Search

Heliozoans are ambush protists that inhabit most limnetic systems. However, ecological information about planktonic heliozoans is still limited. In this study, we investigated seasonal changes in planktonic heliozoan abundance in the deep northern and shallow southern basins of Lake Biwa at pelagic stations between August 2020 and December 2021. We compared planktonic heliozoan abundance levels between the two basins and examined the relationship between heliozoan abundance and environmental variables. In both basins, high levels of planktonic heliozoan abundance were detected in autumn, winter and spring. In the south basin, there was a significant positive correlation between planktonic heliozoan abundance and chlorophyll a concentration as well as the abundance of the diatoms Aulacoseira granulata and Aulacoseira ambigua. These results suggest that planktonic heliozoans directly or indirectly consume diatoms and that heliozoan abundance is subjected to bottom-up control. Furthermore, planktonic heliozoan abundance in the south basin was higher than that in the north basin, possibly due to the presence of waterweeds, which can serve as habitat for heliozoans, and the redistribution of planktonic heliozoans through resuspension from lake bottom sediments. [ABSTRACT FROM AUTHOR]

In this paper we design efficient algorithms for enumerating (1) the rooted trees with exactly n vertices, (2) the maximal planar graphs with exactly n vertices and (3) the linear extensions of a given poset. Those algorithms are based on tree structures of objects, called the family trees. The first algorithm enumerates each ordered tree with exactly n vertices in O (1) time for each after O (n) time preprocessing. The second algorithm enumerates each maximal planar graph with exactly n vertices in O (n 3) time for each on average. The third algorithm enumerates each linear extension of a given poset in O (1) time for each after O (n 2) time preprocessing, where n is the number of the element in the set of the poset. [ABSTRACT FROM AUTHOR]

As interest in natural capital grows and society increasingly recognizes the value of biodiversity, we must discuss how ecosystem observations to detect changes in biodiversity can be sustained through collaboration across regions and sectors. However, there are many barriers to establishing and sustaining large-scale, fine-resolution ecosystem observations. First, comprehensive monitoring data on both biodiversity and possible anthropogenic factors are lacking. Second, some in situ ecosystem observations cannot be systematically established and maintained across locations. Third, equitable solutions across sectors and countries are needed to build a global network. Here, by examining individual cases and emerging frameworks, mainly from (but not limited to) Japan, we illustrate how ecological science relies on long-term data and how neglecting basic monitoring of our home planet further reduces our chances of overcoming the environmental crisis. We also discuss emerging techniques and opportunities, such as environmental DNA and citizen science as well as using the existing and forgotten sites of monitoring, that can help overcome some of the difficulties in establishing and sustaining ecosystem observations at a large scale with fine resolution. Overall, this paper presents a call to action for joint monitoring of biodiversity and anthropogenic factors, the systematic establishment and maintenance of in situ observations, and equitable solutions across sectors and countries to build a global network, beyond cultures, languages, and economic status. We hope that our proposed framework and the examples from Japan can serve as a starting point for further discussions and collaborations among stakeholders across multiple sectors of society. It is time to take the next step in detecting changes in socio-ecological systems, and if monitoring and observation can be made more equitable and feasible, they will play an even more important role in ensuring global sustainability for future generations. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'. [ABSTRACT FROM AUTHOR]

Given a set C of points and a horizontal line L in the plane and a set F of points on L , we want to find a set of disks such that (1) each disk has the center at a point in F (but with arbitrary radius), (2) each point in C is covered by at least one disk, and (3) the cost of the set of disks is minimized. Here the (transmission) cost of a disk with radius r is r α , where α is a positive constant depending on the power consumption model, and the cost of a set of disk is the sum of the cost of disks in the set. In this paper we first give an algorithm based on dynamic programming method to solve the problem in L 1 metric. A naive dynamic programming algorithm runs in O (| C | 3 | F | 2) time. We design an algorithm which runs in O (| C | | F | 2 + | C | log | C |) time. Then we design another algorithm to solve the problem in L 1 metric based on a reduction to a shortest path problem in a directed acyclic graph. The running time of the algorithm is O (| C | 2 + | C | | F |). [ABSTRACT FROM AUTHOR]

Let C be a set of n customers and F be a set of m facilities. An r -gather clustering of C is a partition of the customers in clusters such that each cluster contains at least r customers. The r -gather clustering problem asks to find an r -gather clustering which minimizes the maximum distance between a pair of customers in a cluster. An r -gathering of C to F is an assignment of each customer c ∈ C to a facility f ∈ F such that each facility has zero or at least r customers. The r -gathering problem asks to find an r -gathering that minimizes the maximum distance between a customer and his/her facility. In this work, we consider the r -gather clustering and r -gathering problems when the customers and the facilities are lying on a "star". We show that the r -gather clustering problem and the r -gathering problem with customers and facilities on a star with d rays can be solved in O (n + d d r d d r log d) and O (n + m + (d + log m) d 4 r 2 + d d r d 2 d d r log d) time, respectively. Furthermore, we prove the hardness of a variant of the r -gathering problem, called the min-max-sum r -gathering problem, even when the customers and the facilities are on a star. We also study the r -gathering problem when the customers and the facilities are on a line, and each customer location is uncertain. We show that the r -gathering problem can be solved in O (n k + m n log n + (m + n log k n + n r n r ) log m n) and O (m n log n + (n log n + m) log m n) time when the customers and the facilities are on a line, and the customer locations are given by piecewise uniform functions of at most k + 1 pieces and "well-separated" uniform distribution functions, respectively. [ABSTRACT FROM AUTHOR]