Dynamic Agricultural Landscape Research Articles

Exploring Agricultural Disparities in Western Odisha: A Comprehensive Study Based on Composite Index Scores

The research endeavor delves into the intricate agricultural disparities prevalent in Western Odisha, focusing on crucial metrics such as land area, yield rates, and production trends spanning the years 2020 to 2022. The study encompassed an extensive scope, encompassing 50 blocks distributed across six carefully selected districts: Nuapada, Jharsuguda, Boudh, Sundargarh, Sambalpur, and Baragarh. These districts were meticulously chosen through a process of simple random sampling from a pool of ten districts in the Western Odisha region. To distill meaningful insights, the research harnessed the power of composite indices, drawn from a comprehensive set of fifteen indicators, each illuminating distinct facets of agricultural development. Through the application of Principal Component Analysis (PCA), five key indicators were expertly extracted from this data set. Drawing upon secondary data sourced from the esteemed Statistical Abstracts of Western Odisha districts, and the Directorate of Economics and Statistics (DES), Government of Odisha (2019-2020), the study validated its assumptions by subjecting the extracted components to the rigors of the Kolmogorov-Smirnov test for normal distribution. Primary data was diligently collected from a cohort of 300 households via meticulously structured questionnaires, encompassing vital parameters such as land area (measured in acres), yield rates (measured in kilograms), and production figures (measured in quintals). It was discovered that the data exhibited deviations from normality, prompting the application of non-parametric methodologies. The ensuing Kruskal-Wallis tests unearthed significant disparities among the identified groups, emphasizing substantial distinctions between the Meteoric, Progressive, Mediocre, and Laggard classifications. To gauge the extent of these disparities, the Gini Coefficient (GC) was aptly employed. The findings underscored that the Meteoric group exhibited more pronounced disparities in land area compared to the other groups, along with marked differences in yield rates. Additionally, this group displayed slightly elevated disparities in production figures. These revelatory results furnish a nuanced understanding of the diverse variances in land area, yield rates, and production levels among the distinct groups. This research endeavor, by shedding light on the dynamic agricultural landscape of Western Odisha, not only highlights the disparities but also offers valuable insights into the underlying factors influencing these agricultural outcomes. These insights, in turn, pave the way for targeted interventions aimed at augmenting agricultural productivity in the region. Addressing these identified disparities emerges as a critical step towards fostering a more equitable and sustainable agricultural sector in Western Odisha.

Exploring the Drivers of Sentinel-2-Derived Crop Phenology: The Joint Role of Climate, Soil, and Land Use

The exploration of crop seasonality across a region offers a way to help understand the phenological spatial patterns of complex landscapes, like agricultural ones. Knowing the role of environmental factors in influencing crop phenology patterns and processes is a key aspect for understanding the impact of climate and land use changes on agricultural landscape dynamics. We identified pixels with similar phenological behavior (i.e., pheno-clusters) and compared them to the land cover map of the study area to assess the role of the land management component in controlling the phenological patterns identified. Results demonstrated that soil texture is the most important factor for permanent crops, while large amount of rainfall and high values of available water content are the main drivers in spring cultivations (i.e., irrigated crops). Scarce water availability (in terms of soil texture, low annual precipitation and high minimum temperature) represented the main driving factor for non-irrigated crops, whose phenology is characterized by summer drought and fall-winter productivity. Compared to vegetation maps that use only land cover from a single season or period, using seasonality of the NDVI time series to classify the agricultural landscape provides different and more ecologically relevant information about croplands.

Об изменении гидрографических характеристик рек в степных агроландшафтах за последние десятилетия (на примере бассейна р. Бейсуг, Краснодарский край)

In the Krasnodar territory, agricultural land occupies 62 % of the territory; of which 79 % is arable land. Most of the agricultural land is located on the Azov-Kuban Plain in the northern part of the region in the steppe river basins. The basin of the Beysug river with an area of about 6,000 km2, in terms of its geographical characteristics, should be attributed to representative basins from the standpoint of the modern dynamics of agricultural landscapes and transformations of the river network. The article analyzes the changes in the steppe agricultural landscapes in the Beysug river basin for the period 1999–2020 in terms of changes in the structure of land use and hydrographic characteristics, based on the data of satellite images. The transformation of agrolandscapes is accompanied by redevelopment of the territory, massive construction of dams on rivers, violation of the conditions of natural drainage, which leads to the restructuring of water exchange processes in river basins. Changes in water exchange processes under semi-arid conditions can be sensitive to local landscapes and agriculture. Until now, insufficient attention has been paid to the hydrological aspects of the transformation of steppe landscapes. According to the DEM ASTER GDEM, 15 river basins were identified with the subsequent determination of land use types on the surface of the basins. In each of the basins, a land use structure has been established, which directly affects the hydrographic indicators, and a decrease in the length of watercourses and the density of the river network has been revealed. Over the past 20 years, in the studied basins, the total length of watercourses due to plowing and redevelopment of the surface has decreased by 8–37 %, and in general in the Beysug river basin—by 469 km.

Dynamic role of grasslands as sources of soil-dwelling insect pests: New insights from in silico experiments for pest management strategies

Sustainable pest control strategies hinge on the knowledge of movement ecology within the agricultural landscape where contrasted habitat qualities intermingle, thereby influencing arthropod dispersal. Hence, habitat manipulation in space and time can be a lever for action to control pests with regard to landscape compositional constraints. In this study, we examined the role of grassland arrangements in field colonisation by soil-dwelling pests within a dynamic agricultural landscape, and discussed the implications for pest management with a focus on wireworms. For this purpose, we proposed a framework combining (i) a spatially explicit and mechanistic model describing the pest population dynamics in both aerial and soil compartments involved along its life cycle, and (ii) spatiotemporal representations of various landscape contexts. We addressed the role of grassland in plot history, in plot neighbourhood, or in both history and neighbourhood. Our results show that species with a short life cycle are more responsive to changes in land use, and that the neighbourhood effect strongly relies on dispersal mechanisms (random vs directed movements). We also highlight how the arrangement of grassy landscape elements in space and time can mitigate crop infestation by soil-dwelling pests, thereby emphasizing the relevance of managing grassland regimes. Once informed by critical pest life traits, our approach opens avenue for the exploration of the spatiotemporal land use manipulation meant for pest management. Future research consists in the exploration of suppressive patterns in simplified but realistic agricultural landscapes, generated under agronomic constraints at the farm or landscape scales.

A brighter future: Complementary goals of diversity and multifunctionality to build resilient agricultural landscapes

Humanity places a heavy burden on agricultural landscapes, demanding plentiful food, multiple ecosystem functions, and biodiversity conservation. We quantified areas growing ‘brighter’ and ‘darker’ (i.e., better or worse than expected based on extrinsic constraints) for multifunctionality of ecosystem services (ES) over time across a dynamic agricultural landscape. To explore how areas changing in ES multifunctionality, we likewise explored temporal changes in additional features of resilience in social-ecological systems, including: (1) species functional richness and dispersion, (2) agrodiversity, (3) the diversity of farm characteristics and human demographics in the area, and (4) landscape structure and diversity. We found areas increasing in multifunctionality were likewise becoming more biologically and agriculturally diverse, without large losses in overall food production. This suggests the potential for complementarity among goals of food production, multiple ES, and biological and agricultural diversity for agricultural landscapes. While we cannot distinguish whether diversity is the driver, or the consequence, of ES multifunctionality, we can conclude that building diverse, multifunctional agricultural landscapes are an important goal for general system resilience and the future of food security.

Changes in habitat selection patterns of the gray partridge Perdix perdix in relation to agricultural landscape dynamics over the past two decades.

Changes in agricultural practices have reshaped agricultural landscapes and triggered a drastic decline in spatial and temporal heterogeneity leading to changes in habitat quality and food resources for birds. However, the precise relationships between landscape changes, spatial and temporal heterogeneity, and habitat preferences in response to those changes remain poorly known.We investigated patterns of habitat selection and causes for changes over the years 1997–2017 for the gray partridge Perdix perdix, an iconic farmland species which has experienced a severe decline since the 1950s. Using a long‐term (1997–2017) dataset collected over 435 km2, we modeled relationships between annual land‐cover maps and partridge sightings over 17 5‐year moving windows, assessing the effects of landscape metrics, the strength of the relationships, and the dynamics of habitat suitability.We detected a shift in gray partridge habitat preferences over time, toward more risky habitats. Avoidance of predator reservoirs (woodlands and buildings) has weakened, and selection of human infrastructure, such as roads and tracks, has increased. Since 1997, the mean size of suitable patches has also decreased by about 26%.We have interpreted these changes in habitat selection as being the result of decreasing habitat quality and the increasing prevalence of captive‐reared birds, currently released in their thousands in the study site. Synthesis and applications. The gray partridge has not adjusted well to changes in farming practices, and the low, still decreasing, population density suggests that it is not sustainable, despite local initiatives and the investment in captive‐bird releases. We emphasize that efforts must be redirected toward habitat improvement to restore the density of refuge cover, insects, and seeds in the landscape, hunting management to ensure self‐sustainable populations and massive releases of high‐quality birds. Only integrated local management, involving hunters, farmers, gamekeepers, and scientists can ensure the recovery of this species.

Contrasting beetle assemblage responses to cultivated farmlands and native woodlands in a dynamic agricultural landscape

AbstractThere is an urgent need to identify ways of managing agricultural landscapes for biodiversity conservation without reducing food production. Farming practices that consider spatio‐temporal heterogeneity of farm fields may be a feasible alternative to large‐scale revegetation of farmlands for maintaining arthropod biodiversity and their important ecological function. We examined seasonal differences in beetle assemblages in woodland remnants and four adjoining farmland uses in a highly modified agricultural landscape in southeastern Australia. The farmland uses were crops, fallows, and two restoration treatments (fine woody debris applied over harvested crop fields, and restoration plantings). Unexpectedly, overall species richness was significantly lower in remnants than in adjacent farmlands. Remnants and farmlands supported significantly different assemblages, with a third of species found in both habitats. Abundance responses were taxon‐specific and influenced by interactions between land use and season. In particular, predator abundance was significantly higher in plantings and fallows during spring compared to summer. Detritivore abundance was significantly higher in the woody debris compared to the adjacent remnants. Herbivore abundance did not differ between remnants and farmlands over time. Complex responses provide strong support for a mosaic of land uses to effectively conserve different beetle groups. Species richness results suggest that further agricultural intensification, in farm fields and through the removal of remnant vegetation, risks reducing beetle diversity in this region. Maintaining farmland heterogeneity with a mix of low‐intensity land uses, such as conservation tillage, crop–fallow rotation, restoration plantings, and the novel application of fine woody debris over cultivated fields, may provide seasonal refuge and resources for beetles.

Simulating spatially-explicit crop dynamics of agricultural landscapes: The ATLAS simulator

The spatially-explicit AgriculTural LandscApe Simulator (ATLAS) simulates realistic spatial-temporal crop availability at the landscape scale through crop rotations and crop phenology. Intended to be linked to organism population dynamics, the simulator is developed in a multi-agent platform. The model relies on initial GIS inputs for landscape composition and configuration. Users define typical rotations and crop phenology stages to be included, according to their objectives. In the study, we present two applications to contrasting landscapes, where ATLAS is capable of simulating accurate composition (crop area) and configuration (crop clustering) dynamics. ATLAS has potential applicability to a range of contrasting agricultural landscapes. The benefits of such a simulator are the possibility to study the effects of various simulated management scenarios of crop spatial-temporal availability in relation to target organisms and/or specific ecological processes (e.g. pest, biological control), within a single model framework.

Agricultural landscape dynamics in response to economic transition: Comparisons between different spatial planning zones in Ningbo region, China

Many major agricultural regions worldwide are experiencing drastic landscape transformations. Examining the complex links among agricultural landscape dynamics (ALD), land use and land cover (LULC) change, socioeconomic development and government planning is pivotal to enhance the efficiency of agricultural landscape management. With a case of the Ningbo region (China), this paper employs the structural equation modeling (SEM) to quantify and compare the relationships between ALD and economic transition as well as the mediating LULC factors in different spatial planning zones. ALD are quantified by time series remotely sensed imageries and a set of landscape metrics; and economic transition is described by a set of indicators from three aspects (globalization, decentralization and marketization). Results show that ALD present similar trend in the two spatial planning zones between 1979 and 2013. However, the magnitude of ALD is larger in the non-urban planning zone. In particular, agricultural landscapes change into the fragmented, irregular, decreased, and isolated patterns at a more rapid pace. Economic transition drivers and LULC mediators differ remarkably between the two spatial planning zones. For the urban planning zone, economic transition influences ALD through construction land morphological changes and water body spatial density increases. For the non-urban planning zone, economic transition influences ALD through forest morphological changes and construction land spatial density increases. In addition, the relative importance of ALD determinants differs between the two spatial planning zones. Marketization plays a more critical role in driving ALD in the urban planning zone, while decentralization has a stronger impact on ALD in the non-urban planning zone. It is argued that land use master plan for agricultural landscape protection should be implemented in the non-urban planning zones and land use plan in the two spatial planning zones should be integrated. This study contributes to the understanding of the complex mechanism of ALD in response to economic transition.

RPG Explorer: A new tool to ease the analysis of agricultural landscape dynamics with the Land Parcel Identification System

In the early 2000s a Land Parcel Identification System (LPIS) was set up by each member state of the European Union, to manage agricultural subsidies. These databases describe field geometry and landcover, and provide information on farm characteristics. LPIS data could therefore be used to describe agricultural landscape dynamics, but are seldom put to this purpose by scientists and local stakeholders because it requires the use of GIS software and programming skills. The objective of this paper is thus to present RPG Explorer, a new tool that we developed to analyze agricultural landscape dynamics with LPIS data. RPG Explorer doesn’t require any specific skills in GIS and programming allowing non specialist to deal with complex data.RPG Explorer includes a first module which computes the changes in crop proportions and farm characteristics (numbers of farm, farm area, farm type). A second module computes crop sequences on each farmer block of LPIS data. We also included a crop rotation model in a third module.We illustrated the use of RPG Explorer for two example neighboring catchments located in western France, the Vivier catchment (16,000ha) and the Courance catchment (15,000ha). For example, RPG Explorer easily revealed the evolution of crop proportions, such as the increase of temporary grasslands in the Courance catchment (from 7.2% of the Utilized Agricultural Area (UAA) in 2007 to 11.7% in 2013). The number of farms was also shown to vary a lot: from 230 in 2007 to 207 in 2013 for the Vivier catchment, with a subsequent increase of their mean UAA (from 101ha to 119ha). RPG Explorer also showed that more than half of the Vivier catchment UAA (59%) was occupied by only 50 farms in 2013. Concerning crop sequences, the sunflower → winter wheat sequence was the most frequent 2-year sequence in both catchments, but some differences appeared with for example, a higher proportion of winter wheat → winter wheat sequence in the Courance catchment (7.2% against 3.6%). Crop rotation modeling indicated that the rapeseed → winter wheat → sunflower → winter wheat, sunflower → winter wheat and maize monoculture were the three main crop rotations.Finally, these examples illustrate well the ability for scientist and local stakeholders to easily describe some major agricultural landscape dynamics with RPG Explorer.

Underestimating neonicotinoid exposure: how extent and magnitude may be affected by land-use change.

Potential detrimental impacts of neonicotinoids on non-target organisms, especially bees, have been subject to a wide debate and the subsequent ban of three neonicotinoids by the EU. While recent research has fortified concerns regarding the effects of neonicotinoids on ecosystem service (ES) providers, potential impacts have been considered negligible in systems with a relatively small proportion of arable land and thus lower the use of these pesticides. In this paper we argue that there is not sufficient information to assess magnitude and extent of neonicotinoid application, as well as potential non-target impacts on ES providers in grass-dominated systems with frequent land-use change. Using Ireland as an example, we show that the highly dynamic agricultural landscape, in conjunction with estimated persistence times of neonicotinoids in soils, may lead to a much larger area (18.6 ± 0.6% of the Irish agricultural area) exposed to these pesticides than initially assumed. Furthermore we present a number of important gaps in current research regarding the impacts of neonicotinoids on ES providers in such systems.

农业景观动态对林地地表节肢动物多样性的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 农业景观动态对林地地表节肢动物多样性的影响 DOI: 10.5846/stxb201405150993 作者: 作者单位: 河南大学,河南大学,河南大学,河南大学,河南大学,河南大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目(41071118,41371195) Effects of agricultural landscape dynamics on the species diversity of ground arthropods in woodlands Author: Affiliation: Henan University,,,Henan University,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:以黄河下游典型农区封丘县为研究区,在林地景观中进行地表节肢动物的观测。用物种丰富度和香农多样性指数代表物种多样性,选择代表景观背景的5个竞争模型:生境特性(H1, 2012)、基质特性(H2, 2012)、生境变化(H3, 1984-2012)、基质变化(H4, 1984-2012)和土壤-环境条件(H5, 2012)从4个空间尺度上(100, 250, 350和500 m)进行分析,通过运用基于赤池信息量准则(Akaike information criterion, AIC)的多模型推理(Multi-model Inference, MMI)方法,在R软件里用广义线性模型(Generalized Linear Models, GLM)探究了研究区近30年(1984-2012年)景观背景变化对林地地表节肢动物多样性的影响。研究表明,不同景观背景模型对地表节肢动物多样性的影响具有尺度依赖性。在100 m的尺度下,生境特性(H1)最能够解释香农多样性和物种丰富度,但是随着尺度的增加,生境特性变化(H3)在较大(250、350 m和500 m)的尺度对物种丰富度和香农多样性影响最大,而基质特性和土壤-环境条件(H2和H5)的作用不显著。景观背景对地表节肢动物多样性的解释量达到40%。在研究区域,生境特性是表征香农多样性指数和物种丰富度的指标。 Abstract:Biodiversity is one of the most limiting factors for ecosystem services. It is well known that there are very close connections between agricultural ecosystems and species diversity. Large numbers of non-agricultural wildlife rely on the food and habitats provided by the agricultural landscape. Natural and semi-natural habitats (such as farmland boundaries, woodland, hedges, and creeks) in agro-landscapes have very important effects on ground arthropods inhabiting these microenvironments. The lower reaches of the Yellow River, China, is a major grain producing areas in China, and is important for the security of the national food supply. It is crucial to study the relationships between regional agro-landscape heterogeneity and biodiversity to maximize ecosystem services and to maintain ecosystem stability. In this study, Fengqiu County in Henan Province, which is a typical agricultural region in the lower reaches of the Yellow River, was selected to investigate the effects of agricultural landscape dynamics on the species diversity of ground arthropods in woodlands. The Shannon diversity index and species richness were applied to explore the relationships between landscape changes and arthropod diversity from 1984 to 2012. The role of the landscape context on ground arthropod diversity in woodlands was evaluated by a multi-model inference (MMI) based on the Akaike information criterion (AIC). Five competing models of landscape context were used to analyze how it impacts arthropods. These models included habitat quality (H1, 2012), matrix quality (H2, 2012), habitat change (H3, 1984-2012), matrix quality change (H4, 1984-2012), and soil-environmental conditions (H5, 2012). All of these models were measured respectively at four spatial scales (100, 250, 350, and 500 m) to examine how spatial scales impact ground arthropod diversity. The relationship between the response variables and the predictor variables was analyzed by Generalized Linear Models (GLM) in R statistical software. From 1984 to 2013 in the study area, woodland area increased significantly, while agricultural landscape heterogeneity increased substantially. The dominant groups of ground arthropods included Hymenoptera, Coleoptera, Amphipoda, and Araneae. The impacts of landscape context on ground arthropod diversity in woodlands were significantly scale-dependent. Habitat quality (H1) was the highest supported model for explaining Shannon diversity index and species richness of the ground arthropod community at a small scale (100 m). As the spatial scale increased, the Shannon diversity index and species richness responded mostly to habitat change quality (H3) in the broader surroundings (250, 350, and 500 m). No significant correlation was observed between matrix quality and soil-environmental conditions (H2 and H5). The responses to landscape context of ground arthropod species richness and Shannon diversity index were fairly consistent, significantly responding to habitat quality. Approximately 40% of variation in ground arthropod diversity was explained by the landscape context. In the study area, habitat quality (H1) may represent a good indicator for the Shannon diversity index and species richness. The analytical results showed that historic landscape change also has a predominant influence on the present features of ground arthropod diversity in woodlands;thus, the temporal dynamics of the landscape context may help towards improving our understanding about the interactions between landscape context change and ground arthropod diversity in woodlands. To enhance the explanation for the effects of landscape context on ground arthropods, further studies should consider additional landscape competing models and multi-scale spatiotemporal analysis. 参考文献 相似文献 引证文献

Agricultural landscape pattern changes in response to urbanization at ecoregional scale

Resource preservation efforts are increasingly made at ecoregional scale rather than at administrative level. However, the impact of urbanization on agricultural land at ecoregional scale remains poorly understood. This study integrated remote sensing, geographic information systems, landscape metric analysis, and spatial regression, to quantify agricultural landscape pattern changes in response to urbanization at ecoregional scale, with a case of Qiantang River watershed in China. Results showed that between 1979 and 2009 urbanization accelerated based on four indicators: gross domestic product (GDP), total population (TP), non-agricultural population proportion (NAPP), and expansion intensity index (EII). Characterized by five metrics, agricultural landscapes became less dominant and aggregated, but more instable, fragmented and irregular. Relationships between agricultural landscape pattern changes and urbanization presented great variability, as they differed through time and varied from variables (both urbanization indicators and landscape metrics). Generally, EII was the most powerful urbanization indicator explaining agricultural landscape pattern changes at ecoregional scale. GDP acted as influential factor during periods 1979–1985 and 1985–1994, corroborating the statement that economy was the main contributor to agricultural landscape pattern changes during the 1980s in China. Demographic factors, NAPP in particular, exerted no significant impact. Our study demonstrated an effective approach to identifying key urbanization indicators that governed agricultural landscape dynamics.

Land abandonment and the dynamics of agriculturallandscapes in Mediterranean mountain environments: the case of Ribagorça (Spanish Pyrenees)

Land abandonment and the dynamics of agriculturallandscapes in Mediterranean mountain environments: the case of Ribagorça (Spanish Pyrenees)

Landscape agronomy: a new field for addressing agricultural landscape dynamics

Landscape dynamics increasingly challenge agronomists to explain how and why agricultural landscapes are designed and managed by farmers. Nevertheless, agronomy is rarely included in the wide range of disciplines involved in landscape research. In this paper, we describe how landscape agronomy can help explain the relationship between farming systems and agricultural landscape dynamics. For this, we propose a conceptual model of agricultural landscape dynamics that illustrates the specific contribution of agronomy to landscape research. This model describes the relationship between three elements: farming practices, landscape patterns and natural resources. It can stimulate agronomists to deal with research issues in agricultural landscape dynamics and enhance the interdisciplinary integration of farming systems in wider landscape research. On these premises, we discuss the main research issues that will benefit from an active involvement of agronomy, to understand, but also to assess landscape dynamics and to design relevant decision support systems.

Influence of spatial and temporal dynamics of agricultural practices on the lesser kestrel

Summary1. European agriculture is facing dramatic changes that are likely to have marked impacts on farmland biodiversity. There is an urgent need to develop land management strategies compatible with the conservation of biodiversity.2. We applied a spatially explicit behaviour‐based model to assess how farmland management and the pattern of events across the annual farming calendar influences the foraging decisions of lesser kestrelsFalco naumanniin a cereal steppe landscape. Moreover, we simulated the most likely scenarios of future agricultural changes to predict its impacts on lesser kestrel breeding success. Lesser kestrels have been the subject of serious conservation concern and constitute a good model species to judge impacts on farmland species more widely.3. Our results show that the location of cereal and fallow patches within a 2‐km radius of a kestrel colony influences the total food supply delivered to the nestlings, explaining the differences in breeding success between years and colonies. Furthermore, the particular sequence in which patches are harvested by farmers is also predicted to influence offspring survival.4. Agricultural intensification, simulated by increasing the proportion of cereal fields, is predicted to negatively influence breeding success. However, the field harvesting sequence can play an important role in alleviating the effects of the increased percentage of cereal, as demonstrated by the higher breeding success obtained when harvesting starts from patches farthest from the colonies. The replacement of cereal cultivation by low‐intensity grazed fallows would not be detrimental for kestrels.5. Synthesis and applications. Our results highlight the effectiveness of behaviour‐based models to evaluate the interacting effect of spatial and temporal dynamics of agricultural landscapes and predict the response of populations to environmental change. To optimize food availability for lesser kestrels, land managers should implement long rotational schemes with <60% of the area under extensive cereal cultivation in a 2‐km radius around colonies. Harvesting should start in the cereal patches farthest from colonies. Ideally, the predominant land use around colonies should be fallows. These outcomes illustrate how behaviour‐based models can be applied to identify specific management recommendations that would improve the effectiveness of agri‐environmental schemes, the most accepted tool for maintaining farmland landscapes.

Occupancy and abundance of wintering birds in a dynamic agricultural landscape

AbstractAssessing wildlife management action requires monitoring populations, and abundance often is the parameter monitored. Recent methodological advances have enabled estimation of mean abundance within a habitat using presence–absence or count data obtained via repeated visits to a sample of sites. These methods assume populations are closed and intuitively assume habitats within sites change little during a field season. However, many habitats are highly variable over short periods. We developed a variation of existing occupancy and abundance models that allows for extreme spatio‐temporal differences in habitat, and resulting changes in wildlife abundance, among sites and among visits to a site within a field season. We conducted our study in sugarcane habitat within the Everglades Agricultural Area southeast of Lake Okeechobee in south Florida. We counted wintering birds, primarily passerines, within 245 sites usually 5 times at each site during December 2006–March 2007. We estimated occupancy and mean abundance of birds in 6 vegetation states during the sugarcane harvest and allowed these parameters to vary temporally or spatially within a vegetation state. Occupancy and mean abundance of the common yellowthroat (Geothlypis trichas) was affected by structure of sugarcane and uncultivated edge vegetation (occupancy = 1.00 [${\rm 95\%}\,{\rm C\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over I} }$ = 0.96–1.00] and mean abundance = 7.9 [${\rm 95\%}\,{\rm C\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over I} }$ = 3.2–19.5] in tall sugarcane with tall edge vegetation versus 0.20 [${\rm 95\%}\,{\rm C\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over I} }$ = 0.04–0.71] and 0.22 [${\rm 95\%}\,{\rm C\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over I} }$ = 0.04–1.2], respectively, in short sugarcane with short edge vegetation in one half of the study area). Occupancy and mean abundance of palm warblers (Dendroica palmarum) were constant (occupancy = 1.00,${\rm 95\%}\,{\rm C\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over I} }$ = 0.69–1.00; mean abundance = 18,${\rm 95\%}\,{\rm C\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over I} }$ = 1–270). Our model may enable wildlife managers to assess rigorously effects of future edge habitat management on avian distribution and abundance within agricultural landscapes during winter or the breeding season. The model may also help wildlife managers make similar management decisions involving other dynamic habitats such as wetlands, prairies, and even forested areas if forest management or fires occur during the field season. © 2011 The Wildlife Society.

Biological conservation in dynamic agricultural landscapes: Effectiveness of public policies and trade-offs with agricultural production

Land use change and land management intensification are major drivers of biodiversity loss, especially in agricultural landscapes, that cover a large and increasing share of the world's surface. Incentive-based agri-environmental policies are designed to influence farmers' land-use decisions in order to mitigate environmental degradation. This paper evaluates the effectiveness of agri-environmental schemes for biological conservation in a dynamic agricultural landscape under economic uncertainty. We develop a dynamic ecological economic model of agricultural land-use and spatially explicit population dynamics. We then relate policies (subsidies to grassland, taxation of agricultural intensity) to the ecological outcome (probability of persistence of a species of interest). We also analyze the associated trade-offs between agricultural production (in value) and biological conservation (in probability of persistence) at the landscape scale.

Transformation of agricultural landscapes under rapid urbanization: A threat to sustainability in Hang-Jia-Hu region, China

This paper analyzed the spatiotemporal dynamics of agricultural landscapes within Hang-Jia-Hu region (China) from 1994 to 2003 using a set of metrics that relate closely with sustainability. Considerable urban expansion was identified with the total built-ups increasing by 224.7% from 6.99 × 104 ha to 22.7 × 104 ha. The outcomes indicated that, at the whole region scale, agricultural landscapes became lost, fragmented, transformed and isolated as urbanization intensified. Global Moran’s I statistics and Local Indicators of Spatial Association (LISA) analysis were employed to characterize the spatial dependence and hotspots for intra-level agricultural landscape changes at two grid scales. Generally, isolation of agricultural patches was a localized problem, while shape transformation of agricultural landscapes was a more regionalized problem; hotspots for lost, fragmentation and irregularity of agricultural landscapes concentrated around urban centers, while those for isolation of agricultural patches appeared in rural mountain areas. Spatial regression models further revealed that changes of agricultural landscapes showed diverging relationships with urbanization indicators for each landscape metric. The character and strength of relationships for each landscape metric were different and changed with scale. While our results of agricultural landscape changes consisted with some theoretical predictions in the literature, they also showed different spatiotemporal signatures of urbanization. Resolving these differences will certainly contribute to the ongoing landscape transformation and sustainability debate. This study demonstrated complexities of relationships between urbanization and agricultural landscape changes, and highlighted the importance of selected variables, spatial and temporal scales and incorporation of spatial dimensions when quantifying these relationships.

Quantifying spatiotemporal dynamics of agricultural landscapes using remotely sensed data and landscape metrics

This study focuses on the spatiotemporal dynamics of agricultural lands and differences in rapidly developing urban and declining rural counties in Iowa, USA between 1984 and 2000. The study presents an analysis of land-cover maps derived from Landsat TM and ETM+ satellite imagery and different landscape metrics using FRAGSTATS and IDRISI software. The study provides evidence of both loss of croplands and change in fragmentation between 1984 and 2000. Fragmentation in agriculture-dominated areas increased with the development of urban centres and diversification of land uses. Fragmentation of landscapes, including agricultural land, was found to be higher in the urbanized counties, but was stable or even declined over time in these counties. In contrast, in the context of remote rural areas, agricultural landscapes experienced rapid increase in fragmentation and farmland loss. The urban–rural gradient analysis used in this study showed that the highest fragmentation occurred on the city edges. These findings suggest that farmland fragmentation is a complex process associated with socio-economic trends at regional and local scales. In addition, socio-economic determinants of landscape fragmentation differ between areas with diverging development trajectories. Intensive cropland fragmentation in remote agricultural regions, detected by this research, should be further studied and its possible effects on both agricultural productivity and biodiversity should be carefully considered.