scholarly journals What drives the spatial distribution and dynamics of local species richness in tropical forest?

2017 ◽  
Vol 284 (1863) ◽  
pp. 20171503 ◽  
Author(s):  
Thorsten Wiegand ◽  
Felix May ◽  
Martin Kazmierczak ◽  
Andreas Huth
Keyword(s):  
Species Richness ◽  
Tropical Forest ◽  
Temporal Variation ◽  
Tropical Forests ◽  
Temporal Variability ◽  
Dynamic Models ◽  
Neutral Theory ◽  
Spatial And Temporal Variation ◽  
Demographic Stochasticity ◽  
Spatio Temporal

Understanding the structure and dynamics of highly diverse tropical forests is challenging. Here we investigate the factors that drive the spatio-temporal variation of local tree numbers and species richness in a tropical forest (including 1250 plots of 20 × 20 m 2 ). To this end, we use a series of dynamic models that are built around the local spatial variation of mortality and recruitment rates, and ask which combination of processes can explain the observed spatial and temporal variation in tree and species numbers. We find that processes not included in classical neutral theory are needed to explain these fundamental patterns of the observed local forest dynamics. We identified a large spatio-temporal variability in the local number of recruits as the main missing mechanism, whereas variability of mortality rates contributed to a lesser extent. We also found that local tree numbers stabilize at typical values which can be explained by a simple analytical model. Our study emphasized the importance of spatio-temporal variability in recruitment beyond demographic stochasticity for explaining the local heterogeneity of tropical forests.

scholarly journals Seasonal patterns of dengue incidence in Thailand across the urban-rural gradient

2020 ◽  
Author(s):  
Qifang Bi ◽  
Derek AT Cummings ◽  
Nicholas G. Reich ◽  
Lindsay T. Keegan ◽  
Joshua Kaminsky ◽  
...  
Keyword(s):  
Wavelet Analysis ◽  
Temporal Variation ◽  
Rural Areas ◽  
Urban Areas ◽  
Dynamic Models ◽  
Seasonal Patterns ◽  
Disease Dynamics ◽  
Urban Rural ◽  
Spatio Temporal ◽  
Dengue Epidemics

AbstractIn Southeast Asia, endemic dengue follows strong spatio-temporal patterns with major epidemics occurring every 2-5 years. However, important spatio-temporal variation in seasonal dengue epidemics remains poorly understood. Using 13 years (2003-2015) of dengue surveillance data from 926 districts in Thailand and wavelet analysis, we show that rural epidemics lead urban epidemics within a dengue season, both nationally and within health regions. However, local dengue fade-outs are more likely in rural areas than in urban areas during the off season, suggesting rural areas are not the source of viral dispersion. Simple dynamic models show that stronger seasonal forcing in rural areas could explain the inconsistency between earlier rural epidemics and dengue “over wintering” in urban areas. These results add important nuance to earlier work showing the importance of urban areas in driving multi-annual patterns of dengue incidence in Thailand. Feedback between geographically linked locations with markedly different ecology is key to explaining full disease dynamics across urban-rural gradient.

scholarly journals Aquatic macrophyte community varies in urban reservoirs with different degrees of eutrophication

2014 ◽  
Vol 26 (2) ◽  
pp. 129-142 ◽  
Author(s):  
Suelen Cristina Alves da Silva ◽  
Armando Carlos Cervi ◽  
Cleusa Bona ◽  
André Andrian Padial
Keyword(s):  
Species Richness ◽  
Temporal Variation ◽  
Indicator Species ◽  
Beta Diversity ◽  
Aquatic Macrophytes ◽  
Aquatic Macrophyte ◽  
Wiener Index ◽  
Spatial And Temporal Variation ◽  
Macrophyte Community ◽  
Aquatic Macrophyte Community

AIM: Investigate spatial and temporal variation in the aquatic macrophyte community in four urban reservoirs located in Curitiba metropolitan region, Brazil. We tested the hypothesis that aquatic macrophyte community differ among reservoirs with different degrees of eutrophication. METHODS: The reservoirs selected ranged from oligotrophic/mesotrophic to eutrophic. Sampling occurred in October 2011, January 2012 and June 2012. Twelve aquatic macrophytes stands were sampled at each reservoir. Species were identified and the relative abundance of aquatic macrophytes was estimated. Differences among reservoirs and over sampling periods were analyzed: i) through two‑way ANOVAs considering the stand extent (m) and the stand biodiversity - species richness, evenness, Shannon-Wiener index and beta diversity (species variation along the aquatic macrophyte stand); and ii) through PERMANOVA considering species composition. Indicator species that were characteristic for each reservoir were also identified. RESULTS: The aquatic macrophyte stand extent varied among reservoirs and over sampling periods. Species richness showed only temporal variation. On the other hand, evenness and Shannon-Wiener index varied only among reservoirs. The beta diversity of macrophyte stands did not vary among reservoirs or over time, meaning that species variability among aquatic macrophyte stands was independent of the stand extent and reservoir eutrophication. Community composition depended on the reservoir and sampling period. CONCLUSIONS: Our results support our initial expectation that reservoirs of different degrees of eutrophication have different aquatic macrophyte communities. As a consequence, each reservoir had particular indicator species. Therefore, monitoring and management efforts must be offered for each reservoir individually.

Spatial and temporal variation in morphology in Australian whistlers and shrike-thrushes: is climate change causing larger appendages?

2020 ◽  
Vol 130 (1) ◽  
pp. 101-113
Author(s):  
Isabelle R Onley ◽  
Janet L Gardner ◽  
Matthew R E Symonds
Keyword(s):  
Climate Change ◽  
Body Size ◽  
Temporal Variation ◽  
Relative Size ◽  
Bird Species ◽  
Spatial And Temporal Variation ◽  
Climatic Warming ◽  
Morphological Response ◽  
Allen’S Rule ◽  
Spatio Temporal

Abstract Allen’s rule is an ecogeographical pattern whereby the size of appendages of animals increases relative to body size in warmer climates in order to facilitate heat exchange and thermoregulation. Allen’s rule predicts that one consequence of a warming climate would be an increase in the relative size of appendages, and evidence from other bird species suggests that this might be occurring. Using measurements from museum specimens, we determined whether spatio-temporal variation in bills and legs of Australian Pachycephalidae species exhibits within-species trends consistent with Allen’s rule and increases in temperature attributable to climatic warming. We conducted regression model analyses relating appendage size to spatio-temporal variables, while controlling for body size. The relative bill size in four of the eight species was negatively associated with latitude. Tarsus length showed no significant trends consistent with Allen’s rule. No significant increases in appendage size were found over time. Although bill size in some species was positively correlated with warmer temperatures, the evidence was not substantial enough to suggest a morphological response to climatic warming. This study suggests that climate change is not currently driving adaptive change towards larger appendages in these species. We suggest that other adaptive mechanisms might be taking place.

scholarly journals The Spatio-temporal Analysis of b-value in the Banda Arc, Indonesia

2021 ◽  
Vol 873 (1) ◽  
pp. 012010
Author(s):  
Muhammad Bani Al-Rasyid ◽  
Mira Nailufar Rusman ◽  
Daniel Hamonangan ◽  
Pepen Supendi ◽  
Kartika Hajar Kirana
Keyword(s):  
Temporal Variation ◽  
Temporal Analysis ◽  
B Value ◽  
Spatial And Temporal Variation ◽  
Tectonic Structure ◽  
Time Period ◽  
Banda Arc ◽  
Spatio Temporal ◽  
The Impact ◽  
Large Earthquakes

Abstract Banda arc is a complex tectonic structure manifests by high seismicity due to the collision of a continent and an intra-oceanic island arc. Using the relocated earthquakes data from ISC-EHB and BMKG catalogues from the time period of 1960 to 2018, we have conducted a spatial and temporal variation of b-value using the Guttenberg-Richter formula in the area. Our results show that the spatial distribution of low b-values located in the south of Ambon Island and southeast of Buru Island. On the other hand, the temporal variation of b-value shows a decrease in the northern part of the Banda sea probably high potential to produce large earthquakes in the future. Therefore, further mitigation is needed to minimize the impact of earthquakes in the area.

scholarly journals Diversity of Pseudoscorpiones (Arthropoda: Arachnida) in two fragments of dry tropical forest in the colombian Caribbean region

Caldasia ◽  
2019 ◽  
Vol 41 (1) ◽  
pp. 139-151
Author(s):  
Eduardo Villarreal ◽  
Neis Martínez ◽  
Catalina Romero-Ortiz
Keyword(s):  
Tropical Forest ◽  
Temporal Variation ◽  
Rainy Season ◽  
Dry Season ◽  
Caribbean Region ◽  
Limited Information ◽  
Dry Tropical Forest ◽  
The Caribbean ◽  
Spatio Temporal ◽  
Collection Methods

The Dry Tropical Forest (DTF) is one of the most diverse yet threatened biomes of Colombia. There is limited information about the richness of the order Pseudoscorpiones (Arachnida) in this ecosystem in the country. Pseudoscorpions are ecologically interesting, as they may be good indicators of habitat conservation. However, it is still necessary to gather more knowledge related to its spatio-temporal variation. In this study, pseudoscorpion diversity variation was assessed in two fragments of the Dry Tropical Forest in the Caribbean region of Colombian: Reserva Campesina La Montaña (RCM) and Reserva La Flecha (RLF). Four samplings were carried out between March and September of 2016 to include the dry and rainy season. Pseudoscorpions were collected using litter sifting (SL) and manual capture (MC). A total of 260 individuals belonging to five families and eight species were collected. The most abundant was Pachyolpium granulatum (Olpiidae) and the richest family was Chernetidae. The collection methods were effective and complementary. Spatial variation was significant, but no temporal variation was observed however, there was a marked difference between the abundance at RCM in the dry season and the rainy season. In contrast, at RLF most individuals were found in the dry season in comparison with the rainy season. These new faunistic data is the first of its order in the Atlántico and Bolívar department.

scholarly journals Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

2014 ◽  
Vol XL-8 ◽  
pp. 197-204 ◽  
Author(s):  
S. Naish ◽  
S. Tong
Keyword(s):  
Temporal Variation ◽  
Temporal Dynamics ◽  
Hot Spot ◽  
Seasonal Pattern ◽  
Temporal Distribution ◽  
Health Concern ◽  
Spatial And Temporal Variation ◽  
Dengue Case ◽  
Spatio Temporal ◽  
Over Time

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

scholarly journals INVESTIGATING THE POTENTIAL OF ACTIVITY TRACKING APP DATA TO ESTIMATE CYCLE FLOWS IN URBAN AREAS

2016 ◽  
Vol XLI-B2 ◽  
pp. 515-519
Author(s):  
J. Haworth
Keyword(s):  
Temporal Variation ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Temporal Structure ◽  
Transportation Systems ◽  
Spatial And Temporal Variation ◽  
Linear Regression Models ◽  
Activity Tracking ◽  
Spatio Temporal ◽  
On The Road

Traffic congestion and its associated environmental effects pose a significant problem for large cities. Consequently, promoting and investing in green travel modes such as cycling is high on the agenda for many transport authorities. In order to target investment in cycling infrastructure and improve the experience of cyclists on the road, it is important to know where they are. Unfortunately, investment in intelligent transportation systems over the years has mainly focussed on monitoring vehicular traffic, and comparatively little is known about where cyclists are on a day to day basis. In London, for example, there are a limited number of automatic cycle counters installed on the network, which provide only part of the picture. These are supplemented by surveys that are carried out infrequently. Activity tracking apps on smart phones and GPS devices such as Strava have become very popular over recent years. Their intended use is to track physical activity and monitor training. However, many people routinely use such apps to record their daily commutes by bicycle. At the aggregate level, these data provide a potentially rich source of information about the movement and behaviour of cyclists. Before such data can be relied upon, however, it is necessary to examine their representativeness and understand their potential biases. In this study, the flows obtained from Strava Metro (SM) are compared with those obtained during the 2013 London Cycle Census (LCC). A set of linear regression models are constructed to predict LCC flows using SM flows along with a number of dummy variables including road type, hour of day, day of week and presence/absence of cycle lane. Cross-validation is used to test the fitted models on unseen LCC sites. SM flows are found to be a statistically significant (p<0.0001) predictor of total flows as measured by the LCC and the models yield R squared statistics of ~0.7 before considering spatio-temporal variation. The initial results indicate that data collected using fitness tracking apps such as Strava are a promising data source for traffic managers. Future work will incorporate the spatio-temporal structure in the data to better account for the spatial and temporal variation in the ratio of SM flows to LCC flows.

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