The landscape of fear as an emergent property of heterogeneity: Contrasting patterns of predation risk in grassland ecosystems

The likelihood of encountering a predator influences prey behavior and spatial distribution such that non‐consumptive effects can outweigh the influence of direct predation. Prey species are thought to filter information on perceived predator encounter rates in physical landscapes into a landscape of fear defined by spatially explicit heterogeneity in predation risk. The presence of multiple predators using different hunting strategies further complicates navigation through a landscape of fear and potentially exposes prey to greater risk of predation. The juxtaposition of land cover types likely influences overlap in occurrence of different predators, suggesting that attributes of a landscape of fear result from complexity in the physical landscape. Woody encroachment in grasslands furnishes an example of increasing complexity with the potential to influence predator distributions. We examined the role of vegetation structure on the distribution of two avian predators, Red‐tailed Hawk (Buteo jamaicensis) and Northern Harrier (Circus cyaneus), and the vulnerability of a frequent prey species of those predators, Northern Bobwhite (Colinus virginianus). We mapped occurrences of the raptors and kill locations of Northern Bobwhite to examine spatial vulnerability patterns in relation to landscape complexity. We use an offset model to examine spatially explicit habitat use patterns of these predators in the Southern Great Plains of the United States, and monitored vulnerability patterns of their prey species based on kill locations collected during radio telemetry monitoring. Both predator density and predation‐specific mortality of Northern Bobwhite increased with vegetation complexity generated by fine‐scale interspersion of grassland and woodland. Predation pressure was lower in more homogeneous landscapes where overlap of the two predators was less frequent. Predator overlap created areas of high risk for Northern Bobwhite amounting to 32% of the land area where landscape complexity was high and 7% where complexity was lower. Our study emphasizes the need to evaluate the role of landscape structure on predation dynamics and reveals another threat from woody encroachment in grasslands.     

Spatial Partitioning of Predation Risk in a Multiple Predator-Multiple Prey System

ABSTRACT Minimizing risk of predation from multiple predators can be difficult, particularly when the risk effects of one predator species may influence vulnerability to a second predator species. We decomposed spatial risk of predation in a 2-predator, 2-prey system into relative risk of encounter and, given an encounter, conditional relative risk of being killed. Then, we generated spatially explicit functions of total risk of predation for each prey species (elk [Cervus elaphus] and mule deer [Odocoileus hemionus]) by combining risks of encounter and kill. For both mule deer and elk, topographic and vegetation type effects, along with resource selection by their primary predator (cougars [Puma concolor] and wolves [Canis lupus], respectively), strongly influenced risk of encounter. Following an encounter, topographic and vegetation type effects altered the risk of predation for both ungulates. For mule deer, risk of direct predation was largely a function of cougar resource selection. However, for elk, risk of direct predation was not only a function of wolf occurrence, but also of habitat attributes that increased elk vulnerability to predation following an encounter. Our analysis of stage-based (i.e., encounter and kill) predation indicates that the risk effect of elk shifting to structurally complex habitat may ameliorate risk of direct predation by wolves but exacerbate risk of direct predation by cougars. Information on spatiotemporal patterns of predation will be become increasingly important as state agencies in the western United States face pressure to integrate predator and prey management.     

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

Background

The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity.

Scope

This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies.

Conclusions

Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation.     

Zones of influence for soil organic matter dynamics: A conceptual framework for data and models

Soil organic matter (SOM) is an indicator of sustainable land management as stated in the global indicator framework of the United Nations Sustainable Development Goals (SDG Indicator 15.3.1). Improved forecasting of future changes in SOM is needed to support the development of more sustainable land management under a changing climate. Current models fail to reproduce historical trends in SOM both within and during transition between ecosystems. More realistic spatio‐temporal SOM dynamics require inclusion of the recent paradigm shift from SOM recalcitrance as an ‘intrinsic property’ to SOM persistence as an ‘ecosystem interaction’. We present a soil profile, or pedon‐explicit, ecosystem‐scale framework for data and models of SOM distribution and dynamics which can better represent land use transitions. Ecosystem‐scale drivers are integrated with pedon‐scale processes in two zones of influence. In the upper vegetation zone, SOM is affected primarily by plant inputs (above‐ and belowground), climate, microbial activity and physical aggregation and is prone to destabilization. In the lower mineral matrix zone, SOM inputs from the vegetation zone are controlled primarily by mineral phase and chemical interactions, resulting in more favourable conditions for SOM persistence. Vegetation zone boundary conditions vary spatially at landscape scales (vegetation cover) and temporally at decadal scales (climate). Mineral matrix zone boundary conditions vary spatially at landscape scales (geology, topography) but change only slowly. The thicknesses of the two zones and their transport connectivity are dynamic and affected by plant cover, land use practices, climate and feedbacks from current SOM stock in each layer. Using this framework, we identify several areas where greater knowledge is needed to advance the emerging paradigm of SOM dynamics—improved representation of plant‐derived carbon inputs, contributions of soil biota to SOM storage and effect of dynamic soil structure on SOM storage—and how this can be combined with robust and efficient soil monitoring.     

Experimental warming transforms multiple predator effects in a grassland food web

This experimental study tests new theory for multiple predator effects on communities by using warming to alter predator habitat use and hence direct and indirect interactions in a grassland food web containing two dominant spider predator species, a dominant grasshopper herbivore and grass and herb plants. Experimental warming further offers insight into how climate change might alter direct and indirect effects. Under ambient environmental conditions, spiders used habitat in spatially complementary locations. Consistent with predictions, the multiple predator effect on grasshoppers and on plants was the average of the individual predator effects. Warming strengthened the single predator effects. It also caused the spider species to overlap lower in the vegetation canopy. Consistent with predictions, the system was transformed into an intraguild predation system with the consequent extinction of one spider species. The results portend climate caused loss of predator diversity with important consequences for food web structure and function.     

Spatial decomposition of predation risk using resource selection functions: an example in a wolf–elk predator–prey system

Predation is a fundamental ecological and evolutionary process that varies in space, and the avoidance of predation risk is of central importance in foraging theory. While there has been a recent growth of approaches to spatially model predation risk, these approaches lack an adequate mechanistic framework that can be applied to real landscapes. In this paper we show how predation risk can be decomposed into encounter and attack stages, and modeled spatially using resource selection functions (RSF) and resource selection probability functions (RSPF). We use this approach to compare the effects of landscape attributes on the relative probability of encounter, the conditional probability of death given encounter, and overall wolf and elk resource selection to test whether predation risk is simply equivalent to location of the predator. We then combine the probability of encounter and conditional probability of death into a spatially explicit function of predation risk following Lima and Dill's reformulation of Holling's functional response. We illustrate this approach in a wolf–elk system in and adjacent to Banff National Park, Alberta, Canada. In this system we found that the odds of elk being encountered by wolves was 1.3 times higher in pine forest and 4.1 times less in grasslands than other habitats. The relative odds of being killed in pine forests, given an encounter, increased by 1.2. Other habitats, such as grasslands, afforded elk reduced odds (4.1 times less) of being encountered and subsequently killed (1.4 times less) by wolves. Our approach illustrates that predation risk is not necessarily equivalent to just where predators are found. We show that landscape attributes can render prey more or less susceptible to predation and effects of landscape features can differ between the encounter and attack stages of predation. We conclude by suggesting applications of our approach to model predator–prey dynamics using spatial predation risk functions in theoretical and applied settings.     

Multi-scale species density model for conserving an endangered songbird

Habitat modeling across a landscape that has gradients of habitat conditions requires potential predictor data that can be quantified at biologically relevant scales. We used remotely sensed data to develop a multi-scale density model in 2018 for the golden-cheeked warbler (Setophaga chrysoparia; warbler), a species that breeds in Ashe juniper (Juniperus ashei)-oak (Quercus spp.) woodlands in central Texas, USA. We first classified Ashe juniper and broadleaf tree cover at a 1-m resolution and used this to map potential habitat across the warbler's >67,000-km² breeding range. We then designed a survey for estimating warbler density based on hierarchical distance sampling. We used stratified random sampling to survey for male warblers at 1,804 points across the continuum of tree canopy cover and composition and detected 810 warblers during our surveys. We developed a suite of potential predictor variables for modeling warbler density that reflected vegetation, topography, climate, and anthropogenic land use conditions across the breeding range and developed these at 3 scales representing the territory, site, and landscape. We modeled warbler density and used the best fit model to produce a spatially explicit estimate. Predicted warbler density was influenced by tree canopy cover and canopy height at the territory scale (100-m radius); tree canopy cover, percent of the canopy comprised of juniper, and an interaction between canopy cover and compound topographic index at the site scale (1-km radius); and annual temperature range at the landscape scale (5-km radius). We estimated a population size of 217,444 male warblers (95% CI = 153,917–311,965) and >3,000 males in each recovery unit. After controlling for the duration of point count surveys, our estimate of population size was similar to that reported from the only previous breeding range survey conducted in 2008–2009. Our model results indicated that management activities to increase warbler density should promote woodlands with high tree canopy cover, approximately 60–80% Ashe juniper composition, and tree heights >3 m. In contrast to a patch-based approach, our treatment of habitat variables as continuous helped to credibly map the warbler distribution across areas with broad transitions from woodlands to shrublands. By measuring these predictor variables at biologically relevant scales, we allowed the warbler survey data to define habitat relationships instead of using anthropogenically defined habitat patches. Outcomes from our study show the benefits of developing spatial products tailored to individual species of interest for conservation and management decisions.     

Habitat selection of breeding riparian birds in an urban environment: untangling the relative importance of biophysical elements and spatial scale

Aim Urbanization is a leading threat to global biodiversity, yet little is known about how the spatial arrangement and composition of biophysical elements – buildings and vegetation – within a metropolitan area influence habitat selection. Here, we ask: what is the relative importance of the structure and composition of these elements on bird species across multiple spatial scales? Location The temperate metropolitan area of Cincinnati, Ohio, USA. Methods We surveyed breeding birds on 71 plots along an urban gradient. We modelled relative density for 48 bird species in relation to local woody vegetation composition and structure and to tree cover, grass cover and building density within 50–1000 m of each plot. We used an information‐theoretic approach to compare models and variables. Results At the proximate scale, native tree and understory stem frequency were the most important vegetation variables explaining bird distributions. Species’ responses to landscape biophysical features and spatial scales varied. Most native species responded positively to vegetation measures and negatively to building density. Models combining both local vegetation and landscape information represented best or competitive models for the majority of species, while models containing only local vegetation characteristics were rarely competitive. Smaller spatial scales (≤ 500 m) were most important for 36 species, and eight species had best models at larger scales (> 500 m); however, several species had competitive models across multiple scales. Main conclusions Habitat selection by birds within the urban matrix is the result of a combination of factors operating at both proximate and broader spatial scales. Efforts to manage and design urban areas to benefit native birds require both fine‐scale (e.g., individual landowners and landscape design) and larger landscape actions (e.g., regional comprehensive planning).     

Predator–prey interactions in a ladybeetle–aphid system depend on spatial scale

The outcome of species interactions may manifest differently at different spatial scales; therefore, our interpretation of observed interactions will depend on the scale at which observations are made. For example, in ladybeetle–aphid systems, the results from small‐scale cage experiments usually cannot be extrapolated to landscape‐scale field observations. To understand how ladybeetle–aphid interactions change across spatial scales, we evaluated predator–prey interactions in an experimental system. The experimental habitat consisted of 81 potted plants and was manipulated to facilitate analysis across four spatial scales. We also simulated a spatially explicit metacommunity model parallel to the experiment. In the experiment, we found that the negative effect of ladybeetles on aphids decreased with increasing spatial scales. This pattern can be explained by ladybeetles strongly suppressing aphids at small scales, but not colonizing distant patches fast enough to suppress aphids at larger scales. In the experiment, the positive effects of aphids on ladybeetles were strongest at three‐plant scale. In a model scenario where predators did not have demographic dynamics, we found, consistent with the experiment, that both the effects of ladybeetles on aphids and the effects of aphids on ladybeetles decreased with increasing spatial scales. These patterns suggest that dispersal was the primary cause of ladybeetle population dynamics in our experiment: aphids increased ladybeetle numbers at smaller scales because ladybeetles stayed in a patch longer and performed area‐restricted searches after encountering aphids; these behaviors did not affect ladybeetle numbers at larger spatial scales. The parallel experimental and model results illustrate how predator–prey interactions can change across spatial scales, suggesting that our interpretation of observed predator–prey dynamics would differ if observations were made at different scales. This study demonstrates how studying ecological interactions at a range of scales can help link the results of small‐scale ecological experiments to landscape‐scale ecological problems.     

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range‐wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back‐cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long‐term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long‐term demographic decline and range contraction for a species of high‐conservation concern. Range‐wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal‐limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management.     

A multi-scale approach for identifying conservation needs of two threatened sympatric steppe birds

Habitat selection is an inherently scale-sensitive process in which detected selection patterns frequently depend on the scale of analysis employed. We used a multi-scale modelling approach to identify how the distributions of two sympatric birds are shaped by differential selection at the landscape, land use and microhabitat scales and by human infrastructures as possible sources of disturbance. We studied two threatened steppe birds, the pin-tailed sandgrouse (PTS) and black-bellied sandgrouse (BBS) in central Spain. Land use gradients explained most of the variation in PTS and BBS occurrence, but there was cross-scale interdependence between the lower (microhabitat) and upper (landscape) spatial scales for the PTS. Synergies between the three scales highlighted the importance of integrating habitat scales in a single modelling framework. The process of habitat selection was also modulated by human disturbance. Both species selected ploughs of large size distant from houses, tracks and other infrastructures, although BBS exhibited broader habitat tolerance than the PTS, and was more sensitive to human disturbance. At microhabitat scale, PTS selected ploughs with greater green vegetation cover and insect abundance and fallows with lower dry vegetation cover and height but greater stone cover. This might reflect a trade-off between camouflage (vegetation and stone cover for concealment) and visibility for predator detection and escape. Ploughs and fallows should be maintained by means of traditional 2-year rotations and low management during the breeding season. Ongoing urbanization trends and infrastructure development inside protected areas should be limited. Multi-scale models were key to identify scale-specific factors that determine sandgrouse habitat preferences and conservation requirements at appropriate levels, and are recommended to better guide regional and local conservation efforts of threatened species.     

Behavioral responses of male elk to hunting risk

Prey respond to predation risk with a range of behavioral tactics that can vary based on space use and hunting mode of the predator. Unlike other predators, human hunters are often more spatially and temporally restricted, which creates a period of short-duration, high-intensity predation risk for prey. Consequently, identifying the roles different hunting modes (i.e., archery and rifle), hunts for targeted and non-targeted species, and landscape features play in altering spatial and temporal responses of prey to predation risk by humans is important for effective management of harvested populations. From 2009 to 2016, we used a large-scale experiment including 50 animal-years of location data from 38 unique male elk (Cervus canadensis) to quantify changes in movement and resource selection in response to hunters during 3 separate 5-day controlled hunts for antlered males (elk archery, deer [Odocoileus spp.] rifle, and elk rifle) at the Starkey Experimental Forest and Range in northeast Oregon, USA. We evaluated competing hypotheses regarding elk responses to varying levels of prey risk posed by the different hunt types. We predicted that the strength of elk behavioral responses would increase with perceived hunter lethality (i.e., weak response to elk archery but similar response to elk and deer rifle hunts) and that prey response would be closely associated with hunter activity within the diel cycle (greater during diurnal than nocturnal hours) and across hunting seasons. Elk responses were strongest during diurnal hours when hunters were active on the landscape and were generally more pronounced during both rifle hunts than during the archery hunt (supporting our perceived lethality hypothesis). Male elk avoided open roads across all periods except during nocturnal hours of the breeding season and alternated between avoidance of areas with high canopy cover during nocturnal hours and selection during diurnal hours. In combination these patterns led to distinct distributional changes of male elk from pre-hunt to hunt periods. Patterns of male elk selection highlight the importance of managing for heterogeneous landscapes to meet a variety of habitat, harvest, hunter satisfaction, and escapement objectives.     

How does forest landscape structure explain tree species richness in a Mediterranean context?

Although the strong relationship between vegetation and climatic factors is widely accepted, other landscape composition and configuration characteristics could be significantly related with vegetation diversity patterns at different scales. Variation partitioning was conducted in order to analyse to what degree forest landscape structure, compared to other spatial and environmental factors, explained forest tree species richness in 278 UTM 10 × 10 km cells in the Mediterranean region of Catalonia (NE Spain). Tree species richness variation was decomposed through linear regression into three groups of explanatory variables: forest landscape (composition and configuration), environmental (topography and climate) and spatial variables. Additionally, the forest landscape characteristics which significantly contributed to explain richness variation were identified through a multiple regression model. About 60% of tree species richness variation was explained by the whole set of variables, while their joint effects explained nearly 28%. Forest landscape variables were those with a greater pure explanatory power for tree species richness (about 15% of total variation), much larger than the pure effect of environmental or spatial variables (about 2% each). Forest canopy cover, forest area and land cover diversity were the most significant composition variables in the regression model. Landscape configuration metrics had a minor effect on forest tree species richness, with the exception of some shape complexity indices, as indicators of land use intensity and edge effects. Our results highlight the importance of considering the forest landscape structure in order to understand the distribution of vegetation diversity in strongly human-modified regions like the Mediterranean.     

Snow and land use alter pheasant survival in South Dakota

We examined survival of ring-necked pheasants (Phasianus colchicus) occupying fragmented landscapes within the Prairie Pothole Region in South Dakota, USA, where severe winter weather events historically limited pheasant population growth through increased mortality. Recent landscape transformations could further affect overwinter adult female survival by reducing critical winter resources. Assessing the influence of time-dependent landscape features on survival at small focal scales may reveal spatially important relationships. We captured and monitored 321 adult female pheasants from 2017–2019 and recorded 110 pheasant winter mortalities. Female pheasant winter survival was 0.66 (85% CI = 0.62–0.70) and was inversely correlated to snow depth. We generated Cox proportional hazard models to determine risk of mortality associated with landscape features. Pheasants using landscapes other than perennial cover (i.e., emergent wetland, tall vegetation, woody, food plots) experienced a 2.22 times greater risk of raptor predation than pheasants using perennial cover. Additionally, pheasants experienced a 58% reduced risk of weather mortality when using emergent wetlands. We analyzed resource selection ratios to understand how perceived landscape risks at the population level scaled down to land use selection at the individual level. Female pheasants selected for emergent wetlands, showed no selection for woody features, and avoided tall vegetation (non-aquatic herbaceous vegetation >75 cm) during severe winters. Pheasants would greatly benefit from conservation of emergent wetlands and integrating perennial cover into harvested cropland.     

Spatial heterogeneity and irreversible vegetation change in semiarid grazing systems

Recent theoretical studies have shown that spatial redistribution of surface water may explain the occurrence of patterns of alternating vegetated and degraded patches in semiarid grasslands. These results implied, however, that spatial redistribution processes cannot explain the collapse of production on coarser scales observed in these systems. We present a spatially explicit vegetation model to investigate possible mechanisms explaining irreversible vegetation collapse on coarse spatial scales. The model results indicate that the dynamics of vegetation on coarse scales are determined by the interaction of two spatial feedback processes. Loss of plant cover in a certain area results in increased availability of water in remaining vegetated patches through run-on of surface water, promoting within-patch plant production. Hence, spatial redistribution of surface water creates negative feedback between reduced plant cover and increased plant growth in remaining vegetation. Reduced plant cover, however, results in focusing of herbivore grazing in the remaining vegetation. Hence, redistribution of herbivores creates positive feedback between reduced plant cover and increased losses due to grazing in remaining vegetated patches, leading to collapse of the entire vegetation. This may explain irreversible vegetation shifts in semiarid grasslands on coarse spatial scales.     

Using neutral landscapes to identify patterns of aggregation across resource points

Many organisms are aggregated within resource patches and aggregated spatially across landscapes with multiple resources. Such patchy distributions underpin models of population regulation and species coexistence, so ecologists require methods to analyse spatially‐explicit data of resource distribution and use. I describe a method for analysing maps of resources and testing hypotheses about how resource distribution influences the distribution of organisms, where resource patches can be described as points in a landscape and the number of organisms on each resource point is known. Using a mark correlation function and the linearised form of Ripley's K‐function, this version of marked point pattern analysis can characterise and test hypotheses about the spatial distribution of organisms (marks) on resource patches (points). The method extends a version of point pattern analysis that has wide ecological applicability, it can describe patterns over a range of scales, and can detect mixed patterns. Statistically, Monte Carlo permutations are used to estimate the difference between the observed and expected values of the mark correlation function. Hypothesis testing employs a flexible neutral landscape approach in which spatial characteristics of point patterns are preserved to some extent, and marks are randomised across points. I describe the steps required to identify the appropriate neutral landscape and apply the analysis. Simulated data sets illustrate how the choice of neutral landscape can influence ecological interpretations, and how this spatially‐explicit method and traditional dispersion indices can yield different interpretations. Interpretations may be general or context‐sensitive, depending on information available about the underlying point pattern and the neutral landscape. An empirical example of caterpillars exploiting food plants illustrates how this technique might be used to test hypotheses about adult oviposition and larval dispersal. This approach can increase the value of survey data, by making it possible to quantify the distribution of resource points in the landscape and the pattern of resource use by species.     

The nest predator community of grassland birds responds to agroecosystem habitat at multiple scales

Nest predation is the leading cause of reproductive failure for grassland birds of conservation concern. Understanding variation in nest predation rates is complicated by the diverse assemblage of species known to prey on nests. As part of a long‐term study of grassland bird ecology, we monitored populations of predators known to prey on grassland bird nests. We used information theoretic approach to examine the predator community's association with habitat at multiple scales, including local vegetation structure of grassland patches, spatial attributes of grassland patches (size and shape), and landscape composition surrounding grassland patches (land cover within 400 and 1600 m). Our results confirmed that nest predators respond to habitat at multiple scales and different predator species respond to habitat in different ways. The most informative habitat models we selected included variability in local vegetation (CV in the density of forbs), local patch (area and edge‐to‐interior ratio), and landscape within a 1600 m buffer around grasslands (percent of land covered by human structures and development). As a separate question, we asked if models that incorporated information from multiple scales simultaneously might improve the ability to explain variation in the predator community. Multi‐ scale models were not consistently superior to models derived from variables focused at a single spatial scale. Our results suggest that minimizing human development on and surrounding conservation land and the management of the vegetation structure on grassland fragments both may benefit grassland birds by decreasing the risk of nest predation.     

The effect of landscape pattern on Mediterranean vegetation dynamics: A modelling approach using functional types

Abstract. In the framework of land use changes in the Mediterranean area, I asked to what extent different landscape structures might determine long‐term dynamics in Mediterranean ecosystems. To answer this question, a spatially explicit model was developed (the Melca model), incorporating two functional types of woody species dominant in Mediterranean ecosystems: a resprouter (R) and a non‐resprouter fire‐recruiter (seeders, S). The model was used as a tool for generating hypotheses on the possible consequences of different landscape scenarios. Thus, five different hierarchically structured random landscapes were generated, all having the same cover for the two functional types but different landscape structure (ranging from highly heterogeneous to homogeneous landscapes). After a 100‐yr simulation, plant cover and spatial pattern had changed and the changes were different for the different initial spatial configurations, suggesting that long‐term vegetation dynamics is spatially dependent (the resultant dynamics are sensitive to the initial spatial structure). In the landscapes where R‐type species had a low number of large patches and S‐species had a large number of small patches, the number of R‐patches increased and their size decreased, while the number of S‐patches decreased. In these cases, the final cover of the two types changed little from the initial cover. Landscapes with a large number of small R‐patches interspersed with S‐patches had a decrease in the number of R‐patches, an increase in the number of S‐patches and a decrease in the size of S‐patches. In these landscapes, final cover was significantly changed, increasing in R‐type and decreasing in S‐type species. These results suggest that low spatial autocorrelation (low aggregation) favours R‐type species. Implications for land management are also discussed.