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Abstract: Let $P$ be a set of at most $n$ points and let $R$ be a set of at most $n$ geometric ranges, such as disks or rectangles, where each $p \in P$ has an associated supply $s_{p} > 0$, and each $r \in R$ has an associated demand $d_{r} > 0$. A (many-to-many) matching is a set ${\mathcal A}$ of ordered triples $(p,r,a_{pr}) \in P \times R \times {\mathbb R}_{>0}$ such that $p \in r$ and the $a_{pr}$'s satisfy the constraints given by the supplies and demands. We show how to compute a maximum matching, that is, a matching maximizing $\sum_{(p,r,a_{pr}) \in {\mathcal A}} a_{pr}$. Using our techniques, we can also solve minimum bottleneck problems, such as computing a perfect matching between a set of $n$ red points $P$ and a set of $n$ blue points $Q$ that minimizes the length of the longest edge. For the $L_\infty$-metric, we can do this in time $O(n^{1+\varepsilon})$ in any fixed dimension, for the $L_2$-metric in the plane in time $O(n^{4/3 + \varepsilon})$, for any $\varepsilon > 0$.
Keywords: many-to-many matching, bipartite, planar, geometric matching, approximation
Published in DiRROS: 11.12.2024; Views: 62; Downloads: 27
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Keywords: les, tržne razmere, les
Published in DiRROS: 11.12.2024; Views: 69; Downloads: 21
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Keywords: gozdovi, gozdarstvo, epidemija, Covid-19, lastniki gozdov, izpad dohodka, finančno nadomestilo, odkup lesa
Published in DiRROS: 11.12.2024; Views: 68; Downloads: 22
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Keywords: gozdovi, gozdarstvo, epidemija, Covid-19, lastniki gozdov, sanitarna sečnja, finančno nadomestilo, odkup lesa
Published in DiRROS: 11.12.2024; Views: 72; Downloads: 22
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Abstract: Early detection and rapid response are essential to deal effectively with new introductions of invasive alien species (IAS). Citizen science platforms for opportunistic recording of species are increasingly popular, and there is potential to harvest their data for early detection of IAS, but this has not been tested. 2. We evaluated the potential of data from existing citizen science platforms for early detection of IAS by obtaining 687 first records of species from 30 European countries where there was both an official first record (i.e. published in scientific literature or by a government agency) and a record in a citizen science platform. We tested how the difference between the two (time lag) was related to species traits, popularity in citizen science platforms, public and research attention and regulatory status. 3. We found that for 50% of the time lag records, citizen science platforms reported IAS earlier than or in the same year as the official databases. Although we cannot determine causality (the first official record could have been from a citizen science platform, or contemporaneous with it), this demonstrates that citizen science platforms are effective for IAS early detection. 4. Time lags were largely affected by species traits. Compared with official records, vertebrates were more likely to have earlier records on citizen science platforms, 2 | GONZÁLEZ-MORENO et al. 1 | INTRODUC TION Biological invasions are among the leading causes of global environmental change, affecting human well-being (Shackleton et al., 2019), causing biodiversity declines and disruption of ecosystem services (Bellard et al., 2022; Vilà et al., 2010), and economic losses (Diagne et al., 2021). Globally, we are witnessing an exponential increase in invasive alien species (IAS) records (Mormul et al., 2022), with no saturation in species establishment (Seebens et al., 2018). When dealing with IAS, it is necessary to be proactive and ensure an early detection and rapid response (de Groot et al., 2022, 2023; Groom et al., 2019). This implies detecting new IAS introductions rapidly and deploying adequate control measures to mitigate their further spread (Reaser et al., 2020). However, founder populations typically occur at low density and are difficult to detect (Fitzpatrick et al., 2009), and the areas at risk are often vast and difficult to monitor efficiently (Groom et al., 2019). Documenting the official first introductions of IAS in a country or region is extremely relevant to early detection and rapid response. First, keeping such a registry provides insight into propagule pressure and, if data are pooled across species, colonisation pressure in an area (Roy et al., 2014). Second, first records can reveal pathways of introduction relevant from a biosecurity perspective. Third, the first occurrence of an introduced species outside captivity or cultivation can be used to track temporal patterns of biological invasions (Seebens et al., 2018) and to feed policy indicators on the state of invasions by following introduction rates (Vicente et al., 2022). Lastly, documenting these first records is a legal requirement for some regulated species (e.g. List of Invasive Alien species of Union concern of EU Regulation 1143/2014 reported through EASIN-Notsys) and the notification requirements ensure neighbouring countries or regions are informed on interceptions and new occurrences. Doing this via officially established notification mechanisms allows decision-makers to target resources for further surveillance or management. Traditionally, these official first records (i.e. in written reports or publications by government or researchers) have come from professionals (researchers, conservationists/practitioners and government officials) who made the observations or validated the records. However, citizen science (Heigl et al., 2019) has recently emerged as a potentially effective early warning system for the detection of new IAS introductions (Adriaens et al., 2015; Hulbert et al., 2023; Pocock et al., 2024; Roy et al., 2018) and for tracking of their subsequent spread and impact (de Groot et al., 2022; Johnson et al., 2020; Marchante et al., 2017). Overall, citizen science, as the ‘engagement of non-professionals in scientific investigations’ (Miller-Rushing et al., 2012), is on the rise in environmental sciences and biodiversity research (Dickinson et al., 2010; Pocock et al., 2017), becoming especially pronounced over the last 15 years for biological invasions (Price-Jones et al., 2022). This has been facilitated by the onset of novel technologies in biodiversity research (August et al., 2015; Johnson et al., 2020; Starr et al., 2014), including the use of mobile apps and social media (Adriaens et al., 2015; Howard et al., 2022; Schade et al., 2019). Citizen science might promote faster and more efficient flow of data on IAS introductions and spread, as volunteer observers can act as millions of eyes on the ground (Pocock et al., 2024). This public involvement allows detection of new IAS while their populations are still localised and small (Pawson et al., 2020), or when present within large, sparsely populated areas (e.g. forest ecosystems; de Groot et al., 2023; Hulbert et al., 2023). Citizen scientists can record in private or remote areas that are otherwise rarely visited by professionals (Delaney et al., 2008; Dubaić et al., 2022; Palmer et al., 2017). Besides, current surveillance schemes (e.g. for insect pests using pheromone traps) mostly target specific species than plants or invertebrates. Greater popularity of the IAS in citizen science platforms and its observation in neighbouring countries resulted in earlier citizen science reporting. In contrast, inclusion in the EU priority list resulted in earlier official recording, reflecting the efficacy of targeted surveillance programmes. However, time lags were not affected by the overall activity of citizen platforms per country. 5. Synthesis and applications. Multi-species citizen science platforms for reporting nature sightings are a valuable source of information on early detection of IAS even though they are not specifically designed for this purpose. We recommend that IAS surveillance programmes should be better connected with citizen science platforms, including greater acknowledgement of the role of citizen scientists and better data flow from smaller citizen science initiatives into global databases, to support efficient early detection.
Keywords: invasive species, citizen science, early detection
Published in DiRROS: 11.12.2024; Views: 66; Downloads: 36
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