Landscape Spatial Configuration Research Articles

Landscape fragmentation and regularity lead to decreased carbon stocks in basins: Evidence from century-scale research

Landscapes evolution have significantly altered the Earth's energy balance and biogeochemical cycles, thereby exacerbating climate change. This, in turn, affects surface characteristics and the provision of ecosystem services, especially carbon storage. While recent centuries have witnessed unprecedented landscape changes, limited long-term studies have offered insights into the comparison between present-day features and historical conditions. This study utilized historical reconstruction data and remote sensing imagery to assess landscape evolution and its consequences for carbon stocks over 300 years. Employing multiple regression and random forest models were selected to quantify the influence of key landscape metrics on carbon stocks in the Dongting Lake basin, allowing for a thorough analysis across different sub-basins and land types. The results revealed that intensified human disturbances led to increased landscape fragmentation (+82%), regularity (+56%), and diversity (+37%) within the basin. Moreover, carbon stocks decreased from 4.13 Gt to 3.66 Gt, representing an 11.4% loss, with soil carbon stock experiencing the most considerable reduction (0.24 Gt, 51%). These changes in carbon stock metrics corresponded to shifts in landscape patterns, both undergoing significant transitions at the turn of the 21st century. Meanwhile, fragmentation and regularity played a vital role in explaining carbon stock changes, as their increase contributes to greater carbon losses. Likewise, an increase in landscape diversity correlated with decreased carbon stocks, challenging the prevailing notion that enhanced diversity promotes carbon stocks. The influence of landscape patterns on carbon stocks varies notably across distinct land types. An increase in the dominance of farmland and built-up land led to decreased carbon stocks, while the opposite holds true for forestland. Similarly, a decrease in regularity for farmland, forestland, and built-up land benefits carbon storage, while grassland demonstrates the opposite trend. These findings offer insights for countries and regions in the early stages of development or approaching development, suggesting improvements in land use practices and strategies to address climate change. This involves offsetting land-based carbon emissions through changes in landscape spatial configuration.

Optimization of Landscape Spatial Configuration and Form for Thermal Comfort: A Case Study of Urban Square, Shanghai

Outdoor public spaces that provide a comfortable microclimate significantly contribute to urban livability. However, more elaborate investigations are needed to enhance the research-based design of landscape spatial form for optimal thermal comfort performance. This study aimed to optimize the morphological design of urban squares considering summer and winter microclimates by integrating multiple landscape elements of vegetation, waterbodies, buildings, and ground. The built environment microclimate simulation and validation of multi-physics coupling were conducted for thermal comfort, planar heterogeneity diagramming, and spatial typology identification. Further, research through design (RtD) was applied to reconstruct various spatial configurations and orientation forms to compare the relative thermal comfort areas of these geometrical prototypes in the target time period and square core zone. Among the landscape types, two identified spatial types for achieving better thermal comfort are the opening of a windward enclosure structure (ECS) that draws wind into the square in summer and an ECS without a windward opening that creates a more extended wind protection area in winter. Moreover, results of RtD show that the prototype with the smallest orientation angle to the prevailing wind direction has the most optimized thermal comfort during summer, while the form with a smaller angle to the prevailing wind direction is more favorable in winter. These findings provide methodological guidance for climate-adapted landscape square form optimization.

Oil palm plantations in an aging agricultural landscape in the eastern Amazon: Pushing Amazon forests farther from biodiversity-friendly landscapes

Oil palm plantations across the tropics are intended to promote sustainable production by incorporating degraded lands while sparing old-growth forests. Here, we examine the trajectory of an Amazonian-forest focal landscape as it experiences the expansion of oil palm and its interactions with multiple land-uses. Land-use composition, landscape spatial configuration and structure in a 765.65-km2 watershed were examined over a 16-yr period (2002–2018) via Landsat imagery. Briefly, (1) old-growth forest coverage dropped from 37.3 % to 18.3 % across the whole landscape, (2) secondary forest and arable fields expanded until 2014, and (3) oil palm plantations emerged in 2010 with a positive trend thereafter, resulting in an 11.9 % expansion until 2018. In 2018, only 140.7 km2 of old-growth forest persisted, while oil palm plantations covered 91.8 km2. Oil palm expansion resulted from 14 land-use trajectories, with changes involving old-growth forests accounting for half the area (48.1 %) covered by plantations in 2018. However, only 0.4 % of the plantation area resulted from a direct conversion of old-growth forests. Landscape structure became increasingly degraded, which included the elimination of gallery forests, the proliferation of edge-affected habitats and the collapse of forest structural connectivity. Our results suggest that the eastern Amazon is still experiencing forest loss and exhibit highly dynamic land-use changes. Furthermore, landscapes continue to suffer degradation of key attributes related to biodiversity persistence and the provision of ecosystem services. Oil palm plantations have a catalytic effect on land-use dynamics, speeding up forest shrinking and landscape degradation. The oil palm sector requires a better governance based on guidelines able to guarantee either the persistence or the emergence of biodiversity-friendly landscapes.

Landscape spatial configuration influences phosphorus but not nitrate concentrations in agricultural headwater catchments

AbstractLandscape organized (or structured) heterogeneity influences hydrological and biogeochemical patterns across space and time. We developed landscape indices that describe the spatial configuration of nutrient sources and sinks as a function of their hydrological distance to the stream (lateral dimension) or to the outlet (longitudinal dimension) and their intersection with flow‐accumulation areas. Using monthly nitrate, total phosphorus (TP), soluble reactive phosphorus (SRP) and daily discharge (Q) data from 221 rural catchments (1–300 km2) from 2010–2020, we observed higher variability in flow‐weighted mean concentrations in smaller catchments than in larger ones. The variability in landscape configurations also decreased with increasing catchment size. A landscape configuration index, calculated as mean arable land use weighted by spatial data on hydrological distance and flow accumulation, improved prediction of TP and SRP, but not nitrate, compared to the unweighted mean arable land use. We conclude that landscape configuration influences phosphorus transfer more than nitrate transfer, and that flow‐accumulation zones and riparian areas are critical source areas for TP and SRP, respectively. By contrast, landscape spatial configuration in the lateral (upslope–downslope) and longitudinal (upstream–downstream) dimensions did not have an identifiable influence on nutrients temporal dynamics. The indices developed in this study can help design landscapes that minimize diffuse phosphorus losses to streams and show that landscape management is not a first order control for nitrate losses.

How Landscape Patterns Affect River Water Quality Spatially and Temporally: A Multiscale Geographically Weighted Regression Approach

The water quality of a river can be considered a function of its surrounding landscape. Understanding the relationship between landscape patterns and river water quality is essential for optimizing landscape patterns to reduce watershed pollution and has not yet been solved. A multiscale geographically weighted regression (MGWR) model was used to explore the associations between the landscape patterns and water quality. Our results showed that landscape metrics have varied relationships with the water quality across spatial scales in different seasons. The strongest independent influencing variable for NO3–-N, NH4+-N, and TN was tea gardens, residential land, and varied seasonally, respectively. The impacts of the landscape metrics on the TP were relatively weak throughout the year at the watershed scale. The influence of landscape metrics on NO3–-N was more significant during the flood season, whereas that on NH4+-N was more notable during the non-flood season. Seasonal changes in the influencing landscape metrics of TN were not regular. Although landscape composition more significantly influenced water quality than configuration, the Shannon’s diversity index and patch density were important configuration indices that significantly impacted water quality. Therefore, with limited land availability, it is essential to optimize the landscape spatial configuration without changing the composition of the watershed to reduce the risk of river pollution. This study further indicated that the MGWR model can well quantify the effects of landscape pattern on water quality at the watershed scale.

Impacts of landscape spatial configuration of integrated multi-pond constructed wetlands in a basin on the treatment of non-point source pollution

To assess the retention performance of integrated multi-pond constructed wetlands (MPCWs) for the interception of non-point source (NPS) pollution in a basin, the examination of catchment divisions was applied to explore the impacts of the landscape spatial configuration of MPCWs on the treatment of NPS pollution. An empirical assessment model was established to determine the characteristics of the nitrogen and phosphorus removal performance of MPCWs in different catchment divisions. Average interception efficiencies of TN (4.18%) and TP (5.05%) in the catchment divisions were achieved. The scattered distribution of MPCWs in an annular shape in the catchment was helpful for the collection and interception of wastewater, while the spatial configuration of several MPCWs positioned in a straight line along the elevation obtained unsatisfactory interception performance. The result of the relationship between spatial configuration parameters and interception performance of MPCWs in the catchments estimated that choosing reasonable site locations, increasing the ratio of the MPCW area to the catchment area (A: Ac), the number, areas, and volume of MPCWs in the catchment, and optimizing other spatial configuration parameters such as following the flow direction, connecting to the river or ditch systems, all contributed to the interception performance of MPCWs for the NPS pollution. The overall planning perspective on local special land resources, pollution source structure, and the sustainable allocation of rural agricultural water resources for the parameters optimization of geographical landscape structure was highlighted in the scientific management of MPCWs for controlling NPS pollution in a basin.

Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed

Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R2 increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.

Fragmented landscape generator (flsgen): A neutral landscape generator with control of landscape structure and fragmentation indices

Abstract Neutral landscape models have many applications in ecology, such as supporting spatially explicit simulations, developing and evaluating landscape indices. However, current approaches provide few options to produce large landscapes with controlled composition and fragmentation indices. We introduce flsgen (Fragmented Landscape Generator), a new neutral landscape generator that addresses this limitation by providing a high level of control over 14 landscape indices. The main novelty of flsgen is the decomposition of landscape generation into two steps: the solving of a constraint satisfaction problem and the generation of a landscape raster with a stochastic algorithm. The latter relies on a continuous environmental gradient that influences the landscape's spatial configuration. flsgen can generate fine‐grained artificial landscapes in small amounts of time, which makes it suited to produce large landscape series systematically. We demonstrate the features of flsgen through three illustrative use cases. flsgen is a practical and efficient tool that expands the current possibilities of neutral landscape models and widens their potential applications. To facilitate its uptake, flsgen is available as free and open‐source software through a Java API, a command‐line interface or an R package.

Impact of landscape pattern change on water-related ecosystem services: Comprehensive analysis based on heterogeneity perspective

The transformation of surface landscapes by human activities is the main driving factor that affects changes in ecosystem functions and ecological processes, significantly influencing the ability of regional water ecosystems to deliver products and services to human society. However, the relationship between landscape heterogeneity and multiple water ecosystem services and the mechanisms of dynamic change remain unclear, posing challenges for managing and enhancing ecosystem services through landscape management decisions. Taking the Zishui basin as an example, this study aimed to clarify the impact of landscape heterogeneity on water-related ecosystem services and relationships by analyzing the relative importance and comprehensive impacts of landscape structure composition and landscape spatial configuration changes on three ecosystem services (water production, soil conservation, and water purification). These services were quantified for the years 2000, 2005, 2010, 2015, and 2018 using the InVEST model. Furthermore, quantitative indices were constructed to assess the impact of landscape heterogeneity on water ecosystem services. The results show that annual water yield and soil conservation increased at first and then decreased from 2000 to 2018, with 24.48% and 22.50% overall decreases, respectively. In contrast, the total export of N and P decreased at first and then increased, with 3.65% and 5.18% overall increases, respectively. The contribution indices of landscape pattern changes to water yield, soil conservation, nitrogen export, and phosphorus export were 0.04%–2.02%, 0.08 × 10−2%–0.32 × 10−2%, 13.57%–70.05%, and 11.01%–68.22%, respectively, showing interannual and spatial differences. The impact of landscape pattern change on water-related ecosystem services mainly reflects intensity change, which does not change the dominant relationships. Both landscape composition and configuration have impacts on water-related ecosystem services, but the effects of composition are larger than those of configuration. Among them, the proportions of cultivated land, woodland, and construction land, along with changes in Shannon’s diversity index (SHDI), patch density (PD), and edge density (ED) have obvious influences on water-related ecosystem services and show nonlinear relationships. In summary, the impacts of landscape heterogeneity indicators on water-related ecosystem services have obvious category differences, interannual changes, and spatial differences. This study provides new insight into the driving effects of landscape pattern change on the supply of water-related ecosystem services and will provide a reference for practical land management applications and policy formulation of water ecosystem services.

The influence of landscape spatial configuration on nitrogen and phosphorus exports in agricultural catchments

ContextNitrogen (N) and phosphorus (P) exports from rural landscapes can cause eutrophication of inland and coastal waters. Few studies have investigated the influence of the spatial configuration of nutrient sources—i.e. the spatial arrangement of agricultural fields in headwater catchments—on N and P exports.ObjectivesThis study aimed to (1) assess the influence of the spatial configuration of nutrient sources on nitrate (NO3−) and total phosphorus (TP) exports at the catchment scale, and (2) investigate how relationships between landscape composition (% agricultural land-use) and landscape configuration vary depending on catchment size.MethodsWe analysed NO3− and TP in 19 headwaters (1–14 km², Western France) every two weeks for 17 months. The headwater catchments had similar soil types, climate, and farming systems but differed in landscape composition and spatial configuration. We developed a landscape configuration index (LCI) describing the spatial organisation of nutrient sources as a function of their hydrological distance to streams and flow accumulation zones. We calibrated the LCI’s two parameters to maximise the rank correlation with median concentrations of TP and NO3−.ResultsWe found that landscape composition controlled NO3− exports, whereas landscape configuration controlled TP exports. For a given landscape composition, landscape spatial configuration was highly heterogeneous at small scales (< 10 km2) but became homogeneous at larger scales (> 50 km2).ConclusionsThe spatial configuration of nutrient sources influences TP but not NO3− exports. An ideal placement of mitigation measures to limit diffuse TP export should consider both the hydrological distance to streams and flow accumulation zones.

‘The Best of Two Worlds’—Combining Classifier Fusion and Ecological Models to Map and Explain Landscape Invasion by an Alien Shrub

The spread of invasive alien species promotes ecosystem structure and functioning changes, with detrimental effects on native biodiversity and ecosystem services, raising challenges for local management authorities. Predictions of invasion dynamics derived from modeling tools are often spatially coarse and therefore unsuitable for guiding local management. Accurate information on the occurrence of invasive plants and on the main factors that promote their spread is critical to define successful control strategies. For addressing this challenge, we developed a dual framework combining satellite image classification with predictive ecological modeling. By combining data from georeferenced invaded areas with multispectral imagery with 10-meter resolution from Sentinel-2 satellites, a map of areas invaded by the woody invasive Acacia longifolia in a municipality of northern Portugal was devised. Classifier fusion techniques were implemented through which eight statistical and machine-learning algorithms were ensembled to produce accurate maps of invaded areas. Through a Random Forest (RF) model, these maps were then used to explore the factors driving the landscape-level abundance of A. longifolia. RF models were based on explanatory variables describing hypothesized environmental drivers, including climate, topography/geomorphology, soil properties, fire disturbance, landscape composition, linear structures, and landscape spatial configuration. Satellite-based maps synoptically described the spatial patterns of invaded areas, with classifications attaining high accuracy values (True Skill Statistic, TSS: 0.895, Area Under the Receiver Operating Curve, ROC: 0.988, Kappa: 0.857). The predictive RF models highlighted the primary role of climate, followed by landscape composition and configuration, as the most important drivers explaining the species abundance at the landscape level. Our innovative dual framework—combining image classification and predictive ecological modeling—can guide decision-making processes regarding effective management of invasions by prioritizing the invaded areas and tackling the primary environmental and anthropogenic drivers of the species’ abundance and spread.

Relating land-use/land-cover patterns to water quality in watersheds based on the structural equation modeling

Understanding the relationships between land-use/land-cover (LULC) patterns in watersheds and water quality is of great significance for exploring the causes of non-point source pollution and scientific planning of land use. Multivariate regression methods have often been used to examine the response of specific water contaminants to LULC patterns. However, this also resulted in overlooking the ecological process and biased parameter estimates caused by redundancy where some landscape metrics are strongly correlated. In this study, based on “source-sink” landscape theory, Redundancy Analysis (RDA) and Partial Least Squares Structural Equation Modeling (PLS-SEM) were used to investigate the relationship between LULC patterns and water quality in the surrounding sub-watersheds of the Danjiangkou Reservoir in the dry and rainy seasons. The results showed that water quality parameters were characterized by seasonal differences. In the dry season, only the proportion of the watershed occupied by urban landscapes (P_Urban) had a significant impact on water quality in watersheds (β = 0.835, p < 0.001), so the water quality was only affected by point source pollution in the dry season. In the rainy season, specific water contaminants were categorized as organic and inorganic pollutants. The “sources” of organic and inorganic pollutants were agricultural and urban land, respectively. However, natural vegetation was not only a “sink” of inorganic pollutants, but also a “source” of organic pollutants. Furthermore, agriculture and natural vegetation mediated the effects of landscape spatial configuration on the water quality, yet landscape aggregation negatively moderated the relationship between urban and organic pollution. Therefore, watersheds with high landscape aggregation have small agricultural landscapes and large natural vegetation landscapes where water quality is affected by low levels of inorganic pollution and high levels of organic pollution. However, organic pollution from urban sources was aggravated by watersheds with low landscape aggregation. This study revealed the relationships between LULC patterns and water quality in watersheds and reflected the ecological process to a certain extent.

INTER-RELAÇÃO ENTRE PAISAGEM, ORGANIZAÇÃO FLORÍSTICO-ESTRUTURAL E DEMOGRAFIA DO COMPONENTE ARBÓREO EM FLORESTA COM ARAUCÁRIA

Objetivou-se verificar as interações entre a configuração espacial da paisagem, a organização florístico-estrutural e as taxas demográficas do componente arbóreo em um sistema de fragmentos e corredores de floresta com araucária em Lages, Santa Catarina. Para isso, foi elaborado um modelo conceitual das possíveis inter-relações, que foi avaliado pela técnica de Modelagem de Equações Estruturais. No ano de 2010, foram obtidos as métricas da paisagem (área, distância do vizinho mais próximo e relação borda e o interior da floresta) e os dados do primeiro inventário florestal. Neste caso, foram alocadas parcelas permanentes em cinco fragmentos e corredor florestal, onde todos os indivíduos arbóreos com CAP (circunferência a altura do peito, medida a 1,30 do solo) igual ou superior a 15,7 cm foram identificados e mensurados. Em 2014 foi realizado o segundo inventário, com a inclusão de indivíduos recrutas, contagem de mortos e sobreviventes, e foram calculadas as taxas demográficas. Os dados foram analisados por meio da Análise de Componentes Principais (PCA), Análise de Coordenadas Principais (PCoA), Modelagem de Equações Estruturais e Modelos Lineares Generalizados (GLM). Os resultados demonstraram que a estrutura da paisagem (PCA 1) exerceu influência apenas sobre a organização florístico-estrutural do componente arbóreo, indicada pela distribuição preferencial de espécies arbóreas em função da intensidade da fragmentação. Por sua vez, as taxas demográficas (taxas de ganho e perda em área basal e de mortalidade) foram influenciadas por aspectos estruturais da vegetação (abundância e área basal). Conclui-se que existem variações florístico-estruturais associadas à configuração espacial dos fragmentos na paisagem e que as taxas demográficas apresentam relação com o estágio sucessional da floresta, sintetizado pelas variáveis estruturais de área basal e abundância.

Developing characterisation factors for land fragmentation impacts on biodiversity in LCA: key learnings from a sugarcane case study

Habitat change was identified by the Millennium Ecosystem Assessment as the main direct driver of biodiversity loss. However, while habitat loss is already implemented in Life Cycle Impact Assessment (LCIA) methods, the additional impact on biodiversity due to habitat fragmentation is not assessed yet. Thus, the goal of this study was to include fragmentation effects from land occupation and transformation at both midpoint and endpoint levels in LCIA. One promising metric, combining the landscape spatial configuration with species characteristics, is the metapopulation capacity λ, which can be used to rank landscapes in terms of their capacity to support viable populations spatially structured. A methodology to derive worldwide regionalised fragmentation indexes based on λ was used and combined with the Species Fragmented-Area Relationship (SFAR), which relies on λ to assess a species loss due to fragmentation. We adapted both developments to assess fragmentation impacts due to land occupation and transformation at both midpoint and endpoint levels in LCIA. An application to sugarcane production occurring in different geographical areas, more or less sensitive to land fragmentation, was performed. The comparison to other existing LCIA indicators highlighted its great potential for complementing current assessments through fragmentation effect inclusion. Last, both models were discussed through the evaluation grid used by the UNEP-SETAC land use LCIA working group for biodiversity impact assessment models. Midpoint and endpoint characterisation factors were successfully developed to include the impacts of habitat fragmentation on species in LCIA. For now, they are provided for bird species in all forest ecoregions belonging to the biodiversity hotspots. Further work is required to develop characterisation factors for all taxa and all terrestrial ecoregions.

A methodology to assess habitat fragmentation effects through regional indexes: Illustration with forest biodiversity hotspots

The fragmentation of natural environments is a critical issue involving major challenges for biodiversity conservation and ecosystem management. Large-scale information on areas sensitive to fragmentation is needed to improve the effectiveness of planning efforts. One promising metric combining the landscape spatial configuration with species characteristics is the metapopulation capacity λ, which can be used to rank different fragmented landscapes in terms of their capacity to support viable metapopulations. A methodology to globally derive a fragmentation metric based on metapopulation capacity, at appropriate and meaningful spatial scales for fragmentation mechanisms, was developed. To illustrate the applicability and interest of the methodology, worldwide regionalised fragmentation indexes, calculated with a dispersal distance of 1 km valid for a broad range of species, were provided for all forest ecoregions included in the biodiversity hotspots. Ecoregions were divided by a virtual grid and a statistical analysis of metapopulation capacity values calculated at the grid square scale was performed to obtain a Forest Fragmentation Potential FFP at three levels of spatial aggregation within the ecoregion (highly converted forest, entire forest, and the whole ecoregion). The results highlighted significant intra- and inter-ecoregions differences, showing great potential to extend the use of these indexes to land use planning and areas prioritisation for both ecological protection and restoration. The influence of the different parameters used in the proposed approach is discussed as well as the limitations of the main assumptions. One important result is that the derived methodology can be easily adapted to a large number of species, scales, or regions to improve the coverage of fragmentation indexes.

Global inventory of landscape patterns and latent variables of landscape spatial configuration

We present a regionalization of the entire Earth’s landmass into land units of homogeneous landscape patterns. The input to the regionalization is a high resolution Global Land Cover (GLC) dataset. The GLC is first divided into local landscapes – small non-overlapping square blocks of GLC cells. These blocks are agglomerated into much larger land units using a pattern-based segmentation algorithm. These units are tracts encompassing cohesive patterns of land cover and the procedure divides the entire landmass into tracts of land with discernibly different patterns. We characterize a pattern in each unit by a set of 39 landscape metrics. The resulting spatial database of land units is the major product of this study. We make this database freely available to the community in order to provide foundational information for studies aiming at explaining relationships between landscape pattern and ecological process and between the process and patterns and their controlling factors. The procedure of obtaining the database is described, the quality assessment of units delineation is given, and the statistics of the major properties of the units are presented. To showcase the utility of the new database we use it to demonstrate that a variability of geometric configurations of landscape patterns worldwide can be captured in terms of only two variables – complexity and aggregation – as they explain 70% of the variability. This allows for a meaningful, two-dimensional classification and mapping of landscape patterns on the basis of their geometry. Such mapping reveals that the majority of terrestrial landscapes are characterized by a simple, frequently monothematic, pattern of land cover. Thus, landscapes on Earth are mostly segregated by the land cover type and complex landscapes with a diverse mix of different land cover types are rare exceptions from the prevailing monothematic cover.

Landscape-Abundance Relationships of Male Eastern Wild Turkeys Meleagris gallopavo silvestris in Mississippi, USA

The effects of landscape alteration on wildlife have drawn increasing attention from ecologists as landscapes have rapidly changed worldwide. Large-bodied birds are highly sensitive to habitat loss and fragmentation. We aimed to test two hypotheses concerning landscape-abundance relationships of male Wild Turkeys Meleagris gallopavo silvestris, the largest galliform in North America. The landscape fragmentation hypothesis posits that animal populations would decline linearly with habitat fragmentation, independent of the effects of habitat loss. The landscape composition hypothesis states habitat quantity, measured at spatial scales larger than the individual territory, would influence species abundance. Using the National Land Cover Database, we extracted the metrics of landscape fragmentation and composition at turkey annual dispersal (i.e., a buffer of 16-km radius) and annual home range (i.e., a buffer of 2.15-km radius) scales, respectively, for 28 wildlife management areas across Mississippi, USA. We used the mean annual number of harvested adult males per hunter day during annual spring hunting seasons (mid-March to mid-April) from 2001 to 2005 as a relative abundance index. Male Wild Turkey relative abundance increased with increasing fragmentation of hardwood forest (i.e., deciduous trees as the dominant form of vegetation) at both annual home range and dispersal scales, contrary to the prediction of the landscape fragmentation hypothesis. Male Wild Turkey abundance also increased with increasing landscape interspersion and juxtaposition index (i.e., an index of landscape spatial configuration) at the annual dispersal scale. We found nonlinear relationships between the proportion of hardwood forest and male turkey abundance, supporting the landscape composition hypothesis. Male turkey relative abundance peaked at 29% hardwood forest within the annual dispersal distance. Diverse landscapes are beneficial to Wild Turkeys at large spatial scales.

Rearranging agricultural landscapes towards habitat quality optimisation: In silico application to pest regulation

Modern agriculture suffers from its dependence on chemical inputs and subsequent impacts on health and environment. Alternatively, protecting crops against pests can be achieved through the reinforcement of regulation ecological services. Our work propounds a data-driven methodological framework to derive relevant agricultural landscape rearrangements enhancing populations of beneficial organisms regulating pests.Building on spatialised entomological and geographic data, we developed a parsimonious reaction–diffusion model describing the population dynamics of beneficial organisms. Parameter estimation was carried out in a Bayesian framework accounting for uncertainty in the measurement.Thousands of agricultural landscapes were generated under agronomic specifications dealt with as constraint satisfaction problems. Population dynamics was simulated on each landscape with the fitted reaction-diffusion model mentioned above, and two metrics of abundances allowed the assessment of the regulation performance of the landscape spatial arrangements. One metric is a mean field performance criterion assessing the regulation performance from the landscape composition only, the other is a spatial performance metric assessing the performance resulting from the whole landscape spatial configuration. The former is computed with a non-spatialised form of the population dynamics model, the latter results from the reaction-diffusion model of the population dynamics. Comparing these metrics enabled to quantify the impact of spatial arrangements, hence allowing arrangements proposals.This framework was applied to the case study of a ground beetle species involved in the biological regulation of weeds. The arrangement proposals abides by the productive agronomic constraint that is the landscape composition, while they allow for significant habitat quality enhancement (or deterioration) for the beneficial organism (or a pest). Minor adaptations of our integrated data-driven approach would suit numerous situations ranging from the provision of enhanced ecosystem services to land management for conservation.

Multiple successional pathways in human-modified tropical landscapes: new insights from forest succession, forest fragmentation and landscape ecology research.

Old-growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human-modified tropical landscapes (HMTLs). Secondary forests thus emerge as a potential repository for tropical biodiversity, and also as a source of essential ecosystem functions and services in HMTLs. Such critical roles are controversial, however, as they depend on successional, landscape and socio-economic dynamics, which can vary widely within and across landscapes and regions. Understanding the main drivers of successional pathways of disturbed tropical forests is critically needed for improving management, conservation, and restoration strategies. Here, we combine emerging knowledge from tropical forest succession, forest fragmentation and landscape ecology research to identify the main driving forces shaping successional pathways at different spatial scales. We also explore causal connections between land-use dynamics and the level of predictability of successional pathways, and examine potential implications of such connections to determine the importance of secondary forests for biodiversity conservation in HMTLs. We show that secondary succession (SS) in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio-temporal scales. SS is relatively fast and more predictable in recently modified landscapes and where well-preserved biodiversity-rich native forests are still present in the landscape. Yet the increasing variation in landscape spatial configuration and matrix heterogeneity in landscapes with intermediate levels of disturbance increases the uncertainty of successional pathways. In landscapes that have suffered extensive and intensive human disturbances, however, succession can be slow or arrested, with impoverished assemblages and reduced potential to deliver ecosystem functions and services. We conclude that: (i) succession must be examined using more comprehensive explanatory models, providing information about the forces affecting not only the presence but also the persistence of species and ecological groups, particularly of those taxa expected to be extirpated from HMTLs; (ii) SS research should integrate new aspects from forest fragmentation and landscape ecology research to address accurately the potential of secondary forests to serve as biodiversity repositories; and (iii) secondary forest stands, as a dynamic component of HMTLs, must be incorporated as key elements of conservation planning; i.e. secondary forest stands must be actively managed (e.g. using assisted forest restoration) according to conservation goals at broad spatial scales.

A contemporary decennial examination of changing agricultural field sizes using Landsat time series data.

Field size distributions and their changes have not been studied over large areas as field size change datasets are not available. This study quantifies agricultural field size changes in a consistent manner using Landsat satellite data that also provide geographic context for the observed decadal scale changes. Growing season cloud‐free Landsat 30 m resolution images acquired from 9 to 25 years apart were used to extract field object classifications at seven sites located by examination of a global agricultural yield map, agricultural production statistics, literature review, and analysis of the imagery in the US Landsat archive. High spatial resolution data were used to illustrate issues identifying small fields that are not reliably discernible at 30 m Landsat resolution. The predominant driver of field size change was attributed by literature review. Significant field size changes were driven by different factors, including technological advancements (Argentina and USA), government land use and agricultural policies (Malaysia, Brazil, France), and political changes (Albania and Zimbabwe). While observed local field size changes were complex, the reported results suggest that median field sizes are increasing due to technological advancements and changes to government policy, but may decrease where abrupt political changes affect the agricultural sector and where pastures are converted to arable land uses. In the limited sample considered, median field sizes increased from 45% (France) to 159% (Argentina) and decreased from 47% (Brazil) to 86% (Albania). These changes imply significant impacts on landscape spatial configuration and land use diversity with ecological and biogeochemical consequences.