What determines the spatial extent of landscape effects on species?

Context

Landscape ecologists are often interested in measuring the effects of an environmental variable on a biological response; however, the strength and direction of effect depend on the size of the area within which the environmental variable is measured. Thus a central objective is to identify the optimal spatial extent within which to measure the environmental variable, i.e. the “scale of effect”.

Objectives

Our objectives are (1) to provide a comprehensive summary of the hypotheses concerning what determines the scale of effect, (2) to provide predictions that can be tested in empirical studies, and (3) to show, with a review of the literature, that most of these predictions have so far been inadequately tested.

Methods

We propose 14 predictions derived from five hypotheses explaining what determines the scale of effect, and review the literature (if any) supporting each prediction. These predictions involve five types of factors: (A) species traits, (B) landscape variables, (C) biological responses (e.g. abundance vs. occurrence), (D) indirect influences, and (E) regional context of the study. We identify methodological issues that hinder estimation of the scale of effect.

Results

Of the 14 predictions, only nine have been tested empirically and only five have received some empirical support. Most support is from simulation studies. Empirical evidence usually does not support predictions.

Conclusions

The study of the spatial scale at which landscape variables influence biological outcomes is in its infancy. We provide directions for future research by clarifying predictions concerning the determinants of the scale of effect.

     

Butterfly dispersal in farmland: a replicated landscape genetics study on the meadow brown butterfly (<Emphasis Type="Italic">Maniola jurtina</Emphasis>)

Context

Anthropogenic activities readily result in the fragmentation of habitats such that species persistence increasingly depends on their ability to disperse. However, landscape features that enhance or limit individual dispersal are often poorly understood. Landscape genetics has recently provided innovative solutions to evaluate landscape resistance to dispersal.

Objectives

We studied the dispersal of the common meadow brown butterfly, Maniola jurtina, in agricultural landscapes, using a replicated study design and rigorous statistical analyses. Based on existing behavioral and life history research, we hypothesized that the meadow brown would preferentially disperse through its preferred grassy habitats (meadows and road verges) and avoid dispersing through woodlands and the agricultural matrix.

Methods

Samples were collected in 18 study landscapes of 5 × 5 km in three contrasting agricultural French regions. Using circuit theory, least cost path and transect-based methods, we analyzed the effect of the landscape on gene flow separately for each sex.

Results

Analysis of 1681 samples with 6 microsatellites loci revealed that landscape features weakly influence meadow brown butterfly gene flow. Gene flow in both sexes appeared to be weakly limited by forests and arable lands, whereas grasslands and grassy linear elements (road verges) were more likely to enhance gene flow.

Conclusion

Our results are consistent with the hypothesis of greater dispersal through landscape elements that are most similar to suitable habitat. Our spatially replicated landscape genetics study allowed us to detect subtle landscape effects on butterfly gene flow, and these findings were reinforced by consistent results across analytical methods.

     

Prey distribution,potential landscape supplementation,and urbanization affect occupancy dynamics of American mink in streams

Context

Land-use change can reduce and isolate suitable habitat generating spatial variation in resource availability. Improving species distribution models requires a multi-scale understanding of resource requirements and species’ sensitivities to novel landscapes.

Objectives

We investigated how the spatial distribution of supplementary habitats (permanent wetlands), urbanization, water depths, and distribution of a key prey species (muskrat; Ondatra zibethicus) influence occupancy dynamics of American mink (Neovison vison). Although mink are widespread across North America and a destructive invasive species in Europe, South America, and Asia, we have a limited understanding of factors affecting their spatial distribution.

Methods

We used 6 years of presence–absence data (2007–2012) to evaluate occupancy dynamics of mink at 58–90 stream sites along an urbanization gradient in Illinois, USA. We predicted negative relationships between stream occupancy and urban land cover and distance from permanent wetlands, and positive associations with muskrat presence, water depth, and riparian zone width.

Results

Contrary to our hypothesis, stream sites closer to permanent wetlands had lower occupancy and colonization rates for mink. Occupancy and colonization rates were higher at sites with deeper water, and colonization rates were related negatively to urbanization. Mink were more likely to leave stream habitat if muskrats were not present and permanent wetlands were nearby.

Conclusion

Factors interplaying across multiple scales influenced occupancy dynamics of mink in stream habitat in a highly modified landscape. Our results highlight the importance of considering both direct measures of prey availability and the spatial distribution of supplementary habitats to improve habitat-selection models for carnivores.

     

Multi-scale Mexican spotted owl (<Emphasis Type="Italic">Strix occidentalis lucida</Emphasis>) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Context

Organisms commonly respond to their environment across a range of scales, however many habitat selection studies still conduct selection analyses using a single-scale framework. The adoption of multi-scale modeling frameworks in habitat selection studies can improve the effectiveness of these studies and provide greater insights into scale-dependent relationships between species and specific habitat components.

Objectives

Our study assessed multi-scale nest/roost habitat selection of the federally “Threatened” Mexican spotted owl (Strix occidentalis lucida) in northern Arizona, USA in an effort to provide improved conservation and management strategies for this subspecies.

Methods

We conducted multi-scale habitat modeling to assess habitat selection by Mexican spotted owls using survey data collected by the USFS. Each selected covariate was included in multi-scale models at their “characteristic scale” and we used an all-subsets approach and model selection framework to assess habitat selection.

Results

The “characteristic scale” identified for each covariate varied considerably among covariates and results from multi-scale models indicated that percent canopy cover and slope were the most important covariates with respect to habitat selection by Mexican spotted owls. Multi-scale models consistently outperformed their analogous single-scale counterparts with respect to the proportion of deviance explained and model predictive performance.

Conclusions

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective conservation and management strategies.

     

Landscape context affects site occupancy of pond-breeding anurans across a disturbance gradient in the Brazilian Cerrado

Context

The Brazilian Cerrado, a global biodiversity hotspot, is being converted to agricultural production. Amphibians in particular are susceptible to agricultural practices that threaten both their wetland and upland habitats. Although local site variables are important for determining species occurrence, site occupancy is also mediated by the broader landscape and management context in which the site occurs.

Objectives

Investigate the relative effects of broad-, intermediate-, and local-scale factors on species occurrence for pond-breeding anurans within different landscapes across an agricultural-disturbance gradient in the Cerrado.

Methods

Ponds were surveyed for adult anurans over 3 years within 18 landscapes (each 625 km²) that varied in their degree of agricultural land use (landscape context). We analyzed species distribution models for eight pond-breeding anurans, using hierarchical binomial generalized linear models.

Results

The broader landscape context had a significant effect on the incidence of pond-breeding anurans, even after accounting for variation in other environmental factors at more local (pond) or intermediate (1-km²) scales. The top-ranked models for most species included some combination of broad-, intermediate- and local-scale factors, however. These covariates influenced species occurrence in different ways, with the response to agricultural disturbance varying among species. Although some species were negatively affected, others appeared to benefit from agricultural activities that increased breeding habitat (e.g., impoundments to provide water for cattle).

Conclusions

Landscape context, the degree to which landscapes have been transformed by agricultural land use, has a major influence on the distribution of pond-breeding anurans in the Brazilian Cerrado.

     

A reverse keystone species affects the landscape distribution of woodland avifauna: a case study using the Noisy Miner (<Emphasis Type="Italic">Manorina melanocephala</Emphasis>) and other Australian birds

We explored the effects of a purported ‘reverse keystone species’, the Noisy Miner (Manorina melanocephala) using a long-term, large-scale dataset. Specifically, we identify whether this aggressive bird affects the landscape distribution patterns of other avifauna, by displacing them into, or restricting their distribution to, less productive areas, and in so doing, adheres to ‘isoleg theory’. We sought to determine the effect of abundance of the Noisy Miner on the abundance of other birds (individual species and groups), and determine whether that effect was consistent with varying site productivity, using a negative binomial distribution with a logarithmic link function, and an offset variable to account for variations in search effort. Relationships between abundance of Noisy Miners and habitat variables were examined using a Poisson distribution with a logarithmic link function scaled for extra-variation (quasi-Poisson regression). We demonstrate that when Noisy Miner abundance is low, many small passerine species are more abundant on high productivity sites. However, as Noisy Miner abundance increases, small passerine abundance decreases, with this decrease most apparent on productive sites. The same patterns were not evident for birds considered ‘non-competitors’ of the Noisy Miner. We identify that both site productivity and vegetation structure influence the abundance of the Noisy Miner. We reveal that the species increasingly tolerates ‘less desirable’ habitat attributes with increasing site productivity. The preference of the Noisy Miner for productive areas is likely to have deleterious impacts on the long-term survival and reproductive success of other Australian woodland bird species, many of which have already undergone severe declines.     

Amplified fragment length polymorphism as a tool for molecular characterization of almond germplasm: genetic diversity among cultivated genotypes and related wild species of almond,and its relationships with agronomic traits

Amplified fragment length polymorphism (AFLP) analysis is a rapid and efficient method for producing DNA fingerprints and molecular characterization. Our objectives were to: estimate genetic similarities (GS), marker indices, and polymorphic information contents (PICs) for AFLP markers in almond cultivars; assess the genetic diversity of almond cultivars and wild species, using GS estimated from AFLP fingerprints and molecular characterization; and facilitate the use of markers in inter-specific introgression and cultivar improvement. The genetic diversity of 45 almond cultivars from Iran, Europe, and America, were studied assaying 19 primer combinations. In addition, several agronomic traits were evaluated, including flowering and maturity times, self-incompatibility, and kernel and fruit properties. Out of the 813 polymerase chain reaction fragments that were scored, 781 (96.23%) were polymorphic. GS ranged from 0.5 to 0.96, marker indices ranged from 51.37 to 78.79, and PICs ranged from 0.56 to 0.86. Results allowed the unique molecular identification of all assayed genotypes. However, the correlation between genetic similarity clustering as based on AFLP and clustering for agronomic traits was low. Cluster analysis based on AFLP data clearly differentiated the genotypes and wild species according to their origin and pedigree, whereas, cluster analysis based on agronomic data differentiated according the pomological characterization. Our results showed the great genetic diversity of the almond cultivars and their interest for almond breeding.     

Molecular mapping and characterization of traits controlling fiber quality in cotton

Cotton (Gossypium spp) is the world's leading natural fiber crop. Genetic manipulation continues to play a key role in the improvement of fiber quality properties. By use of DNA-based molecular markers and a polymorphic mapping population derived from an inter specific cross between TM-1 (G. hirsutum) and 3-79 (G. barbadense), thirteen quantitative trait loci (QTLs) controlling fiber quality properties were identified in 3-79, an extra long staple (ELS) cotton. Four QTLs influenced bundle fiber strength, three influenced fiber length, and six influenced fiber fineness. These QTLs were located on different chromosomes or linkage groups and collectively explained 30% to 60%of the total phenotypic variance for each fiber quality property in the F₂ population. The effects and modes of action for the individual QTLs were characterized with 3-79 alleles in TM-1 genetic background. The results indicated more recessive than dominant, with much less additive effect in the gene mode. Transgressive segregation was observed for fiber fineness that could be beneficial to improvement of this trait. Molecular markers linked to fiber quality QTLs would be most effective in marker-assisted selection (MAS) of these recessive alleles in cotton breeding programs. This revised version was published online in August 2006 with corrections to the Cover Date.