Hasil untuk "Ecology"

Gerda Claeskens, Céline Cunen, Nils Lid Hjort

Datasets encountered when examining deeper issues in ecology and evolution are often complex. This calls for careful strategies for both model building, model selection, and model averaging. Our paper aims at motivating, exhibiting, and further developing focused model selection criteria. In contexts involving precisely formulated interest parameters, these versions of FIC, the focused information criterion, typically lead to better final precision for the most salient estimates, confidence intervals, etc. as compared to estimators obtained from other selection methods. Our methods are illustrated with real case studies in ecology; one related to bird species abundance and another to the decline in body condition for the Antarctic minke whale.

Lydia M. O’Sullivan, Clay J. Newton, Keith R. Underwood et al.

In the bison industry, both heifers and bulls are marketed and harvested at various ages, generally ranging from 20 to 30 months. Bulls represent the greatest proportion of the slaughter mix, as the bison industry does not routinely castrate, leaving males intact throughout the growing and finishing phase. This practice makes bulls available for use during the breeding season prior to the finishing phase. Therefore, the objective of this study was to evaluate the influence of bull age and use in the breeding herd on carcass characteristics, meat quality, and sensory characteristics of bison bulls. Grass-finished bison bulls were assigned to one of two finishing treatments: 1) Young bulls (n = 98) finished on fall pasture and harvested at 30 months of age with no exposure to the breeding herd, or 2) Mature bulls (n = 24) finished on early summer pasture and harvested at 36 months of age following use in the breeding herd. Bison were harvested, carcass data were recorded, and striploins were collected for the analysis of meat quality attributes. Mature bulls had greater hot carcass weight, ribeye area, kidney fat percentage, and marbling score compared to Young bulls. Objective tenderness was affected by the interaction of postmortem aging and finishing treatment. Steaks from Young bison bulls were more tender at all aging time points compared to steaks from Mature bison bulls. Variation in tenderness between treatment groups was likely not due to differences in collagen, as total collagen was greater in steaks from Young bulls. Consumer panelists rated steaks from Mature bulls higher for toughness intensity and flavor liking and lower for off-flavor intensity. Trained panelists rated steaks from Young bulls higher for flavor intensity, while ratings for toughness and juiciness were increased for Mature bulls. Collectively, results from this study indicate that bulls used in the breeding herd and marketed at 36 months of age produced heavier carcasses. However, Mature bulls were tougher at all postmortem aging days and required 21 days of aging to reach an acceptable level of tenderness, which was detected by both trained and consumer panelists.

Shing Yan Li, Zhijie Feng, Akshit Goyal et al.

Ecological interactions can dramatically alter evolutionary outcomes in complex communities. Yet, the classic theoretical results of population genetics (e.g., Kimura's fixation formula) largely ignore ecological effects. Here, we address this shortcoming by using dynamical mean-field theory to integrate ecology into classical population genetics models. We show that ecological interactions between parents and mutants result in frequency-dependent selection and can be characterized by a single emergent parameter that measures the strength of ecological feedbacks. We derive an explicit analytic expression for the fixation probability that generalizes Kimura's famous result and analyze it in various ecological and evolutionary limits. We find that ecological interactions suppress fixation probabilities for moderately beneficial mutants when compared to Kimura's predictions, with the strength of suppression increasing with larger effective population sizes, greater selective differences between parent and mutant, and for ecosystems with a large number of "open niches" (i.e., ecosystems well below the packing bound). Frequency-dependent selection also gives rise to prolonged parent-mutant coexistence in complex communities, a phenomenon absent in classical population genetics. Our study establishes a framework for integrating ecological interactions into population genetics models and helps illuminate how ecology can affect evolutionary outcomes.

Li Ji, Huayong Zhang, Huayong Zhang et al.

Warming is a key factor influencing the function of the structure and function of phytoplankton communities. However, the impacts of temperature on phytoplankton resource use efficiency (RUE) in mountain rivers remain poorly understood. Here, the spatiotemporal patterns of phytoplankton community structure (biomass, community composition, and diversity), function (RUE), and the main environmental factors in a high-latitude mountainous stream were investigated to assess how temperature affects the phytoplankton RUE. The results showed that phytoplankton species richness, biomass, and RUE all increased with rising temperature, with species richness significantly higher. There was a shift in the phytoplankton community from dominated by Cyanophyta at lower temperatures to dominated by Cryptophyta at higher temperatures. Phytoplankton RUE was significantly positively correlated to species richness, but no significant relationship was observed between RUE and Pielou’s evenness. Furthermore, redundancy analysis and Mantel tests revealed that water temperature, nutrient (TP, and NH4+-N) and physicochemical variable (flow velocity, and dissolved oxygen) explained 40.40% of the overall variation in phytoplankton RUE. Phytoplankton RUE exhibited stronger responses to environmental variables than phytoplankton biomass or diversity. The results highlighted that temperature directly affected phytoplankton community composition and enhanced RUE by altering environmental conditions and biodiversity. Temperature plays a crucial role in shaping the structure and function of phytoplankton communities in rivers. Our results contribute to the deep understanding of the mechanisms by which temperature influences RUE providing a basis for the sustainable management and conservation of aquatic ecosystems and watersheds.

Tian Jiang, Lei Zhao, Xu Zhang et al.

Species of <i>Craterellus</i> are interesting and important due to their mycorrhizal properties, medicinal value, and edibility. Despite extensive research on <i>Craterellus</i> in China, its taxonomy remains inadequately understood. This study presents three newly described species of <i>Craterellus</i>, namely <i>C. albimarginatus</i>, <i>C. involutus</i>, and <i>C. longitipes</i>, identified through morphological and phylogenetic analyses, with the goal of refining the taxonomy of Chinese <i>Craterellus</i>.

Florian Hartig, Nerea Abrego, Alex Bush et al.

New technologies for acquiring biological information such as eDNA, acoustic or optical sensors, make it possible to generate spatial community observations at unprecedented scales. The potential of these novel community data to standardize community observations at high spatial, temporal, and taxonomic resolution and at large spatial scale ('many rows and many columns') has been widely discussed, but so far, there has been little integration of these data with ecological models and theory. Here, we review these developments and highlight emerging solutions, focusing on statistical methods for analyzing novel community data, in particular joint species distribution models; the new ecological questions that can be answered with these data; and the potential implications of these developments for policy and conservation.

Peggy A. Bevan, Omiros Pantazis, Holly Pringle et al.

Large image collections generated from camera traps offer valuable insights into species richness, occupancy, and activity patterns, significantly aiding biodiversity monitoring. However, the manual processing of these datasets is time-consuming, hindering analytical processes. To address this, deep neural networks have been widely adopted to automate image labelling, but the impact of classification error on key ecological metrics remains unclear. Here, we analyse data from camera trap collections in an African savannah (82,300 labelled images, 47 species) and an Asian sub-tropical dry forest (40,308 labelled images, 29 species) to compare ecological metrics derived from expert-generated species identifications with those generated by deep learning classification models. We specifically assess the impact of deep learning model architecture, proportion of label noise in the training data, and the size of the training dataset on three key ecological metrics: species richness, occupancy, and activity patterns. We found that predictions of species richness derived from deep neural networks closely match those calculated from expert labels and remained resilient to up to 10% noise in the training dataset (mis-labelled images) and a 50% reduction in the training dataset size. We found that our choice of deep learning model architecture (ResNet vs ConvNext-T) or depth (ResNet18, 50, 101) did not impact predicted ecological metrics. In contrast, species-specific metrics were more sensitive; less common and visually similar species were disproportionately affected by a reduction in deep neural network accuracy, with consequences for occupancy and diel activity pattern estimates. To ensure the reliability of their findings, practitioners should prioritize creating large, clean training sets and account for class imbalance across species over exploring numerous deep learning model architectures.

A. Bradley Duthie, Victor J. Luque

Biological evolution is realised through the same mechanisms of birth and death that underlie change in population density. The deep interdependence between ecology and evolution is well-established, and recent models focus on integrating eco-evolutionary dynamics to demonstrate how ecological and evolutionary processes interact and feed back upon each other. Nevertheless, a gap remains between the logical foundations of ecology and evolution. Population ecology and evolution have fundamental equations that define how the size of a population (ecology) and the average characteristic within a population (evolution) change over time. These fundamental equations are a complete and exact description of change for any closed population, but how they are formally linked remains unclear. We link the fundamental equations of population ecology and evolution with an equation that sums how individual characteristics interact with individual fitness in a population. From this equation, we derive the fundamental equations of population ecology and evolutionary biology (the Price equation). We thereby identify an overlooked bridge between ecology and biological evolution. Our unification formally recovers the equivalence between mean population growth rate and evolutionary fitness and links this change to ecosystem function. We outline how our framework can be used to further develop eco-evolutionary theory.

Catarina Leal, Ales Eichmeier, Kateřina Štůsková et al.

With a reduction in available chemical treatments, there is an increased interest in biological control of grapevine trunk diseases. Few studies have investigated the impact of introducing beneficial microorganisms in the rhizosphere on the existing indigenous soil microbiome. In this study, we explored the effect of two biocontrol agents (BCAs), Trichoderma atroviride SC1 (Ta SC1) (Vintec; Certis Belchim) and Bacillus subtilis PTA-271 (Bs PTA-271), on the grapevine rhizosphere bacterial and fungal microbiome as well as plant defense expression using high-throughput amplicon sequencing and quantitative real-time polymerase chain reaction (PCR), respectively. Additionally, we quantified both Ta SC1 and Bs PTA-271 in the rhizosphere over time using droplet digital PCR. The fungal microbiome was more affected by factors such as soil type, BCA treatment, and sampling time compared with the bacterial microbiome. Specifically, Ta SC1 application produced negative impacts on fungal diversity, whereas application of BCAs did not affect bacterial diversity. Interestingly, the survival and establishment of both BCAs showed opposite trends depending on the soil type, indicating that the physicochemical properties of soils have a role in BCA establishment. Fungal co-occurrence networks were less complex than bacterial networks but highly impacted by Ta SC1 application. Soils treated with Ta SC1 presented more complex and stable co-occurrence networks, with a higher number of positive correlations. Induced grapevine defenses also differed according to the soil, being more affected by BCA inoculation on sandy soil. The findings of this research emphasize the complex relationships among microorganisms in the rhizosphere and highlight the significance of taking into account various factors, such as soil type, sampling time, and BCA treatment, and their influence on the structure and dynamics of microbial communities.

Mercy Hokah Kibathi, Mercy Hokah Kibathi, Edith Chepkorir et al.

BackgroundYellow fever virus (YFV) and dengue virus (DENV) are among the major re-emerging arboviruses that pose a significant threat to public health. Their associated burden and prevalence can be substantially underestimated due to insufficient surveillance and inadequate diagnosis. This study aimed to determine evidence of dengue, yellow and related flaviviruses circulation among the rural human populations residing in Nguruman (Kajiado County) and Kerio Valley (Baringo County), two dryland ecosystems in the Kenyan Rift Valley.MethodsSerum samples obtained from febrile patients between 5 and 85 years through a hospital-based cross-sectional survey from July 2020 – May 2023, were screened for neutralizing antibodies to YFV, DENV-2 and related flaviviruses, West Nile virus (WNV) and Zika virus (ZIKV) via Plaque reduction neutralization test (PRNT). The study sites and important demographic characteristics were obtained using a structural questionnaire and the data analyzed and seroprevalence compared. A multinomial logistic regression model was done to predict risk for each of the most prevalent viruses with covariates; age, gender, and occupation.ResultsOverall, 54.5% (50.1–59.0% 95% confidence interval (CI) of the samples tested positive for at least one of the four Flaviviruses. The percentage was significantly higher in Kerio Valley (64.34%, 184/286) than in Nguruman (40.2%, 78/194) (P&lt;0.0001). YFV had the highest prevalence, followed by WNV (16.25%), ZIKV (5.2%), and DENV-2 (1%). Kerio Valley had a significantly higher YFV seroprevalence (51%) than Nguruman (6%) (P&lt;0.0001), while DENV-2 was observed only in Nguruman with a low seropositivity of 2%. In contrast to Nguruman, where seropositivity rates were higher in males at 47.47% (P=0.049), in Kerio Valley, females showed considerably higher viral seropositivity at 60.82% than males (P&lt;0001).ConclusionThe study suggests that there is significant circulation of Flaviviruses in both regions, posing a public health risk, that could potentially contribute to clinical disease. However, seropositivity rates vary for each specific site. Furthermore, there could be a risk of YFV, WNV, and ZIKV transmission in both sites with DENV transmission specifically noted in Nguruman. The study findings inform direct cost-effective actions (such as YF vaccines) and precise surveillance data of vector populations for improved disease risk prediction.

Lu Zhou, Qingli Zhang, Huihuan Luo et al.

To investigate the association of long-term exposure to air pollution with incident arrhythmia from various causes, this prospective cohort study included 442,386 participants from the UK Biobank cohort. Residential annual average exposures at baseline were evaluated, including fine particles (PM2.5), coarse particles (PM2.5–10), nitrogen dioxide (NO2), and nitrogen oxides (NOx). We further constructed a composite air pollution score (APS) to evaluate the concomitant exposure to these four pollutants. The associations of air pollutants with various arrhythmia subtypes were assessed utilizing the Cox proportional hazards model, and the hazard ratios (HRs) for incident arrhythmias were estimated. A total of 41,021 patients with incident arrhythmia were recorded. The HRs of overall arrhythmia associated with a 10 μg/m3 increment in PM2.5, PM2.5–10, NO2, and NOx were 1.26, 0.95, 1.03, and 1.02, respectively. The HR was 1.08 in the highest quintile of the APS compared to the lowest one. For cause-specific arrhythmias, the HRs per unit increment in APS were 1.45, 1.67, 1.51, 1.80, 2.63, and 4.66 for atrial fibrillation, atrioventricular block, ventricular fibrillation/tachycardia, intraventricular block, supraventricular tachycardia, and ventricular premature beats, respectively. Females, older individuals, overweight or obese individuals, and those with low education attainment, low income, or cardiometabolic morbidities had higher HRs associated with pollutants. Long-term exposure to air pollution is linked to increased incidence risks of atrial and ventricular arrhythmias. More focus should be shifted to the impact of air pollution on other arrhythmias besides atrial fibrillation.

Harshith Bachimanchi, Matthew I. M. Pinder, Chloé Robert et al.

The implementation of deep learning algorithms has brought new perspectives to plankton ecology. Emerging as an alternative approach to established methods, deep learning offers objective schemes to investigate plankton organisms in diverse environments. We provide an overview of deep-learning-based methods including detection and classification of phyto- and zooplankton images, foraging and swimming behaviour analysis, and finally ecological modelling. Deep learning has the potential to speed up the analysis and reduce the human experimental bias, thus enabling data acquisition at relevant temporal and spatial scales with improved reproducibility. We also discuss shortcomings and show how deep learning architectures have evolved to mitigate imprecise readouts. Finally, we suggest opportunities where deep learning is particularly likely to catalyze plankton research. The examples are accompanied by detailed tutorials and code samples that allow readers to apply the methods described in this review to their own data.

Yu Meng, Szabolcs Horvát, Carl D. Modes et al.

Does an ecological community allow stable coexistence? Identifying the general principles that determine the answer to this question is a central problem of theoretical ecology. Random matrix theory approaches have uncovered the general trends of the effect of competitive, mutualistic, and predator-prey interactions between species on stability of coexistence. However, an ecological community is determined not only by the counts of these different interaction types, but also by their network arrangement. This cannot be accounted for in a direct statistical description that would enable random matrix theory approaches. Here, we therefore develop a different approach, of exhaustive analysis of small ecological communities, to show that this arrangement of interactions can influence stability of coexistence more than these general trends. We analyse all interaction networks of $N\leqslant 5$ species with Lotka-Volterra dynamics by combining exact results for $N\leqslant 3$ species and numerical exploration. Surprisingly, we find that a very small subset of these networks are "impossible ecologies", in which stable coexistence is non-trivially impossible. We prove that the possibility of stable coexistence in general ecologies is determined by similarly rare "irreducible ecologies". By random sampling of interaction strengths, we then show that the probability of stable coexistence varies over many orders of magnitude even in ecologies that differ only in the network arrangement of identical ecological interactions. Finally, we demonstrate that our approach can reveal the effect of evolutionary or environmental perturbations of the interaction network. Overall, this work reveals the importance of the full structure of the network of interactions for stability of coexistence in ecological communities.

Evan Cleave, Cailin Wark, Emmanuel Kyeremeh

For cities, immigration is now considered a vital part of local economic and community development. Over the past half-century, many cities have experienced a series challenges caused by the impacts of late-stage demographic transition; the slow bleeding of skilled domestic workers to larger metropolitan areas; and the decline of traditional economic sectors. As a result, there has been a prioritization of attracting and retaining high-skilled and well-educated immigrants by local governments through locally-focused, place-based policies. Within this context, this paper examines the ways that cities in the Province of Ontario, Canada are constructing and implementing immigrant attraction, integration, and retention strategies. To achieve this goal, we identified and examined the local immigration policies of the 52 cities in Ontario, 36 of which have a formal immigration policy document. A comprehensive content analysis was conducted on these available to identify the ways that immigration is conceptualized, and the specific policies and approaches that local governments are implementing. Statistical analysis was used to determine if there was variation in policy across different types of cities. Based on this analysis, local governments are generally developing holistic, place-based policies – however, there is variation in approaches across cities of different sizes and geographies. These place-specific policies draw on local assets and advantages (i.e. existing migrant communities; local amenities and attractions; economic and education opportunities) while also work to enhance enhancing local capacity (i.e. building networks and immigration partnerships; training employers and city workers).

Jan-Peter Glock, Julia Gerlach

Abstract Cars are dominating urban traffic in cities around the world, even though daily trips in many cities are often realized with active modes of transportation or public transport. Urban transport planning processes need to adapt to this reality and the necessity of climate change mitigation. Against this background, the research project “Mobility Reporting”, a joint undertaking of the district Pankow in Berlin and researchers from TU Berlin and TU Dresden, established a new, goal-driven, and participative planning process. The process identified local mobility as one of the central planning goals. The 15-min city (FMC) was thus adduced as a benchmark to analyze the district’s current mobility system and development potential. We conducted extensive accessibility analyses to examine the status quo concerning the FMC. We calculated travel times to essential destinations in daily life by foot, public transport, and car. This analysis was accompanied by a mixed online and paper–pencil survey conducted to evaluate the perceived accessibility of people in Pankow. The survey results shed light on the question of which walking time thresholds constitute a “very good” or “good” accessibility. Further analyses included environmental and social variables, allowing us to check whether areas with different accessibility levels also differ regarding the socio-economic characteristics of their inhabitants. For example, do socially advantaged neighborhoods have better local accessibility? Is there a trade-off between exposure to environmental pollution and good accessibility? With this contribution, we shed light on what an FMC is and ought to be. Results from the survey support the normative and political vision of the FMC. Pankow generally offers the merits of a walkable city, showing the expected travel time differences between the dense inner city and the outskirts. Socially disadvantaged neighborhoods are not consistently less accessible. However, there seems to be a trade-off between good accessibility (especially PT accessibility) and correlated externalities of transport, namely air pollution and noise.

Yunfeng Chen, Hang Yang, Beibei Guo et al.

The aim of this trial was to investigate the effects of dietary protein and lipid levels on growth performance and flesh quality of largemouth bass (Micropterus salmoides). A 3 × 3 two-factor design was used, including three crude protein levels of 46%, 50%, 54% (P46, P50, P54) and three crude lipid levels of 8%, 12%, 16% (L8, L12, L16). Thus, a total of nine diets (P46/L8, P46/L12, P46/L16, P50/L8, P50/L12, P50/L16, P54/L8, P54/L12 and P54/L16) were prepared and fed to large-size largemouth bass with initial body weight of 109.7 g for 84 days. At the same dietary protein level, weight gain rate (WGR), protein efficiency rate (PER), viscerosomatic index and polyunsaturated fatty acids (PUFAs) percent in flesh showed an increasing trend with increasing the dietary lipid level, while feed conversion ratio (FCR) showed a decreasing trend. At P46 and P50, whole fish crude protein, muscle crude protein, total collagen content, hardness, springiness, chewiness and shear force increased, and steaming loss and freezing loss decreased with increasing the dietary lipid level, while the above indicators showed an opposite trend at P54. At P50, the protein retention (PR) of 16% crude lipid group was significantly higher than that in the 8% and 12% crude lipid groups (P < 0.05). At the same dietary lipid level, the 50% and 54% crude protein groups presented higher WGR and lower FCR than the 46% crude protein group. The P54/L16 group had the highest WGR (184.4%) and lowest FCR (0.92) among all the groups, but the P50/L16 group presented similar WGR and FCR to the P54/L16 group (P > 0.05). The P50/L16 group showed the highest PER, PR, whole fish protein, muscle protein, total collagen, PUFAs, muscle hardness, springiness, chewiness, shear force and the lowest steaming loss. In conclusion, based on growth performance and flesh quality, the appropriate dietary protein and lipid requirements for large-size largemouth bass were 50% and 16%, respectively.

Valentin Amrhein, Sander Greenland

This is a reply to Muff, S. et al. (2022) Rewriting results sections in the language of evidence, Trends in Ecology & Evolution 37, 203-210.

Zhiming Feng, Zhiming Feng, Mingyou Li et al.

Rice blast, caused by Magnaporthe oryzae (M. oryzae), is one of the most destructive diseases threatening rice production worldwide. Development of resistant cultivars using broad-spectrum resistance (R) genes with high breeding value is the most effective and economical approach to control this disease. In this study, the breeding potential of Pigm gene in geng/japonica rice breeding practice in Jiangsu province was comprehensively evaluated. Through backcross and marker-assisted selection (MAS), Pigm was introduced into two geng rice cultivars (Wuyungeng 32/WYG32 and Huageng 8/HG8). In each genetic background, five advanced backcross lines with Pigm (ABLs) and the same genotypes as the respective recurrent parent in the other 13 known R gene loci were developed. Compared with the corresponding recurrent parent, all these ABLs exhibited stronger resistance in seedling inoculation assay using 184 isolates collected from rice growing regions of the lower region of the Yangtze River. With respect to panicle blast resistance, all ABLs reached a high resistance level to blast disease in tests conducted in three consecutive years with the inoculation of seven mixed conidial suspensions collected from different regions of Jiangsu province. In natural field nursery assays, the ABLs showed significantly higher resistance than the recurrent parents. No common change on importantly morphological traits and yield-associated components was found among the ABLs, demonstrating the introduction of Pigm had no tightly linked undesirable effect on rice economically important traits and its associated grain weight reduction effect could be probably offset by others grain weight genes or at least in the background of the aforementioned two varieties. Notably, one rice line with Pigm, designated as Yangnonggeng 3091, had been authorized as a new variety in Jiangsu province in 2021, showing excellent performance on both grain yield and quality, as well as the blast resistance. Together, these results suggest that the Pigm gene has a high breeding value in developing rice varieties with durable and broad-spectrum resistance to blast disease.

Edoardo Pozio

The main reservoir hosts of nematodes of the genus Trichinella are wild carnivores, although most human infections are caused by the consumption of pork. This group of zoonotic parasites completes the entire natural life cycle within the host organism. However, there is an important phase of the cycle that has only been highlighted in recent years and which concerns the permanence of the infecting larvae in the striated muscles of the host carcasses waiting to be ingested by a new host. To survive in this unique biological niche, Trichinella spp. larvae have developed an anaerobic metabolism for their survival in rotting carcasses and, for some species, a resistance to freezing for months or years in cold regions. Climate changes with increasingly temperatures and reduction of environmental humidity lower the survival time of larvae in host carcasses. In addition, environmental changes affect the biology and ecology of the main host species, reducing their number and age composition due to natural habitat fragmentation caused by increasing human settlements, extensive monocultures, increasing number of food animals, and reduction of trophic chains and biodiversity. All of these factors lead to a reduction in biological and environmental complexity that is the key to the natural host-parasite balance. In conclusion, Trichinella nematodes can be considered as an indicator of a health natural ecosystem.

Kirana Widyastuti, Kirana Widyastuti, Romain Reuillon et al.

Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity).