Autocorrelation Kernel Research Articles

Movement, space-use and resource preferences of European golden jackals in human-dominated landscapes: insights from a telemetry study

During the last half-century, the distribution of golden jackals (Canis aureus) has rapidly increased throughout Europe. Today, golden jackals are thriving in human-dominated landscapes across Southeastern and Central Europe. Most studies on golden jackals have focused on large-scale distribution patterns; to date, little is known about the species’ fine-scale spatial ecology. In this study, we analyzed the movement behavior, space-use and resource selection of six golden jackals fitted with GPS-GSM collars in two study areas in Hungary and Serbia. Two of the jackals were a breeding pair. We found that home range size averaged 11.2 km2 (90% autocorrelated kernel density estimation), and was characterized by significant individual-level variability (range 1.3–32.5 km2). Golden jackal movements and resource selection were strongly influenced by circadian patterns: during the day, jackals travelled an average of 300 m every 6 h, and all monitored individuals selected for vegetation cover, often near edges. At night, golden jackals travelled significantly further (1 km 6 h−1), and were more likely to venture outside of cover into agricultural areas. Movement analysis of the breeding pair revealed that the male and female tended to remain in close proximity during the day, but ranged more independently at night. Altogether, our findings suggest that golden jackals’ ability to thrive in human-dominated landscapes rely on a fine spatio-temporal avoidance of humans.

Sex‐, landscape‐ and climate‐dependent patterns of home‐range size – a macroscale study on an avian generalist predator

Animal home‐ranges are expressions of the biology and ecology of a species, and their size is often considered to be a proxy for habitat quality. Understanding the factors affecting variation in home‐range size may aid prediction of the impact of local or global environmental change on studied populations. To this end, we established an international collaborative programme to gather GPS telemetry data on the Lesser Spotted Eagle Clanga pomarina across a large part of its range. The breeding season home‐ranges of 58 individuals from Estonia, Lithuania, Poland, Hungary and Romania were estimated using autocorrelated kernel density estimation. Differences in home‐range size were analysed using linear mixed‐effects models incorporating global (latitude, longitude, climate) and local (habitat heterogeneity, land cover, topography, human disturbance) variables. Home‐range was significantly affected by habitat heterogeneity, vegetation cover and human disturbance, and also by climate, increasing with greater temperature seasonality. A quadratic relationship between home‐range and Shannon diversity index, found in males, suggests that Eagles use less space in the least and most diverse habitats. Home‐ranges were also smaller close to human settlements, but range size was positively correlated with human population density. The first result reflects the positive influence of agricultural management on prey availability, whereas the second reflects negative impacts of disturbance and loss of foraging space. Home‐ranges of male Eagles were relatively consistent in size and were more linked to environmental conditions compared with those of females. Female home‐ranges were significantly more variable in size and showed less distinctive patterns of relationship with the tested predictors. Sex‐dependent variation in home‐range may result from the different roles of males and females in breeding activities and territoriality limitations of males. The latter factor both limited and increased the home‐range size in different individuals.

Comparative home range size and habitat selection in provisioned and non-provisioned long-tailed macaques (Macaca fascicularis) in Baluran National Park, East Java, Indonesia

The effect of food provisioning on ranging patterns of long-tailed macaques (Macaca fascicularis) in non-anthropogenic areas is largely unknown, as most published studies have focused on urban macaques. In this study, we quantified habitat selection, daily path length and home range size in long-tailed macaques in Baluran National Park, East Java, Indonesia, comparing a non-provisioned to a provisioned group. To track the groups, we deployed six GPS-collars on females in both groups, of which only two collected data. Home range size (90% Auto-correlated Kernel Density Estimate) was 23 times smaller for the provisioned group (10.62 ha) than the non-provisioned group (249.90 ha). Home range size and area changed from dry to wet season for the non-provisioned group. Provisioned group home range size correlated negatively with number of visitors in the national park. Daily path length was significantly higher for the non-provisioned group. The provisioned group preferred settlements, where most of the provisioning occurred, and avoided areas with invasive acacia (Acacia nilotica). The non-provisioned group also avoided invasive acacia, preferred secondary forest in the dry season and restored savannah in the wet season. Food provisioning can affect macaque spatial ecology, by shaping daily travel length and home range size, and changing patterns of habitat selection. Even tourism in a managed national park, where provisioning is strictly prohibited although not always enforced, has significant consequences for animal behaviour and their natural ecosystems.

Ranging behaviour of Long-crested Eagles Lophaetus occipitalis in human-modified landscapes of KwaZulu-Natal, South Africa

The ranging behaviour of raptors in human-altered environments, such as agricultural and suburban landscapes, is becoming increasingly important for conservationists in the context of unprecedented high rates of anthropogenic land use change. We studied the movement ecology of adult Long-crested Eagles Lophaetus occipitalis fitted with geographic positioning system transmitters in an agricultural landscape in KwaZulu-Natal Province, South Africa. Mean home ranges (± SD) of males and females estimated using the autocorrelated kernel density estimator (AKDE) method were 608 ± 552 ha (n = 5) and 664 ± 844 ha (n = 4), respectively. Core areas (KDEhref 50%) were estimated as 80 ± 38 ha and 39 ± 20 ha for males and females, respectively. We also recorded exploratory behaviour (in the form of long excursions) in two of the birds, of up to 49 km from the centre of their home range. The relatively small home ranges reported in this study are suggestive of productive foraging habitats whereby Long-crested Eagles can meet their energy requirements without having to travel long distances to obtain resources. Consistent with predictions, non-breeding male and female Long-crested Eagles showed similar ranging behaviour, which includes occasional exploratory behaviour.

The habitat functional response links seasonal third-order selection to second-order landscape characteristics.

Determining how animals respond to differences in resource availabilities across spatiotemporal extents is critical to our understanding of organism distributions. Variations in resource distribution leading to changes in spatial arrangements across landscapes are indicative of a habitat functional response. Our goal was to assess how resource availabilities influenced both second‐order (i.e., home ranging behavior) and third‐order (i.e., habitat or resource selection) selection by feral pigs (Sus scrofa) in an agricultural landscape. We defined agriculturally based seasons to estimate home range characteristics using autocorrelated kernel density estimation within each season. We then modeled home range size as a function of resource availability (i.e., resource selection analyses) to determine whether individual behaviors were predicted by shifts in home ranging behavior. Both home range analyses and resource selection analyses indicated seasonal differences in selection for agricultural resources as availabilities changed, suggesting second‐ and third‐order selection is mechanistically linked through a habitat functional response.

Anchoring and adjusting amidst humans: Ranging behavior of Persian leopards along the Iran-Turkmenistan borderland.

Understanding the space use and movement ecology of apex predators, particularly in mosaic landscapes encompassing different land-uses, is fundamental for formulating effective conservation policy. The top extant big cat in the Middle East and the Caucasus, the Persian leopard Panthera pardus saxicolor, has disappeared from most of its historic range. Its spatial ecology in the areas where it remains is almost unknown. Between September 2014 and May 2017, we collared and monitored six adult leopards (5 males and 1 female) using GPS-satellite Iridium transmitters in Tandoureh National Park (355 km2) along the Iran-Turkmenistan borderland. Using auto-correlated Kernel density estimation based on a continuous-time stochastic process for relocation data, we estimated a mean home range of 103.4 ± SE 51.8 km2 for resident males which is larger than has been observed in other studies of Asian leopards. Most predation events occurred in core areas, averaging 32.4 ± SE 12.7 km2. Although neighboring leopards showed high spatiotemporal overlap, their hunting areas were largely exclusive. Five out of six of leopards spent some time outside the national park, among human communities. Our study suggests that a national park can play an ‘anchoring’ role for individuals of an apex predator that spend some time in the surrounding human-dominated landscapes. Therefore, we envisage that instead of emphasizing either land sharing or land sparing, a combined approach can secure the viability of resilient large carnivores that are able to coexist with humans in the rugged montane landscapes of west and central Asia.

Space use and movement of jaguar (Panthera onca) in western Paraguay

Abstract Home range and core area size were estimated for jaguar (Panthera onca) in western Paraguay in the Dry Chaco, Humid Chaco and Pantanal using an autocorrelated kernel density estimator. Mean home range size was 818 km2 (95% confidence interval: 425–1981) in the Dry Chaco and 237 km2 (95% confidence interval: 90–427) in the Humid Chaco/Pantanal. Core areas, defined as the home range area where use was equal to expected use, was consistent across sexes and systems represented on average by the 59% home range isopleth (range: 56–64%). Males had a higher probability of larger home ranges and more directional and greater daily movements than females collectively and within systems. The large home ranges in the Dry Chaco are attributable to the relatively low productivity of that semi-arid ecosystem and high heterogeneity in resource distribution while larger than expected home ranges in the Humid Chaco/Pantanal compared to home range estimates from the Brazilian Pantanal may be due to differences in geomorphology and hydrological cycle. The large home ranges of jaguars in western Paraguay and a low proportional area of protected areas in the region demonstrate the importance of private ranchland for the long-term conservation of the species.

Wolf space use during denning season on Prince of Wales Island, Alaska

Wolf Canis lupus reproductive success may be enhanced by access to favorable habitat with limited disturbance during denning season. Therefore, protection of den sites can be an important management strategy for maintaining viable wolf populations. On Prince of Wales Island in southeast Alaska, USA, management agencies recommend protection of dens and surrounding home ranges. However, these agencies are concerned current protection buffer sizes might be inadequate to promote pup‐rearing success. To inform management decisions regarding buffers surrounding wolf dens, we used wolf GPS collar data during 2012–2016 to quantify core and home range area sizes during denning season. We used an autocorrelated kernel density estimator (AKDE) to calculate the extent of home ranges and fit individual wolf movement models. Breeding wolves used smaller core (AKDE 50% isopleth = 6 km2, SD = 4 km2) and home range areas (AKDE 95% isopleth = 57 km2, SD = 17 km2) during denning season (15 April–15 June) than non‐breeding wolves at active dens (core = 69 km2, SD = 45 km2; home range = 252 km2, SD = 161 km2). Home ranges for breeding wolves and wolves belonging to a reproductive pack were smaller than non‐breeding wolves throughout the pup‐rearing period (15 April–31 July). The mean minimum and maximum distance from the core area edge to the active den site (1186–6326 m) varied widely but was smaller for breeding wolves (734–2308 m), and all distances exceeded the existing recommended den buffer distance (366 m). These results underscore the importance of evaluating individual variation in space use when considering management actions intended to protect cooperative breeders or other social carnivores. Wolf managers should recognize the current protection buffer around dens constitutes only a portion of the core area used by breeding wolves, and habitat alterations near den sites may force breeding wolves to use sub‐optimal habitat they would normally avoid.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer’s kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer’s kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Space Use and Movement of a Neotropical Top Predator: The Endangered Jaguar.

Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species’ ecology with an aim towards better conservation of this endangered/critically endangered carnivore—the top predator in the Neotropics.

AKDEC home range size and habitat selection of Sumatran elephants

Context Understanding ranging behaviour and habitat selection of threatened species is crucial for the development of conservation strategies and the design of conservation areas. Our understanding of the actual needs of the critically endangered Sumatran elephant in this context is insufficient. Aims Provide reliable subspecies-specific information on home range size and habitat selection of Sumatran elephants. Methods Using both the new area-corrected autocorrelated kernel density estimation (AKDEC) and two commonly applied conventional methods, the home range sizes of nine Sumatran elephants were estimated. Elephant habitat selection was studied using Manly’s selection ratios. Key results AKDEC home ranges of adults ranged from 275 km2 to 1352 km2. Estimates obtained using conventional KDE and minimum convex polygon (MCP) ranged between 156 km2 and 997 km2. Overall habitat selection was significant for both slope and land-cover type, whereas individual preferences varied to some extent. On the basis of global selection ratios, we found natural forest, pulpwood plantations and gentle slopes (≤4°) to be significantly selected, whereas most areas affected by human activities and steeper slopes were avoided by the majority of animals included in the study. Conclusions As expected, AKDEC estimates were much larger than those obtained using conventional methods because conventional methods have a tendency to underestimate home range size when confronted with autocorrelated movement data and produce estimates that refer to the limited study period only, whereas AKDEC estimates include the predicted animal’s long-term space use. The extremely large AKDEC estimate obtained for a subadult male most likely represents a combination of population dispersal range and temporary home range rather than its final adult home range. Regardless, it appears that Sumatran elephants roam over much larger areas than previously assumed. Natural forests and relatively flat areas are of great importance for Sumatran elephants. The observed intensive use of pulpwood plantations by one individual is likely because of limited availability of alternative suitable habitats. Implications A landscape-wide approach to elephant conservation that takes large home ranges into account, is required, and should include forest protection and restoration and elephant friendly management of existing pulpwood concessions, with special focus on areas with relatively gentle slopes.

Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator.

Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.

Spectrally adapted Mercer kernels for support vector nonuniform interpolation

Interpolation of nonuniformly sampled signals in the presence of noise is a widely analyzed problem in signal processing applications. Interpolators based on Support Vector Machines (SVM) with Gaussian and sinc Mercer kernels have been previously proposed, obtaining good performance in terms of regularization and sparseness. In this paper, inspired in the classical spectral interpretation of the Wiener filter, we explore the impact of adapting the spectrum of the SVM kernel to that of the observed signal. We provide a theoretical foundation for this approach based on a continuous-time equivalent system for interpolation. We study several kernels with different degrees of spectral adaptation to band-pass signals, namely, modulated kernels and autocorrelation kernels. The proposed algorithms are evaluated with extensive simulations with synthetic signals and an application example with real data. Our approach is compared with SVM with Gaussian and sinc kernels and with other well known interpolators. The SVM with autocorrelation kernel provides the highest performance in terms of signal to error ratio in several scenarios. We conclude that the estimated (or actual if known) autocorrelation of the observed sequence can be straightforwardly used as a spectrally adapted kernel, outperforming the classic SVM with low pass kernels for nonuniform interpolation.

Advanced support vector machines for 802.11 indoor location

Due to the proliferation of ubiquitous computing services, locating a device in indoor scenarios has received special attention during recent years. A variety of algorithms are based on Wi-Fi measurements of the received signal strength and estimate the relation between this one and position using previous measurements at known locations. This problem naturally fits in well with learning algorithms such as neural networks, or support vector machines (SVM). However, existing machine learning techniques do not significantly outperform other simpler techniques, such as k-nn. This is mainly due to the fact that these solutions do not include significant a priori information. In this paper, we propose a technique to enhance these algorithms by including certain a priori information within the learning machine, using the spectral information of the training set, and a complex output to take advantage of the cross information in the two dimensions of the location. Specifically, we modify a SVM algorithm to obtain three advanced methods incorporating this information: one using an autocorrelation kernel, another using a complex output, and a third one combining both. These algorithms are compared to the k-nn and an SVM with Gaussian kernel, showing that including the a priori information improves the location performance.

Auto-correlation wavelet support vector machine

A support vector machine (SVM) with the auto-correlation of a compactly supported wavelet as a kernel is proposed in this paper. The authors prove that this kernel is an admissible support vector kernel. The main advantage of the auto-correlation of a compactly supported wavelet is that it satisfies the translation invariance property, which is very important for its use in signal processing. Also, we can choose a better wavelet by selecting from different wavelet families for our auto-correlation wavelet kernel. This is because for different applications we should choose wavelet filters selectively for the autocorrelation kernel. We should not always select the same wavelet filters independent of the application, as we demonstrate. Experiments on signal regression and pattern recognition show that this kernel is a feasible kernel for practical applications.