Spatial Analysis For Conservation and Sustainability
Birds
Birds have evolved to fill a diverse set of niches, and because of their manifold adaptations to different habitats, and the relative ease with which they are detected, they are a great taxon to understand the effects of land use, climate, and other factors on the ability of wild species to maintain viable populations.
Habitat quality is an important consideration when identifying source and sink habitat and setting priority areas for avian conservation. The problem is that different measures may lead to different conclusions about habitat quality, and may also vary in the resources required to estimate them. Individual level measures, such as nest success, and fecundity, will often identify different high quality habitats than population level measures, such as abundance or the number of fledglings produced per unit area. We tested measures of fitness in the Black-throated Sparrow both at the individual and at the population level for six habitats in the northern Chihuahuan Desert, to explore their value as indicators of habitat quality. We compared clutch size, number of nestlings per nest, number of fledglings per successful nest, nest density, nest success, daily nest survival rate, season-long fecundity, number of fledglings produced per 100 ha, and adult abundance, in each habitat type. We also modeled source-sink dynamics to estimate the scale at which they operate, to infer survival rates, and to ascertain the relative source potential of each habitat. We found that fecundity is the best indicator of individual level habitat quality but a poor indicator of population level habitat quality. Nest success (or fecundity, if resources are available to adequately estimate it) plus nest density provide the most robust indicator of population level habitat quality, which is the level at which priority habitats for conservation should be identified. Mesa grassland and black grama grassland functioned as source habitats most consistently, and mesquite was consistently a sink but also probably a reservoir of individuals available to occupy other habitats.
In the United States, housing density has substantially increased in and adjacent to forests. Our goal in this study was to identify how housing density and human populations are associated with avian diversity. We compared these associations to those between landscape pattern and avian diversity, and we examined how these associations vary across the conterminous forested United States. Using data from the North American Breeding Bird Survey, the U.S. Census, and the National Land Cover Database, we focused on forest and woodland bird communities and conducted our analysis at multiple levels of model specificity, first using a coarse-thematic resolution (basic models), then using a larger number of fine-thematic resolution variables (refined models). We found that housing development was associated with forest bird species richness in all forested ecoregions of the conterminous United States. However, there were important differences among ecoregions. In the basic models, housing density accounted for ,5% of variance in avian species richness. In refined models, 85% of models included housing density and/or residential land cover as significant variables. The strongest guild response was demonstrated in the Adirondack-New England ecoregion, where 29% of variation in richness of the permanent resident guild was associated with housing density. Model improvements due to regional stratification were most pronounced for cavity nesters and short-distance migrants, suggesting that these guilds may be especially sensitive to regional processes. The varying patterns of association between avian richness and attributes associated with landscape structure suggested that landscape context was an important mediating factor affecting how biodiversity responds to landscape changes. Our analysis suggested that simple, broadly applicable, land use recommendations cannot be derived from our results. Rather, anticipating future avian response to land use intensification (or reversion to native vegetation) has to be conditioned on the current landscape context and the species group of interest. Our results show that housing density and residential land cover were significant predictors of forest bird species richness, and their prediction strengths are likely to increase as development continues.
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 [R2 = 0.88, P < 0.001, standard error of estimate (SE) = 8 species], followed by canopy nesters (R2 = 0.79, P < 0.001, SE = 3 species) and grassland species (R2 = 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 (R2 = 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.
Conservation of biodiversity requires information at many spatial scales in order to detect and preserve habitat for many species, often simultaneously. Vegetation structure information is particularly important for avian habitat models and has largely been unavailable for large areas at the desired resolution. Airborne LiDAR, with its combination of relatively broad coverage and ?ne resolution provides existing new opportunities to map vegetation structure and hence avian habitat. Our goal was to model the richness of forest songbirds using forest structure information obtained from LiDAR data. In deciduous forests of southern Wisconsin, USA, we used discrete-return airborne LiDAR to derive forest structure metrics related to the height and density of vegetation returns, as well as composite variables that captured major forest structural elements. We conducted point counts to determine total forest songbird richness and the richness of foraging, nesting, and forest edge-related habitat guilds. A suite of 35 LiDAR variables were used to model bird species richness using best-subsets regression and we used hierarchical partitioning analysis to quantify the explanatory power of each variable in the multivariate models. Songbird species richness was correlated most strongly with LiDAR variables related to canopy and midstory height and midstory density (R 2 =0.204, pb0.001). Richness of species that nest in the midstory was best explained by canopy height variables (R 2 =0.197, pb0.001). Species that forage on the ground responded to mean canopy height and the height of the lower canopy (R 2 =0.149, pb0.005) while aerial foragers had higher richness where the canopy was tall and dense and the midstory more sparse (R 2 =0.216, pb0.001). Richness of edge-preferring species was greater where there were fewer vegetation returns but higher density in the understory (R 2 =0.153, pb0.005). Forest interior specialists responded positively to a tall canopy, developed midstory, and a higher proportion of vegetation returns (R 2 =0.195, pb0.001). LiDAR forest structure metrics explained between 15 and 20% of the variability in richness within deciduous forest songbird communities. This variability was associated with vertical structure alone and shows how LiDAR can provide a source of complementary predictive data that can be incorporated in models of wildlife habitat associations across broad geographical extents.
The federally endangered Karner blue butterfly (Lycaeides samuelis) is the focal species for a conservation plan designed to create and maintain barrens habitats. We investigated whether habitat management for Karner blue butterflies influences avian community structure at Fort McCoy Military Installation in Wisconsin, USA. From 2007 through 2009 breeding bird point count and habitat characteristic data were collected at 186 sample points in five habitat types including two remnant barrens types, barrens habitat restored from woodland and managed specifically for the Karner blue butterfly, and two woodland habitat types. Although the bird community of managed barrens was not identical to the communities of remnant barrens, the Field Sparrow (Spizella pusilla), a species of conservation concern, and sparse canopy associated bird species, such as the Baltimore Oriole (Icterus galbula) and Eastern Bluebird (Sialia sialis) were predicted to occupy managed barrens and remnant barrens in similar proportions. Adjacent habitat was the most influential factor in determining the community of bird species using the managed barrens. In Wisconsin, and likely throughout the range of the Karner blue butterfly, management for the butterfly creates habitat that attracts a bird community similar to that of remnant barrens, and benefits several avian species of conservation concern. Additionally, the landscape context surrounding the managed habitat influences avian community composition. Managed barrens that are adjacent to remnant barrens, rather than adjacent to woodland habitats, have the highest potential for conserving barrens breeding birds.
Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Speci ? cally, we asked which data source, time periods, and heat wave indices best predicted changes in avian abundance and species richness. Using mixed effects models, we analyzed associations between these indices and data from the North American Breeding Bird Survey in the central United States between 2000 and 2007 in four ecoregions and ? ve migratory and nesting species groups. We then quanti?ed avian responses to scenarios of severe, but commonly-occurring early, late, and summer-long heat waves. Indices based on MODIS LST data, rather than interpolated air temperatures, were more predictive of avian community structure. Avian communities were more related to 8-day LST exceedances (positive anomalies only); and were generally more sensitive to summer-long heat waves. Across the region, abundance, and to a lesser extent, species richness, declined following heat waves. Among the ecoregions, relationships were most consistently negative in the southern and montane ecoregions, but were positive in a more humid northern ecoregion. Among migratory groups, permanent resident species were the most sensitive, declining in abundance following a summer-long heat wave by 19% and 13% in the montane and southern ecoregions, respectively. Ground-nesting species, which declined in the south by 12% following a late summer heat wave, were more sensitive than avifauna overall. These results demonstrate the value of MODIS LST data for measuring ecologically-relevant heat waves across large regions. Ecologically, these ? ndings highlight the importance of extreme events for avian biodiversity and the considerable variation in response to environmental change associated with different functional groups and geographic regions. The magnitude of the relationships between avian abundance and heat waves reported here raises concerns about the impacts of more frequent and severe heat waves in a warming climate.
1. Habitat conservation, particularly for large, multiple use areas, must account for the needs of multiple species. However, an unresolved issue is how to manage habitat when the needs of resident species con?ict and when the habitat can only be modelled at a coarse scale. Here, we illustrate an approach to optimizing habitat management using an example of a community of forest-breeding birds. 2. We used potential habitat maps for 20 bird species in northern Wisconsin and identi?ed a spatial arrangement that maximizes conservation value for multiple species, maximizes connectivity and minimizes the area needed for conservation. To do this, we ranked each cell of the study area using a nested percentage value, with for example the highest-ranking 1% holding lands of highest conservation value. 3. As we progressively increased the portion of landscape considered, starting with the highestranking habitat ?rst, the number of species for which the minimum habitat requirements were met reached plateaux at 3% and 20% of the landscape. To provide enough area to meet the minimum habitat requirements for all but two species, an estimated 20% of the habitat with the highest conservation value, c. 1 million hectares, would need to be maintained. Of that 20% highest-ranking area, 42% was on public lands, compared with 28% for the study area. 4. Tribal lands held a disproportionally large amount of area estimated to be of high conservation value: within the highest-ranking 1% of land, 14% consisted of tribal lands, while these lands held only 5% of the entire study area's forests. 5. Synthesis and applications. Hierarchical prioritization provided an e?cient mapping approach and the regional perspective necessary to identify management opportunities for a wide range of species. However, it could not explicitly address con?icts among species with overlapping potential habitat but incompatible ?ne-scale habitat needs. Ignoring this issue may lead to a failure to meet conservation objectives. This issue of habitat mischaracterization needs to be recognized in conservation planning objectives, preferably integrated in an optimization strategy, and can only be partly addressed with a post hoc, stepwise heuristic approach
Urbanization causes the simplification of natural habitats, resulting in animal communities dominated by exotic species with few top predators. In recent years, however, many predators such as hawks, and in the US coyotes and cougars, have become increasingly common in urban environments. Hawks in the Accipiter genus, especially, are recovering from widespread population declines and are increasingly common in urbanizing landscapes. Our goal was to identify factors that determine the occupancy, colonization and persistence of Accipiter hawks in a major metropolitan area. Through a novel combination of citizen science and advanced remote sensing, we quantified how urban features facilitate the dynamics and long-term establishment of Accipiter hawks. Based on data from Project FeederWatch, we quantified 21 years (1996–2016) of changes in the spatiotemporal dynamics of Accipiter hawks in Chicago, IL, USA. Using a multi-season occupancy model, we estimated Cooper’s (Accipiter cooperii) and sharp-shinned (A. striatus) hawk occupancy dynamics as a function of tree canopy cover, impervious surface cover and prey availability. In the late 1990s, hawks occupied 26% of sites around Chicago, but after two decades, their occupancy fluctuated close to 67% of sites and they colonized increasingly urbanized areas. Once established, hawks persisted in areas with high levels of impervious surfaces as long as those areas supported high abundances of prey birds. Urban areas represent increasingly habitable environments for recovering predators, and understanding the precise urban features that drive colonization and persistence is important for wildlife conservation in an urbanizing world.
Understanding past and current patterns of species richness is essential for predicting how these patterns may be affected by future global change. The species energy hypothesis predicts that higher abundance and richness of animal species occur where available energy is higher and more consistently available. There is a wide range of remote sensing proxies for available energy, such as vegetation productivity, but it is not clear which best predict species richness. Our goal here was to evaluate different proxies for annual plant productivity from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) as input for the Dynamic Habitat Indices (DHIs), and to determine how well they predict the richness of breeding bird species in six functional guilds across the conterminous United States. The DHIs are measures of vegetation productivity over the course of a year and consist of three components: (1) cumulative productivity (DHI Cum), (2) minimum productivity (DHI Min), and (3) intra-annual variation of productivity (DHI Var). We hypothesized that increases in cumulative and minimum productivity and reductions in intra-annual variation will be associated with higher species richness. We calculated the DHIs from a range of MODIS 1000-m vegetation productivity data sets for 2003– 2014, i.e., the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Fraction of absorbed Photosynthetically Active Radiation (FPAR), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). We summarized bird species richness of different guilds within ecoregions (n = 85) based on abundance maps derived from the N3000 routes of the North American Breeding Bird Survey for 2006 to 2012. Generally, we found all the DHIs had high explanatory power for predicting breeding bird species richness. However, the strength of the associations between the DHIs and bird species richness depended on habitat, nest placement, and migratory behavior. We found highest correlations for habitat-based guilds, such as grassland breeding species (R2 adj 0.66–0.73 for the multiple DHI regression model; R2 adj 0.41–0.61 for minimum DHI) and woodland breeding species (R2 adj 0.34–0.60 for the multiple DHI regression model; R2 adj 0.26–0.51 for cumulative DHI). The strong relationship between the DHIs and bird species richness reinforces the importance of vegetation productivity as a determinant of species diversity patterns, and the usefulness of satellite data for applying the species energy hypothesis to predictions in service to conservation.
Hillside of village sacred forest with view of valley below
In northwestern Yunnan, China, certain patches of forests are considered sacred. What does that mean? It means that people go into the forest to pray or to offer gifts to their same gods because they believe their lives will be blessed and successful if they do so. Jodi was interested in the biodiversity of sacred forests and inventoried which bird species occur there. Jodi end up publishing a bird field guide both in English and in Mandarin as a result of her work (Birds of Shangrila PDF). Later on, Teri conducted interviews with locals because she was interested in understanding how local people see sacred forests, but also to understand if an extra conservation status was necessary in order to preserve these little patches.
Conducting survey about sacred village forests
As a result of the interviews, Teri came to the conclusion that people do not see the forest as a wildlife habitat or as an area that provides other ecosystem service such as clean water or soil protection. Instead, the sacred forests serve the single purpose of pleasing the gods and thereby ensure that people’s lives go on smoothly. This perception of the forest is the same across genders and age groups, which indicates that unless there is a major shift in the local belief system, there is no immediate danger of losing village sacred forest areas.”
