The importance of forest patch networks for the conservation of the Thorn tailed Rayaditos in central Chile
9
0
0
Texto completo
(2) 684. with ‘‘fine-grain’’ fragmentation commonly occupy patches smaller than their home-range area requirements, hence local populations of these birds may occur in ‘‘archipelagos’’, or networks, of patches rather than in single patches (Wiens 1976; Haila 1983; Rolstad and Wegge 1987; Hinsley et al. 1998; Hinsley 2000; Vergara and Marquet 2007). Consequently, conservation of forest birds in forest landscapes requires not only determining critical patch characteristics influencing local population persistence but also identifying patch networks providing connectivity and suitable habitat conditions necessary to ensure regional persistence. The purpose of this study is to assess the importance of single patches and patch networks of sclerophyllous forest in explaining the patch occupancy pattern of the Thorn-tailed Rayadito (Aphrastura spinicauda). Rayaditos are small insectivorous furnariids endemic to the south-temperate forests of Chile and Argentina, for which the north-central sclerophyllous forests of Chile represent the northernmost limit of their distribution range (Araya and Millie 1991). The native sclerophyllous forests, which once covered the low-elevation and pre-Andean areas of central and north-central Chile, have a natural patchy distribution, which is related to microclimatic conditions in this semiarid region (Armesto and Martı́nez 1978; Quintanilla 1983; Del Pozo et al. 1989). Over the last centuries, however, sclerophyllous forests have been extensively fragmented and degraded due to human disturbance and rapid urban growth (Fuentes et al. 1984). The historical degradation and fragmentation of sclerophyllous forests has resulted in a rapid loss of the endemic biodiversity of these ecosystems (Simonetti 1999; Vasquez and Simonetti 1999; Myers et al. 2000). In north-central Chile, rayaditos are distributed exclusively in the moister vegetation types, such as the sclerophyllous forests or relict forests, which are enclosed by xeric and open habitats that are not used by rayaditos (Lazo et al. 1990; Vergara 2007; Vergara and Marquet 2007). Although both density and breeding successes of rayaditos tend to increase in large and functionally connected patches (e.g., Vergara and Marquet 2007), yet methodological approaches to identify suitable networks for rayaditos are still missing. An important strategy to conserve populations of rayaditos in sclerophyllous forest of north-central Chile should be not only conserving single suitable patches but also identifying and maintaining networks of forest patches that provide habitat and connectivity for rayaditos. In order to achieve the objective stated above, we first determined the main patch scale variable accounting for the presence of rayaditos in patches of sclerophyllous forest. Second, we determined the effect of patch connectivity and network attributes on patch occupancy. Third, on the basis of the previous results we identified potential local populations of rayaditos occupying networks of forest patches that must be. conserved to ensure regional persistence of rayaditos in central Chile.. Methods Study area The study area is located on the foothills of the Andes ca. 15 km northeast and east of downtown Santiago (3322¢S, 7030¢W) and it comprises fragments of sclerophyllous vegetation within an area of about 600 km2 (Fig. 1). The climate of this area is Mediterranean semidesertic, with a mean annual rainfall of 310 mm concentrated (65%) during the winter months from June to August. The native vegetation around urban and industrial areas of Santiago has been largely removed for agricultural purposes or cattle grazing since the Spanish occupation in the 16th century (Armesto and Picket 1985). Patches basically include four types of sclerophyllous vegetation in the periphery of the city of Santiago: (1) Sclerophyllous forest with Cryptocarya alba (Lauraceae) as the dominant forest tree species, in addition to Lithraea caustica and Quillaja saponaria; (2) Open savanna of Acacia Caven; (3) Xeric sclerophyllous matorral, located on ridge tops and equatorial-facing slopes with spiny shrubs and cacti as dominant vegetation, including species such as Echinopsis chiloensis, Colliguaja odorifera and Podanthus mitique (Armesto and Martı́nez 1978; Fuentes et al. 1984); (4) Arborescent sclerophyllous matorral, located on ravines and polar slopes with shade-tolerant shrubs as dominant vegetation, including species such as Kageneckia oblonga, Kageneckia angustifolia, Trevoa quinquenervia, Schinus polygama, C. alba, L. caustica and Q. saponaria (Armesto and Martı́nez 1978; Fuentes et al. 1984, 1986; Jaksic 2001). Arborescent sclerophyllous matorral represents an early successional stage of regenerating sclerophyllous forest after fire and human/natural disturbance (Armesto and Picket 1985).. Santiago. 0 3 Km 0 25 Km. N W. E S. Fig. 1 On the left: the study area, located in the periphery of Santiago, Chile. On the right: map showing the location of the surveyed fragments of sclerophyllous forest (black areas) in a matrix of open savanna, open matorral, and urban areas (white areas) in central Chile.
(3) 685. Bird sampling Presence of rayaditos per patch was measured using playbacks, a technique that allowed ensuring a high detection probability, hence a reduction of false zeros in patch occupancy data (Falls 1981). We used tape-records of both common calls and alarm calls of rayaditos. The common call is used by rayaditos to maintain contact in the pair/family (vocalized when rayaditos are moving in the vegetation) and the alarm call is uttered in the presence of potential predators or conspecifics within home ranges (Hahn and Mattes 2000). During the breeding season of rayaditos (October– December), a total of 151 points were randomly distributed among the sampled patches. Within patches the number of points was proportional to patch area, ranging from 1 to 4, and distance between points was always >250 m. During the 2002 breeding season, two sampling counts were conducted on separate occasions (late September and mid-December) in the same patch. Counts lasted 8 min, starting with a playback session of 3 min (Vergara and Marquet 2007), and were carried out between 06:30 h and 14:30 h on rain-free days with little or no wind. Tapes were played back at relatively low volume (3 W) to avoid attracting birds from neighboring patches. Patch-scale variables Previous studies in north-central Chile have determined that rayaditos are distributed mainly in sclerophyllous forest and arborescent matorral (Vergara et al. 2003; Vergara 2007), and individuals of that species are absent from open savanna, urban areas, and xeric matorral (Lazo et al. 1990; Jaksic 2001; Vergara and Marquet 2007). Considering these findings, we used a GIS database (‘‘Catastro de Vegetación Nativa de Chile’’, CONAF-CONAMA-BIRF 1999), which provides information on land use and vegetation types at a 1:50,000 scale, to identify patches of sclerophyllous forest and arborescent matorral (hereafter both vegetation types are referred to as sclerophyllous forest), which can be potentially occupied by rayaditos. Consequently, in our analyses we considered that the matrix surrounding patches of sclerophyllous forest was composed by open savanna, urban areas, and xeric sclerophyllous matorral. Since this GIS database is based on aerial and satellite photos taken between 1994 and 1997, we used more recent aerial photos (1:20,000) taken in 2002 to digitize forest patches, calculate their areas, and estimate edgeto-edge patch distances (required to calculate patch connectivity; see below). Exact patch positions and their boundaries were checked in the field with a global positioning system (GPS) with differential correction. A total of 120 forest patches were sampled randomly from a total of 438 patches previously identified in the study area (Fig. 1). All selected forest patches were located more than 200 m apart. Within selected forest. patches, and at each bird sampling point (see below), we used a 0.04-ha plot where six variables were measured: (1) total canopy cover (%) using a densitometer; (2) tree density (number of trees/ha); (3) quadratic mean diameter at breast height (dbh) (cm), using a wooden caliper; (4) canopy height (m), measured as the average height of all trees (>5 cm dbh) within each 0.04 ha plot (Vergara and Marquet 2007), using a clinometer; (5) Cryptocarya Alba cover (%), using a densitometer; and (6) altitude (meters above sea level), using an altimeter. All these variables may be important in habitat selection by rayaditos (e.g., Vergara 2006; Vergara and Marquet 2007).. Patch connectivity In order to determine the effect of functional connectivity on patch occupancy we estimated the patch connectivity index proposed by Hanski (1994): Si ¼. k X. dij. exp a Abj. for dij[0;. j6¼i. where Si is the patch connectivity of patch i, dij is the distance between patch i and patch j (m); and Aj is the size (ha) of patch j. Parameter b, which scales the per capita emigration rate of individuals from a patch, was set equal to 0.5 (see e.g., Hanski et al. 2000), because its maximum likelihood estimate did not converge (i.e., its variance was not calculated). We considered a negative exponential dispersal kernel with parameter a giving the mean dispersal distance of rayaditos (e.g., Vergara and Marquet 2007). In order to estimate the value of parameter a, we fitted a nonlinear logistic regressions by minimizing a log-likelihood function with binomial error implemented using the bbmle package of R 2.8.1 software (R Development Core Team 2008).. Patch network We determined the effect of patch network attributes in explaining patch occupancy of rayaditos. Patch network structure was determined by means of a graph approach that considers patches as nodes and connections between patches as edges (Harary 1969; Minor and Urban 2007). Edges were established by assuming that forest patches were functionally connected when distances between patches were less than a specified daily movement threshold distance, i.e., the maximum distance that an individual bird could move through the matrix habitat within its home range (e.g., Andersson and Bodin 2009). Using a negative exponential dispersal kernel (see ‘‘Patch connectivity’’), we estimated the daily movement threshold distance as the between-patch distance at which rayaditos move with a probability equal to 0.05 (e.g., Moilanen 2004). We used Conefor Sensinode 2.2 (Saura and Torne 2009) to identify network compo-.
(4) 686. Statistical models Patch occupancy rates were zero-inflated since rayaditos occupied only 16 (13.3%) out of 120 patches of sclerophyllous forest surveyed. Consequently, in order to assess patch occupancy patterns we used logistic Hurdle regression, which removes the effects of zero-inflation in the presence/absence model and over-dispersion in the non-zero observations (Potts and Elith 2006). Also, this analysis assumes that zero observations are all true negatives, making it a suitable methodological approach for assessing presence/absence data from playback surveys (Potts and Elith 2006). We performed the following steps to develop and select patch occupancy models: (1) we built and compared models with only patch-scale variables (including habitat and patch area); (2) we built a patch connectivity model; (3) we built a component-size model; (4) we built and compared mixed models that included the additive effect of patch-scale variables of the best patch-scale models (see step 1), patch connectivity, and component size; and (4) the best models developed in the previous steps were then selected again. At each step outlined above, the best three models were selected based on an information theoretical approach outlined by Burnham and Anderson (2002), ranking them according to their DAICc values, which provide a measure of the strength of evidence for each model. Models with DAICc < 2 (the difference in AICc between the model with the smallest AICc value and the current model) were considered to have substantial support. In addition, we assessed model accuracy by estimating the area under the receiver operating characteristic curve (AUC), which describes the relationship between the sensitivity and specificity, with values above 0.7 indicating high model accuracy or acceptable discrimination (Swets 1988). To avoid multicollinearity, we did not include highly correlated variables (r > 0.6) as predictors for the same model. Predictor variables that departed from normality were log transformed. The strength of each model parameter was interpreted using both odd ratios estimated from model-averaged regression coefficients and the proportion of change in odd ratios (Hosmer and Lemeshow 2000). A variable cannot be considered a useful predictor in the logistic model when its odds ratio is not different from 1.0 (Hosmer and Lemeshow 2000). We used the best logistic regression model (see above) to predict the occupancy probability of patches and components. For this analysis, the predicted probability of patch occupancy was determined using the cut-off probability that maximized the sum of model sensitivity. and specificity (Agresti 1996). A network component was considered occupied if at least one patch belonging to such component was predicted to be occupied.. Results The mean dispersal distance of rayaditos (a) was estimated as 309.6 ± 59.2 m (coefficient ±95% confidence intervals). Using a negative exponential dispersal kernel, the maximum distance between patches for which dispersion of rayaditos could be possible (with a 95 confidence level) was estimated as 927.5 m. Using this threshold distance, we identified a total of 16 network components of sclerophyllous forest within the study area (Fig. 2). Logistic regressions indicated that although patchscale variables have an important contribution in explaining patch occupancy by rayaditos, the inclusion of patch connectivity and component size into the models greatly increases their accuracy and parsimony (Table 1). The best three patch-scale models did not support the hypothesis that patch occupancy is affected only by patch scale variables (DAICc ‡ 11.3, Table 1). Those models included, respectively, the effects of the following predictor variables: (1) patch area; (2) dbh and patch area; and (3) Cryptocarya alba cover and patch 30. 25. 20. Distance (Km). nents, i.e., groups (subnets) of forest patches located at less than the daily threshold distance (Pascual-Hortal and Saura 2006; Bodin and Norberg 2007). Once components were identified, we estimated the component size as the sum of the areas of the forest patches belonging to the same component.. 15. 10. 5. 0 0. 5. 10. 15. 20. 25. Distance (km) Fig. 2 Networks of sclerophyllous forest patches in the study area. Occupied patches predicted by a logistic regression model (see text) are represented by full circles and empty patches by open circles. The size of the circles is proportional to the patch size. Shaded areas comprising occupied networks (i.e., with at least one occupied patch) were established using threshold dispersal distance for rayaditos.
(5) 687 Table 1 Patch occupancy models for the Thorn-tailed Rayadito in the Fray Jorge forest ranked according to their corrected Akaike information criterion (AICc) Model variables. AICc. Patch-scale models PA + Dbh 102.2 PA + Ca 99.5 PA 94.9 Connectivity model Con 87.6 Component size CS 96.3 Mixed models (patch-scale variables, connectivity, and component size) PA + Con 84.6 Dbh + Con 89.0 PA + CS 86.9. DAICc. AUC. 18.58 15.88 11.28. 0.67 0.74 0.71. 3.98. 0.81. 11.7. 0.72. 0.00 5.38 2.30. 0.84 0.70 0.82. The area under the receiver operating characteristic curve (AUC), and the change in AICc (DAICc) are specified for each model Dbh diameter at breast height, PA patch area, Ca Cryptocarya alba cover, Con connectivity, CS component size. Table 2 Model estimates of logistic regression coefficients, standard errors (SE), odd ratios, and 95% confidence intervals for patch habitat variables affecting the patch occupancy probability by the Thorn-tailed Rayadito in fragmented sclerophyllous forests of central Chile Variable. Coefficient. SE. Odds ratio. 95% CI. Diameter at breast height Altitude Patch area Canopy height Canopy cover Cryptocarya alba cover Connectivity Component size. 0.117 0.002 0.982 0.208 0.043 0.068 1.16 0.922. 0.072 0.002 0.306 0.219 0.029 0.031 0.425 0.208. 1.124 1.002 2.669 1.231 1.043 1.07 3.189 2.5143. (1.29–0.97) (1.00–0.99) (4.89–1.46) (1.90–0.79) (1.11–0.99) (1.14–1.01) (7.40–1.38) (3.79–1.17). area (Table 1). We did not include dbh and C. alba cover in the same regression model because these variables were strongly correlated (r = 0.84, p < 0.001, n = 120). The connectivity model had a DAICc equal to 3.98 and an AUC equal to 81%, indicating some degree of support and an acceptable accuracy (Table 1). The most parsimonious model was a mixed model, which included the additive effect of patch area and patch connectivity (Table 1). This mixed model was also the most accurate one, with an AUC equal to 84%, indicating that sensitivity is high, even for smaller specificity values (Table 1). Other mixed models that included the effects of component size and patch area had a DAICc equal to 2.3 and an AUC equal to 82%, indicating some degree of support and an acceptable accuracy (Table 1). However, we did not include connectivity and component size in the same regression model because these two variables were correlated (r = 0.68, p < 0.001, n = 120). With the exception of patch area, C. alba cover, component size, and connectivity, all confidence intervals of odd ratios estimated from model-averaged model parameters overlapped 1.0 (Table 2). Model-averaged odd ratios indicated that for every 1.0% increase in cover of C. alba, 1.0 ha in patch connectivity, 1.0 log(ha) in patch area, and 1.0 log(ha) in component size, patch occupancy probability increased by 7.0, 218.9, 166.9,. and 151.4%, respectively (Table 2). The best logistic regression (Table 1) predicted a total of 33 patches of sclerophyllous forest that may be potentially occupied by rayaditos within the study area (Fig. 2). However, those occupied patches were distributed in only six network components (38%).. Discussion Most habitat fragmentation studies have assumed that ecological processes are similar in forest fragments and oceanic islands as predicted by island biogeography and classic metapopulation theories (e.g., Ricketts 2001; Henle et al. 2004). Since the effect of isolation on dispersal tends to be stronger in islands, single islands are usually occupied by true local populations and hence population persistence can be understood through colonization extinction dynamics (Hanski 1999; Watling and Donnelly 2006). On the contrary, if bird species in fragmented landscapes tend to be unaffected by the composition of the surrounding matrix, the number of forest fragments used by an individual bird will be proportional to its habitat area requirements (e.g., Haila 1983). Similarly, fragments of sclerophyllous forest provide complementary and supplementary habitat for rayaditos that nest or forage in a single patch, and hence.
(6) 688. network components of sclerophyllous forest can be important landscape features increasing their individual fitness and landscape connectivity. The results of this study suggest that although patchscale attributes such as patch area or vegetation structure (including C. Alba cover) are important predictors of patch occupancy, the distance and area of neighboring patches expressed as functional connectivity also affect patch occupancy. This connectivity effect suggests that focal patches cannot provide enough resources to meet the life-history requirements of rayaditos. A similar result was obtained by Vergara and Marquet (2007) in a relict patchy forest, where rayaditos used different patches during the breeding season. Thus, in a narrow spatial scale rayaditos use patches based on the size of both the focal and neighboring patches (connectivity), and hence the loss of neighboring forest patches may reduce the probability of a patch being occupied. Furthermore, rayaditos also use network components that provide sufficient breeding habitat for supporting local populations (see below). Recently, a series of new approaches for identifying components of connected habitat patches have been proposed (e.g., Bodin and Norberg 2007; Minor and Urban 2007; Urban et al. 2009). Some spatial compartment assessment methods permit identifying components based on a variable degree of separation between groups of habitat patches (compartments) rather than on a binary perspective of components, such as the approach used in this study (see e.g., Bodin and Norberg 2007). However, our binary approach provides a background for understanding the spatial structure of rayaditos populations in central Chile and for assessing characteristics of network components important for the conservation of this species. Our results suggest that the persistence of rayaditos in central Chile can be possible if network components of sclerophyllous forest occupied by rayaditos are conserved. Although logistic models including the effect of component size were not the best among all tested models, we determined that larger network components had a greater probability of being occupied than small components. This result can be explained by the fact that large-sized components had a greater variation in the size of forest patches (including larger patches) and contained a large number of functionally connected patches. Indeed, the connectivity index and component size were highly correlated, probably due to both variables are functions of the daily movement threshold distance and patch size. However, these two variables can be understood at different spatial scales: connectivity is a characteristic of a patch while component size is a network attribute (see below). The mixed model that included the effects of component size and patch area suggests that not only patch size is crucial in determining the chance of a component being occupied but also the number of neighboring patches. Similarly, Andersson and Bodin (2009), using a component-based analysis, determined that 5–10 ha. components had the largest explanatory power for the presence of the coal tit (Parus ater) than other component sizes. The results of Andersson and Bodin (2009) suggest that 5–10 ha is the minimum component size for component occupancy by coal tits. However, in a similar study conducted in a fragmented rainforest, Awade and Metzger (2008) showed that the abundance of two bird species exhibited a negative relationship with component size. Probably, rayaditos and coal tits respond similarly to network attributes because in both cases the matrix is composed mostly by unsuitable habitat (Vergara and Marquet 2007). Reduced availability of suitable habitat at the landscape scale could force rayaditos to disperse over greater distances and select larger component sizes (since no alternative habitat is available). Graph theory provides an opportunity to establish and assess the spatial structure of available habitat at different spatial scales (e.g., Minor and Urban 2007). However, understanding how the spatio-temporal dynamics of populations is influenced by network attributes could be dependent on the different mechanisms determining animal movements across the landscape. In this study it is not clear whether the six occupied network components (determined using the daily movement threshold distance) may or may not constitute independent local populations. Consequently, the dispersal distance of rayaditos and their patch occupancy dynamics should be further studied in order to define the spatial structure of populations of rayaditos in central Chile. First, the likelihood parameter a represents the mean dispersal distance of a Rayadito according to a negative exponential kernel, which can generate a dispersal kernel predicting extremely low probabilities for species with long dispersal distances (e.g., Baguette 2003). Second, 1-year data may not be enough to draw definitive conclusions about the dynamics of populations occupying single patches and patch networks. Third, it is probable that individuals that disperse locally within their home ranges contribute most to explain dispersal distance and hence functional connectivity (Fagan and Lutscherb 2006). On the contrary, natal and breeding dispersal distances are critical for colonization events and metapopulation dynamics (Trakhtenbrot et al. 2005). The mean natal and breeding dispersal distances of birds are usually >1 km (e.g., Paradis et al. 1998), but for rayaditos the estimated mean dispersal distance was around 300 m. Fourth, dispersal and foraging behavior of rayaditos is different during the non-breeding season, when rayaditos move longer distances forming familiar flocks (Vergara and Marquet 2007). Thus, it is possible that the landscape use pattern and dispersal distance of rayaditos change after the breeding season, with rayaditos dispersing into the Andean valleys (Vergara, unpublished data). Therefore, network components as defined in this study could be considered as a second hierarchy level (above the patch-scale level) in the population structure of rayaditos, representing suitable connected habitats for some individuals. Furthermore, clusters of components.
(7) 689. connected via natal or breeding dispersal could function as independent local populations. We suggest that both habitat use and population structure of rayaditos are scale-dependent, with patchand network-scales being important for population persistence. Based in this multi-scale approach, the following conservation prescriptions should be considered to conserve rayaditos in central Chile: (1) maintaining large and connected patches of mature sclerophyllous forest, which may play a crucial role in providing highquality habitat to rayaditos; (2) maintaining large clusters of large-sized patches of matorral and sclerophyllous forest, which provide habitat and connectivity to rayaditos; (3) forest restoration to increase the size of network components (both in terms of number of connected patches as well as of mean size of the connected patches); and (4) establishing corridors of sclerophyllous forest between occupied patch networks. Acknowledgments This study was financed by a postdoctoral fellowship under FONDECYT 3060083, FONDECYT 11080085 and Dicyt 02-0895SC. We express our gratitude to Jan O. Nyström (Swedish Museum of Natural History), Beatriz Levi, and Samy Atala for suggestions and improvements in English language, and two anonymous reviewers for their valuable comments on the manuscript.. References Agresti A (1996) An introduction to categorical data analysis. Wiley, New York Andersson E, Bodin O (2009) Practical tool for landscape planning? An empirical investigation of network based models of habitat fragmentation. Ecography 32:123–132 Araya B, Millie G (1991) Guı́a de Campo de las Aves de Chile, 4th edn. Editorial Universitaria, Santiago Armesto JJ, Martı́nez JA (1978) Relationships between vegetation structure and slope aspect in the Mediterranean region of Chile. J Ecol 66:881–889 Armesto JJ, Picket STA (1985) A mechanistic approach to the study of succession in the Chilean matorral. Rev Chil Hist Nat 58:9–17 Awade M, Metzger JP (2008) Using gap-crossing capacity to evaluate functional connectivity of two Atlantic rainforest birds and their response to fragmentation. Austral Ecol 33:863– 871 Baguette M (2003) Long distance dispersal and landscape occupancy in a metapopulation of the cranberry fritillary butterfly. Ecography 26:153–160 Bender DJ (2003) Using patch isolation metrics to predict animal movement in binary landscapes. Landsc Ecol 18:17–39 Bodin Ö, Norberg J (2007) A network approach for analyzing spatially structured populations in fragmented landscape. Landsc Ecol 22:31–44 Brotons L, Monkkonen M, Martin JL (2003) Are fragments islands? Landscape context and density–area relationships in boreal forest birds. Am Nat 162:343–357 Burke DM, Nol E (1998) Influence of food abundance, nestsite habitat, and forest fragmentation on breeding ovenbirds. Auk 115:96–104 Burnham KP, Anderson DR (2002) Model selection and inference. Springer, Berlin Heidelberg New York Carlsson A, Kindvall O (2001) Spatial dynamics in a metapopulation network: recovery of a rare grasshopper Stauroderus scalaris from population refuges. Ecography 24:452–460. CONAF-CONAMA-BIRF (1999) Catastro y evaluación de recursos vegetacionales nativos de Chile. Informe Nacional con Variables Ambientales. Corporación Nacional Forestal, Santiago Del Pozo AH, Fuentes ER, Hajek ER, Molina JD (1989) Microclimatic patchiness and shrub clumps in the matorral of central Chile. Rev Chil Hist Nat 62:85–94 Drechsler M (2005) Probabilistic approaches to scheduling reserve selection. Biol Conserv 122:253–262 Fagan W, Lutscherb F (2006) Average dispersal success: linking home range, dispersal, and metapopulation dynamics to reserve design. Ecol Appl 16:820–828 Falls JB (1981) Mapping territories with playback: an accurate census method for songbirds. Stud Avian Biol 6:86–91 Fuentes ER, Otaiza RD, Alliende MC, Hoffmann AJ, Poiani A (1984) Shrub clumps of the Chilean matorral vegetation: structure and possible maintenance mechanisms. Oecologia 62:405–411 Fuentes ER, Hoffmann AJ, Poiani A, Alliende MC (1986) Vegetation change in large clearings: patterns in the Chilean matorral. Oecologia 68:358–366 Hahn I, Mattes H (2000) Vocalisations of the Masafuera Rayadito Aphrastura Masafuerae on Isla Alejandro Selkirk, Chile. Bioacoustics 11:57–64 Haila Y (1983) Land birds on northern islands: a sampling metaphor for insular colonization. Oikos 41:334–351 Hanski I (1994) A practical model of metapopulation dynamics. J Anim Ecol 63:151–162 Hanski I (1999) Metapopulation ecology. Oxford University Press, Oxford Hanski I, Ovaskainen O (2000) The metapopulation capacity of a fragmented landscape. Nature 404:755–758 Hanski I, Alho J, Moilanen A (2000) Estimating the parameters of migration and survival for individuals in metapopulations. Ecology 81:239–251 Harary F (1969) Graph theory. Addison-Wesley, Reading Henle K, Davies KF, Kleyer M, Margules C, Settele J (2004) Predictors of species sensitivity to fragmentation. Biodivers Conserv 13:207–251 Hinsley SA (2000) The costs of multiple patch use by birds. Landsc Ecol 15:765–775 Hinsley SA, Bellamy PE, Enoksson B, Fry G, Gabrielsen L, McCollin D, Schotman A (1998) Geographical and land-use influences on bird species richness in small woods in agricultural landscapes. Glob Ecol Biogeogr 7:125–135 Hosmer DW, Lemeshow S (2000) Applied logistic regression. Wiley, New York Jaksic FM (2001) Spatiotemporal variation patterns of plants and animals in San Carlos de Apoquindo, central Chile. Rev Chil Hist Nat 74:477–502 Keitt TH, Urban DL, Milne BT (1997) Detecting critical scales in fragmented landscapes. Conserv Ecol 1:4 (online). http://www. consecol.org/vol1/iss1/art4/ Lazo I, Anabalon JJ, Segura A (1990) Perturbación humana del matorral y su efecto sobre un ensamble de aves nidificantes de Chile central. Rev Chil Hist Nat 63:293–297 Minor E, Urban DL (2007) Graph theory as a proxy for spatially explicit population models in conservation planning. Ecol Appl 17:1771–1782 Moilanen A (2004) SPOMSIM: software for stochastic patch occupancy models of metapopulation dynamics. Ecol Model 179:533–550 Moilanen A, Hanski I (1998) Metapopulation dynamics: effects of habitat quality and landscape structure. Ecology 79:2503–2515 Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858 Ozgul A, Armitage KB, Oli MK, Blumstein DT, Van Vuren DH (2006) Effects of patch quality and network structure on patch occupancy dynamics of a yellow-bellied marmot metapopulation. J Anim Ecol 75:191–202 Paradis E, Baillie SR, Sutherland WJ, Gregory RD (1998) Patterns of natal and breeding dispersal in birds. J Anim Ecol 67: 518–536.
(8) 690 Pascual-Hortal L, Saura S (2006) Comparison and development of new graph-based landscape connectivity indices: towards the prioritization of habitat patches and corridors for conservation. Landsc Ecol 21:959–967 Potts J, Elith J (2006) Comparing species’ abundance models. Ecol Model 199:153–163 Quintanilla V (1983) Biogeografı́a de Chile. Colección Geografı́a de Chile. Instituto Geográfico Militar, Chile R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Radford JQ, Bennett AF (2007) The relative importance of landscape properties for woodland birds in agricultural environments. J Appl Ecol 44:737–747 Ricketts TH (2001) The matrix matters: effective isolation in fragmented landscapes. Am Nat 158:87–99 Rolstad J, Wegge P (1987) Distribution and size of capercaillie leks in relation to old forest fragmentation. Oecologia 72:389–394 Saura S, Torne J (2009) Conefor Sensinode 2.2: a software package for quantifying the importance of habitat patches for landscape connectivity. Environ Model Softw 24:135–139 Simonetti J (1999) Diversity and conservation of terrestrial vertebrates in Mediterranean Chile. Rev Chil Hist Nat 72:493–500 Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293 Thomas JA, Bourn NAD, Clarke RT, Stewart KE, Simcox DJ, Pearman GS, Curtis R, Goodger B (2001) The quality and isolation of habitat patches both determine where butterflies persist in fragmented landscapes. Proc R Soc Lond Ser B Biol Sci 268:1791–1796 Trakhtenbrot A, Nathan R, Perry G, Richardson DM (2005) The importance of long-distance dispersal in biodiversity conservation. Divers Distrib 11:173–181. Uezu A, Metzger JP, Vielliard JME (2005) Effects of structural and functional connectivity and patch size on the abundance of seven Atlantic forest bird species. Biol Conserv 123:507–519 Urban DL, Minor ES, Treml EA, Schick RS (2009) Graph models of habitat mosaics. Ecol Lett 12:260–273 Vasquez R, Simonetti J (1999) Life history traits and sensitivity to landscape change: the case of birds and mammals of Mediterranean Chile. Rev Chil Hist Nat 72:517–525 Vergara PM (2006) Estructura espacial de la población de rayaditos (Aphrastura spinicauda) del bosque fragmentado de Fray Jorge. PhD Thesis, Facultad de Ciencias Biologicas, Pontificia Universidad Católica de Chile Vergara PM (2007) Effects of nest box size on the nesting and renesting pattern of Aphrastura spinicauda and Troglodytes aedon. Ecol Austral 17:133–141 Vergara PM, Marquet PA (2007) On the seasonal effect of landscape structure on a bird species: the Thorn-tailed Rayadito in a relict forest in northern Chile. Landsc Ecol 22:1059–1071 Vergara PM, Marquet P, Zeballos H (2003) Nesting of the Thorntailed Rayadito (Aphrastura Spinicauda) in the metropolitan region of Central Chile. In: Abstracts of VII Neotropical ornithological congress, Chile Watling JI, Donnelly MA (2006) Fragments as islands: a synthesis of faunal responses to habitat patchiness. Conserv Biol 20:1016–1025 Wiens JA (1976) Populations responses to patchy environments. Annu Rev Ecol Syst 7:81–120 Zanette L, Doyle P, Tremont SM (2000) Food shortage in small fragments: evidence from an area-sensitive passerine. Ecology 81:1654–1666.
(9) Copyright of Ecological Research is the property of Springer Science & Business Media B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use..
(10)
Figure
Documento similar
In the “big picture” perspective of the recent years that we have described in Brazil, Spain, Portugal and Puerto Rico there are some similarities and important differences,
Keywords: Metal mining conflicts, political ecology, politics of scale, environmental justice movement, social multi-criteria evaluation, consultations, Latin
In this thesis we have presented several modelling techniques that can improve the cur- rent state-of-art of statistical cosmology: an improved halo modelling, a more realistic
For instance, (i) in finite unified theories the universality predicts that the lightest supersymmetric particle is a charged particle, namely the superpartner of the τ -lepton,
Given the much higher efficiencies for solar H 2 -generation from water achieved at tandem PEC/PV devices ( > 10% solar-to-H 2 energy efficiency under simulated sunlight) compared
Plotinus draws on Plato’s Symposium (206c4–5) – “procreate in what is beautiful” – 3 in order to affirm that mixed love (which is also a love of beauty) is fecund, although
As a means to probe the possible fractal structure of the galaxy distribution we have studied the scaling of the num- ber density and angular correlation function of galaxies
Even though the 1920s offered new employment opportunities in industries previously closed to women, often the women who took these jobs found themselves exploited.. No matter
