The law of diminishing returns: woodland birds respond to native vegetation cover at multiple spatial scales and over time

Cunningham, Ross B.; Lindenmayer, David B.; Crane, Mason; Michael, Damian; Barton, Philip S.; Gibbons, Philip; Okada, Sachiko; Ikin, Karen; Stein, John

doi:10.1111/ddi.12145

Cited by 57 publications

(55 citation statements)

References 47 publications

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“…Previous research within the study region has shown that bird species richness is related to vegetation cover at each of these scales [23]. To measure vegetation cover in each year, we used grids of Forest Extent (FE) derived from Landsat TM and MSS satellite imagery from 2002 and 2008 (see [42] for a detailed description of the satellite imagery specifications).…”

Section: Methodsmentioning

confidence: 99%

Multi-Scale Associations between Vegetation Cover and Woodland Bird Communities across a Large Agricultural Region

et al. 2014

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Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1) How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2) Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3) Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha) over two time periods across a large (6,800 km2) agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricultural landscapes may lead to improved conservation of bird communities.

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Section: Methodsmentioning

confidence: 99%

Multi-Scale Associations between Vegetation Cover and Woodland Bird Communities across a Large Agricultural Region

et al. 2014

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“…That is, is inference spatially limited or extensive? The large array of sites, farms and landscapes in our quasi-experiment on the South West Slopes of New South Wales represent the range of environments across the entire bioregion [42,43], and the study therefore has extensive inference over several million hectares. Conversely, the scope of inference of our landscape studies in the unique range of habitats at Booderee National Park is relevant only to that 6600 ha in that reserve [44,45].…”

Section: Structural Featuresmentioning

confidence: 99%

“…The hierarchical design encompasses 23 landscapes (with and without restoration plantings, with 12 landscapes in one region and 11 in another), two farms within those 23 landscapes (farms with and without restoration plantings) and four sites located on the 46 farms within the 23 landscapes (comprising plantings and remnant woodland patches) [38]. This design provided a powerful basis from which to make inferences about the impacts of planting on biodiversity at the landscape, farm and site levels [42,43]. A final key question is: Is there inefficient use of limited resources?…”

Section: Sizementioning

confidence: 99%

“…The inference can then focus on changes taking place over time as well as on crosssectional differences. Studies of this nature can clearly distinguish changes over time from differences between sites; each site becomes its own control and so provides a powerful opportunity for assessing direct effects that are not obscured by cross-sectional differences (see [42,43]). …”

Section: 'Experiments' Provide a Secure Foundation For Monitoring Stumentioning

confidence: 99%

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Approaches to Landscape Scale Inference and Study Design

Cunningham

Lindenmayer

2016

Curr Landscape Ecol Rep

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Human modification of landscapes is a pervasive global issue with major implications for biodiversity conservation and ecological processes. However, the effects of landscape modification can be challenging to quantify. Here we briefly describe the strengths and weaknesses of four types of studies in landscape ecology: observational studies, true experiments, quasi-experiments and natural experiments. Observational investigations are based on the measurement of a given ecosystem or ecological process; they lack active interventions (e.g. manipulation of sites) to study biotic response. They do not interfere with the ecosystem under study, but the inferential status of the results from observational studies is weak. True experiments represent an organised and planned inquiry conducted under at least partially controlled conditions. They involve artificially altering or manipulating a landscape to yield information about the effects of variables that have been manipulated. True experiments are the most powerful form of study to support strong inference, but they have some limitations, such as the random assignment of treatments being relatively expensive and/or impractical to implement. In quasiexperiments and natural experiments, a management treatment (e.g. a tree planting) is compared with one or more contrasting treatments. However, there can be little or no random assignment of areas to interventions (treatments), as they already exist. The inferential status of quasi-experiments is weaker than that of a true experiment, and the former have fewer practical constraints. We provide a brief summary of important statistical questions and issues to be considered in developing designs for quasi-experiments that are often also relevant to other types of landscape ecology studies.

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“…Although there is presumably not a single 'best' spatial scale at which to associate species and their habitats for all species or ecological conditions, it is possible to reveal relevant ecological associations when the scale of analysis approaches the operational scale of the process of interest. Studies often use expert knowledge to set the scale of analysis, or in some cases use expert-informed designs to collect data at 'fine-' versus 'large-' spatial scales to compare their relative explanatory power (e.g., Saab 1999;Coppeto et al 2006;Cunningham et al 2014). Unfortunately, information regarding the ecological processes shaping the distribution or abundance of a species is often lacking, let alone the spatial scale at which these processes may act.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian method for assessing multi-scale species-habitat relationships

2017

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Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multiscale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

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The law of diminishing returns: woodland birds respond to native vegetation cover at multiple spatial scales and over time

Cited by 57 publications

References 47 publications

Multi-Scale Associations between Vegetation Cover and Woodland Bird Communities across a Large Agricultural Region

Multi-Scale Associations between Vegetation Cover and Woodland Bird Communities across a Large Agricultural Region

Approaches to Landscape Scale Inference and Study Design

A Bayesian method for assessing multi-scale species-habitat relationships

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