Multiscale effects of habitat and surrounding matrices on waterbird diversity in the Yangtze River Floodplain

Context

With the expansion in urbanization, understanding how biodiversity responds to the altered landscape becomes a major concern. Most studies focus on habitat effects on biodiversity, yet much less attention has been paid to surrounding landscape matrices and their joint effects.

Objective

We investigated how habitat and landscape matrices affect waterbird diversity across scales in the Yangtze River Floodplain, a typical area with high biodiversity and severe human-wildlife conflict.

Methods

The compositional and structural features of the landscape were calculated at fine and coarse scales. The ordinary least squares regression model was adopted, following a test showing no significant spatial autocorrelation in the spatial lag and spatial error models, to estimate the relationship between landscape metrics and waterbird diversity.

Results

Well-connected grassland and shrub surrounded by isolated and regular-shaped developed area maintained higher waterbird diversity at fine scales. Regular-shaped developed area and cropland, irregular-shaped forest, and aggregated distribution of wetland and shrub positively affected waterbird diversity at coarse scales.

Conclusions

Habitat and landscape matrices jointly affected waterbird diversity. Regular-shaped developed area facilitated higher waterbird diversity and showed the most pronounced effect at coarse scales. The conservation efforts should not only focus on habitat quality and capacity, but also habitat connectivity and complexity when formulating development plans. We suggest planners minimize the expansion of the developed area into critical habitats and leave buffers to maintain habitat connectivity and shape complexity to reduce the disturbance to birds. Our findings provide important insights and practical measures to protect biodiversity in human-dominated landscapes.

     

Saproxylic species are linked to the amount and isolation of dead wood across spatial scales in a beech forest

Context

Dead wood is a key habitat for saproxylic species, which are often used as indicators of habitat quality in forests. Understanding how the amount and spatial distribution of dead wood in the landscape affects saproxylic communities is therefore important for maintaining high forest biodiversity.

Objectives

We investigated effects of the amount and isolation of dead wood on the alpha and beta diversity of four saproxylic species groups, with a focus on how the spatial scale influences results.

Methods

We inventoried saproxylic beetles, wood-inhabiting fungi, and epixylic bryophytes and lichens on 62 plots in the Sihlwald forest reserve in Switzerland. We used GLMs to relate plot-level species richness to dead wood amount and isolation on spatial scales of 20–200 m radius. Further, we used GDMs to determine how dead wood amount and isolation affected beta diversity.

Results

A larger amount of dead wood increased beetle richness on all spatial scales, while isolation had no effect. For fungi, bryophytes and lichens this was only true on small spatial scales. On larger scales of our study, dead wood amount had no effect, while greater isolation decreased species richness. Further, we found no strong consistent patterns explaining beta diversity.

Conclusions

Our multi-taxon study shows that habitat amount and isolation can strongly differ in the spatial scale on which they influence local species richness. To generally support the species richness of different saproxylic groups, dead wood must primarily be available in large amounts but should also be evenly distributed because negative effects of isolation already showed at scales under 100 m.

     

Nonparametric machine learning for mapping forest cover and exploring influential factors

Context

The contribution of forest ecosystem services to human well-being varies over space following the dynamics in forest cover. Use of machine learning models is increasing in projecting forest cover changes and investigating the drivers, yet references are still lacking for selecting machine learning models for spatial projection of forest cover patterns.

Objectives

We assessed the ability of nonparametric machine learning techniques to project the spatial distribution of forest cover and identify its drivers using a case study of Tasmania, Australia.

Methods

We developed, evaluated, and compared the performance of four nonparametric machine learning models: support vector regression (SVR), artificial neural networks (ANN), random forest (RF), and gradient boosted regression trees (GBRT).

Results

The results demonstrated that RF far outperformed the other three models in both fitting and projection accuracy, and required less computional costs. GBRT outperformed SVR and ANN in projection accuracy. However, RF exhibited serious overfitting due to the full growth of its decision trees. The influence rankings of explanatory variables on spatial patterns of forest cover were different under the four models. Land tenure type and rainfall were identified among the top four most influential variables by all four models. The ranking produced by the RF model was significantly different with topographic factors associated with land clearing and production costs (elevation and distance to timber facilities) being the two most influential variables.

Conclusions

We encourage practitioners to consider nonparametric machine learning methods, especially RF, when facing problems of complex environmental data modelling.

     

Application of a dynamic model using agronomic and economic data to evaluate the sustainability of the olive grove landscape of Estepa (Andalusia,Spain)

Context

In the Andalusia region (Spain), olive grove agro-systems cover a wide area, forming social-ecological landscapes. Recent socioeconomic changes have increased the vulnerability of these landscapes, resulting in the abandonment and intensification of farms. The provision of the main ecosystem services of these landscapes have thus been degraded.

Objectives

To analyse the sustainability of an olive grove social-ecological landscape in Andalusia. Specifically, to develop a quantitative model proposing land planning and management scenarios, considering abandonment, production and economic benefits of olive crops in different conditions of erosion and management.

Methods

We applied a dynamic model using agronomic and economic data, to evaluate different types of olive management. We considered different levels of erosion, the loss of production related to this erosion, and useful life spans for each type of management. We simulated scenarios for the long-term assessment of dynamics of crops, abandonment rate, production and benefits.

Results

(a) There was a loss of productive lands and benefits in the medium term in the more intensive crops. (b) Scenarios that partially incorporated ecological management proved to be more sustainable without economic subsidies. (c) The spatial combination of integrated, intensive and ecological plots was sustainable, and was well balanced from an economic, productive and ecological point of view.

Conclusions

Scenarios that partially incorporate ecological management allowed the best economic and environmental balance. However, to ensure the sustainability of olive landscapes, farmers should be financially rewarded for their role in the conservation of ecosystem services through landscape stewardship and direct environmental payments.

     

Separating the effects of habitat amount and fragmentation on invertebrate abundance using a multi-scale framework

Context

Herbicide treatments in viticulture can generate highly contrasting mosaics of vegetated and bare vineyards, of which vegetated fields often provide better conditions for biodiversity. In southern Switzerland, where herbicides are applied at large scales, vegetated vineyards are limited in extent and isolated from one another, potentially limiting the distribution and dispersal ability of organisms.

Objectives

We tested the separate and interactive effects of habitat amount and fragmentation on invertebrate abundance using a multi-scale framework, along with additional environmental factors. We identified which variables at which scales were most important in predicting patterns of invertebrate abundance.

Methods

We used a factorial design to sample across a gradient of habitat amount (area of vegetated vineyards, measured as percentage of landscape PLAND) and fragmentation (number of vegetated patches, measured as patch density PD). Using 10 different spatial scales, we identified the factors and scales that most strongly predicted invertebrate abundance and tested potential interactions between habitat amount and fragmentation.

Results

Habitat amount (PLAND index) was most important in predicting invertebrate numbers at a field scale (50 m radius). In contrast, we found a negative effect of fragmentation (PD) at a broad scale of 450 m radius, but no interactive effect between the two.

Conclusions

The spatial scales at which habitat amount and fragmentation affect invertebrates differ, underpinning the importance of spatially explicit study designs in disentangling the effects between habitat amount and configuration. We showed that the amount of vegetated vineyards has more influence on invertebrate abundance, but that fragmentation also contributed substantially. This suggests that efforts for augmenting the area of vegetated vineyards is more beneficial for invertebrate numbers than attempts to connect them.

     

Quantifying spatial–temporal change in land-cover and carbon storage among exurban residential parcels

The area of land occupied by exurban residential development is significant and has been increasing over the past several decades in the United States. Considerable attention has been drawn to the measurement of regional-scale patterns of land-cover change and assessment of its environmental and socioeconomic consequences. Yet little is known about the quantity of land-cover change within individual exurban residential parcels, which reflect homeowner preferences, land-management strategies, and the ecosystem services they generate. Similarly, little is known about the spatial autocorrelation of land cover among parcels and how it may change over time. Using a dataset delineating land-cover change within exurban residential parcels in southeastern Michigan from 1960 to 2000, the quantity and composition of land cover and carbon storage are examined. The spatial similarity of land-cover quantity among neighboring parcels is evaluated using local indicators of spatial association. Results show, among other findings, that (1) the number of exurban residential parcels, the quantity of tree cover, and amount of carbon storage increased steadily from 1960 to 2000; (2) the distribution of parcel sizes remained relatively constant and dominated by small parcels; (3) an increasing proportion of parcels were significantly similar to their neighbors; and (4) using a benefits transfer approach, new exurban parcels are estimated to store ~15,000–29,000 kg C over the study period. The measured changes in land cover and carbon storage improve our understanding of how ecosystem services may change in human-dominated landscapes and provide evidence that policy opportunities are available to increase carbon management.     

Park features that encourage park visitation among older adults: A qualitative study

BackgroundParks provide many opportunities for promoting physical, social, and mental wellbeing among older adults and are therefore considered a good setting to promote healthy ageing. However, older adults are the age group least frequently observed visiting parks. To attract more older adults to parks, it is important to understand their needs and preferences for park design. The aim of this qualitative study was to gain in-depth information about older adults’ preferred park features for park visitation.MethodsSemi-structured interviews were conducted with 25 older adults aged > 60 years who visited a recently renewed urban park in Ghent, Belgium at least once since its renewal. The interviews were conducted in-park or in the nursing home adjacent to the park until saturation of information was obtained. All interviews were transcribed verbatim, pseudonymised, and analysed by inductive content analysis using NVivo 12 software.ResultsThe most preferred park activities were walking, sitting, and watching the environment. The park features liked by older adults were good quality and accessible walking paths, nature and vegetation, openness and structural layout of the park, and sufficient and good quality sitting areas. The park features that they did not like mostly related to poor park maintenance.ConclusionsThis study provides an overview of park features that older adults perceive as important for park visitation. It is the first qualitative study in Belgium to assess which park features entice older adults to visit parks, and it contributes to the limited European knowledge on this topic. The evidence can help urban planners, landscape architects, and policymakers to (re)design attractive local parks that promote healthy ageing.     

Predicting the assembly of novel communities in urban ecosystems

Context

Ecological communities in urban ecosystems are assembled through ecological processes, such as species interactions, dispersal, and environmental filtering, but also through human factors that create and modify the landscape. These complex interactions make it difficult to untangle the relationships between social–ecological dynamics and urban biodiversity.

Objectives

As a result, there has been a call for research to address how human activities influence the processes by which ecological communities are structured in urban ecosystems. We address this research challenge using core concepts from landscape ecology to develop a framework that links social-ecological dynamics to ecological communities using the metacommunity perspective.

Methods

The metacommunity perspective is a useful framework to explore the assembly of novel communities because it distinguishes between the effects of local environmental heterogeneity and regional spatial processes in structuring ecological communities. Both are shaped by social–ecological dynamics in urban ecosystems.

Results

In this paper, we define social, environmental, and spatial processes that structure metacommunities, and ultimately biodiversity, in cities. We then address how our framework could be applied in urban ecosystem research to understand multi-scalar biodiversity patterns.

Conclusions

Our framework provides a theoretical and empirical foundation for transdisciplinary research to examine how social-ecological dynamics mediate the assembly of novel communities in urban ecosystems.

     

Motif: an open-source R tool for pattern-based spatial analysis

Context

Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns.

Objectives

We developed an R package motif as a set of open-source tools for pattern-based spatial analysis.

Methods

This package provides most of the functionality of existing software (except spatial segmentation), but also extends the existing ideas through support for multi-layer raster datasets. It accepts larger-than-RAM datasets and works across all of the major operating systems.

Results

In this study, we describe the software design of the tool, its capabilities, and present four case studies. They include calculation of spatial signatures based on land cover data for regular and irregular areas, search for regions with similar patterns of geomorphons, detection of changes in land cover patterns, and clustering of areas with similar spatial patterns of land cover and landforms.

Conclusions

The methods implemented in motif should be useful in a wide range of applications, including land management, sustainable development, environmental protection, forest cover change and urban growth monitoring, and agriculture expansion studies. The motif package homepage is https://nowosad.github.io/motif.

     

Behavioral switching in Magellanic woodpeckers reveals perception of habitat quality at different spatial scales

Context

The switching pattern between behavioral modes provides a mechanistic basis for understanding how animals perceive and memorize the habitat quality in their home ranges.

Objectives

We assessed if Magellanic woodpeckers (Campephilus magellanicus) move based on habitat quality at local (neighboring trees) and home range scales.

Methods

We used state-space models to examine the relationship between remotely-sensed estimates of habitat quality (tree decay) and movement of adult woodpeckers tracked with GPS telemetry in southern Chile.

Results

Woodpeckers spent most time (>?80%) in the area-restricted search (ARS) mode in contrast to the exploratory transient mode, characterized by frequent directional displacements (>?50 m). The extent to which individuals switched between behavioral modes was related to habitat quality at different scales. Woodpeckers switched to and remained in the ARS mode when encountering moderate levels of heterogeneity in habitat quality. At very low or high heterogeneity levels, however, individuals switched to and remained in the transient mode, respectively. Likewise, as habitat quality declined locally and across home range, woodpeckers were more likely to adopt a transient mode.

Conclusions

Although woodpeckers seemed to easily perceive and memorize habitat quality at different spatial scales, our results suggest that spatial memory will less effective under extreme levels of habitat heterogeneity.

     

Can trail spatial attributes predict trail use level in urban forest park? An examination integrating GPS data and space syntax theory

Understanding users’ spatial distribution in forest park is crucial for providing visitors with quality recreation experiences and for park planning and management. Utilizing users’ spatial distribution data, this study aims at investigating associations between trail use level and trail spatial attributes, through examining two large urban forest parks (Gongqing forest park and Paotaiwan forest park) in Shanghai, China. Users’ spatial distribution was measured utilizing GPS trackers with the interval of 10 seconds. This study conceptualizes trail spatial attributes as trail metric attributes and trail configurational attributes. Trail metric attributes include trail mean distance to gates, length, width and level of enclosure, which are calculated based on park map and on-site observation. We computed trail configurational attributes utilizing space syntax theory, which comprise measures of global integration, control, and connectivity. Trail connection with features/facilities, visual connection with water and shading are included as covariate variables. In total, we obtained 134 valid samples in Gongqing forest park and 210 valid samples in Paotaiwan forest park for analysis. Multivariate regression analyses indicate that when involving covariate variables, consistently in both parks, a greater trail usage is significantly related to trail shorter mean distance to park gate, trail width wider than 3 meters, higher global integration and higher control values. Collectively, these four trail spatial attributes explained 31.7 % (p < 0.001) and 27.3 % (p < 0.001) of the variances in trail use level in Gongqing forest park and Paotaiwan forest park. These findings provide direct implications to park designers and managers for providing visitors with different desirable social conditions, and ultimately improve users’ experiences and satisfactions.     

Mapping landscape connectivity for large spatial extents

Context

Mapping landscape connectivity across large spatial extents is an important component of ecological reserve network designs and species recovery plans. It can, however, be limited by computational power. One way to overcome this problem is to split the study area into smaller tiles, map landscape connectivity within each of those tiles, and then merge tiles back together to form composite connectivity maps.

Objectives

We tested the effects of landscape structure on the accuracy of composite landscape connectivity maps created from tiles and tested two methods to increase this accuracy.

Methods

We correlated replicate, composite current density maps with untiled maps. We tested whether our findings depended on the composition of the landscape by testing maps with corridors, barriers, different mixtures of high- and low-cost habitat, and road networks.

Results

We found that composite current density maps underestimated large-scale connectivity and overestimated the contribution of small habitat patches to overall connectivity. These biases became more pronounced as the tiles became relatively smaller. Landscapes with corridors or barriers were particularly sensitive. We increased the accuracy of tiled maps by increasing pixel size or by averaging several maps created using a “moving window” approach.

Conclusions

There is a trade-off between tile size and pixel size when modelling connectivity across large spatial extents. We suggest using the largest tile size possible when tiling is necessary, in conjunction with increased pixel size and a moving window method to increase accuracy of the composite current density maps.

     

Contrasting time-scale effects of land-use legacy on species richness,diversity and composition in Mediterranean scrubland communities

Context

It is known that land-use and land-cover (LULC) changes affect plant community assembly for decades. However, both the short- and the long-term effects of contrasting LULC change pathways on this assembly are seldom explored.

Objectives

To assess how LULC change pathways affect woody plant community parameters (i.e. species richness, diversity and evenness) and species’ presence and abundance, compared with environmental factors and neutral processes.

Methods

The study was performed in Mediterranean limestone scrublands in NE Spain. Cover of each woody species was recorded in 150 scrubland plots belonging to five LULC change pathways along the past century, identified using land-cover maps and fieldwork. For each plot, total woody and herbaceous vegetation cover, local environmental variables and geographical position were recorded. Effects of these pathways and factors on plant community parameters and on species presence and abundance were assessed, considering spatial effects potentially associated to neutral processes.

Results

Species richness and diversity were associated with LULC change pathways and elevation, while evenness was only associated with this last. Pathways and environmental variables explained similar variance in both species’ presence and cover. In general, while community parameters were affected by recent-past (1956) use, species presence and abundance were associated with far-past (pre-1900) cropping. No relevant spatial effect was detected for any studied factor.

Conclusions

Historical LULC changes and current environmental factors drive local-scale community assembly in Mediterranean scrublands to an equal extent, while contrasting time-scale effects are found at community and species level. Neutral, dispersal-based processes are found to be non-relevant.

     

Influence of high-resolution data on the assessment of forest fragmentation

Context

Remote sensing has been a foundation of landscape ecology. The spatial resolution (pixel size) of remotely sensed land cover products has improved since the introduction of landscape ecology in the United States. Because patterns depend on spatial resolution, emerging improvements in the spatial resolution of land cover may lead to new insights about the scaling of landscape patterns.

Objective

We compared forest fragmentation measures derived from very high resolution (1 m²) data with the same measures derived from the commonly used (30 m?×??30 m; 900 m²) Landsat-based data.

Methods

We applied area-density scaling to binary (forest; non-forest) maps for both sources to derive source-specific estimates of dominant (density ≥?60%), interior (≥?90%), and intact (100%) forest.

Results

Switching from low- to high-resolution data produced statistical and geographic shifts in forest spatial patterns. Forest and non-forest features that were “invisible” at low resolution but identifiable at high resolution resulted in higher estimates of dominant and interior forest but lower estimates of intact forest from the high-resolution source. Overall, the high-resolution data detected more forest that was more contagiously distributed even at larger spatial scales.

Conclusion

We anticipate that improvements in the spatial resolution of remotely sensed land cover products will advance landscape ecology through re-interpretations of patterns and scaling, by fostering new landscape pattern measurements, and by testing new spatial pattern-ecological process hypotheses.

     

Marine connectivity in spatial conservation planning: analogues from the terrestrial realm

Context

Spatial prioritization is an analytical approach that can be used to provide decision support in spatial conservation planning (SCP), and in tasks such as conservation area network design, zoning, planning for impact avoidance or targeting of habitat management or restoration.

Methods

Based on literature, we summarize the role of connectivity as one component of relevance in the broad structure of spatial prioritization in both marine and terrestrial realms.

Results

Partially diffuse, directed connectivity can be approximated in Zonation-based multi-criteria SCP by applying hydrodynamic modelling, knowledge on species traits, and information on species occurrences and quality of habitats. Sources and destinations of larvae or propagules can be identified as separate spatial layers and taken into account in full-scale spatial prioritization involving data on biota, as well as economic factors, threats, and administrative constraints. While population connectivity is an important determinant of metapopulation persistence, the importance of marine connectivity depends on species traits and the marine environment studied. At one end of the continuum are species that occupy isolated habitats and have long pelagic larval durations in deeper sea areas with strong directional currents. At the other extreme are species with short pelagic durations that occupy fragmented habitats in shallow topographically complex sea areas with weak and variable currents.

Conclusions

We conclude that the same objectives, methods, and analysis structures are applicable to both terrestrial and marine spatial prioritization. Marine spatial conservation planning, marine spatial planning, marine zoning, etc., can be implemented using methods originated in the terrestrial realm of planning.

     

Park availability,accessibility, and attractiveness in relation to the least and most vulnerable inhabitants

With this paper, we enrich the environmental justice debate by investigating differences in the provision of parks in Lodz, Poland, at three levels: availability, accessibility, and attractiveness. A park is ‘available’ when it exists within a suitable distance from where we live; it is ‘accessible’ when we feel that we are welcome there, and we can freely reach and safely use this park; it is ‘attractive’ when we willingly want to use it and spend time there. Our research hypothesis is that the most vulnerable groups of inhabitants concentrate around parks whose provision is affected by the largest number of barriers at each of the three levels, while the least vulnerable benefit from the vicinity of parks that are the least affected. Apart from the statistical analysis – the correlation between the indicators that represent the three levels of park provision and those that represent the most and least economically vulnerable using Pearson’s coefficient – we scrutinize three case study parks. The results confirm that there are inequalities at the level of attractiveness for the most vulnerable groups; meanwhile, no statistically significant results were recorded for the least vulnerable groups. The differences would probably be more explicit had socioeconomic segregation been higher in Lodz. The results may also be influenced by the unique postsocialist and postindustrial legacy of our city. The ongoing revitalization of the city center and the increased activity of developers may exclude the most vulnerable inhabitants and deepen segregation.     

Accounting for spatial autocorrelation improves the estimation of climate,physical environment and vegetation’s effects on boreal forest’s burn rates

Context

Wildfires play a crucial role in maintaining ecological and societal functions of North American boreal forests. Because of their contagious way of spreading, using statistical methods dealing with spatial autocorrelation has become a major challenge in fire studies analyzing how environmental factors affect their spatial variability.

Objectives

We aimed to demonstrate the performance of a spatially explicit method accounting for spatial autocorrelation in burn rates modelling, and to use this method to determine the relative contribution of climate, physical environment and vegetation to the spatial variability of burn rates between 1972 and 2015.

Methods

Using a 482,000 km² territory located in the coniferous boreal forest of eastern Canada, we built and compared burn rates models with and without accounting for spatial autocorrelation. The relative contribution of climate, physical environment and vegetation to the burn rates variability was identified with variance partitioning.

Results

Accounting for spatial autocorrelation improved the models’ performance by a factor of 1.5. Our method allowed the unadulterated extraction of the contribution of climate, physical environment and vegetation to the spatial variability of burn rates. This contribution was similar for the three groups of factors. The spatial autocorrelation extent was linked to the fire size distribution.

Conclusions

Accounting for spatial autocorrelation can highly improve models and avoids biased results and misinterpretation. Considering climate, physical environment and vegetation altogether is essential, especially when attempting to predict future area burned. In addition to the direct effect of climate, changes in vegetation could have important impacts on future burn rates.