Adaptive vs. neutral genetic diversity: implications for landscape genetics

Genetic diversity is important for the maintenance of the viability and the evolutionary or adaptive potential of populations and species. However, there are two principal types of genetic diversity: adaptive and neutral – a fact widely neglected by non-specialists. We introduce these two types of genetic diversity and critically point to their potential uses and misuses in population or landscape genetic studies. First, most molecular-genetic laboratory techniques analyse neutral genetic variation. This means that the gene variants detected do not have any direct effect on fitness. This type of genetic variation is thus selectively neutral and tells us nothing about the adaptive or evolutionary potential of a population or a species. Nevertheless, neutral genetic markers have great potential for investigating processes such as gene flow, migration or dispersal. Hence, they allow us to empirically test the functional relevance of spatial indices such as connectivity used in landscape ecology. Second, adaptive genetic variation, i.e. genetic variation under natural selection, is analysed in quantitative genetic experiments under controlled and uniform environmental conditions. Unfortunately, the genetic variation (i.e. heritability) and population differentiation at quantitative, adaptive traits is not directly linked with neutral genetic diversity or differentiation. Thus, neutral genetic data cannot serve as a surrogate of adaptive genetic data. In summary, neutral genetic diversity is well suited for the study of processes within landscapes such as gene flow, while the evolutionary or adaptive potential of populations or species has to be assessed in quantitative genetic experiments. Landscape ecologists have to mind these differences between neutral and adaptive genetic variation when interpreting the results of landscape genetic studies.     

Making the connection: combining habitat suitability and landscape connectivity to understand species distribution in an agricultural landscape

Landscape Ecology - The current biodiversity crisis has intensified the need to predict species responses to landscape modification and has renewed attention on the fundamental question of what...     

Considering landscape connectivity and gene flow in the Anthropocene using complementary landscape genetics and habitat modelling approaches

Landscape Ecology - A comprehensive understanding of how rapidly changing environments affect species gene flow is critical for mitigating future biodiversity losses. While recent methodological...     

Effects of exurban development on trophic interactions in a desert landscape

Context

Mechanisms of ecosystem change in urbanizing landscapes are poorly understood, especially in exurban areas featuring residential or commercial development set in a matrix of modified and natural vegetation. We asked how development altered trophic interactions and ecosystem processes in the matrix.

Objectives

We examined the effect of varying degrees of exurban development (housing density) on a trophic system that included an apex mammalian predator (coyote, Canis latrans), mammalian herbivores (lagomorphs and rodents), and herbaceous plants. We tested the hypothesis that plant recruitment would be negatively affected by exurban development due either to increases in herbivores associated with increased resource availability (a bottom–up effect) or to a reduction in predators that avoid humans (a top–down effect).

Methods

In Las Cruces, New Mexico, USA, four replicate sites were located in each of three urbanization levels: high density exurban, low density exurban, and wildland dominated by Chihuahuan Desert vegetation. Seedling trays measured herbivory rates, live trapping estimated abundance of pocket mice and kangaroo rats, and remotely-triggered wildlife cameras estimated the activity of lagomorphs and coyotes.

Results

Increased herbivory on seedlings and decreased herbaceous plant recruitment were observed in high density exurban areas. Overall rodent abundance, seed consumption rates, and activity of the lagomorph Lepus californicus did not vary with urbanization level. Activity by another lagomorph, Sylvilagus audubonii, and coyotes was highest in dense exurban areas, consistent with a bottom–up effect.

Conclusions

Exurban development can have important indirect effects on trophic interactions occurring in adjacent, untransformed ecosystems. Similar to earlier studies, such effects in the Chihuahuan Desert may be mediated by bottom–up processes associated with anthropogenic inputs.

     

A practical toolbox for design and analysis of landscape genetics studies

Landscape genetics integrates theory and analytical methods of population genetics and landscape ecology. Research in this area has increased in recent decades, creating a plethora of options for study design and analysis. Here we present a practical toolbox for the design and analysis of landscape genetics studies following a seven-step framework: (1) define the study objectives, (2) consider the spatial and temporal scale of the study, (3) design a sampling regime, (4) select a genetic marker, (5) generate genetic input data, (6) generate spatial input data, and (7) choose an analytical method that integrates genetic and spatial data. Study design considerations discussed include choices of spatial and temporal scale, sample size and spatial distribution, and genetic marker selection. We present analytical methods suitable for achieving different study objectives. As emerging technologies generate genetic and spatial data sets of increasing size, complexity, and resolution, landscape geneticists are challenged to execute hypothesis-driven research that combines empirical data and simulation modeling. The landscape genetics framework presented here can accommodate new design considerations and analyses, and facilitate integration of genetic and spatial data by guiding new landscape geneticists through study design, implementation, and analysis.     

Fragmenting fragments: landscape genetics of a subterranean rodent (Mammalia,Ctenomyidae) living in a human-impacted wetland

Landscape Ecology - Anthropogenic activities have detrimental impacts on natural habitats and the species inhabiting them. In particular, habitat fragmentation has a profound effect on the dynamics...     

Governing the landscape: potential and challenges of integrated approaches to landscape sustainability in Indonesia

Landscape Ecology - In recent years, landscape sustainability, the maintenance and improvement of biodiversity, ecosystem services, and human well-being in landscapes, has become a core objective...     

景观生态理念在高速公路景观中的运用——以宁波象山港大桥接线工程为例

分析高速公路绿化中生态景观组成的几个重要部分,并根据景观生态学理论、以宁波象山港大桥接线工程为例介绍景观生态理念在高速公路景观中的运用.     

Bridging landscape preference and landscape design: A study on the preference and optimal combination of landscape elements based on conjoint analysis

Landscape preference is the focus of landscape research, in which the relationship between landscape elements and landscape preference is an important issue. Most previous studies have analysed correlation between the landscape preference scored by the public and scores on the quality of landscape elements by experts; some have compared the effects of individual landscape elements on landscape preference by photo simulation. In this study, landscape preference is regarded as the selection preference of landscape element combination. The conjoint analysis method is used to further explore the ranking and optimal combination of the significant degrees of impact of landscape elements on landscape preference when multiple landscape element combinations are used. The results show that the influence degrees of landscape elements on landscape preference in urban parks followed the order water, square, openness of the landscape, vegetation, road and seats. The optimal combination of landscape elements is the open landscape with flowing water, a shaded square, rich vegetation, a road and seats. This study demonstrates the advantages of the conjoint analysis method over the univariate method in controlling multiple variables, improving experimental efficiency and obtaining more meaningful results. A combination of urban park landscape elements based on landscape preference is helpful to inspire landscape architects to make choices among multiple landscape elements, provides evidence-based design methods for landscape design and offers basic parameters for the wide application of the parametric design or computational design of landscape architecture.     

The effects of landscape patterns on ecosystem services: meta-analyses of landscape services

Purpose

The recently introduced concept of ‘landscape services’—ecosystem services influenced by landscape patterns—may be particularly useful in landscape planning by potentially increasing stakeholder participation and financial funding. However, integrating this concept remains challenging. In order to bypass this barrier, we must gain a greater understanding of how landscape composition and configuration influence the services provided.

Methods

We conducted meta-analyses that considered published studies evaluating the effects of several landscape metrics on the following services: pollination, pest control, water quality, disease control, and aesthetic value. We report the cumulative mean effect size (E₊₊), where the signal of the values is related to positive or negative influences.

Results

Landscape complexity differentially influenced the provision of services. Particularly, the percentage of natural areas had an effect on natural enemies (E₊₊ =?0.35), pollination (E₊₊?=?0.41), and disease control (E₊₊?=?0.20), while the percentage of no-crop areas had an effect on water quality (E₊₊?=?0.42) and pest response (E₊₊?=?0.33). Furthermore, heterogeneity had an effect on aesthetic value (E₊₊?=?0.5) and water quality (E₊₊ =???0.40). Moreover, landscape aggregation was important to explaining pollination (E₊₊?=?0.29) and water quality (E₊₊?=?0.35).

Conclusions

The meta-analyses reinforce the importance of considering landscape structure in assessing ecosystem services for management purposes and decision-making. The magnitude of landscape effect varies according to the service being studied. Therefore, land managers must account for landscape composition and configuration in order to ensure the maintenance of services and adapt their approach to suit the focal service.

     

Landscape ecology: Population genetics at the metapopulation level

Distribution of genetic diversity in a landscape depends on both within and among population processes. Selective pressures within populations have traditionally been studied by population genetics, which usually assumes that populations are at equilibrium. However, when selection pressures within and among populations are different, landscape processes are required to define an equilibrium (landscape being defined as the habitat of a set of populations called a metapopulation, and populations will differ depending on their situation in the landscape, i.e. their age and the state of neighboring populations). We examine reproduction systems and life history traits, for which variation depends on landscape processes. Predictions of their states in a metapopulation are drawn from theoretical models, and confronted to observations collected in natural populations.     

The scientific basis for the design of landscape sustainability: A conceptual framework for translational landscape research and practice of designed landscapes and the six Es of landscape sustainability

Landscape researchers and practitioners, using the lens of sustainability science, are breaking new ground about how people’s behaviors and actions influence the structure, function, and change of designed landscapes in an urbanizing world. The phrase—the scientific basis of the design for landscape sustainability—is used to describe how sustainability science can contribute to translational landscape research and practice about the systemic relationships among landscape sustainability, people’s contact with nature, and complex place-based problems. In the first section of this article, important definitions about the scientific basis of the design for landscape sustainability are reviewed including the six Es of landscape sustainability—environment, economic, equity, aesthetics, experience, and ethics. A conceptual framework about the six Es of landscape sustainability for designed landscapes is introduced. The interrelatedness, opportunities, contradictions, and limitations of the conceptual framework are discussed in relation to human health/security, ecosystem services, biodiversity, and resource management. The conceptual framework about the six Es of landscape sustainability for designed landscapes follows the tradition in which landscape researchers and practitioners synthesize emerging trends into conceptual frameworks for advancing basic and applied activities.     

Measuring landscape connectivity: On the importance of within-patch connectivity

Context

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity.

Objectives

A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results.

Methods

The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (m_eff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity.

Results

We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using m_eff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT.

Conclusions

Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

     

Design in science: extending the landscape ecology paradigm

Landscape ecological science has produced knowledge about the relationship between landscape pattern and landscape processes, but it has been less effective in transferring this knowledge to society. We argue that design is a common ground for scientists and practitioners to bring scientific knowledge into decision making about landscape change, and we therefore propose that the pattern–process paradigm should be extended to include a third part: design. In this context, we define design as any intentional change of landscape pattern for the purpose of sustainably providing ecosystem services while recognizably meeting societal needs and respecting societal values. We see both the activity of design and the resulting design pattern as opportunities for science: as a research method and as topic of research. To place design within landscape ecology science, we develop an analytic framework based on the concept of knowledge innovation, and we apply the framework to two cases in which design has been used as part of science. In these cases, design elicited innovation in society and in science: the design concept was incorporated in societal action to improve landscape function, and it also initiated scientific questions about pattern–process relations. We conclude that landscape design created collaboratively by scientists and practitioners in many disciplines improves the impact of landscape science in society and enhances the saliency and legitimacy of landscape ecological scientific knowledge.     

Surface metrics for landscape ecology: a comparison of landscape models across ecoregions and scales

Context

The patch-mosaic model is lauded for its conceptual simplicity and ease with which conventional landscape metrics can be computed from categorical maps, yet many argue it is inconsistent with ecological theory. Gradient surface models (GSMs) are an alternative for representing landscapes, but adoption of surface metrics for analyzing spatial patterns in GSMs is hindered by several factors including a lack of meaningful interpretations.

Objectives

We investigate the performance and applicability of surface metrics across a range of ecoregions and scales to strengthen theoretical foundations for their adoption in landscape ecology.

Methods

We examine metric clustering across scales and ecoregions, test correlations with patch-based metrics, and provide ecological interpretations for a variety of surface metrics with respect to forest cover to support the basis for selecting surface metrics for ecological analyses.

Results

We identify several factors complicating the interpretation of surface metrics from a landscape perspective. First, not all surface metrics are appropriate for landscape analyses. Second, true analogs between surface metrics and patch-based, landscape metrics are rare. Researchers should focus instead on how surface measures can uniquely measure spatial patterns. Lastly, scale dependencies exist for surface metrics, but relationships between metrics do not appear to change considerably with scale.

Conclusions

Incorporating gradient surfaces into landscape ecological analyses is challenging, and many surface metrics may not have patch analogs or be ecologically relevant. For this reason, surface metrics should be considered in terms of the set of pattern elements they represent that can then be linked to landscape characteristics.

     

Spatial scaling and multi-model inference in landscape genetics: <Emphasis Type="Italic">Martes americana</Emphasis> in northern Idaho

Individual-based analyses relating landscape structure to genetic distances across complex landscapes enable rigorous evaluation of multiple alternative hypotheses linking landscape structure to gene flow. We utilize two extensions to increase the rigor of the individual-based causal modeling approach to inferring relationships between landscape patterns and gene flow processes. First, we add a univariate scaling analysis to ensure that each landscape variable is represented in the functional form that represents the optimal scale of its association with gene flow. Second, we use a two-step form of the causal modeling approach to integrate model selection with null hypothesis testing in individual-based landscape genetic analysis. This series of causal modeling indicated that gene flow in American marten in northern Idaho was primarily related to elevation, and that alternative hypotheses involving isolation by distance, geographical barriers, effects of canopy closure, roads, tree size class and an empirical habitat model were not supported. Gene flow in the Northern Idaho American marten population is therefore driven by a gradient of landscape resistance that is a function of elevation, with minimum resistance to gene flow at 1500 m.     

Deep time: the emerging role of archaeology in landscape ecology

Given the goals of landscape ecology, information from archaeological sites provides a useful source of evidence regarding cultural practices, anthropogenic change, local conditions, and distributions of organisms at a variety of scales across both space and time. Due to the time depth available from the archaeological record, long-term processes can be studied and issues of land use legacies, human influence on landscape heterogeneity, and system histories can be addressed. Archaeological data can produce a diachronic record of past population size, population structure, biogeography, age-at-death, and migration patterns, useful for making ecosystem and wildlife management decisions. Researchers can use archaeological knowledge to differentiate between native and alien taxa, inform restoration plans, identify sustainable harvesting practices, account for modern distributions of taxa, predict future biogeographic changes, and elucidate the interplay of long- and short-term ecological processes.