Simple Landscape Research Articles

Effects of animal movement strategies and costs on the distribution of active subsidies across simple landscapes

Cross-ecosystem transfer of resources (spatial subsidies) can greatly impact recipient ecosystems. Many subsidies are actively moved by animals, which regularly transfer nutrients within and among ecosystems. Researchers have yet to integrate knowledge of animal movement and spatial subsidies to enhance predictions of subsidy spatial distribution and ecosystem effects. To examine this, we implemented a spatially explicit simulation model of animals that switch habitats due to behavioral or ontogenetic shifts. We explored how movement strategy (correlated random walk) and patterns of mortality risk affected the spatial distribution of living (consumer subsidies) and dead individuals (nutrient/energy subsidies). We ran models varying the correlation in a correlated random walk and explored four patterns of mortality risk: uniform mortality, higher mortality in the edge at the habitat boundary, a decreasing gradient and an increasing gradient of mortality risk as individuals move away from the boundary. For each scenario, we calculated the maximum extent, the distance of peak density and the peak density (a measure of maximum impact of the subsidy) of living and dead individuals. As expected, subsidy impact declined as deposition distance increased. Straighter movements resulted in deposition farther beyond the local habitat boundary with lower impact than more sinuous movements. Similarly, consumer subsidies were deposited farther from the boundary with lower impact than nutrient/energy subsidies. Patterns of mortality risk also affected the impact and deposition distance but to a lesser degree. Uniform mortality and increasing gradients of mortality risk deposited subsidies farther from the habitat boundary than did edge mortality and decreasing gradients. Edge mortality scenarios also resulted in higher densities of subsidies than other patterns of mortality risk. Our simulations represent a very simple, first attempt at using movement ecology to predict the spatial distribution and impacts of subsidies. More complex models and empirical tests are necessary to further assess movement ecology's utility for predicting subsidies.

Ca2+ binding enhanced mechanical stability of an archaeal crystallin.

Structural topology plays an important role in protein mechanical stability. Proteins with β-sandwich topology consisting of Greek key structural motifs, for example, I27 of muscle titin and 10FNIII of fibronectin, are mechanically resistant as shown by single-molecule force spectroscopy (SMFS). In proteins with β-sandwich topology, if the terminal strands are directly connected by backbone H-bonding then this geometry can serve as a “mechanical clamp”. Proteins with this geometry are shown to have very high unfolding forces. Here, we set out to explore the mechanical properties of a protein, M-crystallin, which belongs to β-sandwich topology consisting of Greek key motifs but its overall structure lacks the “mechanical clamp” geometry at the termini. M-crystallin is a Ca2+ binding protein from Methanosarcina acetivorans that is evolutionarily related to the vertebrate eye lens β and γ-crystallins. We constructed an octamer of crystallin, (M-crystallin)8, and using SMFS, we show that M-crystallin unfolds in a two-state manner with an unfolding force ∼90 pN (at a pulling speed of 1000 nm/sec), which is much lower than that of I27. Our study highlights that the β-sandwich topology proteins with a different strand-connectivity than that of I27 and 10FNIII, as well as lacking “mechanical clamp” geometry, can be mechanically resistant. Furthermore, Ca2+ binding not only stabilizes M-crystallin by 11.4 kcal/mol but also increases its unfolding force by ∼35 pN at the same pulling speed. The differences in the mechanical properties of apo and holo M-crystallins are further characterized using pulling speed dependent measurements and they show that Ca2+ binding reduces the unfolding potential width from 0.55 nm to 0.38 nm. These results are explained using a simple two-state unfolding energy landscape.

Rolling Pampas agroecosystem: which landscape attributes are relevant for determining bird distributions?

Agricultural intensification is among the main factors affecting biodiversity. The Rolling Pampas of Argentina have undergone through a process of landscape transformation and agricultural intensification that altered avian diversity patterns. Grassland area loss is argued to be the main reason for grassland bird species declines, but there is a lack of studies that compare cropland vs. pastures including other landscape features as determinants of species richness and distribution. Also, it is needed to understand how these relations are modified at different spatial scales. In this study, we explored how species are associated to different landscape attributes and elements like land use, roadside vegetation, trees, homesteads, and water bodies. Our aim was to explore how bird species are associated to the new elements of the Pampas agroecosystem at different spatial scales to reveal which are important for avian management. We ran field surveys covering a range of land use and landscape complexity, defined by the variety of component features. We performed canonical correspondence and diversity partition analyses to determine the association of species with land use, landscape complexity, and particular anthropogenic elements. Our results show that land use type is an important driver of bird species distributions, but it is also controlled by the presence of trees, houses, and water bodies that provide nesting and food resources. Simple landscapes have higher species turnover rates (beta diversity) than complex ones with similar gamma diversity, demonstrating that the effect of landscape simplification on bird diversity differs across spatial scales, leading to different possible management and conservation strategies. New approaches are needed to manage agroecosystems for avian conservation. We need to take pragmatic approaches, and in highly disturbed ecosystems, anthropic elements have to be included as constituent parts of the system.

BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure

Summary A notable increase in failure of managed European honeybee Apis mellifera L. colonies has been reported in various regions in recent years. Although the underlying causes remain unclear, it is likely that a combination of stressors act together, particularly varroa mites and other pathogens, forage availability and potentially pesticides. It is experimentally challenging to address causality at the colony scale when multiple factors interact. In silico experiments offer a fast and cost‐effective way to begin to address these challenges and inform experiments. However, none of the published bee models combine colony dynamics with foraging patterns and varroa dynamics.We have developed a honeybee model, BEEHAVE, which integrates colony dynamics, population dynamics of the varroa mite, epidemiology of varroa‐transmitted viruses and allows foragers in an agent‐based foraging model to collect food from a representation of a spatially explicit landscape.We describe the model, which is freely available online (www.beehave-model.net). Extensive sensitivity analyses and tests illustrate the model's robustness and realism. Simulation experiments with various combinations of stressors demonstrate, in simplified landscape settings, the model's potential: predicting colony dynamics and potential losses with and without varroa mites under different foraging conditions and under pesticide application. We also show how mitigation measures can be tested. Synthesis and applications. BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics.

Plant diversity in Mediterranean cereal fields: Unraveling the effect of landscape complexity on rare arable plants

Landscape complexity is thought to increase plant diversity in Mediterranean dryland cereal fields, although this assumption has not been tested specifically for rare arable plants (RAP). Standardized landscape metrics may help elucidate efforts to enhance RAP conservation. Our paper evaluates the impact of the surrounding landscape on the plant diversity and species composition for both total species and rare arable plants (RAP) at three contrasted field positions (boundary – first metre of non-cultivated habitat surrounding a field-, edge – first metre of cultivated habitat adjacent to the boundary- and centre) in 90 conventional cereal fields in 45 landscapes (2 fields per landscape) over three regions in the NE Iberian Peninsula (15 landscapes per region). Total species richness (S) and Shannon diversity (H′) were partitioned into α- and β-components. β-Components accounted the maximum contribution to the total diversity. Sαlandscape – species richness within-landscape and H′αlandscape – Shannon diversity within-landscape of total species and Sαlandscape of RAP were higher in structurally complex landscapes than in simple ones. The positive effect of landscape complexity on the αlandscape diversity was highest at the boundary for total species but at the edge for RAP. Two subsets of RAP, G1 and G2, were identified according to their response to landscape metrics gradients. G1 and G2 were assembled in complex and simplified landscapes, respectively. Landscape metrics explained the highest variation in species composition at the boundary and the edge for total species and exclusively at the edge for RAP. Moreover, the variation in species composition explained by landscape metrics was higher for RAP than for total species. Thus, RAP assemblages in arable fields are greatly influenced by processes operating at the landscape scale which may filter plant species. Our study provided a formal framework to help policy makers identify landscape configurations that most benefit plant conservation policies. As a depleted species pool may prevent the re-assembly of RAP, agri-environmental schemes targeting landscapes with useful structural elements supporting diversity may increase populations of RAP. Low-input farming practices at the edge of the arable fields in complex landscapes are expected to be the best cost-effective methods for enhancing RAP.

Association between patterns in agricultural landscapes and the abundance of wheat aphids and their natural enemies

Effect of different landscape patterns on insect distribution and diversity was determined by studying wheat fields in complex and simple agricultural landscapes. We studied the influence of simple and complex agricultural landscapes on wheat aphids and their natural enemies in terms of the time of migration, abundance, population growth rate of the aphids and parasitoid abundance. The results indicate that the diversity of natural enemies is greater in the complex agricultural landscape and the effect of natural enemies on the abundance of wheat aphids was greater in the complex non-crop habitat. Wheat aphid hyperparasitoid populations differed in different agricultural landscapes with a greater number of parasites in complex agricultural landscapes. Resident times of predatory natural enemies differ in simple and complex agricultural landscapes. The number and types of predatory natural enemies are higher in complex than simple agricultural landscapes. Aphid population growth rates and the maximum population densities of wheat aphids differed significantly in simple and complex landscapes. Maximum population densities of different wheat aphids were very different in simple and complex landscape structures. The population growth rates and maximum population densities of the different predatory natural enemies and hyperparasitoids differed greatly.

Species composition and diversity of parasitoids and hyper-parasitoids in different wheat agro-farming systems.

Insect communities depend on both their local environment and features of the surrounding habitats. Diverse plant communities may enhance the abundance and species diversity of local natural enemies, which is possible due to a higher abundance and species diversity in complex landscapes. This hypothesis was tested using cereal aphid parasitoids and hyper-parasitoids by comparing 18 spring wheat fields, Triticum aestivum L. (Poales: Poaceae), in structurally-complex landscapes (dominated by semi-natural habitat, > 50%, n = 9) and structurally-simple landscapes dominated by arable landscape (dominated by crop land, > 80%, n = 9). The agricultural landscape structure had significant effects on the number of parasitoid and hyper-parasitoid species, as 26 species (17 parasitoids and 9 hyper-parasitoids) were found in the complex landscapes and 21 were found in the simple landscapes (14 parasitoids and 7 hyper-parasitoids). Twenty-one species occurred in both landscape types, including 14 parasitoids and 7 hyper-parasitoids species. The species diversity of parasitoids and hyper-parasitoids were significantly different between the complex and simple landscapes. In addition, arable fields in structurally-simple agricultural landscapes with little semi-natural habitats could support a lower diversity of cereal aphid parasitoids and hyper-parasitoids than structurally-complex landscapes. These findings suggest that cereal aphid parasitoids and hyper-parasitoids need to find necessary resources in structurally-complex landscapes, and generalizations are made concerning the relationship between landscape composition and biodiversity in agricultural landscapes. Overall, abundance, species richness, and species diversity increased with increasing plant diversity and landscape complexity in spring wheat fields and increasing amounts of semi-natural habitats in the surrounding landscape.

Management Intensity and Topography Determined Plant Diversity in Vineyards

Vineyards are amongst the most intensive forms of agriculture often resulting in simplified landscapes where semi-natural vegetation is restricted to small scattered patches. However, a tendency toward a more sustainable management is stimulating research on biodiversity in these poorly investigated agro-ecosystems. The main aim of this study was to test the effect on plant diversity of management intensity and topography in vineyards located in a homogenous intensive hilly landscape. Specifically, this study evaluated the role of slope, mowing and herbicide treatments frequency, and nitrogen supply in shaping plant diversity and composition of life-history traits. The study was carried out in 25 vineyards located in the area of the Conegliano-Valdobbiadene DOCG (Veneto, NE Italy). In each vineyard, 10 plots were placed and the abundance of all vascular plants was recorded in each plot. Linear multiple regression was used to test the effect of management and topography on plant diversity. Management intensity and topography were both relevant drivers of plant species diversity patterns in our vineyards. The two most important factors were slope and mowing frequency that respectively yielded positive and negative effects on plant diversity. A significant interaction between these two factors was also demonstrated, warning against the detrimental effects of increasing mowing intensity on steep slope where plant communities are more diverse. The response of plant communities to mowing frequency is mediated by a process of selection of resistant growth forms, such in the case of rosulate and reptant species. The other two management-related factors tested in this study, number of herbicide treatments and N fertilization, were less influential. In general, our study corroborates the idea that some simple changes in farming activities, which are compatible with grape production, should be encouraged for improving the natural and cultural value of the landscape by maintaining and improving wild plant diversity.

Agricultural landscape simplification does not consistently drive insecticide use

The increase in agricultural production over the past 40 y has greatly altered land-use patterns, often resulting in simplified landscapes composed of large swaths of monocultures separated by small fragments of natural lands. These simplified landscapes may be more susceptible to insect pest pressure because of the loss of natural enemies and the increased size and connectivity of crop resources, and a recent analysis from a single year (2007) suggests this increased susceptibility results in increased insecticide use. I broaden the temporal analysis of this connection between landscape simplification and insecticide use by examining cross-sectional and panel data models from multiple decades (US Department of Agriculture Census of Agriculture years 2007, 2002, 1997, 1992, 1987) for seven Midwestern states composed of over 560 counties. I find that although the proportion of county in cropland--my metric for landscape simplification--was positively correlated with insecticide use in 2007, this relationship is absent or reversed in prior census years and when all years are analyzed together. This broader temporal perspective suggests that landscape simplification has inconsistent effects on insecticide use and that multiyear studies will be key to unlocking the true drivers of variation in insecticide application.

Differentiating simple and composite tectonic landscapes using numerical fault slip modeling with an example from the south central Alborz Mountains, Iran

The tectonically driven growth of mountains reflects the characteristics of the underlying fault systems and the applied tectonic forces. Over time, fault networks might be relatively static, but stress conditions could change and result in variations in fault slip orientation. Such a tectonic landscape would transition from a “simple” to a “composite” state: the topography of simple landscapes is correlated with a single set of tectonic boundary conditions, while composite landscapes contain inherited topography due to earlier deformation under different boundary conditions. We use fault interaction modeling to compare vertical displacement fields with topographic metrics to differentiate the two types of landscapes. By successively rotating the axis of maximum horizontal stress, we produce a suite of vertical displacement fields for comparison with real landscapes. We apply this model to a transpressional duplex in the south central Alborz Mountains of Iran, where NW oriented compression was superseded by neotectonic NE compression. The consistency between the modeled displacement field and real landforms indicates that the duplex topography is mostly compatible with the modern boundary conditions, but might include a small remnant from the earlier deformation phase. Our approach is applicable for various tectonic settings and represents an approach to identify the changing boundary conditions that produce composite landscapes. It may be particularly useful for identifying changes that occurred in regions where river profiles may no longer record a signal of the change or where the spatial pattern of uplift is complex.

Bird diversity relates to agri-environment schemes at local and landscape level in intensive farmland

In Europe, more than 20 billion Euros have been paid to farmers for agri-environment schemes (AESs) during the last half decade to counteract negative effects of farming on the environment. In Sweden alone 0.4 billion Euros are paid to farmers for AESs every year, but large-scale analyses of the relationship between AESs and biodiversity are scarce in northern Europe. We surveyed farmland birds at over 600 sites in non-crop habitats in 37 arable dominated landscapes (each 25km2) in southern Sweden and investigated if bird species richness and abundance were related to the amount of agricultural land receiving subsidies for five common AESs. Abundance and species richness of three subsets of farmland birds were positively associated with AES for management of permanent pastures, and bird abundance was associated to habitat elements managed for the maintenance of nature and cultural values (e.g. old buildings, infield non-crop islands, stone walls and ditches). Farmland bird abundance was also positively associated with the amount of grasslands (leys and especially pastures) and set-aside without subsidies, whereas neither richness nor abundance was positively associated with the amount of organic fields at the local scale (i.e. within a 250m radius). However, bird diversity was related to increased area of organic fields at the landscape scale (i.e. 25km2); with a positive relationship in the most simplified landscapes but a negative relationship in more complex landscapes (i.e. with less arable land and more woodlands). Our results show that AESs are targeting habitats and habitat elements of high farmland bird diversity with the possible exception of organic farming in less simplified landscapes. Future studies investigating effects of AES management need to collect longitudinal before–after data on the change of biodiversity and need to investigate the possible landscape-dependent outcomes of specific management tied to AESs.

Environmental factors driving the effectiveness of European agri‐environmental measures in mitigating pollinator loss – a meta‐analysis

In Europe, agri-environmental schemes (AES) have been introduced in response to concerns about farmland biodiversity declines. Yet, as AES have delivered variable results, a better understanding of what determines their success or failure is urgently needed. Focusing on pollinating insects, we quantitatively reviewed how environmental factors affect the effectiveness of AES. Our results suggest that the ecological contrast in floral resources created by schemes drives the response of pollinators to AES but that this response is moderated by landscape context and farmland type, with more positive responses in croplands (vs. grasslands) located in simple (vs. cleared or complex) landscapes. These findings inform us how to promote pollinators and associated pollination services in species-poor landscapes. They do not, however, present viable strategies to mitigate loss of threatened or endangered species. This indicates that the objectives and design of AES should distinguish more clearly between biodiversity conservation and delivery of ecosystem services.

Community variability in aphid parasitoids versus predators in response to agricultural intensification

Abstract Agricultural intensification (AI) is a great threat to biodiversity and its negative effects on species richness of different communities have been repeatedly shown. The effects of AI on community composition and variability, however, are important for assessing the predictability of community responses, but have rarely been studied simultaneously and across different taxonomic groups. In this study, we focused on parasitoids (primary and secondary) and predators (hoverflies and carabid beetles) of aphids in winter wheat fields with contrasting AI regimes (low AI, i.e. organic fields in structurally complex landscapes vs. high AI, i.e. conventional fields in structurally simple landscapes). We found divergence in species composition of more specialised, low‐dispersing primary and secondary parasitoids within high AI fields, probably due to the disruption of the exchanges of species between local populations in structurally simple landscapes. In contrast, species composition of less specialised, highly dispersing carabid beetles and hoverflies converged in fields with high AI, where they were characterised by the dominance of a single, vagile species adapted to high land‐use conditions. Furthermore, temporal community shifts were only pronounced in primary parasitoids and hoverflies, with higher temporal changes in fields with high AI in primary parasitoids. Collectively, our results illustrate that environmental homogenisation due to AI does not necessarily induce spatio‐temporal homogenisation of communities, but rather can have contrasting effects on more specialised, low‐dispersive parasitoids versus more generalised, high‐dispersive predators, thereby demonstrating great differences in the predictability of responses to AI among aphid natural enemies.

Natural enemy interactions constrain pest control in complex agricultural landscapes

Biological control of pests by natural enemies is a major ecosystem service delivered to agriculture worldwide. Quantifying and predicting its effectiveness at large spatial scales is critical for increased sustainability of agricultural production. Landscape complexity is known to benefit natural enemies, but its effects on interactions between natural enemies and the consequences for crop damage and yield are unclear. Here, we show that pest control at the landscape scale is driven by differences in natural enemy interactions across landscapes, rather than by the effectiveness of individual natural enemy guilds. In a field exclusion experiment, pest control by flying insect enemies increased with landscape complexity. However, so did antagonistic interactions between flying insects and birds, which were neutral in simple landscapes and increasingly negative in complex landscapes. Negative natural enemy interactions thus constrained pest control in complex landscapes. These results show that, by altering natural enemy interactions, landscape complexity can provide ecosystem services as well as disservices. Careful handling of the tradeoffs among multiple ecosystem services, biodiversity, and societal concerns is thus crucial and depends on our ability to predict the functional consequences of landscape-scale changes in trophic interactions.

Landscape composition, connectivity and fragment size drive effects of grassland fragmentation on insect communities

Summary Calcareous grasslands are among the most species‐rich habitats in Europe, but are increasingly threatened due to abandonment and fragmentation. Little is known about how the surrounding landscape influences fragmentation effects. Here, we focus on the interaction between habitat fragmentation and landscape composition on leafhoppers, a highly diverse group of insects, including many species that are likely to be vulnerable to changes in their environment. We selected 14 small and 14 large fragments of calcareous grassland in Central Germany, differing in isolation from other calcareous grasslands and in composition of the surrounding landscape. Leafhoppers, sampled by sweep netting, were either specialists that depended on calcareous grasslands or generalists that could use the landscape matrix, but still required low‐productivity habitats. Increasing habitat isolation reduced leafhopper species richness in simple (dominated by arable crops), but not in complex landscapes. This effect was driven by the generalist species. In simple landscapes, leafhoppers may find it more difficult to reach the next suitable fragment due to a lack of alternative resources during dispersal. Moreover, we found that generalist species richness increased with increasing connectivity on small fragments, whereas it remained stable with increasing connectivity on large fragments. In small, isolated fragments, a higher extinction rate combined with a lower probability of recolonization is thought to cause the reduced species richness. Synthesis and applications. Our results show for the first time that insect species richness can be negatively affected by increasing habitat isolation in simplified but not in complex landscapes and in small but not in large fragments. We provide evidence that mitigating the negative effects of habitat fragmentation needs to take the surrounding landscape into account. Management efforts should prioritize (i) an increase in connectivity of small, isolated fragments, (ii) an increase in connectivity of fragments in simple landscapes and (iii) enhanced dispersal by increasing heterogeneity of both landscape composition and configuration. Moreover, extensive management of fragments by grazing or mowing to increase local habitat quality for leafhoppers would benefit other insect groups as well.

Are farmsteads over-looked biodiversity hotspots in intensive agricultural ecosystems?

Farmland biodiversity continues to decline because changes in modern agriculture have led to the degradation and loss of key habitats. One farmland habitat that has received little attention during development of conservation measures is farmsteads. We use bird count data from a survey conducted at over 600 sites in 3725km2 agricultural landscapes in southern Sweden to investigate the importance of farmsteads as potential sources of biodiversity in simplified landscapes. We found that farmsteads, on average, had more bird species and individuals than semi-natural pastures and infield infield non-crop islands, probably due to a larger area of non-field habitats at farmstead sites. Presence of farm animals was an important predictor of bird diversity and numbers at farmsteads while variables associated with arable land-use intensification had limited effect. Old farmsteads with no current active farming, on average, had low bird numbers. We found no effect of agricultural intensification at the landscape level on alpha diversity at farmstead sites. Rather, species richness and abundance of birds tended to increase as landscapes became characterized by more intensive agriculture with larger fields. Farmsteads are widespread in simplified agricultural landscapes and may provide habitat to a range of farmland species. Applying conservation measures to farmsteads and local surroundings that increase the availability of safe nest-sites and good foraging grounds for birds could be implemented through publicity driven schemes. This combined with other agri-environment schemes in the surrounding landscape could enhance the amount of critical resources for farmland birds.

Spatially explicit computation of sustainability indicator values for the automated assessment of land-use options

Contemporary land-use planning is based on project-specific evaluation methods from various scientific disciplines and has come to focus more recently on the integration of sustainability issues. Context-specific sets of indicators are typically used to evaluate and quantify the sustainability of different planning options for given contexts. The evaluation of these indicators relies heavily on (expert) stakeholder input and can therefore not simply be integrated into standardized and automated assessment tools. This is seen as one of the reasons why sustainability – despite being widely accepted as one of the most crucial aspects in any development – is often not considered on equal terms in decision making and planning compared to environmental risks and economic considerations. In this paper we propose a scheme to transfer the evaluation of site-specific sets of sustainability indicators into automated quantitative and spatially explicit assessments, which can be integrated into multidisciplinary spatial optimization algorithms. Using simple landscape metrics along with typical spatial data and stakeholder knowledge on a brownfield near Potsdam, Germany, this transfer is implemented for an existing site-specific indicator set to evaluate the sustainability of brownfield redevelopment options in a case study. The automatic spatial evaluation and analysis of hundreds of systematically designed land-use options is explored to provide a detailed understanding of the indicator-based evaluation of sustainable land-use planning on the study site. The results suggest that a spatially explicit algorithmic evaluation of sustainability indicators may significantly improve the applicability, comprehensiveness and reliability of the indicator-based evaluation of sustainability.

Sensitivity and effectiveness and of landscape metric scalograms in determining the characteristic scale of a hierarchically structured landscape

Landscape metric scalograms (the response curves of landscape metrics to changing grain size) have been used to illustrate the scale effects of metrics for real landscapes. However, whether they detect the characteristic scale of hierarchically structured landscapes remains uncertain. To address this question, the scalograms of 26 class-level metrics were systematically examined for a simple random landscape, seven hierarchical neutral landscapes, and the real landscape of the Xilin River Basin of Inner Mongolia, China. The results show that when the fraction of the focal patch type (P) is below a critical value (P c), most metric scalograms are sensitive to change in single-scale and lower-level hierarchical structure and insensitive to change in higher-level hierarchical structure. The scalograms of only a few metrics measuring spatial aggregation and connectedness are sensitive to change in intermediate-level hierarchical structure. Most metric scalograms explicitly identify the characteristic scale of a single-scale landscape and fine or intermediate characteristic scales of a multi-scale landscape for both simulated and real landscapes. When P exceeds P c, only some metrics detect scale and change in structure. The scalograms of total class area and Euclidean nearest-neighbor distance cannot detect scale or change in structure in either case. Landscape metric scalograms are useful for addressing scale issues, including illustrating the scale effects of spatial patterns, detecting multi-scale patterns, and developing possible scaling relations.

Seasonal persistence of bumblebee populations is affected by landscape context

Bumblebee communities and their foraging resources were surveyed in south Swedish agricultural landscapes of contrasting complexity, defined by the size of arable fields and the amount of permanent grazed pastures. After the flowering of oilseed rape (OSR), simplified landscapes contained substantially less herbaceous flower resources and a lower proportion of perennials, compared to complex ones. The seasonal pattern of bumblebee abundance differed between landscape types. Initial bumblebee abundances were equal in both landscape types. However, by late July there was a sharp decline of bumblebees in simple landscapes, while the abundance continued to increase in complex landscapes. This suggests that a larger proportion of bumblebee colonies may fail to reproduce in simple landscapes despite a beneficial early season. Overall, bumblebee abundance in late July was positively related to three inter-related variables: area of permanent pasture, area of ley fields and total amount of herbaceous flowers, while early abundances (June to early July) did not relate to these variables. We suggest that in simplified landscapes of this region, bumblebee abundance is limited by floral resources mainly from midsummer and onward. Spring and early summer resources may indeed be sufficient for colony establishment and initial growth even in simplified landscapes, possibly as a result of large scale farming of OSR. The initially equal abundances of workers in simple and complex landscapes, as well as the fact that also many of the regionally rare species seem to persist in simple landscapes, suggest that rare species can survive in pockets of beneficial habitat and/or there may be an inflow of queens from nearby complex landscapes. If the latter is true, further simplification or abandonment of complex landscapes may threaten bumblebee populations also in neighbouring simple landscapes.

A Square Root Approximation of Transition Rates for a Markov State Model

Trajectory- or mesh-based methods for analyzing the dynamical behavior of large molecules tend to be impractical due to the curse of dimensionality---their computational cost increases exponentially with the size of the molecule. We propose a method to break the curse by a novel square root approximation of transition rates, Monte Carlo quadrature and a discretization approach based on solving linear programs. With randomly sampled points on the molecular energy landscape and randomly generated discretizations of the molecular configuration space as our initial data, we construct a matrix describing the transition rates between adjacent discretization regions. This transition rate matrix yields a Markov state model of the molecular dynamics. We use Perron cluster analysis and coarse-graining techniques in order to identify metastable sets in configuration space and approximate the transition rates between the metastable sets. Application of our method to a simple energy landscape on a two-dimensional configuration space provides proof of concept and an example for which we compare the performance of different discretizations. We show that the computational cost of our method grows only polynomially with the size of the molecule. However, finding discretizations of higher-dimensional configuration spaces in which metastable sets can be identified remains a challenge.