Landscape-Level Associations of Wintering Waterbird Diversity and Abundance from Remotely Sensed Wetland Characteristics of Poyang Lake

Dronova, Iryna; Beissinger, Steven R.; Burnham, James; Gong, Peng

doi:10.3390/rs8060462

Cited by 30 publications

(23 citation statements)

References 68 publications

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“…Modelled associations with habitat features can also be combined with spatially-explicit information on relevant environmental predictors to derive spatially-explicit predictions on the extent and distribution of suitable habitats for waterbirds [ 75 ]. Such spatially-explicit predictions could be periodically updated by incorporating remote-sensing data on environmental conditions [ 76 , 77 ], serving as a formidable addition to the toolbox of ecologists, stakeholders and managers.…”

Section: Discussionmentioning

confidence: 99%

How will climate change affect endangered Mediterranean waterbirds?

et al. 2018

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Global warming and direct anthropogenic impacts, such as water extraction, largely affect water budgets in Mediterranean wetlands, thereby increasing wetland salinities and isolation, and decreasing water depths and hydroperiods (duration of the inundation period). These wetland features are key elements structuring waterbird communities. However, the ultimate and net consequences of these dynamic conditions on waterbird assemblages are largely unknown. We combined regular sampling of waterbird presence through one annual cycle with in-situ data on relevant environmental predictors of waterbird distribution to model habitat selection for 69 species in a typical Mediterranean wetland network in southwestern Spain. Species associations with environmental features were subsequently used to predict changes in habitat suitability for each species under three climate change scenarios (encompassing changes in environmental predictors that ranged from 10% to 50% change as predicted by regional climatic models). Waterbirds distributed themselves unevenly throughout environmental gradients and water salinity was the most important gradient structuring the distribution of the community. Environmental suitability for the guilds of diving birds and vegetation gleaners will decline in future climate scenarios, while many small wading birds will benefit from changing conditions. Resident species and those that breed in this wetland network will also be more negatively impacted than those using this area for wintering or stopover. We provide a tool that can be used in a horizon-scanning framework to identify emerging issues in waterbird conservation and to anticipate suitable management actions.

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Section: Discussionmentioning

confidence: 99%

How will climate change affect endangered Mediterranean waterbirds?

et al. 2018

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“…Unfortunately, few studies have incorporated wild birds into geographically explicit models (Gilbert and Pfeiffer 2012), largely because obtaining spatial inputs for these populations is difficult. Datasets within Asia have been driven by range maps (Williamson et al 2013) or limited to small regions or few species (Zeng et al 2015;Dai et al 2016;Dronova et al 2016). Therefore, a technique that makes the most of available data to address pressing conservation and human health concerns is of the utmost importance.…”

Section: Introductionmentioning

confidence: 99%

Species distribution modeling in regions of high need and limited data: waterfowl of China

et al. 2018

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Background: A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources. Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multidisciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China. Methods: Faced with limited data, we built species distribution models using a habitat suitability approach for China's breeding and non-breeding (hereafter, wintering) waterfowl. An extensive review of the literature was used to determine model parameters for habitat modeling. Habitat relationships were implemented in GIS using land cover covariates. Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available. Results: We developed suitability models for 42 waterfowl species (30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps. Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China. Wintering waterfowl suitability was highest in the lowland regions of southeastern China. Validation measures indicated strong performance in predicting species presence. Comparing our model outputs to China's protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized. Conclusions: These suitability models are the first available for many of China's waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically important areas, providing an example of how this approach may aid others faced with the challenge of addressing conservation issues with little data to inform decision making.

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“…A configuration comprising spectral bands from the visible to the near-infrared is typical for satellite sensors with a high spatial resolution as, for example, GeoEye, Ikonos, KompSat, Pleiades, QuickBird, RapidEye, or SPOT-6/7, while spectral bands in the shortwave infrared (SWIR) are usually missing. At this point, Worldview-3 (launched in 2014) is an exception with 16 multispectral bands including eight SWIR bands with a nominal pixel ground resolution of 3.7 m. The integration of SWIR bands with an adequate resolution, however, has been shown to be essential for classification purposes and the spectral discrimination of vegetation [15,16].For birds, remote sensing data have been widely used to map their habitats, and to predict distribution and abundance (e.g., [17][18][19][20][21][22]). Remotely sensed spectral data were either used directly for modelling approaches [17] or, more commonly, indirectly by an integration of remote sensing-derived products such as land cover data [22], vegetation indices [23], or image derived textural metrics [24].…”

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confidence: 99%

“…Remotely sensed spectral data were either used directly for modelling approaches [17] or, more commonly, indirectly by an integration of remote sensing-derived products such as land cover data [22], vegetation indices [23], or image derived textural metrics [24]. Existing studies were largely based on coarse to intermediate resolution MODIS [21,22,25] or Landsat products [20,26,27]. The majority of studies using remote sensing derived products were based on freely available spatial data, such as subregional habitat maps [28], regional cropland data layers [29], and national or global land cover data sets [30,31].…”

mentioning

confidence: 99%

“…For birds, remote sensing data have been widely used to map their habitats, and to predict distribution and abundance (e.g., [17][18][19][20][21][22]). Remotely sensed spectral data were either used directly for modelling approaches [17] or, more commonly, indirectly by an integration of remote sensing-derived products such as land cover data [22], vegetation indices [23], or image derived textural metrics [24].…”

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Combining Multiband Remote Sensing and Hierarchical Distance Sampling to Establish Drivers of Bird Abundance

Richter

Heim

et al. 2019

Remote Sensing

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Information on habitat preferences is critical for the successful conservation of endangered species. For many species, especially those living in remote areas, we currently lack this information. Time and financial resources to analyze habitat use are limited. We aimed to develop a method to describe habitat preferences based on a combination of bird surveys with remotely sensed fine-scale land cover maps. We created a blended multiband remote sensing product from SPOT 6 and Landsat 8 data with a high spatial resolution. We surveyed populations of three bird species (Yellow-breasted Bunting Emberiza aureola, Ochre-rumped Bunting Emberiza yessoensis, and Black-faced Bunting Emberiza spodocephala) at a study site in the Russian Far East using hierarchical distance sampling, a survey method that allows to correct for varying detection probability. Combining the bird survey data and land cover variables from the remote sensing product allowed us to model population density as a function of environmental variables. We found that even small-scale land cover characteristics were predictable using remote sensing data with sufficient accuracy. The overall classification accuracy with pansharpened SPOT 6 data alone amounted to 71.3%. Higher accuracies were reached via the additional integration of SWIR bands (overall accuracy = 73.21%), especially for complex small-scale land cover types such as shrubby areas. This helped to reach a high accuracy in the habitat models. Abundances of the three studied bird species were closely linked to the proportion of wetland, willow shrubs, and habitat heterogeneity. Habitat requirements and population sizes of species of interest are valuable information for stakeholders and decision-makers to maximize the potential success of habitat management measures.the effectiveness of conservation interventions [1,3]. Yet, despite the rapid global decline in species richness and abundance over the past decades [4,5], a major challenge in conservation ecology is our limited knowledge on the population sizes and habitat preferences of animal species in understudied regions [6][7][8]. Here, the use of remote sensing data to predict species distributions and abundances is vital to improve large-scale biodiversity monitoring and species conservation [2,3,9].Optical remote sensing is often suggested as a powerful tool to assist with the mapping of protected habitats and vegetation. Moreover, spaceborne remote sensing offers the opportunity to map larger areas in a systematic, repeatable, and spatially exhaustive manner [10,11]. Apart from the spatial extent of the data, its grain or spatial resolution is another relevant issue of spatial scale. Ideally, the pixel resolution of remotely sensed and considered environmental data (e.g., information on habitat features) should match to model their relationships [12]. For example, the classical multispectral configuration of Landsat-4 to Landsat-8 provides a pixel size of 30 × 30 m and an image extent of 185 × 185 km. This allows linking Landsat data to en...

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Landscape-Level Associations of Wintering Waterbird Diversity and Abundance from Remotely Sensed Wetland Characteristics of Poyang Lake

Cited by 30 publications

References 68 publications

How will climate change affect endangered Mediterranean waterbirds?

How will climate change affect endangered Mediterranean waterbirds?

Species distribution modeling in regions of high need and limited data: waterfowl of China

Combining Multiband Remote Sensing and Hierarchical Distance Sampling to Establish Drivers of Bird Abundance

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