The pace of past climate change vs. potential bird distributions and land use in the United States

Climate change may drastically alter patterns of species distributions and richness, but predicting future species patterns in occurrence is challenging. Significant shifts in distributions have already been observed, and understanding these recent changes can improve our understanding of potential future changes. We assessed how past climate change affected potential breeding distributions for landbird species in the conterminous United States. We quantified the bioclimatic velocity of potential breeding distributions, that is, the pace and direction of change for each species’ suitable climate space over the past 60 years. We found that potential breeding distributions for landbirds have shifted substantially with an average velocity of 1.27 km yr^?1, about double the pace of prior distribution shift estimates across terrestrial systems globally (0.61 km yr^?1). The direction of shifts was not uniform. The majority of species’ distributions shifted west, northwest, and north. Multidirectional shifts suggest that changes in climate conditions beyond mean temperature were influencing distributional changes. Indeed, precipitation variables that were proxies for extreme conditions were important variables across all models. There were winners and losers in terms of the area of distributions; many species experienced contractions along west and east distribution edges, and expansions along northern distribution edges. Changes were also reflected in the potential species richness, with some regions potentially gaining species (Midwest, East) and other areas potentially losing species (Southwest). However, the degree to which changes in potential breeding distributions are manifested in actual species richness depends on landcover. Areas that have become increasingly suitable for breeding birds due to changing climate are often those attractive to humans for agriculture and development. This suggests that many areas might have supported more breeding bird species had the landscape not been altered. Our study illustrates that climate change is not only a future threat, but something birds are already experiencing.     

Bird diversity: a predictable function of satellite-derived estimates of seasonal variation in canopy light absorbance across the United States

Aim  To investigate the relationships between bird species richness derived from the North American Breeding Bird Survey and estimates of the average, minimum, and the seasonal variation in canopy light absorbance (the fraction of absorbed photosynthetically active radiation, fPAR) derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS).
Location  Continental USA.
Methods  We describe and apply a 'dynamic habitat index' (DHI), which incorporates three components based on monthly measures of canopy light absorbance through the year. The three components are the annual sum, the minimum, and the seasonal variation in monthly fPAR, acquired at a spatial resolution of 1 km, over a 6-year period (2000–05). The capacity of these three DHI components to predict bird species richness across 84 defined ecoregions was assessed using regression models.
Results  Total bird species richness showed the highest correlation with the composite DHI [ R ² = 0.88, P  < 0.001, standard error of estimate (SE) = 8 species], followed by canopy nesters ( R ² = 0.79, P  < 0.001, SE = 3 species) and grassland species ( R ² = 0.74, P  < 0.001, SE = 1 species). Overall, the seasonal variation in fPAR, compared with the annual average fPAR, and its spatial variation across the landscape, were the components that accounted for most ( R ² = 0.55–0.88) of the observed variation in bird species richness.
Main conclusions  The strong relationship between the DHI and observed avian biodiversity suggests that seasonal and interannual variation in remotely sensed fPAR can provide an effective tool for predicting patterns of avian species richness at regional and broader scales, across the conterminous USA.     

Housing arrangement and location determine the likelihood of housing loss due to wildfire

Surging wildfires across the globe are contributing to escalating residential losses and have major social, economic, and ecological consequences. The highest losses in the U.S. occur in southern California, where nearly 1000 homes per year have been destroyed by wildfires since 2000. Wildfire risk reduction efforts focus primarily on fuel reduction and, to a lesser degree, on house characteristics and homeowner responsibility. However, the extent to which land use planning could alleviate wildfire risk has been largely missing from the debate despite large numbers of homes being placed in the most hazardous parts of the landscape. Our goal was to examine how housing location and arrangement affects the likelihood that a home will be lost when a wildfire occurs. We developed an extensive geographic dataset of structure locations, including more than 5500 structures that were destroyed or damaged by wildfire since 2001, and identified the main contributors to property loss in two extensive, fire-prone regions in southern California. The arrangement and location of structures strongly affected their susceptibility to wildfire, with property loss most likely at low to intermediate structure densities and in areas with a history of frequent fire. Rates of structure loss were higher when structures were surrounded by wildland vegetation, but were generally higher in herbaceous fuel types than in higher fuel-volume woody types. Empirically based maps developed using housing pattern and location performed better in distinguishing hazardous from non-hazardous areas than maps based on fuel distribution. The strong importance of housing arrangement and location indicate that land use planning may be a critical tool for reducing fire risk, but it will require reliable delineations of the most hazardous locations.     

Refugee species: which historic baseline should inform conservation planning?

Understanding species' historical ranges can provide important information for conservation planning in the face of environmental change. Cromsigt et al. (this issue) comment on our recent European bison (Bison bonasus) range reconstruction, suggesting that bison were already 8000 years ago a refugee species (i.e. restricted to marginal habitat due to past human pressure) and that species distribution models (SDM) are generally of limited use for refugee species conservation. While we welcome this discussion, we find no evidence for the claim that human pressure prior to 8000 BP determined where bison occurred. More importantly, as human pressure is generally high and increasing, attempts to restore species across their former range may fail where the factors that relegated species into refugee status are still at play or where their optimal habitat has vanished. Identifying areas where human pressure is low and where refugee species have persisted over the last millennia is crucial, and SDM based on historical data are important for doing so. Refugee species suffer from the shifting baseline syndrome, but careful reality checks are needed and all available data should be considered before determining the baseline that should inform conservation planning.     

Conservation of Forest Birds: Evidence of a Shifting Baseline in Community Structure

Background

Quantifying changes in forest bird diversity is an essential task for developing effective conservation actions. When subtle changes in diversity accumulate over time, annual comparisons may offer an incomplete perspective of changes in diversity. In this case, progressive change, the comparison of changes in diversity from a baseline condition, may offer greater insight because changes in diversity are assessed over longer periods of times. Our objectives were to determine how forest bird diversity has changed over time and whether those changes were associated with forest disturbance.

Methodology/Principal Findings

We used North American Breeding Bird Survey data, a time series of Landsat images classified with respect to land cover change, and mixed-effects models to associate changes in forest bird community structure with forest disturbance, latitude, and longitude in the conterminous United States for the years 1985 to 2006. We document a significant divergence from the baseline structure for all birds of similar migratory habit and nest location, and all forest birds as a group from 1985 to 2006. Unexpectedly, decreases in progressive similarity resulted from small changes in richness (<1 species per route for the 22-year study period) and modest losses in abundance (−28.7–−10.2 individuals per route) that varied by migratory habit and nest location. Forest disturbance increased progressive similarity for Neotropical migrants, permanent residents, ground nesting, and cavity nesting species. We also documented highest progressive similarity in the eastern United States.

Conclusions/Significance

Contemporary forest bird community structure is changing rapidly over a relatively short period of time (e.g., ∼22 years). Forest disturbance and forest regeneration are primary factors associated with contemporary forest bird community structure, longitude and latitude are secondary factors, and forest loss is a tertiary factor. Importantly, these findings suggest some regions of the United States may already fall below the habitat amount threshold where fragmentation effects become important predictors of forest bird community structure.     

Satellite image texture and a vegetation index predict avian biodiversity in the Chihuahuan Desert of New Mexico

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 textures 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.     

Periodicity in spatial data and geostatistical models: autocorrelation between patches

Several recent studies in landscape ecology have found periodicity in correlograms or semi-variograms calculated, for instance, from spatial data of soils, forests, or animal populations. Some of the studies interpreted this as an indication of regular or periodic landscape patterns. This interpretation is in disagreement with other studies that doubt whether such analysis is valid. The objective of our study was to explore the relationship between periodicity in landscape patterns and geostatistical models. We were especially interested in the validity of the assumption that periodicity in geostatistical models indicates periodicity in landscape pattern, and whether the former can characterize frequency and magnitude of the latter. We created maps containing various periodic spatial patterns, derived correlograms from these, and examined periodicity in the correlograms. We also created non-regular maps that we suspected would cause periodicity in correlograms. Our results demonstrate that a) various periodic spatial patterns produce periodicity in correlograms derived from them, b) the distance-lags at which correlograms peak correspond to the average distances between patch centers, c) periodicity is strongest when the diameter of patches is equal to the distance between patch edges, d) periodicity in omni-directional correlograms of complex spatial patterns (such as checkerboards) are combinations of several waves because inter-patch distances differ with direction; multiple directional correlograms can decompose such complexity, and e) periodicity in correlograms can also be caused when the number of patches in a study site is small. These results highlight that correlograms can be used to detect and describe regular spatial patterns. However, it is crucial to ensure that the assumption of stationarity is not violated, i.e., that the study area contains a sufficiently large number of patches to avoid incorrect conclusions.     

Complex effects of scale on the relationships of landscape pattern versus avian species richness and community structure in a woodland savanna mosaic

Landscape pattern metrics are widely used for predicting habitat and species diversity. However, the relationship between landscape pattern and species diversity is typically measured at a single spatial scale, even though both landscape pattern, and species occurrence and community composition are scale‐dependent. While the effects of scale on landscape pattern are well documented, the effects of scale on the relationships between spatial pattern and species richness and composition are not well known. Here, our main goal was to quantify the effects of cartographic scale (spatial resolution and extent) on the relationships between spatial pattern and avian richness and community structure in a mosaic of grassland, woodland, and savanna in central Wisconsin. Our secondary goal was to evaluate the effectiveness of a newly developed tool for spatial pattern analysis, multiscale contextual spatial pattern analysis (MCSPA), compared to existing landscape metrics. Landscape metrics and avian species richness had quadratic, exponential, or logarithmic relationships, and these patterns were generally consistent across two spatial resolutions and six spatial extents. However, the magnitude of the relationships was affected by both resolution and extent. At the finer resolution (10‐m), edge density was consistently the best predictor of species richness, followed by an MCSPA metric that measures the standard deviation of woody cover across extents. At the coarser resolution (30‐m), NDVI was the best predictor of species richness by far, regardless of spatial extent. Another MCSPA metric that denotes the average woody cover across extents, together with percent of woody cover, were always the best predictors of variation in avian community structure. Spatial resolution and extent had varying effects on the relationships between spatial pattern and avian community structure. We therefore conclude that cartographic scale not only affects measures of landscape pattern per se, but also the relationships among spatial pattern, species richness, and community structure, often in complex ways, which reduces the efficacy of landscape metrics for predicting the richness and diversity of organisms.