, D., Song, J.-I., Newman, J. A., Thompson, I. P., Lilley, A. K., et al. Larger islands house more bacterial taxa. Science, 308 (5730), 1884–1884, 2005. 3 [12] Levins, R. Some demographic and genetic consequences of environmental heterogeneity for biological control. American Entomologist, 15 (3), 237–240, 1969. 3, 21, 65 [13] Hastings, A., Wolin, C. L. Within-patch dynamics in a metapopulation. Ecology, 70 (5), 1261–1266, 1989. 3, 21 [14] Horn, H. S., MacArthur, R. H. Competition among fugitive species in a harlequin environment. Ecology, 53 (4), 749–752, 1972. 3 [15] Hanski, I. Coexistence of competitors in patchy environment. Ecology, 64 (3), 493–500, 1983. [16] Slatkin, M. Competition and regional coexistence. Ecology, 55 (1), 128–134, 1974. 3, 21 [17] Harrison, S., Quinn, J. F. Correlated environments and the persistence of metapopulations. Oikos, pags. 293–298, 1989. 3 [18] Day, J. R., Possingham, H. P. A stochastic metapopulation model with variability in patch size and position. Theoretical population biology, 48 (3), 333–360, 1995. 4 [19] Moilanen, A. Patch occupancy models of metapopulation dynamics: efficient parameter estimation using implicit statistical inference. Ecology, 80 (3), 1031–1043, 1999. [20] Hanski, I., Ovaskainen, O. The metapopulation capacity of a fragmented landscape. Nature, 404 (6779), 755–758, 2000. 4 [21] Gilpin, M. Metapopulation dynamics: empirical and theoretical investigations. Academic press, 2012. 4 [22] Burgman, M. A., Ferson, S., Ak¸cakaya, H. R. Risk assessment in conservation biology, tomo 12. Springer Science & Business Media, 1993. 4 [23] Taylor, P. D., Fahrig, L., Henein, K., Merriam, G. Connectivity is a vital element of landscape structure. Oikos, pags. 571-573,1993.4 [24] Urban, D., Keitt, T. Landscape connectivity: a graph-theoretic perspective. Ecology, 82 (5), 1205–1218, 2001. 4, 5 [25] Fortuna, M. A., Gomez-Rodrıguez, C., Bascompte, J. Spatial network structure and amphibian persistence in stochastic environments. Proceedings of the Royal Society B: Biological Sciences, 273 (1592), 1429–1434, 2006. 5 [26] Keitt, T. H., Urban, D. L., Milne, B. T. Detecting critical scales in fragmented landscapes. Conservation ecology, 1 (1), 1997. [27] Minor, E. S., Urban, D. L. Graph theory as a proxy for spatially explicit population models in conservation planning. Ecological applications, 17 (6), 1771–1782, 2007. 5 [28] Saura, S., Rubio, L. A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography, 33 (3), 523–537, 2010. 5 [29] Schick, R. S., Lindley, S. T. Directed connectivity among fish populations in a riverine network. Journal of applied ecology, 44 (6), 1116–1126, 2007. [30] Estrada, E., Bodin, O. Using network centrality measures to manage landscape connectivity. Ecological Applications, 18 (7), 1810–1825, 2008. 5 [31] Pascual-Hortal, L., Saura, S. Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Landscape ecology, 21 (7), 959–967, 2006. 5 [32] Masuda, N., Miwa, H., Konno, N. Geographical threshold graphs with small-world and scale-free properties. Physical Review E, 71 (3), 036108, 2005. 5, 7, 10, 12, 21, 63 [33] Dale, M., Fortin, M.-J. From graphs to spatial graphs. Annual Review of Ecology, Evolution, and Systematics, pags. 21–38, 2010. 7 [34] Turner, M. G., Gardner, R. H., O’neill, R. V., O’Neill, R. V. Landscape ecology in theory and practice, tomo 401. Springer, 2001. 7 [35] Jonsen, I. D., Taylor, P. D. Fine-scale movement behaviors of calopterygid damselflies are influenced by landscape structure: an experimental manipulation. Oikos, 88 (3), 553–562, 2000. 7 [36] Haddad, N. M. Corridor and distance effects on interpatch movements: a landscape experiment with butterflies. Ecological Applications, 9 (2), 612–622, 1999. 7 [37] Konigsberg. https://www.maa.org/press/periodicals/convergence/leonard-eulers-solution-to-the-konigsberg-bridge-problem-konigsberg, 2005. Accessed: 2022-10-31. 8 [38] West, D. B., et al. Introduction to graph theory, tomo 2. Prentice hall Upper Saddle River, 2001. 9 [39] Taubert, F., Fischer, R., Groeneveld, J., Lehmann, S., Muller, M. S., Rodig, E., et al. Global patterns of tropical forest fragmentation. Nature, 554 (7693), 519–522, 2018. 10 [40] Dytham, C. The effect of habitat destruction pattern on species persistence: a cellular model. Oikos, pags. 340–344, 1995. 15 [41] Sader, S. A., Joyce, A. T. Deforestation rates and trends in costa rica, 1940 to 1983. Biotropica, pags. 11–19, 1988. 15 [42] Fearnside, P. M. Spatial concentration of deforestation in the brazilian amazon. Ambio, pags. 74–81, 1986. 16 [43] Holme, P., Kim, B. J., Yoon, C. N., Han, S. K. Attack vulnerability of complex networks. Physical review E, 65 (5), 056109, 2002. 16 [44] Cohen, R., Erez, K., Ben-Avraham, D., Havlin, S. Breakdown of the internet under intentional attack. Physical review letters, 86 (16), 3682, 2001. 16 [45] Min, B., Do Yi, S., Lee, K.-M., Goh, K.-I. Network robustness of multiplex networks with interlayer degree correlations. Physical Review E, 89 (4), 042811, 2014. 19 [46] Swihart, R. K., Feng, Z., Slade, N. A., Mason, D. M., Gehring, T. M. Effects of habitat destruction and resource supplementation in a predator–prey metapopulation model. Journal of Theoretical Biology, 210 (3), 287–303, 2001. 22, 27, 48, 50, 63 [47] Harrison, S. Local extinction in a metapopulation context: an empirical evaluation. Biological journal of the Linnean Society, 42 (1-2), 73–88, 1991. 26, 27 [48] Richter-Dyn, N., Goel, N. S. On the extinction of a colonizing species. Theoretical population biology, 3 (4), 406–433, 1972. 26 [49] Sjogren, P. Extinction and isolation gradients in metapopulations: the case of the pool frog (rana lessonae). Biological Journal of the Linnean society, 42 (1-2), 135–147, 1991. 26 [50] Goodman, D., et al. The demography of chance extinction. Viable populations for conservation, 11, 34, 1987. 26 [51] Karr, J. R. Population variability and extinction in the avifauna of a tropical land bridge island. Ecology, pags. 1975–1978, 1982. 26 [52] Pimm, S. L., Jones, H. L., Diamond, J. On the risk of extinction. The American Naturalist, 132 (6), 757–785, 1988. 26 [53] Ehrlich, P. R., Murphy, D. D., Singer, M. C., Sherwood, C., White, R., Brown, I. Extinction, reduction, stability and increase: the responses of checkerspot butterfly (euphydryas) populations to the california drought. Oecologia, 46 (1), 101–105, 1980. 26 [54] Dunning, J. B., Danielson, B. J., Pulliam, H. R. Ecological processes that affect populations in complex landscapes. Oikos, pags. 169–175, 1992. 27 [55] Henttonen, H., Oksanen, T., Jortikka, A., Haukisalmi, V. How much do weasels shape microtine cycles in the northern fennoscandian taiga? Oikos, pags. 353–365, 1987. 27 [56] Henttonen, H., Kaikusalo, A., Tast, J., Viitala, J. Interspecific competition between small rodents in subarctic and boreal ecosystems. Oikos, pags. 581–590, 1977. 27 [57] Andersson, M., Erlinge, S. Influence of predation on rodent populations. Oikos, pags. 591–597, 1977. 27 [58] Hanski, I., Hansson, L., Henttonen, H. Specialist predators, generalist predators, and the microtine rodent cycle. The Journal of Animal Ecology, pags. 353–367, 1991. 27 [59] Ebenhard, T. Colonization in metapopulations: a review of theory and observations. Biological Journal of the Linnean Society, 42 (1-2), 105–121, 1991. 27, 28 [60] Williamson, M. H., Brown, K. C. The analysis and modelling of british invasions. Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 314 (1167), 505–522, 1986. 27 [61] Holekamp, K. E., Sherman, P. W. Why male ground squirrels disperse: a multilevel analysis explains why only males leave home. American Scientist, 77 (3), 232–239, 1989. 28 [62] Dobson, F. S., Jones, W. T. Multiple causes of dispersal. The American Naturalist, 126 (6), 855–858, 1985. 28 [63] Pusey, A. E. Sex-biased dispersal and inbreeding avoidance in birds and mammals. Trends in ecology & evolution, 2 (10), 295–299, 1987. 28 [64] Pugh, S. R., Tamarin, R. H. Inbreeding in a population of meadow voles, microtus pennsylvanicus. Canadian Journal of Zoology, 66 (8), 1831–1834, 1988. 28 [65] Mason, D. M., Patrick, E. V. A model for the space–time dependence of feeding for pelagic fish populations. Transactions of the American Fisheries Society, 122 (5), 884–901, 1993. 28 [66] Zollner, P. A. Comparing the landscape level perceptual abilities of forest sciurids in fragmented agricultural landscapes. Landscape ecology, 15 (6), 523–533, 2000. 28 [67] Fahrig, L. Relative effects of habitat loss and fragmentation on population extinction. The Journal of wildlife management, pags. 603–610, 1997. 47, 48 [68] Millennium Ecosystem Assessment. URL https://www.millenniumassessment.org/documents/document.356.aspx.pdf, Year: 2005. 47 [69] Earth, G. Our forests — timelapse in google earth. URL https://www.youtube.com/watch?v=b4eLTYUcj7k. 47 [70] Battisti, C. Habitat fragmentation, fauna and ecological network planning: Toward a theoretical conceptual framework. Italian Journal of Zoology, 70 (3), 241–247, 2003. 48 [71] Bascompte, J., Sole, R. V. Habitat fragmentation and extinction thresholds in spatially explicit models. Journal of Animal ecology, pags. 465–473, 1996. 48 [72] Bascompte, J., Sol´e, R. V. Effects of habitat destruction in a prey–predator metapopulation model. Journal of Theoretical Biology, 195 (3), 383–393, 1998. 48, 49, 50, 51, 65 [73] Tilman, D., May, R. M., Lehman, C. L., Nowak, M. A. Habitat destruction and the extinction debt. Nature, 371 (6492), 65–66, 1994. 48, 59 [74] Torok, P., Helm, A. Ecological theory provides strong support for habitat restoration. Biological Conservation, 206, 85–91, 2017. 48 [75] Tilman, D., Lehman, C. L. Habitat destruction and species extinctions. Spatial ecology, pags. 233–249, 1997. 48 [76] Gawecka, K. A., Bascompte, J. Habitat restoration in spatially explicit metacommunity models. Journal of Animal Ecology, 90 (5), 1239–1251, 2021. 48, 55, 56 [77] Lande, R. Extinction thresholds in demographic models of territorial populations. The American Naturalist, 130 (4), 624–635, 1987. 49 |
| Materias: | Física > Dinámica poblacional de especies ecológicas |
| Divisiones: | Gcia. de área de Investigación y aplicaciones no nucleares > Gcia. de Física > Sistemas complejos y altas energías > Física estadística interdisciplinaria |
| Código ID: | 1154 |
| Depositado Por: | Tamara Cárcamo |
| Depositado En: | 03 Aug 2023 16:06 |
| Última Modificación: | 03 Aug 2023 16:06 |
Personal del repositorio solamente: página de control del documento
