Crop Landscape Research Articles

Predicting the effect of landscape structure on epidemic invasion using an analytical estimate for infection rate.

The influence of landscape structure on epidemic invasion of agricultural crops is often underestimated in the construction and analysis of epidemiological models. Computer simulations of individual-based models (IBMs) are widely used to characterize disease spread under different management scenarios but can be slow in exploring large numbers of different landscape configurations. Here, we address the problem of finding an analytical measure of the impact of the spatial structure of a crop landscape on the invasion and spread of plant pathogens. We explore the potential of using an analytical approximation for the rate, , at which susceptible crop fields become infected at the start of an epidemic to predict the effect that the spatial structure of a host landscape will have on an epidemic. We demonstrate the validity of this approach using two models: (i) a general IBM of the invasion and spread of a pathogen through an abstract host landscape; and (ii) an IBM of a real-life example for a virus disease spreading through a cassava landscape. Finally, we demonstrate that the analytical approach based on an estimate of the rate, , can be used to identify spatial structures that effect deceleration of an invading pathogen.

Landscape composition and orchard management effects on bat assemblages and bat foraging activity in apple crops

AbstractBats are acknowledged as suppliers of essential ecosystem services such as insect pest control in agroecosystems. Little is known, however, on how bat assemblages respond to the gradients imposed by anthropogenic landscapes and farming practices and how these environmental effects translate into changes in bat foraging. In this study, we use cider apple crop in northern Spain as a model to address the filtering effects of landscape composition and orchard management on, simultaneously, quantitative and qualitative characteristics of bat local assemblages and their foraging activity. For that, we carried out acoustic monitoring of bats and sampled pest moth abundance across a wider range of apple orchards covering different landscape contexts and local management conditions. We found that bat assemblages markedly varied across orchards, according mostly to landscape composition gradients but with contrasting landscape effects on different assemblage characteristics. Namely, higher levels of rural urbanization and lower cover of seminatural woody habitats around orchards promoted bat total activity and the number of bat species/species complexes. However, this also altered bat assemblage composition, increasing dominance by the most abundant species, and decreased bat functional diversity. Additionally, a greater cover of apple tree canopy within the orchards decreased bat total activity. Landscape gradients led into predictable variations of bat foraging activity, suggesting a potential persistence of pest control services even in landscapes with limited seminatural habitat cover. The present study highlights the differential responses of bat assemblages to apple crop landscape and orchard‐scale conditions, hindering the establishment of straightforward management guidelines. Further analysis on the relationship between bat assemblage characteristics and pest control is necessary to understand how ecosystem services can be promoted through management in the apple agroecosystem.

Landscape crop diversity contributes to higher pollination effectiveness and positively affects rapeseed quality in Mediterranean agricultural landscapes

Pollination is crucial for biodiversity and food security. Heterogeneous agricultural landscapes have a positive effect on pollinator abundance and enhance crop production and quality. In this study, we explored the effects of three landscape features (past crop diversity measured as the Equivalent Richness of crop functional Groups in the previous year [ERGp], semi-natural habitat percentage [SNH], and mean field size [MFS]) and pollinator densities (wild bees [WB] and honey bees [HB]) on pollination and seed quantity and quality in rapeseed crops. Surveying the pollinator density in 20 rapeseed fields revealed a positive relationship with ERGp in the landscape. A pollinator exclusion experiment compared bagged and open-pollinated self-compatible rapeseed plants and revealed insect pollination effectiveness (fruits per flower and number of seeds per pod) and seed quality (oil content). Seed parameters were evaluated in relation to pollinator density (WB-HB) and landscape characteristics. The ERGp emerged as a crucial landscape feature that positively impacted WB density. When insect pollinators were excluded, plants exhibited reduced pollination effectiveness and seed quality. Analysis of open-pollinated plants highlighted ERGp as the most influential variable, positively affecting both sets of parameters. The MFS and SNH showed different but important relationships. Total tocopherol and α-tocopherol were positively correlated with pollinator density in HB, whereas WB showed a positive correlation with γ-tocopherol levels. Increased ERGp positively affected pollinator density and pollination effectiveness, thereby improving oilseed rape production quantity and quality. This study provides new insights into agroecosystem management and pollinator-friendly practices.

Regulation of surface and sub-surface soil organic carbon sequestration in water-limited landscapes with integration of circular perennial grass buffer strips

Soil organic carbon (SOC) sequestration through innovations in agriculture, including integrating perennial grasses with annual crops, can mitigate climate change. However, integrating circular buffer strips (CBS) of perennial grasses with annual crops in water-limited semi-arid landscapes is a new concept, and how SOC and nitrogen (N) pools respond to CBS and what drives SOC sequestration in the surface and sub-surface depths with CBS integration in typical annual cropping is lacking. Our evaluation of the response of SOC and N fractions under buffer strip grass (BSG), adjacent buffer strip corn (BSC), and continuous conventional corn (CCC) without grass buffer after six years of grass establishment show contrasting trends. The SOC in 0–20 cm depth was 13.1 % greater under BSC than under CCC, while BSG had 49.7–68.2 and 17–29.9 % greater potentially mineralizable carbon (PMC) than CCC and BSC in 40–60 and 60–80 cm, respectively. Mineral-associated organic carbon (MAOC) in 60–80 cm depth was 29.9 % greater under BSG than CCC. Soils under BSC also accumulated 65.6 % more particulate organic carbon (POC) than under CCC in 0–20 cm. While POC contributed to SOC sequestration in surface soils, an increase in MAOC contributed to SOC accumulation in deeper profiles. Integrating buffer strips of perennial grasses enhances soil profile C sequestration in semi-arid agroecosystems through divergent mechanisms in surface and subsurface depths.

Exploring optimal features and image analysis methods for crop type classification from the perspective of crop landscape heterogeneity

Agricultural landscape structure (e.g., the shape of fields, crop diversity, and landscape heterogeneity) greatly influences the selection of methods for large-scale crop mapping using remote sensing data. However, in-depth assessments of its impacts on crop mapping remain infrequent in the existing literature. This study investigated the optimal crop identification features and image analysis methods including pixel- and object-based approaches on crop classification, through the integration of spectral and textural features across various quantitative agricultural landscapes. In the experiments, crop fields were initially delineated into four distinct landscapes using the K-means clustering algorithm based on analyzing 13 selected landscape metrics such as PLAND, LSI and SHDI. Both pixel- and object-based approaches were then employed to conduct crop classification was then conducted using 48 selected features including 9 band reflectance, 23 vegetation indices (VIs), and 16 textures) and two image analysis methods. Specifically, five classification schemes for the different combinations of feature datasets and image analysis methods were explored to assess the impacts of crop heterogeneity on crop classification. Results indicated the five landscape metrics (e.g., SPLIT, SHEI, Average distance, etc.) performed best in assessing crop heterogeneity. In general, spectral bands and VIs had a higher contribution in the compositional heterogeneity, while textural features and VIs played a more important role in the configurational heterogeneity. VIs in the object-based approach and texture features in the pixel-based approach can improved crop classification accuracy in configurational landscapes. The findings provide a theoretical basis on selecting optimal features and image analysis methods for crop classification in complex agricultural landscapes.

Deer in the agriculture-forest matrix: Interacting effects of land uses on browsing pressure on trees

Cervids inhabit mosaic landscapes that are strongly influenced by human land use and actions. Forestry and agriculture influence both the foodscape and the risk landscape, thus influencing how cervids respond to resource-risk trade-offs. Furthermore, these land use types interact to shape cervid use of the landscape. For example, cervids can forage in open agricultural fields providing high quality forage during the night, while using nearby forest patches to reduce risk during the day. Hence, actions conducted in one of these land use types will likely influence the use of the other by cervids. In this study, we investigate how agricultural and silvicultural practices interact to shape cervid use of the forest and their impact on commercially valuable trees. More specifically, we investigate the effect of growing nutrient dense crops in mixed forest-agriculture landscapes. We hypothesized that the sowing of such crops may not only attract cervids to the agricultural parts of the landscape, but also lead to increased browsing levels in adjacent forest areas where cervids seek cover. Moreover, such high quality crops may not only influence the number of animals, but also increase the intake rate of fibrous tree saplings of individual cervids to nutritionally balance the high input of easily-digestible macronutrients from the crops. We tested these ideas by conducting a large landscape-scale experiment where we manipulated the foodscape by growing two crop types on 28 fields (14 fields with high-quality oat versus 14 fields with lower-quality grass) and measuring cervid use of tree saplings in the forest patches adjacent these fields. We also investigated how forage availability in the forest patches and the distance from field edge affected browsing on tree saplings. Finally, we compared the effects of crop type and forest forage availability on the browsing pressure on coniferous versus deciduous tree species. We studied this in a multispecies ungulate system, where four cervid species occur sympatrically. We show that the type of crop sown influenced browsing pressure on tree saplings in nearby forests, with higher browsing levels in forests surrounding oat compared to grass fields. Moreover, browsing pressure in these forests was influenced by the availability of young trees in the forest stands, where more young trees led to reduced browsing pressure on individual saplings. Our study emphasizes that human practices that shape features of the foodscape in one land use type will influence the impact cervids have in another land use type. Hence, our study highlights the importance of considering the actions and impacts of different land uses simultaneously for predicting cervid foraging patterns in mixed forest-agriculture landscapes.

Expansion of apple cultivation increases the abundance of codling moth (Cydia pomonella) in agricultural landscapes of China.

Agricultural land-use change is an important driver of pest population dynamics, and can alter source-sink dynamics and the concentration-dilution effects of the landscape. Understanding the effects of land use on pests at both landscape and regional levels is essential for the development of sustainable pest management strategies given the large changes occurring in cropping systems in China. At the landscape level, we investigated the impacts of landscape composition and edge density on pheromone trap catch of codling moth (Cydia pomonella) in apple orchards, in Aksu, Xinjiang, China. At the regional scale, we conducted a meta-analysis using data from studies performed across the Aksu area in recent decades, to assess the relationship between trends in codling moth abundance and the area of apple cultivation. Both extensive planting of apple and large areas of annual crops in the landscape increased the abundance of codling moth, whereas the presence of secondary host plants (peach, pear, walnut, plum, and apricot) had a negative effect. Seminatural habitats and landscape edge density did not significantly affect codling moth abundance. The responses of different generations of codling moth to landscape factors were varied. At the regional level, codling moth occurrence was positively correlated with the expansion of apple production areas. Expansion of apple cultivation increases the abundance of codling moth in agricultural landscapes. We recommend decreasing the area devoted to monocultures of apple when designing agricultural landscapes and increasing plantings of secondary host crops to dilute and reduce the abundance of codling moth. © 2024 Society of Chemical Industry.

Different management strategies exert distinct influences on microclimate of soil and canopy in tea fields through surface-atmosphere interactions

Agricultural management strategies are crucial in regulating the soil-atmosphere interaction. The crop landscape is influenced by farmers through different field practices, and further impacts the variations of soil temperature, soil moisture, and field microclimate. To examine how different management strategies affect the dynamics of canopy and soil parameters (canopy temperature, soil temperature and soil moisture) and the aforementioned interaction, two observation systems were installed in an organic-certified (ORG) tea field and a conventional (CONV) tea field in northern Taiwan. Due to the application of different field practices, the leaf area in ORG is higher. The results show that the diurnal range of canopy temperature in CONV was larger than that in ORG (7.52 °C vs 5.97 °C). However, the daily loss rate of soil water content in ORG was two times faster than that in CONV (0.97% d−1 vs. 0.45% d−1). The outcomes imply that the organic practices in this study lead to higher evapotranspiration and milder variation in temperature on the canopy scale. These findings suggest that the application of organic practice could help to mitigate the changes of microclimate in tea field. In addition, the adoption of appropriate management strategies could assist farmers in adapting to environmental fluctuations and provide quantitative references of microclimate in tea field under different agricultural applications and climatic conditions.

Integrating perennial staple food crops in agroforestry systems: A case study of chestnut (Castanea sp.) in Germany

In a time of multiple global challenges, trees gain more and more attention as an important component of sustainable land use systems, as they can produce food and provide multiple other ecosystem services at the same time. In Germany, traditional orchard meadows (so-called “Streuobstwiesen”) are in decline, although they are well known for their ecological value. In modern agroforestry systems staple perennial food crops seem to be rarely integrated. Here, we propose to use emerging chestnut cultivation for revitalizing traditional orchard meadows, diversifying forests, and integrating perennial staple food crops in modern agroforestry systems. In this study, we interviewed 64 chestnut growers in Germany and aimed to (1) explore characteristics of chestnut stands and management; (2) evaluate the main motivations, aims, and challenges of chestnut growers; (3) identify perceived outcomes of chestnut cultivation and measures for upscaling; and (4) analyze differences between groups of chestnut growers. Our results show that most growers aimed to increase tree numbers and foster the spread of chestnut trees as cultural assets. Sustainable food production was the motivation most often named by the respondents. A guide for cultivation, as well as better funding, were mentioned as the most wanted and easy to implement measures for up-scaling production and consumption. Junior chestnut growers were better connected to other chestnut growers and were more motivated by sustainable food production than senior growers. Pest and diseases as well as legal and funding situations were aspects hampering chestnut cultivation. We suggest that chestnut trees can serve as a valuable element of a diverse tree crop landscape providing staple food crops while supporting ecosystem services.

Is olive crop modelling ready to assess the impacts of global change?

Olive trees, alongside grapevines, dominate the Mediterranean tree crop landscape. However, as climate change intensifies, the Mediterranean region, which encompasses 95% of the global olive cultivation area, faces significant challenges. Rising carbon dioxide (CO2) levels, increasing temperatures, and declining precipitation pose substantial threats to olive tree performance. Photosynthesis, respiration, phenology, water use and ultimately yield are possibly the main factors affected. To address this future scenario, it is crucial to develop adaptation and mitigation strategies. Nevertheless, breeding programs and field management practice testing for tree crops are time-consuming endeavors. Fortunately, models can accelerate the evaluation of tailored solutions. In this review, we critically examine the current state of olive tree modeling and highlight key areas requiring improvement. Given the expected impact of climate change, prioritizing research on phenology, particularly regarding bloom and pollination, is essential. Simulations of biomass should incorporate approaches that account for the interactive effects of CO2 and temperature on photosynthesis and respiration. Furthermore, accurately simulating the influence of water stress on yield necessitates the development of models that integrate canopy behavior with root performance under conditions of water scarcity. By addressing these critical aspects, olive tree models can enhance our understanding of climate change impacts and inform sustainable agricultural practices.

Within-field spatial patterns of Helicoverpa zea (Lepidoptera: Noctuidae) and spatial associations with stink bugs and their injury in field corn.

The corn earworm, Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), is a cosmopolitan pest in the field crop landscape in the southeastern United States. Field corn (Zea mays L.) is the most important midseason host for H. zea where intensive selection pressure occurs for resistance to insecticidal toxins from Bacillus thuringiensis (Bt). Because spatial patterns of H. zea in field corn have not been extensively studied, field corn was sampled for H. zea larvae and injury in 2021 and 2022. Patterns of spatial aggregation were identified in a number of fields in both larval populations and injury. Aggregation of H. zea larvae was less common at R5 than at R2. Associations between the spatial patterns of H. zea and the variability in crop phenology were identified in some fields, with positive associations between plant height and H. zea larvae, indicating that ovipositing H. zea moths avoid areas with reduced plant height and delayed reproductive maturity. Additionally, negative spatial associations between stink bug ear injury and H. zea larvae and their injury were found in a small number of cases, indicating some spatial interactions between the two pest complexes and their injury. Results from these studies provide valuable insight into the spatial patterns of H. zea in field corn. An understanding of the local dispersal and population dynamics of H. zea can be used to help further improve integrated pest management and insect resistance management programs for this major polyphagous pest.

Passive monitoring of avian habitat on working lands.

Intensive agricultural landscapes are a challenge for wildlife managers, policy makers, and landowners hoping to increase the diversity of desired wildlife species, such as grassland birds, which require urgent conservation action. In intensive agricultural landscapes, like those of the midwestern USA, most land area is privately owned and operated and managed primarily for production. Conducting ecological research in intensive agricultural landscapes thus requires collaborative approaches aimed at farm owners and operators. Recent advances in acoustic data collection and high-resolution habitat mapping, including low-cost acoustic recorders and satellite remote sensing, may be well positioned to address this challenge by enabling expanded assessments and monitoring of wildlife populations and habitats across regions. This study examined fine grain habitat characteristics and their relationship with avian biodiversity in intensive agricultural landscapes at 44 agricultural sites across Iowa, USA. Passive acoustic monitoring and manual identification of bird species allowed for measurement of vocalizing bird richness. High resolution mapping of noncrop vegetation provided detailed information on small noncrop vegetation habitat complexes within row-crop agriculture. Measures of image texture provided characterizations of compositional heterogeneity within noncrop vegetation. General linear Poisson modeling demonstrated robust associations between noncrop vegetation and vocalizing bird richness, yet variation in grassland bird richness was not well predicted by noncrop vegetation. Noncrop vegetation texture demonstrated potential as a predictor of vocalizing bird richness, though not better than or when combined with noncrop vegetated area, indicating it may not be an independent measure of habitat quality. Passive acoustic monitoring resulted in useful data at 44 out of 60 originally selected sites, with some lost to failed recorders and/or collaboration issues. Challenges remain in detecting habitat characteristics that promote grassland birds in row crop landscapes. Working toward probabilistic research design across privately owned working landscapes and incorporating more detailed management practice information would improve the transferability of this approach to farmland management and policy.

Retrieval of crop biophysical-biochemical variables from airborne AVIRIS-NG data using hybrid inversion of PROSAIL-D

Sustainable agricultural growth and management reduces over-utilization of farm resources and squeezes risk of negative impacts on environment. Monitoring continuous crop growth and health under various conditions at different spatio-temporal resolutions is a key to assess yield stability, crop diversity, adaptability, mitigation for stress and response. The quantification of crop biophysical and biochemical variables spatially from remotely sensed data with help of spectroscopic methods provide a reliable discerning information in the context of crop foliar condition like leaf greenness, senescence, canopy density, crop growth, stress and eco-physiological processes. Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) airborne hyperspectral data offers high spatial and spectral resolution giving a unique advantage and opportunity to test retrievals of crop biophysical (BP)-biochemical (BC) variables under varying conditions over different types of crops. A hybrid inversion of leaf-canopy Radiative Transfer model – PROSAIL-D complemented with use of data driven nonlinear non-parametric methods which offer simplicity, fastness, reliability and competency is a powerful method to retrieve crop biophysical and biochemical variables. The Hyperspectral band (feature) selection is a computationally cost efficient method to overcome data redundancy in high dimensional correlated input spectral bands. The determination of optimum subset or combination of hyperspectral bands specific to retrieval of vegetation properties (including canopy effects) determined using feature selection algorithm for regression-based retrievals are active research topic unlike classification problems in which it is more common. A band selection algorithm based on Gaussian Processes Regression was used to choose most sensitive bands from in-situ biophysical-biochemical measurements and crop spectral signatures collected for analysis in two different agricultural regions: Raichur (Karnataka) and Anand (Gujarat) districts of India representing diverse landscapes, heterogeneous crop canopies and agro climatic settings. The retrieval algorithm for AVIRIS-NG image employed a decision tree ensemble algorithm Canonical Correlation Forests using the optimum subset of bands for retrieval of targeted crop variable. Validation of retrieved crop variables were done using in-situ ground observations collected over heterogeneous diverse crop landscape. The results showed chlorophyll (RMSE = 6.61 µg cm−2), equivalent water thickness (RMSE = 0.002 cm), leaf area index (RMSE = 0.35 m2/m−2) and dry matter (RMSE = 0.003 g cm−2), carotenoid (RMSE = 14.3 µg cm−2), anthocyanin (RMSE = 12.92 µg cm−2) retrieved with better accuracies. The results obtained in context of feature (band) selection approach for Radiative Transfer model inversion show overlapping of sensitive spectral bands of chlorophyll-ab, carotenoid and anthocyanin especially between narrow spectral range 480 to 560 nm as predominant reason for decreased accuracies of anthocyanin and carotenoid compared to other variable. This poses a limitation as well as opportunity for further research in signal separation in context of feature selection approach especially in context of broader spectral bandwidths. It also sets ground for further development of feature selection algorithms that use hybrid regression methods customized for crop specific traits.

Small floral patches are resistant reservoirs of wild floral visitor insects and the pollination service in agricultural landscapes

Small floral patches that coexist with crops in agricultural landscapes can function as biodiversity reservoirs. However, the influence of the landscape context and agricultural management on the capacity of these small green infrastructures to support diversity is poorly understood. Here, we evaluate the effect of landscape simplification, agricultural intensification in the neighbourhood, and quality of the floral habitats on the success of these patches to support flower-visiting insect communities as well as the pollination service they provide.To this aim, we sampled floral patches located in 18 paired olive farms with contrasting herb cover management (intensive vs. low-intensity), distributed along a wide gradient of landscape complexity at the regional scale of South Spain. We conducted surveys of flower-visiting insects in 36 multi-floral stands and 36 mono-floral stands of Sinapis alba Linnaeus (1753) within these floral patches. Mono-floral stands were used to evaluate variations in the pollination service through number of viable seeds and seed set.Results revealed that the abundance and diversity of flower-visiting insects respond to the quality of the floral patch (diversity of flowers) but not to landscape context nor agricultural management around it. Moreover, the pollination service was similar and high (seed set ca. 100 %) in all floral patches regardless of their context.Our findings highlight the importance of even small floral patches that function as reservoirs of diversity of flower-visiting insects and the pollination service. They also show the high resistance of these patches to agricultural intensification and simplification in olive grove landscapes.

Legacy of landscape crop diversity enhances carabid beetle species richness and promotes granivores

It is well understood that agricultural expansion and associated loss of semi-natural habitat in the landscape are major drivers for the marked decline in biodiversity. While conserving remaining semi-natural habitat patches is essential to reverse ongoing biodiversity declines, increasing focus has also been put on diversifying cropland itself by increasing landscape crop diversity as a measure of compositional heterogeneity, and reducing field sizes as a measure of configurational heterogeneity. Both these cropland diversification approaches have shown promise to enhance biodiversity in the year of sampling, but it is unknown whether legacies of crop diversity in the landscape promote biodiversity by building up arthropod communities over time. We selected 14 faba bean fields in landscapes dominated by cropland. The fields were chosen along three gradients: landscape crop diversity of the year of sampling (2017), landscape crop diversity of the previous year (2016) and mean field size in landscapes. Using pitfall traps, we show that the carabid beetle species richness is higher in landscapes with higher crop diversity in the previous year. Especially, granivorous carabid beetles benefitted from legacies of crop diversity. Rove beetles were more abundant and genus rich in landscapes with larger field sizes, while spiders were not responding to any of the landscape variables. A diversity of crops in the landscape and their associated weed communities could provide more diverse food resources and shelter habitats, which build populations of carabid beetle species over time. There is a need to explore the effects of agri-environmental schemes across multiple years to better understand legacy effects, and to structure sustainable agricultural landscapes.

Decreased efficiency of pollen collection due to Sulfoxaflor exposure leads to a reduction in the size of bumble bee workers in late European summer

Bumble bees (Bombus terrestris) are important pollinators of wild and crop plants. Despite their importance in the process of fruit and seed production on crop sites, their activity may be impaired due to exposure to pesticides. This species has a yearly life cycle and colony success may rely on effective foraging of workers on ruderal plants late in summer when most crops are no longer flowering. In the current study, we investigated the effect of chronic exposure to Sulfoxaflor on aspects of the foraging behavior of bumble bees and whether Sulfoxaflor influences the body size of workers of B. terrestris in a crop landscape. We found that 2 weeks of continuous exposure to Sulfoxaflor influenced workers’ foraging dynamics and collection of resources. However, there was no evidence that the 5 ppb dose of the pesticide impacted the ability of bees to handle flowers with different traits. Workers from colonies exposed to Sulfoxaflor were smaller. The effect on worker size may be explained as a consequence of the reduced pollen income per unit of worker foraging. Thus, if the effects of Sulfoxaflor applied directly to crops had the same effect as that observed on commercial bumble bees after our chronic exposure, it might negatively impact colony success due to the impact on pollen collection and the reduction in the size of workers.

GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands

Optimizing soil—crop—landscape occurrence is essential for sustainable intensification and food security, but little work has been done to evaluate these parameters on Tribal lands. The objective of this study was to develop first ever high-resolution crop suitability maps and compare two established crop suitability models for their ability to optimize soil resource management of the Quapaw Tribal lands. We built on previously developed continuous soil properties maps for 22,880 ha of Quapaw Tribal lands that used a digital elevation model and a fuzzy-logic based data mining approach to calculate and evaluate the Dideriksen and Storie crop suitability indices. Suitability index results were evaluated against observed yield (n ≥ 130,000) within the study area. Results showed that the observed yield was positively correlated with the Storie suitability index (Spearman rho = 0.16, p < 0.01), but not the Dideriksen index, suggesting the Storie index is more appropriate than the Dideriksen for modeling crop suitability in this area. Additionally, very little (<13%) of the highly suitable soils in the Quapaw Tribal lands are currently used for crop production, suggesting potential yield gaps from the underutilization of highly suitable soils. Future research could improve estimates through the development of novel suitability indices for closing yield gaps and further improved sustainable intensification.

NATURAL COVER SURROUNDING THE FARM FIELD REDUCES CROP DAMAGE AND PEST ABUNDANCE IN BRAZILIAN DRYLAND

ABSTRACT One of the major ecosystem services delivered to agriculture worldwide is the reduction of pests by natural enemies. However, the landscape composition affects multiple dimensions of pest control, and non-crop habitat surrounding farm fields shows variable responses across geographies. Here, crop damage and pest abundance were compared between local farms with two antagonistic land cover and land use aspects (1- High conservation, landscape with high structural complexity; 2- High degradation, landscapes with low complexity). The field data were collected at experimental guava orchards in the Cariri Paraibano, one of the driest regions in the Brazilian Caatinga. The results show that damage caused by orthopterans and their abundance was significantly smaller in the landscape with high structural complexity. Therefore, the results support the hypothesis that crop damage and pest abundance are smaller in landscapes with high structural complexity. Additionally, the results are very important for the dryland regions as they provide information about the relationship between landscape structure and crop damage plus pest abundance in a regional gap. As drylands are critically endangered in all American continents, sustainable agricultural landscapes with the application of natural cover restoration can help drylands to achieve sustainable development.

Commodity crops in biodiversity-rich production landscapes: Friends or foes? The example of cotton in the Mid Zambezi Valley, Zimbabwe

The production and trade of agricultural commodities is a major driver of the loss of tropical biodiversity. In the Mid Zambezi Valley, Zimbabwe, which is home to many emblematic African mammals, cotton production has historically been a major driver of land cover change. The collapse of cotton production in Zimbabwe over the last decade provides a unique opportunity to understand the linkages between the profitability of cotton and land-use changes in this multifunctional landscape. By re-visiting 141 households that had been surveyed in 2007 and combining this panel survey data with a land cover analysis and secondary data, we demonstrate that the decreasing profitability of cotton led to a shift from cotton farming (mean area per farm decreasing from 1.79 ± 2.05 ha in 2007 to 0.72 ± 0.90 ha in 2020) to livestock farming (mean number of cattle and goats per farm increasing several-fold between 2007 and 2020), resulting in drastic land cover changes. Indeed, open vegetation (including crops, fallows and grazing areas) expanded from 10 to 20% of the total land cover area between 2007 and 2020. Populations of wildlife species have declined drastically during this period, although this cannot be attributed solely to the observed changes in land cover. However, increasing human-wildlife conflicts are likely to threaten the long-term coexistence of people and wildlife in the area. We argue that commodity crops can be an opportunity for nature conservation, not only a threat, and that conservation needs to support a ‘living income’ for people coexisting with wildlife.

Can ecological landscape pattern influence dry-wet dynamics? A national scale assessment in China from 1980 to 2018

Land cover has been demonstrated to have substantial impacts on climate and dry-wet environment, but potential influence of landscape pattern dynamics accompanying land cover change on drought remains unclear. In this study, response of dry-wet dynamics to landscape pattern in China was examined. Results suggest that landscape pattern in China's nine agricultural districts had transformed to varying extents and showed spatiotemporal heterogeneity from 1980 to 2018. For forest landscape, the highest annual average Percentage of Landscape (PLAND) was recorded in SC, reaching 62.26%; and the highest Largest Patch Index (LPI) was presented in YGP, followed by SC, with annual values of 53.79% and 46.26% respectively. The QTP has the most prominent forest connectivity in spite of its lower abundance. For grass landscape, the highest abundance and dominance were recorded in QTP, with annual PLAND fluctuation range of 49.66%—63.52% and annual LPI variation range of 34.10%—58.46%, which is associated with its climate and altitude. The most prominent crop landscape abundance and dominance were recorded in HHHP, with annual PLAND fluctuating interval of 56.53%—60.64%, indicating the highest agricultural development level in this district. At landscape level, dry-wet circumstance could be improved with enhancements in the largest patch percentage, patch density and spatial connectivity, while worsen with increases of landscape fragmentation and separated degree. At class level, increases in abundance and dominance of forest and crop landscapes would reduce drought risk, while it was opposite for grass landscape. Improved forest connectedness would optimize dry-wet environment and reduce drought risk. The PLAND of forest and crop landscapes contributed the most prominent effect to alleviate drought intensity. Compared with forestland and grassland, determining suitable crop landscape configuration to reduce drought risk is more complex because the balance between agricultural economic benefits and ecological landscape effects should be taken into account.