Behavioural Response in an Asilid Fly: Influence of Ecological and Environmental Factors on Spatial Density Dependence

2021 ◽  
Author(s):  
MARCELA K. CASTELO ◽  
JOSÉ E. CRESPO
Keyword(s):  
Spatial Scale ◽  
Chemical Cues ◽  
Spatial Scales ◽  
Behavioural Response ◽  
Spatial Density ◽  
Density Dependent ◽  
Searching Strategy ◽  
Local Host ◽  
Oviposition Substrate ◽  
Pampas Region

Abstract Behavioural response of a parasitoid shows the effect on host parasitism patterns at a given host distribution resulting in an increase or decrease of parasitism intensity according to local host densities. This relationship could be proportional, positive, or negative, as a consequence of foraging of parasitoids searching for hosts. Mallophora ruficauda is a fly parasitoid of Cyclocephala signaticollis scarab beetle larvae and a predator of honeybees. Females search and place egg-clusters overground in open grasslands near beehives. Larvae actively searching for host underground following chemical cues arising from the host itself. The parasitism pattern is a result of this complex host-searching strategy which is shared between both stages of the fly. In this work we carried out a study at four spatial scales in apiaries located in the Pampas region of Argentina. We found that parasitism is inverse density-dependent at high female activity and direct density-dependent at low female activity at the larger spatial scale. We found a direct density dependent pattern associated to substrate height at intermediate spatial scale that is lost when the habitat has abundant oviposition substrates. Conversely, parasitism is inversely density-dependent at both smaller spatial scales, associated to oviposition substrate distance and saturation of healthy host by larvae attacking. Additionally, M. ruficauda does not select the oviposition substrates according to the abundance of Cyclocephala signaticollis inhabiting underground. This work shows the importance of a proper scale for analysis of factors that influence population dynamics and how environmental characteristics mould parasitism patterns in this dipteran parasitoid.

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

scholarly journals The spatial scale of density-dependent growth and implications for dispersal from nests in juvenile Atlantic salmon

Oecologia ◽  
2010 ◽  
Vol 165 (4) ◽  
pp. 959-969 ◽  
Author(s):  
Sigurd Einum ◽  
Grethe Robertsen ◽  
Keith H. Nislow ◽  
Simon McKelvey ◽  
John D. Armstrong
Keyword(s):  
Atlantic Salmon ◽  
Spatial Scale ◽  
Density Dependent ◽  
Juvenile Atlantic Salmon ◽  
Dependent Growth

scholarly journals Characteristics of Climate Change and Extreme Weather from 1951 to 2011 in China

2018 ◽  
Vol 15 (11) ◽  
pp. 2540 ◽  
Author(s):  
Chunli Zhao ◽  
Jianguo Chen ◽  
Peng Du ◽  
Hongyong Yuan
Keyword(s):  
Climate Change ◽  
Spatial Scale ◽  
Spatial Scales ◽  
Seasonal Fluctuation ◽  
Extreme Weather ◽  
Temperature And Precipitation ◽  
Weather Variation ◽  
Variation Characteristics ◽  
Established Fact ◽  
Temporal And Spatial

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.

Scale-dependent relationships between benthic habitat characteristics and abundances of blacklip abalone, Haliotis rubra (Leach)

2010 ◽  
Vol 61 (11) ◽  
pp. 1227 ◽  
Author(s):  
Elisabeth M. A. Strain ◽  
Craig R. Johnson
Keyword(s):  
Spatial Scale ◽  
Red Algae ◽  
Positive Relationship ◽  
Spatial Scales ◽  
Habitat Characteristics ◽  
Benthic Habitat ◽  
Sessile Invertebrates ◽  
Haliotis Rubra ◽  
The Relationship ◽  
Biotic Characteristics

Habitat characteristics can influence marine herbivore densities at a range of spatial scales. We examined the relationship between benthic habitat characteristics and adult blacklip abalone (Haliotis rubra) densities across local scales (0.0625–16 m2), at 2 depths, 4 sites and 2 locations, in Tasmania, Australia. Biotic characteristics that were highly correlated with abalone densities included cover of non-calcareous encrusting red algae (NERA), non-geniculate coralline algae (NCA), a matrix of filamentous algae and sediment, sessile invertebrates, and foliose red algae. The precision of relationships varied with spatial scale. At smaller scales (0.0625–0.25 m2), there was a positive relationship between NERA and ERA, and negative relationships between sediment matrix, sessile invertebrates and abalone densities. At the largest scale (16 m2), there was a positive relationship between NERA and abalone densities. Thus, for some biotic characteristics, the relationship between NERA and abalone densities may be scalable. There was very little variability between depths and sites; however, the optimal spatial scale differed between locations. Our results suggest a dynamic interplay between the behavioural responses of H. rubra to microhabitat and/or to abalone maintaining NERA free of algae, sediment, and sessile invertebrates. This approach could be used to describe the relationship between habitat characteristics and species densities at the optimal spatial scales.

scholarly journals Spatial scale-dependent land–atmospheric methane exchanges in the northern high latitudes from 1993 to 2004

2014 ◽  
Vol 11 (7) ◽  
pp. 1693-1704 ◽  
Author(s):  
X. Zhu ◽  
Q. Zhuang ◽  
X. Lu ◽  
L. Song
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Scale ◽  
Water Table ◽  
Spatial Scales ◽  
Grid Cell ◽  
High Latitudes ◽  
Atmospheric Methane ◽  
Ch4 Emissions ◽  
Biogeochemical Models ◽  
Macro Scale

Abstract. Effects of various spatial scales of water table dynamics on land–atmospheric methane (CH4) exchanges have not yet been assessed for large regions. Here we used a coupled hydrology–biogeochemistry model to quantify daily CH4 exchanges over the pan-Arctic from 1993 to 2004 at two spatial scales of 100 km and 5 km. The effects of sub-grid spatial variability of the water table depth (WTD) on CH4 emissions were examined with a TOPMODEL-based parameterization scheme for the northern high latitudes. We found that both WTD and CH4 emissions are better simulated at a 5 km spatial resolution. By considering the spatial heterogeneity of WTD, net regional CH4 emissions at a 5 km resolution are 38.1–55.4 Tg CH4 yr−1 from 1993 to 2004, which are on average 42% larger than those simulated at a 100 km resolution using a grid-cell-mean WTD scheme. The difference in annual CH4 emissions is attributed to the increased emitting area and enhanced flux density with finer resolution for WTD. Further, the inclusion of sub-grid WTD spatial heterogeneity also influences the inter-annual variability of CH4 emissions. Soil temperature plays an important role in the 100 km estimates, while the 5 km estimates are mainly influenced by WTD. This study suggests that previous macro-scale biogeochemical models using a grid-cell-mean WTD scheme might have underestimated the regional CH4 emissions. The spatial scale-dependent effects of WTD should be considered in future quantification of regional CH4 emissions.

Synchrony of frond dynamics among patches of the clonal seaweed Mazzaella parksii (Rhodophyta) at local spatial scale

2004 ◽  
Vol 84 (5) ◽  
pp. 883-886 ◽  
Author(s):  
Ricardo Scrosati
Keyword(s):  
Spatial Scale ◽  
Seasonal Changes ◽  
Pacific Coast ◽  
Spatial Scales ◽  
Sampling Effort ◽  
Confidence Limits ◽  
Seasonal Trends ◽  
Intertidal Seaweed ◽  
The Mean

This study investigated the synchrony of frond dynamics among patches of the intertidal seaweed Mazzaella parksii (=M. cornucopiae; Rhodophyta: Gigartinales) at local spatial scale. At Prasiola Point (Pacific coast of Canada), the mean synchrony of the seasonal changes in frond density among seven permanent, 100-cm2 quadrats was significant (mean Pearson's r=0·73, with 0·65–0·81 as 95% confidence limits) between 1993 and 1995. This indicates that predicting seasonal trends for non-monitored patches at local spatial scale can be done relatively well based on observations on a limited number of quadrats. The identification of the spatial scales at which seaweed populations covary synchronously will permit minimizing sampling effort while retaining the ability to make valid predictions for non-monitored sites.

scholarly journals Evaluation of Asian summer precipitation in different configurations of a high-resolution general circulation model in a range of decision-relevant spatial scales

2021 ◽  
Vol 25 (12) ◽  
pp. 6381-6405
Author(s):  
Mark R. Muetzelfeldt ◽  
Reinhard Schiemann ◽  
Andrew G. Turner ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Scale ◽  
Diurnal Cycle ◽  
General Circulation ◽  
Spatial Scales ◽  
Summer Precipitation ◽  
Physical Geography ◽  
Simulated Precipitation ◽  
The Mean ◽  
Precipitation Bias

Abstract. High-resolution general circulation models (GCMs) can provide new insights into the simulated distribution of global precipitation. We evaluate how summer precipitation is represented over Asia in global simulations with a grid length of 14 km. Three simulations were performed: one with a convection parametrization, one with convection represented explicitly by the model's dynamics, and a hybrid simulation with only shallow and mid-level convection parametrized. We evaluate the mean simulated precipitation and the diurnal cycle of the amount, frequency, and intensity of the precipitation against satellite observations of precipitation from the Climate Prediction Center morphing method (CMORPH). We also compare the high-resolution simulations with coarser simulations that use parametrized convection. The simulated and observed precipitation is averaged over spatial scales defined by the hydrological catchment basins; these provide a natural spatial scale for performing decision-relevant analysis that is tied to the underlying regional physical geography. By selecting basins of different sizes, we evaluate the simulations as a function of the spatial scale. A new BAsin-Scale Model Assessment ToolkIt (BASMATI) is described, which facilitates this analysis. We find that there are strong wet biases (locally up to 72 mm d−1 at small spatial scales) in the mean precipitation over mountainous regions such as the Himalayas. The explicit convection simulation worsens existing wet and dry biases compared to the parametrized convection simulation. When the analysis is performed at different basin scales, the precipitation bias decreases as the spatial scales increase for all the simulations; the lowest-resolution simulation has the smallest root mean squared error compared to CMORPH. In the simulations, a positive mean precipitation bias over China is primarily found to be due to too frequent precipitation for the parametrized convection simulation and too intense precipitation for the explicit convection simulation. The simulated diurnal cycle of precipitation is strongly affected by the representation of convection: parametrized convection produces a peak in precipitation too close to midday over land, whereas explicit convection produces a peak that is closer to the late afternoon peak seen in observations. At increasing spatial scale, the representation of the diurnal cycle in the explicit and hybrid convection simulations improves when compared to CMORPH; this is not true for any of the parametrized simulations. Some of the strengths and weaknesses of simulated precipitation in a high-resolution GCM are found: the diurnal cycle is improved at all spatial scales with convection parametrization disabled, the interaction of the flow with orography exacerbates existing biases for mean precipitation in the high-resolution simulations, and parametrized simulations produce similar diurnal cycles regardless of their resolution. The need for tuning the high-resolution simulations is made clear. Our approach for evaluating simulated precipitation across a range of scales is widely applicable to other GCMs.

scholarly journals Forest birds respond to the spatial pattern of exurban development in the Mid-Atlantic region, USA

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2039 ◽  
Author(s):  
Marcela Suarez-Rubio ◽  
Todd R. Lookingbill
Keyword(s):  
Spatial Pattern ◽  
Spatial Scale ◽  
Forest Fragmentation ◽  
Spatial Scales ◽  
The United States ◽  
Forest Edge ◽  
Forest Birds ◽  
Bird Diversity ◽  
Forest Loss ◽  
Exurban Development

Housing development beyond the urban fringe (i.e., exurban development) is one of the fastest growing forms of land-use change in the United States. Exurban development’s attraction to natural and recreational amenities has raised concerns for conservation and represents a potential threat to wildlife. Although forest-dependent species have been found particularly sensitive to low housing densities, it is unclear how the spatial distribution of houses affects forest birds. The aim of this study was to assess forest bird responses to changes in the spatial pattern of exurban development and also to examine species responses when forest loss and forest fragmentation were considered. We evaluated landscape composition around North American Breeding Bird Survey stops between 1986 and 2009 by developing a compactness index to assess changes in the spatial pattern of exurban development over time. Compactness was defined as a measure of how clustered exurban development was in the area surrounding each survey stop at each time period considered. We used Threshold Indicator Taxa Analysis to detect the response of forest and forest-edge species in terms of occurrence and relative abundance along the compactness gradient at two spatial scales (400-m and 1-km radius buffer). Our results showed that most forest birds and some forest-edge species were positively associated with high levels of compactness at the larger spatial scale; the proportion of forest in the surrounding landscape also had a significant effect when forest loss and forest fragmentation were accounted for. In contrast, the spatial configuration of exurban development was an important predictor of occurrence and abundance for only a few species at the smaller spatial scale. The positive response of forest birds to compactness at the larger scale could represent a systematic trajectory of decline and could be highly detrimental to bird diversity if exurban growth continues and creates more compacted development.

Sign in / Sign up

Export Citation Format

Share Document