Management of matter fluxes by biogeochemical barriers at the agricultural landscape level⋆

Long-term studies of the influence of biogeochemical barriers (shelterbelts and stretches of meadows) on water cycling and control of ground water pollution in an agricultural landscape have shown that more solar energy is used for evapotranspiration in shelterbelts than in cultivated fields or meadows. Therefore, annual water runoff from cultivated fields is about 170% higher than from coniferous forest, 60% higher than deciduous forest and 16% higher than meadows. The differences in evapotranspiration rates between shelterbelts and meadows increases when additional energy input for evapotranspiration is provided by transport of heat from cultivated fields to these habitats by advection. The average water percolation time through the unsaturated zone of soils varies by 100%. A shelterbelt, having a mixed species composition, more effectively screens the passage of chemical compounds dissolved in ground water than shelterbelts composed of one tree species. Peat soils have a very high cation exchange capacity which increases the efficiency of riparian meadows for the control of ground water pollution. Natural landscape features which assist in controlling matter cycles are of great importance for modifying chemical outputs from agricultural watersheds.     

How has the state-of-the-art for quantification of landscape pattern advanced in the twenty-first century?

Landscape Ecology - Landscape ecology was founded on the idea that there is a reciprocal relationship between spatial pattern and ecological processes. I provide a retrospective look at how the...     

Small forest patches as pollinator habitat: oases in an agricultural desert?

Landscape Ecology - Small forest fragments are often the most abundant type of semi-natural habitat in intensive agricultural landscapes. Wild pollinators can use these forest patches as nesting or...     

How can forest fragments support protected areas connectivity in an urban landscape in Brazil?

Cities continue to grow worldwide, and the highly modified urban landscape becomes an inhospitable environment for many species because the natural vegetation cover is commonly fragmented, and the remnants are often isolated. Protected Areas (PAs) located surrounding or within urban areas may not achieve their goal of protecting local or regional biodiversity. Thus, an urban ecological network is essential to support their PAs. Thus, this study aimed at assessing the PAs connectivity in an urban landscape in Brazil and understanding whether urban forest fragments can support an urban ecological network. Besides spatial models based on functional connectivity and graph theory, we used participatory techniques to design the resistance surface and the least-cost paths (LCPs) for Atlantic Forest birds. The results showed critical paths (LCPs), important areas for restoration programs for improving PAs connectivity, and essential forest fragments for conservation and restoration. Although the landscape has a forest structure with 1873 forest fragments and 516 links through which the LCPs were structured, most forest fragments and LCPs cannot provide the necessary support for the PAs connectivity. The current ecological network is dependent on forest fragments neighboring (outside PAs) and the flux dispersions occurred mainly in the peri-urban areas. Riparian zones and anthropic grasslands also showed importance for the PAs connectivity. We identified only 28 forest fragments spatially connected, presenting several sizes, and located near large forest areas, relevant PAs, and riparian zones. Six of these forest fragments, smaller than ten hectares and strategically located in the urban matrix, were indicated for restoration actions. The current low connectivity among PAs brings the importance of native vegetation restoration in the riparian zone and anthropic grassland and the importance of the periurban areas to promote biodiversity connectivity in the urban landscape.     

Forest recovery in a tropical landscape: what is the relative importance of biophysical,socioeconomic, and landscape variables?

Socioeconomic changes in many areas in the tropics have led to increasing urbanization, abandonment of agriculture, and forest re-growth. Although these patterns are well documented, few studies have examined the drivers leading to landscape-level forest recovery and the resulting spatial structure of secondary forests. Land cover transitions from agricultural lands to secondary forest in the island of Puerto Rico have been ongoing since the 1940s. This study is a glimpse into this landscape level trend from 1991 to 2000. First, we relied on Landsat images to characterize changes in the landscape structure for forest, urban, and agricultural land classes. We found that although forest cover has increased in this period, forest has become increasingly fragmented while the area of urban cover has spread faster and become more clustered. Second, we used logistic regression to assess the relationship between the transition to forest and 21 biophysical, socioeconomic, and landscape variables. We found that the percentage of forest cover within a 100 m radius of a point, distance to primary roads and nature reserves, slope, and aspect are the most important predictors of forest recovery. The resulting model predicts the spatial pattern of forest recovery with accuracy (AUC-ROC = 0.798). Together, our results suggest that forest recovery in Puerto Rico has slowed down and that increasing pressure from urbanization may be critical in determining future landscape level forest recovery. These results are relevant to other areas in the tropics that are undergoing rapid economic development.     

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.

     

Landscape and local effects on occupancy and densities of an endangered wood-warbler in an urbanizing landscape

Context

Golden-cheeked warblers (Setophaga chrysoparia), an endangered wood-warbler, breed exclusively in woodlands co-dominated by Ashe juniper (Juniperus ashei) in central Texas. Their breeding range is becoming increasingly urbanized and habitat loss and fragmentation are a main threat to the species’ viability.

Objectives

We investigated the effects of remotely sensed local habitat and landscape attributes on point occupancy and density of warblers in an urban preserve and produced a spatially explicit density map for the preserve using model-supported relationships.

Methods

We conducted 1507 point-count surveys during spring 2011–2014 across Balcones Canyonlands Preserve (BCP) to evaluate warbler habitat associations and predict density of males. We used hierarchical Bayesian models to estimate multiple components of detection probability and evaluate covariate effects on detection probability, point occupancy, and density.

Results

Point occupancy was positively related to landscape forest cover and local canopy cover; mean occupancy was 0.83. Density was influenced more by local than landscape factors. Density increased with greater amounts of juniper and mixed forest and decreased with more open edge. There was a weak negative relationship between density and landscape urban land cover.

Conclusions

Landscape composition and habitat structure were important determinants of warbler occupancy and density, and the large intact patches of juniper and mixed forest on BCP (>2100 ha) supported a high density of warblers. Increasing urbanization and fragmentation in the surrounding landscape will likely result in lower breeding density due to loss of juniper and mixed forest and increasing urban land cover and edge.

     

Getting lost in the matrix? On how the characteristics and arrangement of linear landscape elements influence ecological connectivity

Landscape Ecology - Linear landscape elements (LLEs) such as ditches and hedgerows can increase the ecological connectivity of habitat embedded within agricultural areas by acting as corridors for...     

What determines the scale of landscape effect on tropical arboreal mammals?

Landscape Ecology - Biodiversity patterns depend on landscape structure, but the spatial scale at which such dependence is strongest (scale of effect, SoE) remains poorly understood, especially for...     

Landscape effects on scales of movement by white-tailed deer in an agricultural–forest matrix

Understanding how organisms respond to landscape heterogeneity is foundational to landscape ecology. We characterized seasonal scales of movement of white-tailed deer (Odocoileus viginianus) in an agricultural–forest matrix using first-passage time analysis (FPT) for 62 GPS-collared individuals. We investigated whether those scales were driven by demographic or landscape features. We found FPT for each individual across all seasons was typically dominated by a peak in variance of FPT/area at scales (radii) from 425 to 1,675 m. These peaks occurred at scales consistent with seasonal space use. We observed additional lower magnitude peaks at larger scales (3,000–6,000 m) and small scales (25–150 m). Peaks at larger scales were associated with seasonal migrations and dispersal events. Small scale peaks may represent resting or foraging behavior. Female movements were organized at smaller scales than males in the spring/summer season. Models relating landscape features to movement scales suggest that deer perceive and move within the landscape differently as the roles of dominant land-cover types shift seasonally. During winter, configuration (interspersion/juxtaposition) of land-cover types is more important to deer than during spring/summer and fall. During spring/summer and fall, movement behavior may be dictated by reproductive and harvest activities.     

Allerton Park 1983: the beginnings of a paradigm for landscape ecology?

In 1983, a group of incipient landscape ecologists met to discuss the nature and future directions for landscape ecology. The themes emerging from this conference—movement of materials, organisms, and energy through a landscape; the genesis of landscape patterns; the effects of landscape structure on the spread of disturbances; and the potential contributions of landscape ecology to resource management—established a foundation for the development of landscape ecology in North America over the following decades. I discuss these contributions in the light of where landscape ecology is today.

Do small-grain processes matter for landscape scale questions? Sensitivity of a forest landscape model to the formulation of tree growth rate

Process-based forest landscape models are valuable tools for testing basic ecological theory and for projecting how forest landscapes may respond to climate change and other environmental shifts. However, the ability of these models to accurately predict environmentally-induced shifts in species distributions as well as changes in forest composition and structure is often contingent on the phenomenological representation of individual-level processes accurately scaling-up to landscape-level community dynamics. We use a spatially explicit landscape forest model (LandClim) to examine how three alternative formulations of individual tree growth (logistic, Gompertz, and von Bertalanffy) influence model results. Interactions between growth models and landscape characteristics (landscape heterogeneity and disturbance intensity) were tested to determine in what type of landscape simulation results were most sensitive to growth model structure. We found that simulation results were robust to growth function formulation when the results were assessed at a large spatial extent (landscape) and when coarse response variables, such as total forest biomass, were examined. However, results diverged when more detailed response variables, such as species composition within elevation bands, were considered. These differences were particularly prevalent in regions that included environmental transition zones where forest composition is strongly driven by growth-dependent competition. We found that neither landscape heterogeneity nor the intensity of landscape disturbances accentuated simulation sensitivity to growth model formulation. Our results indicate that at the landscape extent, simulation results are robust, but the reliability of model results at a finer resolution depends critically on accurate tree growth functions.     

Temporal variability of connectivity in agricultural landscapes: do farming activities help?

Landscape Ecology - In landscapes where natural habitats have been severely fragmented by intensive farming, survival of many species depends on connectivity among habitat patches. Spatio-temporal...     

Is Nutrient Contamination of Groundwater Causing Eutrophication of Groundwater-Fed Meadows?

There is an ongoing debate as to whether nutrient contamination of groundwater under agricultural fields may cause nutrient-enrichment and subsequent eutrophication in discharge areas. Often, there is only circumstantial evidence to support this supposition (proximity of agricultural fields, direction of water flow, highly productive vegetation). Research on solute transport along a flow path is necessary to evaluate the risk for eutrophication. In this paper we present results of such a study. Two transects were established in a discharge meadow, a few meters downstream from fertilized cornfields. Highly productive vegetation in parts of the meadow suggested nutrient-enrichment caused by inflow of contaminated groundwater. This supposition was supported by an analysis of groundwater flow paths, residence times and chloride as tracer for pollution. However, the fate of nutrients along the flow path indicated otherwise. While we found high concentrations of DIN (dissolved inorganic nitrogen), P and K under the cornfields, DIN and P concentrations drop below detection limit when groundwater enters the meadow. Only K progressed into the meadow but did not enter the root zone. We conclude that (1) polluted groundwater from the cornfields did not cause the nutrient-enrichment, as indicated by the highly productive vegetation. Restoration projects in discharge areas should not focus upon measures in upstream areas if only circumstantial evidence is available. Solute transport should be considered as well. (2) Because K clearly showed to be the most mobile nutrient, its importance for nutrient-enrichment in discharge wetlands merits more attention in future research.     

How does the landscape context of occurrence data influence models of invasion risk? A comparison of independent datasets in Massachusetts,USA

The spatial distribution of non-native, invasive plants on the landscape is strongly influenced by human action. People introduce non-native species to new landscapes and regions (propagule pressure) as well as increase ecosystem invasibility through disturbance of native ecosystems. However, the relative importance of different landscape drivers of invasion may vary with landscape context (i.e., the types and amounts of surrounding land cover and land use). If so, data collected in one context may not be appropriate for predicting invasion risk across a broader landscape. To test whether independent occurrence datasets suggest similar landscape drivers of invasion, we compared landscape models based on data compiled by the Invasive Plant Atlas of New England (IPANE), which are contributed opportunistically by trained citizen scientists, to models based on Forest Stewardship plans (FSPs), which are located in privately owned and relatively undisturbed forests. We evaluated 16 landscape variables related to propagule pressure and/or disturbance for significant predictors of invasive plant presence based on presence/absence and count regression models. Presence and richness of invasive plants within FSPs was most influenced by proportion of open land and proximity to residential areas, which are both sources of propagules in forest interiors. In contrast, IPANE invasive plant presence and richness for the same area was influenced by distance to roads and streams. These results suggest that landscape drivers of invasion vary considerably depending on landscape context, and the choice of occurrence dataset will strongly influence model results.     

Analysis of landscape pattern change trajectories within areas of intensive agricultural use: case study in a watershed of southern Québec, Canada

This study aimed at capturing the spatial variability of landscape patterns and their trajectories of change from 1950 to 2000 within a watershed, which is representative of areas of intensive agricultural use. After an analysis of landscape features changes for the entire watershed based on aerial photographs, hierarchical clustering analysis provided a typology of landscape patterns for the cadastral lots. Following that, the trajectory of change of each lot was characterized (nature, importance, direction, rate of change). Seven types of landscape patterns are distinguished by the relative importance of different classes of landscape features and 51 trajectories of change were identified for the lots. The analysis shows that although the majority of lots were subjected to a homogenization of their landscape patterns since 1950, this trend is not entirely uniform and that since 2000 it occurs alongside trends towards diversification of certain landscape features on some lots. Furthermore, nearly a third of the lots are not following the main trajectories of change detected. Thus, the results suggest that extrinsic forces (policies, technologies) that are directing main changes in areas of intensive agricultural use toward uniformity could be modulated by internal forces (uses and values of the population). A better understanding of theses internal forces seems crucial to manage landscapes. From a methodology standpoint, although the hierarchical clustering analyses appear useful for understanding the spatial and temporal variability of landscape patterns, particular attention must be given to validating the typology chosen to characterize them.     

Addressing the interplay of poverty and the ecology of landscapes: a Grand Challenge Topic for landscape ecologists?

We argue for the landscape ecology community to adopt the study of poverty and the ecology of landscapes as a Grand Challenge Topic. We present five areas of possible research foci that we believe that landscape ecologists can join with other social and environmental scientists to increase scientific understanding of this pressing issue: (1) scale and poverty; (2) landscape structure and human well-being; (3) social and ecological processes linked to spatial patterns in landscapes; (4) conservation and poverty, and (5) applying the landscape ecologist’s toolkit. A brief set of recommendations for landscape ecologists is also presented. These include the need to utilize broad frameworks that integrate social and ecological variables, build capacity to do this kind of work through the development of strong collaborations of researchers in developed and developing countries, create databases in international locations where extreme poverty exists, and create a new generation of researchers capable of addressing this pressing social and environmental issue.