Predictors of specialist avifaunal decline in coastal marshes

Coastal marshes are one of the world's most productive ecosystems. Consequently, they have been heavily used by humans for centuries, resulting in ecosystem loss. Direct human modifications such as road crossings and ditches and climatic stressors such as sea‐level rise and extreme storm events have the potential to further degrade the quantity and quality of marsh along coastlines. We used an 18‐year marsh‐bird database to generate population trends for 5 avian species (Rallus crepitans, Tringa semipalmata semipalmata, Ammodramus nelsonii subvirgatus, Ammodramus caudacutus, and Ammodramus maritimus) that breed almost exclusively in tidal marshes, and are potentially vulnerable to marsh degradation and loss as a result of anthropogenic change. We generated community and species trends across 3 spatial scales and explored possible drivers of the changes we observed, including marsh ditching, tidal restriction through road crossings, local rates of sea‐level rise, and potential for extreme flooding events. The specialist community showed negative trends in tidally restricted marshes (?2.4% annually from 1998 to 2012) but was stable in unrestricted marshes across the same period. At the species level, we found negative population trends in 3 of the 5 specialist species, ranging from ?4.2% to 9.0% annually. We suggest that tidal restriction may accelerate degradation of tidal marsh resilience to sea‐level rise by limiting sediment supply necessary for marsh accretion, resulting in specialist habitat loss in tidally restricted marshes. Based on our findings, we predict a collapse of the global population of Saltmarsh Sparrows (A. caudacutus) within the next 50 years and suggest that immediate conservation action is needed to prevent extinction of this species. We also suggest mitigation actions to restore sediment supply to coastal marshes to help sustain this ecosystem into the future.     

Object-Based Classification as an Alternative Approach to the Traditional Pixel-Based Classification to Identify Potential Habitat of the Grasshopper Sparrow

The traditional method of identifying wildlife habitat distribution over large regions consists of pixel-based classification of satellite images into a suite of habitat classes used to select suitable habitat patches. Object-based classification is a new method that can achieve the same objective based on the segmentation of spectral bands of the image creating homogeneous polygons with regard to spatial or spectral characteristics. The segmentation algorithm does not solely rely on the single pixel value, but also on shape, texture, and pixel spatial continuity. The object-based classification is a knowledge base process where an interpretation key is developed using ground control points and objects are assigned to specific classes according to threshold values of determined spectral and/or spatial attributes. We developed a model using the eCognition software to identify suitable habitats for the Grasshopper Sparrow, a rare and declining species found in southwestern Québec. The model was developed in a region with known breeding sites and applied on other images covering adjacent regions where potential breeding habitats may be present. We were successful in locating potential habitats in areas where dairy farming prevailed but failed in an adjacent region covered by a distinct Landsat scene and dominated by annual crops. We discuss the added value of this method, such as the possibility to use the contextual information associated to objects and the ability to eliminate unsuitable areas in the segmentation and land cover classification processes, as well as technical and logistical constraints. A series of recommendations on the use of this method and on conservation issues of Grasshopper Sparrow habitat is also provided.     

Use of data on avian demographics and site persistence during overwintering to assess quality of restored riparian habitat

Monitoring responses by birds to restoration of riparian vegetation is relatively cost-effective, but in most assessments species-specific abundances, not demography, are monitored. Data on birds collected during the nonbreeding season are particularly lacking. We captured birds in mist nets and resighted banded birds to estimate species richness and diversity, abundance, demographic indexes, and site-level persistence of permanent-resident and overwintering migrants in remnant and restored riparian sites in California. Species richness in riparian remnants was significantly higher than in restored sites because abundances of uncommon permanent residents were greater in remnants. Species richness of overwintering migrants did not differ between remnants and restored sites. Responses among overwintering migrants (but not permanent residents) to remnant and restored riparian sites differed. Capture rates were higher in remnant or restored riparian sites for 7 of 10 overwintering migratory species. For Lincoln's Sparrows (Melospiza lincolnii) and White-crowned Sparrows (Zonotrichia leucophrys) proportions of older birds were significantly higher in remnants, even though capture rates of these species were higher in restored sites. Overwinter persistence of 4 migrant species was significantly higher in remnant than in restored sites. A higher proportion of Hermit Thrushes (Catharus guttatus, 56.3%), older Fox Sparrows (Passerella iliaca, 57.1%), Lincoln's Sparrows (59.7%), and White-crowned Sparrows (67.8%) persisted in remnants than restored sites. Our results suggest restored riparian sites provide habitat for a wide variety of species in comparable abundances and diversity as occurs in remnant riparian sites. Our demographic and persistence data showed that remnants supported some species and age classes to a greater extent than restored sites.