Historical Occurrence Research Articles

Excision and reinsertion of Ac macrotransposons in maize.

Eukaryotic Macrotransposons (MTns) can be formed by 2 nearby elements flanking a segment of host DNA. The maize Ac transposon can form Ac::MTns, but little is known about Ac::MTn transposition activities. Here, we studied 3 Ac::MTns at the maize p1 locus, each of which is composed of a segment of maize p1 genomic DNA (up to 15 kb) bounded by a fractured Ac element (fAc, 2039 bp), and a full-length Ac element in direct orientation. The resulting Ac::MTns are of 16, 16.5, and 22 kb total length. From these 3 Ac::MTns, we identified 10 independent cases of macrotransposition, and observed similar features of transposition between Ac::MTn and standard Ac/Ds, including characteristic excision footprints and insertion target site duplications. Nine out of the 10 Ac::MTn reinsertion targets were genetically linked to the donor sites, another similarity with Ac/Ds standard transposition. We also identified a MTn-like structure in the maize B73 reference genome and 5 NAM founder lines. The MTn in diverse lines is flanked by target site duplications, confirming the historic occurrence of MTn transposition during genome evolution. Our results show that Ac::MTns are capable of mobilizing segments of DNA long enough to include a typical full-length plant gene and in theory could erode gene colinearity in syntenic regions during plant genome evolution.

Alpine plants are on the move: Quantifying distribution shifts of Australian alpine plants through time

AbstractAimAlpine plant species’ distributions are thought to have been shifting to higher elevations in response to climate change. By moving upslope, species can occupy cooler and more suitable environments as climate change warms their current ranges. Despite evidence of upslope migration in the northern hemisphere, there is limited evidence for elevational shifts in southern hemisphere plants. Our study aimed to determine if alpine plants in Australia have migrated upslope in the last 2 to 6 decades.LocationKosciuszko National Park, NSW, Australia.MethodsWe collated historic occurrence data for 36 Australian alpine plant species from herbarium specimens and historic field observations and combined these historic data with modern occurrence data collected in the field.ResultsEleven of the thirty‐six species had shifted upslope in mean elevation and four species showed downslope elevational shifts. The rate of change for upslope shifts varied between 4 and 10 m per year and the rate of change for most downslope shifts was between 4 and 8 m per year, with one species shifting downslope at a high rate of 18 m per year. Additionally, some species showed shifts upward in their upper range edge and/or upward or downward shifts in their lower range edge. Five species also showed range contractions in the difference between their lower and upper range edges over time, while two showed range expansions. We found no significant differences in elevational shifts through time among herbaceous dicotyledons, herbaceous monocotyledons and shrubs.Main ConclusionsPlant elevational shifts are occurring rapidly in the Australian alpine zone. This may allow species to persist under climate change. However, if current warming trends continue, several species within the Australian alpine zone will likely run out of suitable habitat within a century.

Maximizing species distribution model performance when using historical occurrences and variables of varying persistency

AbstractOccurrence data used to build species distribution models often include historical records from locations in which the species no longer exists. When these records are paired with contemporary environmental values that no longer represent the conditions the species experienced, the model creates false associations that hurt predictive performance. The extent of mismatching increases with the number of historical occurrences and with inclusion of environmental variables that are prone to change over time. Indeed, the mismatch between occurrence data and contemporaneous environmental variables is a common dilemma when modeling rare or cryptic species, especially those of conservation concern that were once more abundant. Herein, we assess (1) the impact of historical occurrences on model performance across three sets of environmental variables of increasing persistency and (2) the performance of models built using selected‐historical occurrences from locations that showed evidence of limited environmental change over time. Concepts are tested on federally listed flatwoods salamanders, reflecting real‐world conservation management efforts. We predicted that, compared to other occurrence sets, (1) historical occurrences would perform best with environmental variables that were more persistent, (2) recent occurrences would perform best when the environmental variables were more impersistent, and that (3) our selected‐historical occurrences would perform best with a combination of persistent and impersistent variables. Our results showed the expected inversion of model performance of recent and historical occurrences across environmental variables of increasing persistency when evaluated by correct predictions. However, the inversion was not seen in area under the curve performance, in which historical occurrences outperformed recent occurrence models across all variable sets. Selected‐historical occurrences did not notably improve performance over all‐historical occurrences in any metric or variable set. To maximize utility and performance, modelers could acknowledge potential trade‐offs from inclusion of historical occurrences and consider number and age of recent and historical occurrences available, the persistency of environmental variables considered, and how their conservation goals are reflected in model design and evaluation, particularly with respect to sensitivity versus specificity. Our study lends support for inclusion of historical occurrences, with the potential exception of mostly impersistent variables when sensitivity is the highest priority.

Moth flies (Diptera: Psychodidae) of the Moravskoslezské Beskydy Mts. and Podbeskydská pahorkatina Uplands, Czech Republic, III.

Abstract Here, we present the latest findings on moth fly (Psychodidae: Diptera) species richness in the Moravskoslezské Beskydy Mts. and Podbeskydská Pahorkatina Uplands, based on both previously published and unpublished data and new samples collected between 2007 and 2020. Two species new to the fauna of the Czech Republic were recorded (Sycorax feuerborni Jung, 1954 and Jungiella (Jungiella) revelica Vaillant, 1972), bringing the total number of moth fly species in the Czech Republic to 180 (Ježek et al. 2021). In addition, five species were recorded for the first time in the area of interest: Trichomyia parvula Szabó, 1960 (second locality in the Czech Republic); Paramormia (Phyllotelmatoscopus) acuta (Krek, 1971) (third record in the Czech Republic); Philosepedon (Philosepedon) perdecorum Omelková & Ježek, 2012 (third locality and fourth record); Pericoma (Pericoma) ljubiniensis Krek, 1969 (second finding and third locality); Tonnoiriella pulchra (Eaton, 1893) (sixth area and first finding in the Czech Carpathians). The finding of Jungiella (Jungiella) valachica (Vaillant, 1963) confirms its historical occurrence in the region. In the latest survey, we collected 108 species from 29 localities, of which 16 are critically endangered, eight endangered and three vulnerable. Nine localities were evaluated as species-rich, i.e. Hluchý 1. (58 species), Vysutý 2. (56), Hluchý 2. (53), Vysutý 4. (49), Skalická Morávka 2. (46), Chladná voda 3. (44), Hluchý 3. (43), Morávka - spring and Obidová 1. (both 42). The total number of moth flies found within the Moravskoslezské Beskydy Mts. and Podbeskydská pahorkatina Uplands now stands at 124 species, representing 68.9 % of total Czech fauna.

Analysis of early Japanese meteorological data and historical weather documents to reconstruct the winter climate between the 1840s and the early 1850s

Abstract. The East Asian winter monsoon causes orographic snowfall over the windward side of the Japanese islands (facing the Sea of Japan and the northwesterly winter monsoon flow) and negative temperature anomalies around Japan. Daily weather information recorded in old Japanese diaries can provide useful information on the historical occurrences of snowfall days. Here, this information was combined with recently recovered early daily instrumental temperature data collected during the 19th century to reconstruct the occurrence of winter monsoon outbreak days (WMDs) from the 1840s to the early 1850s in Japan. Analyses of interannual and intra-seasonal variations in WMDs revealed active winter monsoon outbreaks in the early 1840s. In 1840/41 and 1841/42, these synchronously occurred with extreme snow events reported in central and southern China. However, winter monsoon outbreaks were absent during the middle to late winters of the mid-1840s and 1853/1854. Freezing records of Lake Suwa in central Japan showed that it did not freeze during 1844/1845 and 1853/1854, which was in agreement with our finding of inactive winter monsoons in these years. Comparing the occurrences of WMDs with early instrumental surface pressure data revealed that WMDs were associated with the active phases of the winter monsoon, as represented by an east–west surface pressure gradient over East Asia.

A database of common vampire bat reports

The common vampire bat (Desmodus rotundus) is a sanguivorous (i.e., blood-eating) bat species distributed in the Americas from northern Mexico southwards to central Chile and Argentina. Desmodus rotundus is one of only three mammal species known to feed exclusively on blood, mainly from domestic mammals, although large wildlife and occasionally humans can also serve as a food source. Blood feeding makes D. rotundus an effective transmissor of pathogens to its prey. Consequently, this species is a common target of culling efforts by various individuals and organizations. Nevertheless, little is known about the historical distribution of D. rotundus. Detailed occurrence data are critical for the accurate assessment of past and current distributions of D. rotundus as part of ecological, biogeographical, and epidemiological research. This article presents a dataset of D. rotundus historical occurrence reports, including >39,000 locality reports across the Americas to facilitate the development of spatiotemporal studies of the species. Data are available at https://doi.org/10.6084/m9.figshare.15025296.

Historical droughts in Irish catchments 1767–2016

AbstractRecent prolonged dry periods in summer 2018 and spring 2020 have reawakened interest in drought in Ireland, prompting questions regarding historical drought occurrence and potential long‐term risks. Employing 250 years of monthly precipitation and flow reconstructions, we investigate historical drought in Irish catchments evaluating the characteristics (number of events, duration, and deficits) of moderate, severe, and extreme droughts as well as the propagation of meteorological to hydrological drought. Using standardized indices, we identify three distinct catchment types. Cluster 1 catchments, located in the wetter northwest are characterized by small areas, low groundwater storage, and the highest frequency of hydrological drought relative to other catchments. Cluster 3 catchments, located in the drier east and southeast have larger areas, greater groundwater storage, the highest frequency of meteorological drought but the least hydrological droughts. However, once established, droughts in Cluster 3 tend to be more persistent with large accumulated deficits. Cluster 2 catchments, located in the southwest and west, are intermediate to Clusters 1 and 3, with hydrological droughts typically of shorter durations, reduced accumulated deficits but greater mean deficits. The most extreme droughts based on accumulated deficits across all catchments occurred in 1803–1806, 1854–1859, 1933–1935, 1944–1945, 1953–1954, and 1975–1977. Although not as severe, droughts in 1887–1888, 1891–1894, and 1971–1974 also appear as significant extremes. Changes in drought characteristics reveal a complex picture with the direction, magnitude, and significance of trends dependent on the accumulation period used to define drought, the period of record analysed, and the reference period used to standardize indices. Of particular note is a tendency towards shorter, more intense meteorological and hydrological droughts. Our findings offer important insight for drought and water management in Ireland given the paucity of extreme droughts in short observed river flow records.

The Relationship Between Institutional and Organizational Party Power: Evidence from the Minnesota House’s Experimental Setting

How parties manage capitols and constituencies in the American context is the subject of much political inquiry. This research examines whether majority parties’ institutional capability depends on their ability to organize beyond the legislative chamber. An opportunity to examine such a question presents itself in a curious historical occurrence, the Minnesota Legislature’s abrupt de jure ban on political parties. Using data compiled from the Minnesota House of Representatives, I compare partisan characteristics in roll call voting in the context of an experimental setting. The results suggest legislative leadership powers lose efficacy when party’s organizational capacity beyond the chamber diminishes.

Self-Attention-Based Deep Learning Network for Regional Influenza Forecasting.

Early prediction of influenza plays an important role in minimizing the damage caused, as it provides the resources and time needed to formulate preventive measures. Compared to traditional mechanistic approach, deep/machine learning-based models have demonstrated excellent forecasting performance by efficiently handling various data such as weather and internet data. However, due to the limited availability and reliability of such data, many forecasting models use only historical occurrence data and formulate the influenza forecasting as a multivariate time-series task. Recently, attention mechanisms have been exploited to deal with this issue by selecting valuable data in the input data and giving them high weights. Particularly, self-attention has shown its potential in various forecasting tasks by utilizing the predictive relationship between objects from the input data describing target objects. Hence, in this study, we propose a forecasting model based on self-attention for regional influenza forecasting, called SAIFlu-Net. The model exploits a long short-term memory network for extracting time-series patterns of each region and the self-attention mechanism to find the similarities between the occurrence patterns. To evaluate its performance, we conducted extensive experiments with existing forecasting models using weekly regional influenza datasets. The results show that the proposed model outperforms other models in terms of root mean square error and Pearson correlation coefficient.

New Perspectives on The Tigray War

Ethiopia’s location is in the horn of Africa. It is Africa's oldest independent country and the second-largest country in terms of population in the continent. Ethiopia was historically called Abyssinia which was derived from the Arabic form of the Ethiosemitic name. And although former President Abiy-Ahmed remains the first and only Ethiopian Head of State to have won the Nobel peace prize in 2019 for bringing an end to the over one decade-long conflict with Eritrea. More importantly, he has been subject to numerous criticisms and scrutiny due to the occurrence of several mass protests, incarcerations of political figures and opponents as well as the censorship of the internet, journalists which ultimately led to the resurgence of ethnic and tribal divisions between Ethiopians. This can be termed as the cause for open conflict in the Northern region of Tigray. This paper will investigate and establish new perspectives of the Tigray war through the backdrop of historical occurrences and how the metamorphosis of these occurrences have helped define and shape the state of affairs in Tigray.

New records in non-native vascular plants of Russian Lapland.

BackgroundThe non-native vascular plants of Murmansk Region (European Russia) are under active investigation towards the compilation of the first complete checklist. This work is part of the project 'Flora of Russian Lapland', which ultimately aims at the complete inventory of the taxonomy, distribution and status of vascular plant species in Murmansk Region, based on the comprehensive database of herbarium specimens, field observations and literature.New informationNew territory-level records of non-native vascular plants emerged during our inventory of herbarium collections and recent fieldwork. Fourteen species (Anthemisruthenica, Aruncusdioicus, Bromuscommutatus, Chaerophyllumhirsutum, Galegaorientalis, Geumaleppicum, Leonurusquinquelobatus, Lepidiumdensiflorum, Levisticumofficinale, Myrrhisodorata, Phleumphleoides, Prunusarmeniaca, Rorippasylvestris, Seneciovernalis) are reported as new to Murmansk Region. The historical occurrences of alien plants appeared in the territory largely as contaminants (of seed or forage). In particular, Rorippasylvestris and Seneciovernalis arrived with the forage imported during the Second World War. All recent occurrences originated by escape from confinement (ornamental purposes, horticulture, agriculture), reflecting a high diversity of the modern assortment of cultivated plants in commerce and private gardens. Regarding the invasion status, five alien species are considered casual and eight species are treated as locally established or persisting (for uncertain time). Only one species, Galegaorientalis, is considered naturalised and capable of further spreading in the territory, although without invasive potential.

«To Tell about China»

China has gotten much more involved in debating and solving international concerns in recent years. This is the concept behind China's new foreign policy line, Diplomatic Activism. President Xi Jinping's speech on “unprecedented changes not seen in hundreds of years” poses new and pressing questions for Chinese diplomats, politicians, and academics to consider, such as “What role should China play in the world?” and “How can we effectively solve the current complex international issues?” As a result, the Chinese leadership has called for “telling China’s stories well” with other countries in order to assume the role of a big power and offer their thoughts and potential answers to this tough situation. The article considers a number of issues related to the concept of “Telling China’s stories well”, ranging from the inability of Western theories and Chinese tradition to correctly interpret China's actions at this stage to the need to develop and systematize the Chinese experience based on Chinese historical experience, cultural and philosophical heritage, as well as the demands of the times, and so on. The “Four matters of confidence”, in particular, is examined as an important component of the “China’s stories”. The author came to a conclusion that the notion of “Telling China’s stories” is a historical occurrence, because the Chinese had previously learnt to do so in antiquity in order to guarantee their dominance over the surrounding vassal states. And, with the assistance of Edgar Snow, and others, the CCP effectively informed the world about communist actions in the new history of China. Today, the new China is actively “talking about its stories” in order to promote and contribute to the creation of a new world order based on cohabitation, mutual benefit etc., rather than Western-centrism. Author expresses his deep appreciation to Prof. A.N. Karneev for constructive comments on the article's content and editing.

Forecasting variance of NiftyIT index with RNN and DNN

A time series is an order of observations engaged serially in time. The prime objective of time series analysis is to build mathematical models that provide reasonable descriptions from training data. The goal of time series analysis is to forecast the forthcoming values of a series based on the history of the same series. Forecasting of stock markets is a thought-provoking problem because of the number of possible variables as well as volatile noise that may contribute to the prices of the stock. However, the capability to analyze stock market leanings could be vital to investors, traders and researchers, hence has been of continued interest. Plentiful arithmetical and machine learning practices have been discovered for stock analysis and forecasting/prediction. In this paper, we perform a comparative study on two very capable artificial neural network models i) Deep Neural Network (DNN) and ii) Long Short-Term Memory (LSTM) a type of recurrent neural network (RNN) in predicting the daily variance of NIFTYIT in BSE (Bombay Stock Exchange) and NSE (National Stock Exchange) markets. DNN was chosen due to its capability to handle complex data with substantial performance and better generalization without being saturated. LSTM model was decided, as it contains intermediary memory which can hold the historic patterns and occurrence of the next prediction depends on the values that preceded it. With both networks, measures were taken to reduce overfitting. Daily predictions of the NIFTYIT index were made to test the generalizability of the models. Both networks performed well at making daily predictions, and both generalized admirably to make daily predictions of the NiftyIT data. The LSTM-RNN outpaced the DNN in terms of forecasting and thus, grips more potential for making longer-term estimates.

Mac Giolla Phádraig Dál gCais: an ancient clan rediscovered

Y-DNA analysis of Fitzpatricks has turned traditional historical narratives of how the surname was taken on its head. The attachment of the surname Fitzpatrick to the Barons of Upper Ossory, who were supposedly the descendants of Mac Giolla Phádraig Osraí and, in turn, of an ancient Laighin (Leinster) lineage, is no longer sustainable. DNA insights and critical assessment of historical records have demonstrated that those who claim to descend from the barons have a Y-haplotype consistent with them emerging from a line of clerics out of a Norman-Irish origin ca. 1200 AD. Questions arise, therefore, regarding the origins of other large Fitzpatrick groups who, based on Y-DNA, can be shown to descend from ancient Irish. Could any of these lines descend from the Mac Giolla Phádraig Osraí of old, those of Annalistic fame? For the first time, this article introduces the Mac Giolla Phádraig Dál gCais in a scholarly narrative. Mac Giolla Phádraig Dál gCais are, unquestionably, an ancient Pátraic surname clan. But are they also a Mac Giolla Phádraig lineage that arose in Osraí in ancient times? Such a question radically disrupts traditional narratives, yet the answer is ‘maybe’ – sound historical, genealogical, and name occurrence evidence supports the view that there is no need to adhere to a singular patrimony for the Mac Giolla Phádraig Osraí and that a Dál gCais line was well positioned to have territory in Osraí and adopt Mac Giolla Phádraig as a surname. With certainty, the Mac Giolla Phádraig who are the subject of this article are Dál gCais on a genetic basis since, via their paternal haplotype, they share common ancestry with Brian Bóruma, High King of Ireland. The descendants of those Mac Giolla Phádraig Dál gCais feature through ancient records for An Clár (Clare) are still found in the County, yet many derive from lines that were dispersed from their ancient An Clár homelands in the seventeenth-century. From An Clár to Oileáin Árann (Arann Islands), and Gaillimh (Galway), and – one way or another – on to Maigh Eo (Mayo), and Ros Comáin (Roscommon), they are a great and ancient Mac Giolla Phádraig Clan, who at times held much wealth, power, and influence. And some were smugglers!

Current state of critically endangered Neotinea ustulata (Orchidaceae) in Lithuania and report on a new record of the species

Neotinea ustulata (Orchidaceae) is a rapidly declining species throughout much of its range and is classified as critically endangered in Lithuania. Most of the historical occurrences of the species were concentrated in northwestern Lithuania, while the largest extant population was in the southern part of the country. In July 2022, a new population of Neotinea ustulata was discovered in an urbanised habitat in Šiauliai in northern Lithuania. A total of 84 individuals of this species were recorded in the population. In the southern part of Lithuania (Varėna distr.), the studied population comprised 86 individuals in 2002 and had decreased to 64 individuals by 2022. The total currently known population of the species in the country consists of about 150 individuals and remains critically endangered. The individuals of Neotinea ustulata studied in Šiauliai were significantly lower and had shorter inflorescences than the plants studied in Varėna district in 2002 and 2022. Since the population of Neotinea ustulata in Šiauliai is in an urbanised area, its conservation poses a significant challenge, making it difficult to make long-term predictions on the development of the population. Therefore, it is essential to continue searching for populations of Neotinea ustulata in the country, perform detailed studies on the plants’ reproductive potential, and properly organise the management and protection of extant populations and their habitats.

IPODfish – A new method to infer the historical occurrence of diadromous fish species along river networks

Available information on diadromous fish species historical occurrences is generally biased and incomplete across species distribution range and spatial scales. This work aims to establish a new methodological framework (iPODfish – Inferring Past Occurrences of Diadromous Fish) to obtain a more complete representation of the historical occurrences of diadromous fish species over their full distribution range. The iPODfish is based on assumptions, rules and thresholds derived from the interplay between freshwater network features, diadromous fish species ecology and known historical occurrence. These are used to establish historical pseudo-occurrences at the segment scale, i.e., locations where the species was most likely to be present or absent. The methodology is expressed by a tree-like representation of a stepwise, information supported, decision process. It has five steps (separating main river segments from tributary segments; accounting for segments specificities; imposing the relative distance threshold; imposing the Strahler value threshold, and; establishing the sub-basin Strahler threshold), divides into two moments of application (main river followed by the tributaries) and establishes presences, pseudo-presences and pseudo-absences. The iPODfish can deal with multiple information sources, cope with data bias and provide a reliable consistent historical occurrence output at the segment scale for the known historical geographical range of the species. Despite its inference nature, iPODfish is still a conservative procedure leading to ecologically coherent outputs that may be applied to any diadromous fish species (with a relevant amount of historical data available) in any river network throughout the globe because the concepts and definitions used are general ecological features of diadromous and freshwater networks. The method outputs are applicable in biogeographical and/or macroecological studies using historical data and may prove useful to the management and conservation of diadromous fish species.

Fire hazard forecast by the regional climate change projection using the ETA model: a case study in Bahia, Brazil

This article proposes a method for predicting fire occurrence, considering regional climate change projection using the Eta model, with a 20 km resolution, for the RCP4.5 and RCP8.5 scenarios. Fire occurrence in the state of Bahia was calculated as a function of the three main sensitivity factors on a daily time-scale: days without precipitation, precipitation, and maximum temperature. Historical fire occurrences from 1998 to 2018 and meteorological data from 1960 to 2018 were obtained from official institutes, and weather forecast parameters from 2018 to 2050 were downscaled from the web platform PROJETA. The correlations between the meteorological factors and fire occurrence were calculated for the historical data and a weight factor corresponding to a control simulation. Afterwards, a correction factor was determined, based on the historical fire occurrence data used for the forecast in the two scenarios. The results indicate that between 2018 and 2050, risk of fire will have an average increase of 27% at the RCP4.5 and 38% at the RCP8.5 scenario.

Identification of the historical drought occurrence on the Danube River and its tributaries

Identification of the historical drought occurrence on the Danube River and its tributaries

Movement patterns of a Critically Endangered elasmobranch (Dipturus intermedius) in a Marine Protected Area

Abstract Marine Protected Areas (MPAs) are widely used in marine management, but for mobile species understanding the spatio‐temporal scale of management measures that is required to deliver conservation benefits depends on a detailed knowledge of species’ movements that is often lacking. This is especially the case for species of skate (Rajidae) for which relatively few movement studies have been conducted. In Scotland, the Loch Sunart to the Sound of Jura MPA covering 741 km2 has been designated for the conservation of the Critically Endangered flapper skate (Dipturus intermedius), but fine‐scale movements within this area remain poorly understood. A passive acoustic telemetry study which coupled acoustic tagging of 42 individuals and a static array of 58 receivers was conducted from March 2016 to June 2017. Using acoustic detection time series, angler capture–recapture data and depth time series from archival tags, fine‐scale movements of individuals were investigated. Overall, 33 of the 42 tagged individuals were detected. Residency, site fidelity and transiency were documented. Residency around receivers, lasting from 3 to more than 12 months, was documented in 16 acoustically detected individuals (48%) and all life‐history categories, but was most noticeable among females. Acoustic detections were associated with depth, salinity and season, but there was no evidence that individuals formed close‐knit groups in the areas in which they were detected. Taken together with historical occurrence records of flapper skate, the prevalence and scale of residency documented here suggest that the MPA is sufficiently large to benefit a notable percentage (38 [24–52]%) of skate found in the study area over monthly and seasonal timescales. This result strengthens the case for the use of MPAs to support the conservation of flapper skate and other skate species that display similar movement patterns in areas of high local abundance.

A General Framework for Spatio-Temporal Modeling of Epidemics With Multiple Epicenters: Application to an Aerially Dispersed Plant Pathogen

The spread dynamics of long-distance-dispersed pathogens are influenced by the dispersal characteristics of a pathogen, anisotropy due to multiple factors, and the presence of multiple sources of inoculum. In this research, we developed a flexible class of phenomenological spatio-temporal models that extend a modeling framework used in plant pathology applications to account for the presence of multiple sources and anisotropy of biological species that can govern disease gradients and spatial spread in time. We use the cucurbit downy mildew pathosystem (caused by Pseudoperonospora cubensis) to formulate a data-driven procedure based on the 2008 to 2010 historical occurrence of the disease in the U.S. available from standardized sentinel plots deployed as part of the Cucurbit Downy Mildew ipmPIPE program. This pathosystem is characterized by annual recolonization and extinction cycles, generating annual disease invasions at the continental scale. This data-driven procedure is amenable to fitting models of disease spread from one or multiple sources of primary inoculum and can be specified to provide estimates of the parameters by regression methods conditional on a function that can accommodate anisotropy in disease occurrence data. Applying this modeling framework to the cucurbit downy mildew data sets, we found a small but consistent reduction in temporal prediction errors by incorporating anisotropy in disease spread. Further, we did not find evidence of an annually occurring, alternative source of P. cubensis in northern latitudes. However, we found a signal indicating an alternative inoculum source on the western edge of the Gulf of Mexico. This modeling framework is tractable for estimating the generalized location and velocity of a disease front from sparsely sampled data with minimal data acquisition costs. These attributes make this framework applicable and useful for a broad range of ecological data sets where multiple sources of disease may exist and whose subsequent spread is directional.