Global climate models predict increases in the frequency and intensity of extreme climatic events such as hurricanes, which may abruptly alter ecological processes in forests and thus affect avian diversity. Developing appropriate conservation measures necessitates identifying patterns of avifauna response to hurricanes. We sought to answer two questions: (1) does avian diversity, measured as community similarity, abundance, and species richness, change in areas affected by hurricane compared with unaffected areas, and (2) what factors are associated with the change(s) in avian diversity? We used North American Breeding Bird Survey data, hurricane track information, and a time series of Landsat images in a repeated measures framework to answer these questions. Our results show a decrease in community similarity in the first posthurricane breeding season for all species as a group, and for species that nest in the midstory and canopy. We also found significant effects of hurricanes on abundance for species that breed in urban and woodland habitats, but not on the richness of any guild. In total, hurricanes produced regional changes in community similarity largely without significant loss of richness or overall avian abundance.We identified several potential mechanisms for these changes in avian diversity, including hurricane-induced changes in forest habitat and the use of refugia by birds displaced from hurricane-damaged forests. The prospect of increasing frequency and intensity of hurricanes is not likely to invoke a conservation crisis for birds provided we maintain sufficient forest habitat so that avifauna can respond to hurricanes by shifting to areas of suitable habitat.
File: rittenhouse_0.pdf
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Increasing surface temperatures and climatic variability associated with global climate change are expected to produce more frequent and intense heat waves and droughts in many parts of the world. Our goal was to elucidate the fundamental, but poorly understood, effects of these extreme weather events on avian communities across the conterminous United States. Specifically, we explored: (1) the effects of timing and duration of heat and drought events, (2) the effects of jointly occurring drought and heat waves relative to these events occurring in isolation, and (3) how effects vary among functional groups related to nest location and migratory habit, and among ecoregions with differing precipitation and temperature regimes. Using data from remote sensing, meteorological stations, and the North American Breeding Bird Survey, we used mixed effects models to quantify responses of overall and functional group abundance to heat waves and droughts (occurring alone or in concert) at two key periods in the annual cycle of birds: breeding and post-fledging. We also compared responses among species with different migratory and nesting characteristics, and among 17 ecoregions of the conterminous United States. We found large changes in avian abundances related to 100-year extreme weather events occurring in both breeding and post-fledging periods, but little support for an interaction among time periods. We also found that jointly-, rather than individually-occurring heat waves and droughts were both more common and more predictive of abundance changes. Declining abundance was the only significant response to post-fledging events, while responses to breeding period events were larger but could be positive or negative. Negative responses were especially frequent in the western U.S., and among ground-nesting birds and Neotropical migrants, with the largest single-season declines (36%) occurring among ground-nesting birds in the desert Southwest. These results indicate the importance of functional traits, timing, and geography in determining avian responses to weather extremes. Because dispersal to other regions appears to be an important avian response, it may be essential to maintain habitat refugia in a more climatically variable future.
File: Albright_et_al_2010_Combined_effects_of_heat_waves_and_droughts_on_avian_communities.pdf
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Droughts are expected to become more frequent under global climate change. Avifauna depend on precipitation for hydration, cover, and food. While there are indications that avian communities respond negatively to drought, little is known about the response of birds with differing functional and behavioural traits, what time periods and indicators of drought are most relevant, or how response varies geographically at broad spatial scales. Our goals were thus to determine (1) how avian abundance and species richness are related to drought, (2) whether community variations are more related to vegetation vigour or precipitation deviations and at what time periods relationships were strongest, (3) how response varies among avian guilds, and (4) how response varies among ecoregions with different precipitation regimes. Using mixed effect models and 1989-2005 North American Breeding Bird Survey data over the central United States, we examined the response to 10 precipitation- and greennessbased metrics by abundance and species richness of the avian community overall, and of four behavioural guilds. Drought was associated with the most negative impacts on avifauna in the semiarid Great Plains, while positive responses were observed in montane areas. Our models predict that in the plains, Neotropical migrants respond the most negatively to extreme drought, decreasing by 13.2% and 6.0% in abundance and richness, while permanent resident abundance and richness increase by 11.5% and 3.6%, respectively in montane areas. In most cases, response of abundance was greater than richness and models based on precipitation metrics spanning 32-week time periods were more supported than those covering shorter time periods and those based on greenness. While drought is but one of myriad environmental variations birds encounter, our results indicate that drought is capable of imposing sizable shifts in abundance, richness, and composition on avian communities, an important implication of a more climatically variable future.
File: AlbrightetalGCB2010.pdf
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Habitat transformations and climate change are among the most important drivers of biodiversity loss. Understanding the factors responsible for the unequal distribution of species richness is a major challenge in ecology. Using data from the North American Breeding Bird Survey to measure species richness and a change metric extracted from the MODerate resolution Imaging Spectroradiometer (MODIS), we examined the influence of energy variability on the geographic distribution of avian richness across the conterminous U.S. and in the different ecoregions, while controlling for energy availability. The analysis compared three groups of birds: all species, Neotropical migrants, and permanent residents. We found that interannual variability in available energy explained more than half of the observed variation in bird richness in some ecoregions. In particular, energy variability is an important factor in explaining the patterns of overall bird richness and of permanent residents, in addition to energy availability. Our results showed a decrease in species richness with increasing energy variability and decreasing energy availability, suggesting that more species are found in more stable and more productive environments. However, not all ecoregions followed this pattern. The exceptions might reflect other biological factors and environmental conditions. With more ecoclimatic variability predicted for the future, this study provides insight into how energy variability influences the geographical patterns of species richness.
File: Rowhani-Ecosystems-2008.pdf
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Predicting broad-scale patterns of biodiversity is challenging, particularly in ecosystems where traditional methods of quantifying habitat structure fail to capture subtle but potentially important variation within habitat types. With the unprecedented rate at which global biodiversity is declining, there is a strong need for improvement in methods for discerning broad-scale differences in habitat quality. Here, we test the importance of habitat structure (i.e. fine-scale spatial variability in plant growth forms) and plant productivity (i.e. amount of green biomass) for predicting avian biodiversity. We used image texture (i.e. a surrogate for habitat structure) and vegetation indices (i.e. surrogates for plant productivity) derived from Landsat Thematic Mapper (TM) data for predicting bird species richness patterns in the northern Chihuahuan Desert of New Mexico. Bird species richness was summarized for forty-two 108 ha plots in the McGregor Range of Fort Bliss Military Reserve between 1996 and 1998. Six Landsat TM bands and the normalized difference vegetation index (NDVI) were used to calculate first-order and second-order image texture measures. The relationship between bird species richness versus image texture and productivity (mean NDVI) was assessed using Bayesian model averaging. The predictive ability of the models was evaluated using leave-one-out cross-validation. Texture of NDVI predicted bird species richness better than texture of individual Landsat TM bands and accounted for up to 82.3% of the variability in species richness. Combining habitat structure and productivity measures accounted for up to 87.4% of the variability in bird species richness. Our results highlight that texture measures from Landsat TM imagery were useful for predicting patterns of bird species richness in semi-arid ecosystems and that image texture is a promising tool when assessing broad-scale patterns of biodiversity using remotely sensed data.
File: StLouis_2009_Ecography.pdf
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Analyses of avian demographic patterns across entire, contiguous landscapes are rare, but such analyses are important for understanding population dynamics. We selected the Black-throated Sparrow in the northern Chihuahuan Desert as a model to test patterns of abundance and nest success across a landscape. We integrated abundance, nest density, and nesting success measured on sampling plots with a classified satellite map of the distribution of seven habitat types to analyze spatial and temporal patterns contributing to the population dynamics of this species. Adult relative abundance ranged from ,1 bird/100 ha in pinyon-juniper habitat to 24- 39 birds/100 ha in shrubland habitats. Nest density was consistently high in mesquite, moderate to high in creosotebush, and low in black grama grassland; this value exhibited more temporal variability than relative abundance of adults. Nest success rates exhibited a strong habitat effect and ranged from 8% in mesquite to 47% in black grama grassland; overall population nest success was 0.266. In all three years, nest success in mesquite was significantly lower than in all other habitat types (P , 0.01). There was no correlation between nest success and adult relative abundance. While mesquite habitat contained about one-third of all adults in the three years of the study, it contributed as little as 10% of successful nests. In creosotebush, the relative contribution to both adult abundance and successful nests was relatively high. Mesa grassland contained relatively few adults, but up to 44% of successful nests. We discuss how habitat selection theory suggests mechanisms for the observed patterns. Mesquite appears to be a population sink for Black-throated Sparrows and may be an ecological trap. While we do not propose that there is cause for conservation concern for this widespread species, our results underscore the pitfalls associated with using adult abundance as an indicator of habitat quality. The method presented here is applicable for many species and ecosystems and, thus, may be an important tool for conservation and management, as well as a new avenue for scientific investigation of landscape-level population dynamics.
File: Pidgeon_etal_EA2003.pdf
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Many wild species are affected by human activities occurring at broad spatial scales. For instance, in South America, habitat loss threatens Greater Rhea (Rhea americana) populations, making it important to model and map their habitat to better target conservation efforts. Spatially explicit habitat modeling is a powerful approach to understand and predict species occurrence and abundance. One problem with this approach is that commonly used land cover classifications do not capture the variability within a given land cover class that might constitute important habitat attribute information. Texture measures derived from remote sensing images quantify the variability in habitat features among and within habitat types; hence they are potentially a powerful tool to assess species-habitat relationships. Our goal was to explore the utility of texture measures for habitat modeling and to develop a habitat suitability map for Greater Rheas at the home range level in grasslands of Argentina. Greater Rhea group size obtained from aerial surveys was regressed against distance to roads, houses, and water, and land cover class abundance (dicotyledons, crops, grassland, forest, and bare soil), normalized difference vegetation index (NDVI), and selected first- and second-order texture measures derived from Landsat Thematic Mapper (TM) imagery. Among univariate models, Rhea group size was most strongly positively correlated with texture variables derived from near infrared reflectance measurement (TM band 4). The best multiple regression models explained 78% of the variability in Greater Rhea group size. Our results suggest that texture variables captured habitat heterogeneity that the conventional land cover classification did not detect. We used Greater Rhea group size as an indicator of habitat suitability; we categorized model output into different habitat quality classes. Only 16% of the study area represented high-quality habitat for Greater Rheas (group size =15). Our results stress the potential of image texture to capture within-habitat variability in habitat assessments, and the necessity to preserve the remaining natural habitat for Greater Rheas.
File: Bellis_etal_EA_2008_0.pdf
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Patterns of association between humans and biodiversity typically show positive, negative, or negative quadratic relationships and can be described by 3 hypotheses: biologically rich areas that support high human population densities co-occur with areas of high biodiversity (productivity); biodiversity decreases monotonically with increasing human activities (ecosystem stress); and biodiversity peaks at intermediate levels of human influence (intermediate disturbance). To test these hypotheses, we compared anthropogenic land cover and housing units, as indices of human influence, with bird species richness and abundance across the Midwestern United States. We modeled richness of native birds with 12 candidate models of land cover and housing to evaluate the empirical evidence. To assess which species were responsible for observed variation in richness, we repeated our model-selection analysis with relative abundance of each native species as the response and then asked whether natural-history traits were associated with positive, negative, or mixed responses. Native avian richness was highest where anthropogenic land cover was lowest and housing units were intermediate based on model-averaged predictions among a confidence set of candidate models. Eighty-three of 132 species showed some pattern of association with our measures of human influence. Of these species approximately 40% were negatively associated, approximately 6% were positively associated, and approximately 7% showed evidence of an intermediate relationship with human influence measures. Naturalhistory traits were not closely related to the direction of the relationship between abundance and human influence. Nevertheless, pooling species that exhibited any relationship with human influence and comparing them with unrelated species indicated they were significantly smaller, nested closer to the ground, had shorter incubation and fledging times, and tended to be altricial. Our results support the ecosystem-stress hypothesis for the majority of individual species and for overall species diversity when focusing on anthropogenic land cover. Nevertheless, the great variability in housing units across the land-cover gradient indicates that an intermediate-disturbance relationship is also supported. Our findings suggest preemptive conservation action should be taken, whereby areas with little anthropogenic land cover are given conservation priority. Nevertheless, conservation action should not be limited to pristine landscapes because our results showed that native avian richness and the relative abundance of many species peaked at intermediate housing densities and levels of anthropogenic land cover
File: Lepczyk_etal_ConsBio_2010.pdf
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The lack of management experience at the landscape scale and the limited feasibility of experiment at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse ( Tympanuchus phasianellus) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.
File: Akcakaya_etal_ConsBio2004.pdf
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We tested image texture as a predictor of bird species richness in a semi-arid landscape of New Mexico. Bird species richness was summarized from 10-min point counts conducted at 12 points within 42 plots (108 ha each) from 1996 to 1998. We calculated 14 first- and second-order texture measures in eight different window sizes on a set of digital orthophotos acquired in 1996. For each of the 42 plots, we summarized mean and standard deviation of each texture value within multiple window sizes. The relationship between image texture and average bird species richness was assessed using linear regression models. Single image texture measures such as the standard deviation described up to 57% of the variability in species richness. Coupling multiple measures of texture or coupling elevation with a single texture measure described up to 63% of the variability in bird species richness. Models incorporating two measures of texture and coarse habitat type described 76% of the variability in bird species richness. These results show that image texture analysis is a very promising tool for characterizing habitat structure and predicting patterns of species richness in semi-arid ecosystems. This method has several advantages over methods that rely on classified imagery, including cost-effectiveness, incorporation of within-habitat vegetation variability, and elimination of errors associated with boundary delineation.
File: st-louis-rse-2006.pdf
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