Mixed Landscape Research Articles

Bird remains from the Middle Paleolithic levels (MIS3) of Llonin Cave (Peñamellera Alta, Asturias, Spain)

Birds are abundant in fossil assemblages of Quaternary sites; they can be used in landscape recon­struction as they are well adapted to the environment. Here we present the analysis of the avian assemblage from the Middle Paleolithic levels of the Llonin Cave, where 558 bird remains have been recovered from levels G-VI and CP-VIII, belonging to at least ten different taxa: Aves indet., Galliformes indet., Lagopus lagopus Linnaeus, 1758, Tetrastes bonasia Linnaeus, 1758, Columba livia/oenas Gmelin, 1789/Linnaeus, 1758, Passeriformes indet., Alaudidae indet., Motacilla sp., Turdus sp., Corvidae indet., Garrulus glandarius Linnaeus, 1758, Pyrrhocorax sp., Pyrrhocorax pyrrhocorax Linnaeus, 1758, Pyrrhocorax graculus Linnaeus, 1766 and Corvus corax Linnaeus, 1758. This assemblage is similar to other assemblages from the Upper Pleistocene of the north of the Iberian Peninsula, and it reflects a mixed landscape, with open areas and woodland. The taphonomic analysis points to a mixed origin of the accumulation, mainly formed by medium-sized corvids dying in the cave, and also raptors accumulating their prey.

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Dynamic space use of Andalusian rice fields by Lesser Black‐backed Gulls (Larus fuscus) is driven by flooding pattern

Research on the space use and behaviour of waterbirds yields important insights on human–wildlife interactions of ecological and societal importance under global change. The extent to which dynamic (within‐season) changes in anthropogenic landscapes affect these interactions is poorly understood. Lesser Black‐backed GullsLarus fuscusare prominent bio‐vectors of biological, synthetic and inorganic materials and have exhibited large increases in abundance in parts of southern Europe in recent decades. We combined GPS tracking, earth observation, accelerometry and field observations to study the space use of overwintering gulls in a mixed rice field landscape in Andalusia, southern Spain. We used Manly selectivity metrics, a common quantitative measurement of habitat selection, and classified remote sensing imagery directly to evaluate space use and habitat selection for these gulls and how it changed throughout the rice harvest cycle. Analysis of over 45 000 GPS fixes and 14 classified remotely sensed images from winter 2016/17 showed dynamic space use driven by the harvest‐related flooding across the rice harvest cycle. Prior to harvest, gulls foraged in rice paddies during the day and roosted in adjacent waterbodies (the River Guadalquivir and fish ponds) at night. During harvest, they spent nearly 100% of their daily cycle within the rice fields, foraging in harvested paddies and roosting in post‐harvest, flooded paddies. After harvest, they roosted in flooded paddies at night and foraged at landfills in the surrounding landscape. Gull space use at landscape and paddy scales was closely linked to dynamic land and water management over the rice agricultural cycle, illustrating how human activities influence the movements of ecologically important, human‐associated bio‐vectors such as gulls. The frequent early‐spring movement patterns of gulls between landfills and agricultural fields makes them an important bio‐transport link for potentially toxic materials and pathogens between waste sites and places where food is grown for human consumption.

Phytoremediation of azoxystrobin and imidacloprid by wetland plant species Juncus effusus, Pontederia cordata and Sagittaria latifolia

Azoxystrobin (strobilurin fungicide) and imidacloprid (neonicotinoid insecticide) have been detected in surface waters near treated agricultural, urban, and mixed landscapes. The hazards of pesticide runoff can be prevented through best management practices, including the establishment of diverse wetland plant barriers that can phytoremediate the chemicals in which they come into contact with. In this study, the wetland plant species softrush (Juncus effusus), pickerelweed (Pontederia cordata), and arrowhead (Sagittaria latifolia) were planted in sandy soil containers that were then placed in azoxystrobin or imidacloprid treated water. Every week for 2 months, water samples were collected for pesticide residue analysis using high-performance liquid chromatography (HPLC). At 14, 28, and 56 days after initiation, plants were destructively harvested and analyzed for pesticide residue in soil, above-ground vegetation, and below-ground vegetation. Results from this study report P. cordata reduced greater azoxystrobin (51.7% reduction compared to treated non-planted containers) compared to J. effusus and S. latifolia (24.9% and 28.7% reduction from non-planted containers) at 56 days. However, S. latifolia reduced greater imidacloprid (79.3% reduction compared to non-planted containers) compared to J. effusus and P. cordata (36.0% and 37.1% reduction from non-planted containers) at 56 days. Novelty statement: While research has found that wetland plants can absorb and remediate synthetic chemicals, this practice is only sustainable if used with native plants that require low maintenance and are tolerant to the applied substances. Various previous studies observe plants that are fast-growing, tolerant to environmental conditions, require low-maintenance, and are hardy. However, these plant species are not always suitable for any location and are often considered invasive and/or weed-like. The present research initiates a list of plant species which can be used within the southeastern United States and similar areas to phytoremediate commonly used pesticides azoxystrobin and imidacloprid and prevent off-target movement into sensitive water systems.

Habitat and crop selection by red deer in two different landscape types

Crop raiding ungulates can cause costly yield losses and conflicts between agriculture, game management, and conservation. It is therefore crucial to know how, where, and when ungulates use different habitats and crops. In this study we used resource selection functions and GPS-tagged red deer Cervus elaphus (n = 38) in two different study areas (North – mainly forested land and South – mainly arable land), to investigate how red deer use arable land and different crop types in relation to availability and distance to forest cover in Sweden. Our study shows a transitional use of arable land and forests by red deer. Red deer spend on average 45% and 21% of their time in arable land in South and North respectively. In the North, arable land was selected while forest and wetlands were selected in the South. The selection of different crops also differed between the two study areas, for example rapeseed was highly selected during both seasons in South while it was used to a lower degree in relation to its availability in the North. In both study areas the probability of red deer presence on the agricultural fields decreased with distance to forest. The significant use of arable land and unharvested crops by the increasing red deer population in Sweden highlights a risk for crop damage that may need further consideration for farming practices as well as for damage and wildlife management. In our case damage mitigation should focus on rapeseed in the South, whereas there is a less clear pattern of selection among growing crops in the North. The differences in habitat and crop selection between the two areas also highlights the need of knowledge about red deer habitat selection at a regional level to be able to adapt damage mitigation and wildlife management strategies accordingly. Moreover, the transitional use of arable land and forests by red deer in mixed landscapes may imply that consumption of certain crops can affect browsing patterns and damage levels within forests and vice versa, that may have implication for both agriculture and forestry and calls for future studies.

Bat responses to changes in forest composition and prey abundance depend on landscape matrix and stand structure

Despite the key importance of the landscape matrix for bats, we still not fully understand how the effect of forest composition interacts at combined stand and landscape scales to shape bat communities. In addition, we lack detailed knowledge on the effects of local habitat structure on bat-prey relationships in forested landscapes. We tested the assumptions that (i) forest composition has interacting effects on bats between stand and landscape scales; and (ii) stand structure mediates prey abundance effects on bat activity. Our results indicated that in conifer-dominated landscapes (> 80% of coniferous forests) bat activity was higher in stands with a higher proportion of deciduous trees while bats were less active in stands with a higher proportion of deciduous trees in mixed forest landscapes (~ 50% of deciduous forests). Moth abundance was selected in the best models for six among nine bat species. The positive effect of moth abundance on Barbastella barbastellus was mediated by vegetation clutter, with dense understory cover likely reducing prey accessibility. Altogether, our findings deepen our understanding of the ecological processes affecting bats in forest landscapes and strengthen the need to consider both landscape context and trophic linkage when assessing the effects of stand-scale compositional and structural attributes on bats.

Assessment of Tuscany Landscape Structure According to the Regional Landscape Plan Partition

The landscape is considered a strategic asset by the Tuscan regional government, also for its economic role, meaning that a specific Landscape Plan has been developed, dividing the region into 20 Landscape Units and representing the main planning instrument at the regional level. Following the aims of the Landscape Plan and the guidelines of the European Landscape Convention, it is necessary to develop an adequate assessment of the landscape, evaluating the main typologies and their characteristics. The aim of this research is to carry out an assessment of the landscape diversity in Tuscany based on 20 study areas, analyzing land uses and landscape mosaic structures through the application of landscape metrics: number of land uses, mean patch size (MPS), Hill’s diversity number, edge density (ED), patch density (PD), land use diversity (LUD). The results highlight a correlation between the landscape typologies (forest, agricultural, mixed, periurban) and the complexity of the landscape structure, especially in relation to MPS and PD, while the combination of PD and LUD calculated on the basis of a hexagonal grid allows obtaining landscape complexity maps. Despite the phenomena of reforestation and urban sprawl of recent decades, Tuscany still preserves different landscape typologies characterized by a good level of complexity. This is particularly evident in mixed landscapes, while agricultural landscapes have a larger variability because of different historical land organization forms. The methodology applied in this study provided a large amount of data about land uses and the landscape mosaic structure and complexity and proved to be effective in assessing the landscape structure and in creating a database that can represent a baseline for future monitoring.

Modeling tree canopy height using machine learning over mixed vegetation landscapes

Although the random forest algorithm has been widely applied to remotely sensed data to predict characteristics of forests, such as tree canopy height, the effect of spatial non-stationarity in the modeling process is oftentimes neglected. Previous studies have proposed methods to address the spatial variance at local scales, but few have explored the spatial autocorrelation pattern of residuals in modeling tree canopy height or investigated the relationship between canopy height and model performance. By combining Light Detection and Ranging (LiDAR) and Landsat datasets, we used spatially-weighted geographical random forest (GRF) and traditional random forest (TRF) methods to predict tree canopy height in a mixed dry forest woodland in complex mountainous terrain. Comparisons between TRF and GRF models show that the latter can lower predefined extreme residuals, and thus make the model performance relatively stronger. Moreover, the relationship between model performance and degree of variation of true canopy height can vary considerably within different height quantiles. Both models are likely to present underestimates and overestimates when the corresponding tree canopy heights are high (>95% quantile) and low (<median), respectively. This study provides a critical insight into the relationship between tree canopy height and predictive abilities of random forest models when taking account of spatial non-stationarity. Conclusions indicate that a trade-off approach based on the actual need of project should be taken when selecting an optimal model integrating both local and global effects in modeling attributes such as canopy height from remotely sensed data.

Does the crested porcupine select coppice forest? Habitat preference and activity patterns of a large rodent in the Lago di Vico Natural Reserve

Abstract The crested porcupine Hystrix cristata L. is a large rodent, which mainly occurs in agro-forestry ecosystems in Italy. In this study, we modelled the occupancy of this species in forest ecosystems, to identify environmental characteristics affecting its presence. The study was conducted at Lago di Vico Natural Reserve (Latium, Central Italy) in 2018–2019. The sampling design included a 1 km2 grid, where 263 detections were recorded at 39 out of 57 camera-trap points. Dendroauxometric data were collected at each site as covariates in the statistical models. According to our best occupancy model, the crested porcupine mostly occurs in habitats not totally covered by forests, but composed by mixed landscape patches both for the land use (crops, woods) and for the coverage (forested areas, open areas, bushes). We also analysed activity rhythms of the crested porcupine across seasons and in relation to the moon phases. The analysis of 543 videos showed that crested porcupine is strictly nocturnal throughout the year and avoided bright nights, despite the local absence of potential predators.

Water use and drainage of subtropical, mixed landscapes varies with turf coverage and season

We conducted a three-year drainage lysimeter study of mixed (woody plant-turf) landscape water demand relative to reference evapotranspiration, drainage, and plant growth in humid, subtropical central Florida. The aim was to develop information to guide more efficient water planning, landscape design, and irrigation management in a seasonally dry monsoon climate using three representative landscape species – southern magnolia (Magnolia virginiana), sweet viburnum (Viburnum odoratissimum), and St. Augustinegrass (Stenotaphrum secundatum) – at turf coverage of 90, 75, and 60% of the total landscape area. Water inputs (daily rainfall, irrigation) and drainage were recorded with a datalogger to calculate monthly actual evapotranspiration (ETA) for each lysimeter using a water balance approach. Growth was measured non-destructively (magnolia height, canopy and trunk diameter, viburnum dry mater, canopy cross section, and volume) every three weeks, while turf clippings were collected during the spring to late fall growing season. Woody plants imbedded in turf with ostensibly deeper root systems underlying turfgrass roots were more efficient at scavenging water, minimizing drainage, and leaching risk. Reducing turfgrass coverage to 60% diminished drainage by 70 cm in the wet season and 50 cm in the dry season compared to 90% turfgrass cover, and increased rainfall utilization rate to 0.81 compared to 0.40 for 90% turf across both seasons. Mixed turf-woody plant landscape ETA differed minimally across turf coverage treatments during the dry season, with approximately 70% of reference ETA versus 90% during the wet season, likely due to less surface evaporation. To conserve water and reduce drainage during the monsoonal dry season, mixed turf-woody plant landscape irrigation can be scheduled based on water demand at 70% of local evapotranspiration (0.7 Plant Factor). These results give water suppliers and landscape architects tools to design urban landscapes and develop regulations to efficiently promote and track mixed landscape irrigation water consumption in a monsoonal climate with a pronounced dry season. Further, water managers can reduce drainage and risk of groundwater pollution by encouraging design of landscapes with woody plants imbedded in turfgrass to scavenge water moving below the turfgrass root zone.

Ultra-fast growth of cuprate superconducting films: Dual-phase liquid assisted epitaxy and strong flux pinning

Cuprate superconductors are key candidate materials toward high energy-efficient devices. Improving their growth rate and performance under magnetic fields are indispensable for achieving even higher efficiency. For the first time, we demonstrated the ultra-high rate up to 100 nm/s in the growth of dual-phase cuprate superconducting film (EuBa2Cu3O7-BaHfO3). The growth rate achieved is two orders of magnitude higher than that at lab-scale and was also the highest on record to our best knowledge. Epitaxial growth mechanism assisted by the transient liquid phase is proposed, as evidenced by formation of Eu2BaCuO5 and Ba–Cu–O metastable phases under high supersaturation conditions. The high growth rate results in formation of mixed defective landscape, consisting of short nanorods, nanoparticles and naturally formed defects (e.g., staking faults). Due to such unique microstructure, we confirm that weak Jc anisotropy is dominated by random pinning mechanism. Contribution of isotropic and anisotropic Jc to Jctotal also varies with temperatures and magnetic field strength, which is a consequence of evolution of dominant pinning in film. As a result, the in-field current carrying capacity is significantly enhanced (exceeding 430 A/4 mm-width at 4.2 K, 18 T, B//c), being among the top tier of commercialized superconductor materials. This study establishes the correlation between ultra-high growth rate and flux pinning behaviors, which provides feasibility of dramatically improvement of production efficiency with the low price-performance ratio of future high temperature superconductor.

Long-term data shows increasing dominance of Bombus terrestris with climate warming

While many bumblebee species decline due to climate and land-use changes, others cope well with contemporary conditions. One example is Bombus terrestris, which is common in intensively managed agricultural landscapes. During the 20th century its subgenus, which includes the B. lucorum complex (B. lucorum, B. cryptarum and B. magnus) came to dominate Scandinavian bumblebee communities, but the specific contribution of B. terrestris remains to be understood. Using historical data on males, we assessed how the relative abundances of B. terrestris and the B. lucorum complex changed over the past 150 years in southernmost Sweden. We tested if these changes differed between simplified and mixed landscapes and whether the relative abundance of B. terrestris was related to annual mean temperatures. Because floral availability has advanced as a response to climate change, we also tested if the activity period of males (estimated as catching date) has advanced and whether the advancement differs between taxa. The relative abundance of B. terrestris increased similarly in both landscapes, from 21% to 79% over the period, and this was largely explained by increasing temperature. Male activity period has advanced similarly in the two taxa, with 41 days between 1900 and 2015. Although the dominance of B. terrestris correlates clearly with annual mean temperature, it remains to disentangle why. It also remains to understand whether the success of B. terrestris occurs at the expense of other species or simply reflects that this species copes better with contemporary conditions.

Love thy neighbors? Beneficial and pest arthropod populations in a pear and cherry orchard landscape

Neighboring vegetation in an agricultural landscape can impact pest and beneficial arthropod populations in tree fruit orchards. In a pear monocrop region (such as Wenatchee WA, northwestern United States), the concern is that specialist pests can migrate from orchard to orchard and maintain an area-wide high population. In a mixed landscape region (such as Hood River OR, NW USA), the concern is that chemical control measures against invasive pests in nearby cherry orchards can disrupt biological control in pear orchards by killing beneficial arthropods. Specifically, we asked whether surrounding pear and cherry area cover (% in 1 km2), presence of adjacent cherry orchards, and pesticide impact scores influenced the abundance and richness of common pests (pear psylla and two-spotted spider TSS mites) and beneficial arthropods (the parasitoid wasp Trechnites insidiosus and generalist predators) in pear orchards in OR and WA. Pests and beneficial arthropods were collected in pear plots in OR and WA in 2016–2018 using a combination of methods (sticky cards, beat trays, leaf samples). A generalized linear mixed model revealed that surrounding pear cover area did not affect any of the outcome variables. Surrounding cherry cover had variable effects on pest and beneficial abundance in different regions and years, such as a negative correlation with predator abundance (OR 2016), a positive correlation with parasitoid abundance (WA 2017), and higher pear psylla abundance in cherry-adjacent pear plots (OR 2018). Furthermore, a quantile regression showed that pear orchards with low surrounding cherry cover had high variance in parasitoid abundance, while pear orchards with high surrounding cherry cover had consistently low parasitoid abundance. Pesticide impact scores negatively influenced predator and parasitoid abundance and beneficial richness in WA, but not in OR. Pear plots with higher pesticide impact scores had higher TSS mite abundance (in both OR and WA 2018), but did not affect pear psylla abundance. A redundancy analysis (RDA) showed that beneficial population assemblages tended to cluster away from pear plots with high pesticide impact scores. This study shows how landscape and chemical control practices can have variable impacts on pear orchards located in different regions.

Antibiotic Resistance in Shiga Toxigenic Escherichia coli Isolates from Surface Waters and Sediments in a Mixed Use Urban Agricultural Landscape.

Antibiotic resistance (AR) phenotypes and acquired resistance determinants (ARDs) detected by in silico analysis of genome sequences were examined in 55 Shiga toxin-producing Escherichia coli (STEC) isolates representing diverse serotypes recovered from surfaces waters and sediments in a mixed use urban/agricultural landscape in British Columbia, Canada. The isolates displayed decreased susceptibility to florfenicol (65.5%), chloramphenicol (7.3%), tetracycline (52.7%), ampicillin (49.1%), streptomycin (34.5%), kanamycin (20.0%), gentamycin (10.9%), amikacin (1.8%), amoxicillin/clavulanic acid (21.8%), ceftiofur (18.2%), ceftriaxone (3.6%), trimethoprim-sulfamethoxazole (12.7%), and cefoxitin (3.6%). All surface water and sediment isolates were susceptible to ciprofloxacin, nalidixic acid, ertapenem, imipenem and meropenem. Eight isolates (14.6%) were multidrug resistant. ARDs conferring resistance to phenicols (floR), trimethoprim (dfrA), sulfonamides (sul1/2), tetracyclines (tetA/B), and aminoglycosides (aadA and aph) were detected. Additionally, narrow-spectrum β-lactamase blaTEM-1b and extended-spectrum AmpC β-lactamase (cephalosporinase) blaCMY-2 were detected in the genomes, as were replicons from plasmid incompatibility groups IncFII, IncB/O/K/Z, IncQ1, IncX1, IncY and Col156. A comparison with surveillance data revealed that AR phenotypes and ARDs were comparable to those reported in generic E. coli from food animals. Aquatic environments in the region are potential reservoirs for the maintenance and transmission of antibiotic resistant STEC, associated ARDs and their plasmids.

Mapping soil slaking index and assessing the impact of management in a mixed agricultural landscape

Abstract. Soil aggregate stability is a useful indicator of soil physical health and can be used to monitor condition through time. A novel method of quantifying soil aggregate stability, based on the relative increase in the footprint area of aggregates as they disintegrate when immersed in water, has been developed and can be performed using a smartphone application – SLAKES. In this study the SLAKES application was used to obtain slaking index (SI) values of topsoil samples (0 to 10 cm) at 158 sites to assess aggregate stability in a mixed agricultural landscape. A large range in SI values of 0 to 7.3 was observed. Soil properties and land use were found to be correlated with observed SI values. Soils with clay content &gt;25 % and cation exchange capacity (CEC) : clay ratio &gt;0.5 had the highest observed SI values. Variation in SI for these soils was driven by organic carbon (OC) content which fit a segmented exponential decay function. An OC threshold of 1.1 % was observed, below which the most extreme SI values were observed. Soils under dryland and irrigated cropping had lower OC content and higher observed SI values compared to soils under perennial cover. These results suggest that farm managers can mitigate the effects of extreme slaking by implementing management practices to increase OC content, such as minimum tillage or cover cropping. A regression-kriging method utilising a Cubist model with a suite of spatial covariates was used to map SI across the study area. Accurate predictions were produced with leave-one-out cross-validation, giving a Lin's concordance correlation coefficient (LCCC) of 0.85 and a root-mean-square error (RMSE) of 1.1. Similar validation metrics were observed in an independent test set of samples consisting of 50 observations (LCCC = 0.82; RMSE = 1.1). The potential impact of implementing management practices that promote soil OC sequestration on SI values in the study area was explored by simulating how a 0.5 and 1.0 % increase in OC would impact SI values at observation points and then mapping this across the study area. Overall, the maps produced in this study have the potential to guide management decisions by identifying areas that currently experience extreme slaking and highlighting areas that are expected to have a significant reduction in slaking by increasing OC content.

A baseline estimate of regional agricultural water demand from GEO-LEO satellite observations

Agricultural water demand (AWD) and irrigation water demand (IWD) were assessed (2009–2018) over India using geostationary and polar orbiting satellites. A novel concept of satellite based composite crop-coefficient was introduced to address bulk AWD from mixed agricultural landscape. Significant spatio-temporal variation of AWD was observed over India. The decadal mean of annual AWD was found to be 1521 km3 contributing around 52% (789 km3) and 48% (732 km3) in kharif and rabi seasons, respectively. The decadal average IWD over India was found to be 360 km3. At annual scale, around 75% of AWD was found fulfilled by effective rainfall and the rest 25% is the IWD. The decadal trend of AWD and IWD showed significant increasing trend over Indian region. The study provides a baseline reference for regional agricultural water management policy over diverse agro-climatic regions of India with an opportunity to optimize AWD and IWD at different locations.

Changes in agriculture-biodiversity trade-offs in relation to landscape context in the Argentine Chaco

Better balancing agricultural production and biodiversity conservation is a central goal for many landscapes. Yet, empirical work on how to best achieve such a balance has focused mainly on the local scale, thereby disregarding that landscape context might mediate biodiversity-agriculture trade-offs. Focusing on vertebrates in the Argentine Chaco, we evaluate how trade-offs between agriculture and biodiversity vary with landscape context, from landscapes where agricultural and natural areas are separated to landscapes where both are interspersed. We modelled the distributions of 226 vertebrates and use the resulting maps to describe the species richness of ecosystem-service providing guilds. We calculated three agricultural intensity metrics, and evaluated how both species richness and agricultural intensity vary along a gradient of landscape configuration, while controlling for landscape composition. Species richness and agricultural yields both varied with landscape configuration. Biodiversity was highest in mixed landscapes where agricultural and natural area are interspersed, whereas agricultural yields showed a more heterogeneous response, with some yield metrics highest in mixed and others in separated landscapes. As a result, agriculture/biodiversity trade-offs depended strongly on landscape configuration, irrespective of landscape composition. We also identified large areas with low vertebrate richness and agricultural yields, suggesting considerable potential for improving in at least one dimension. Agriculture/biodiversity trade-offs varied with landscape configuration, suggesting that landscape design can balance these trade-offs. Our simple and broadly applicable approach can provide baseline information for landscape planning aimed at realizing co-benefits between agriculture and biodiversity—in the Gran Chaco and elsewhere.

A simple-to-use management approach to boost adaptive capacity of forests to global uncertainty

Given the uncertainty of global environmental changes, forest managers need reliable and science-based tools to support planning decisions. To evaluate the state of forests as well as the outcomes of new management practices aimed at fostering the adaptive capacity of forest ecosystems, methods and metrics for practitioners should be self-explanatory, based on easily-available data, and straightforward to use. Here, we present and apply the functional network approach, a trait-based approach that scales-up from species functional traits to community-level functional diversity and from stands to landscape-level functional connectivity, to guide sustainable forest management when faced with global change. In the functional network approach, (1) tree and shrub species are clustered into functional groups based on selected functional traits, (2) forest stands become the nodes of the network, and (3) functional traits can be exchanged between nodes according to species dispersal capacity via functional connectivity. We complemented the functional network approach with an assessment of stand-level vulnerability to natural disturbances. This new approach was applied to a mixed temperate forest landscape in south-eastern Canada to test four management scenarios varying in intensity (5–40% of the landscape area) and silvicultural strategy, including planting tree species from rare functional groups or harvesting tree species from predominant functional groups. Managed stands were ranked according to functional diversity and vulnerability to disturbances, and species were considered for planting based on their contribution to functional diversity and level of vulnerability. We found that a species-rich forest may be a functionally poor ecosystem so its adaptive capacity and resilience may be strongly compromised in the face of high global uncertainty. In addition, both functional diversity and connectivity increased with more intense management, and when functionally rare species were planted. By adopting the functional network approach, forest practitioners have a new simple-to-use tool to evaluate landscape-level functional diversity, vulnerability, and functional connectivity. This tool can be used to inform both plans for mitigating natural disturbances and strategies for enhancing overall ecosystem adaptive capacity to future environmental conditions and societal demands.

Bat Diversity in Imbak Canyon Conservation Area: Note on their Echolocation Calls and Ectoparasites

Imbak Canyon Conservation Area (ICCA) is one of the conservation areas managed by the Sabah Foundation, which comprise of mixed vegetation forest landscape. A bat survey was conducted at ICCA from August 16th to 26th, 2017. A total of 141 individuals of bats representing 17 species were recorded from the eight nights of mist netting and harp trapping at various sites within the conservation area. Echolocation calls from 120 individuals of insectivorous bats representing 13 species were recorded, with 90% accuracy in relative amount. The captured bats were screened for ectoparasites from Order Diptera (91%), Mesostigmata (5%) and Ixodida (1%), and indicate that there is 66.7% prevalence. The results from the survey are paramount in enhancing information and knowledge on Bornean bats and their obligate ectoparasites.

Every hill has its leopard: patterns of space use by leopards (Panthera pardus) in a mixed use landscape in India.

Understanding abundance and distribution of species is often necessary for wildlife conservation. However, elusive species such as the leopard (Panthera pardus) that have wide geographical distribution and typically low abundance pose a constant challenge to conservationists due to logistical and methodological constraints. Although leopard abundance has been estimated at the scale of protected areas or other smaller regions, reliable information describing leopard distribution over large spatial scales remains largely unavailable. Knowledge about space use by leopards within landscapes could help improve conservation management, reduce human-wildlife conflict, and also facilitate population status monitoring. We carried out occupancy surveys across c. 24,000 km2 in southern India in a landscape that consisted a mosaic of leopards’ natural habitats and highly human-dominated areas. We investigated the effects of key ecological and anthropogenic variables in determining leopard space use patterns. We addressed imperfect detections obtained using sign surveys conducted on spatially replicated transects within sampling units by modeling detection as a function of spatial auto-correlation and covariates. Our results show that the probability of site-use by leopards across the landscape varied between 0.02 (95% CI [0.01–0.09]) and 0.99 (95% CI [0.99–1.0]) across the study area. The best model (AIC weight = 0.97) showed that the probability of leopard space use was affected by the proportion of natural habitats and the presence of large wild prey in the sampling unit. Given that India is undergoing rapid modifications due to economic changes and demand for natural resources, we emphasize the need for landscape-based approach for conserving and monitoring leopards. We argue that leopards are an indicator of functional ecosystems represented by scrub, deciduous forest and rocky outcrops that do not always get prioritized for conservation, unlike densely forested habitats. Similarly, conservation of natural large wild prey, especially outside the protected area system, should assume greater importance, which could also have a positive impact on reducing human-leopard conflict.