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    Spatial scale and the synchrony of ecological disruption

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    Hard times tear coupled seabirds apart

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    Many seabirds form long-term pairings, but do not necessarily mate for life — and are more likely to ‘break up’ in years when environmental conditions are unfavourable, researchers reveal.

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    doi: https://doi.org/10.1038/d41586-021-03509-z

    References1.Ventura, F., Granadeiro, J. P., Lukacs, P. M., Kuepfer, A. & Catry, P. Proc. R. Soc. B https://doi.org/10.1098/rspb.2021.2112 (2021).Article 

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    Phosphorus supply affects long-term carbon accumulation in mid-latitude ombrotrophic peatlands

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    The significance of region-specific habitat models as revealed by habitat shifts of grey-faced buzzard in response to different agricultural schedules

    Study regionsWe conducted the field survey in the Kyushu of southern Japan (Fig. 2a,b). The rice-transplanting schedule in Kyushu, is generally late (in late June24) because it is necessary to delay rice-transplanting timing after the harvest of wheat as a back crop22,23. However, since the technique of early transplanting was established around 1960, early transplanting (in early April24) has been practiced instead of a back crop of wheat in some areas in Kyushu25,26, so the rice-transplanting schedules differ at the regional scale. We established two study regions with early-transplanting schedules (Karatsu in northern Kyushu; N33.4, E129.9 and Amakusa in central Kyushu; N32.5, E130.1), and two study regions with late-transplanting schedules (Itoshima in northern Kyushu; N33.6, E130.2 and Uki in central Kyushu; N32.6, E130.8) (Fig. 2c–f). Each study region is 10–20 km2, and the distances between the regions are 20–140 km. Climatic conditions between the regions are similar (Supplementary Table S3). The size of each region is much larger than the size of the typical territory of breeding buzzards (approximately 500 m radius from the nest18).Figure 2Map of (a) Japan and (b) the entire study regions, (c) Karatsu, (d) Amakusa, (e) Itoshima and (f) Uki. Squares represent study blocks. Light and dark grey areas indicate waterbodies and residential areas, respectively. Background map source is the black map of Japan (http://www.craftmap.box-i.net/japan/line.php) and the topographic data of Fundamental Geospatial Data developed by the Geospatial Information Authority of Japan (https://www.gsi.go.jp/kiban/).Full size imageBuzzards surveyWe examined the distribution of buzzards in 2019. Buzzards are migratory birds that breed in Japan, northeastern China, and the Russian Far East in summer, and overwinter in the Ryukyu Islands, Southeast Asia, and southern China27. In our study regions, buzzards start breeding in April, soon after returning from their wintering area. Buzzards incubate their eggs from late April until late May when they hatch. Once the eggs hatch, buzzards feed nestlings. Then nestlings start to fledge in late June, but the adults continue feeding their fledglings for several weeks. Buzzards migrate to their wintering grounds around October. The breeding season of buzzards thus overlaps largely with the rice production season, but there is a slight but significant differences in seasonality, i.e., paddies are already planted and flooded before hatching in early rice-transplanting schedules, while not yet flooded in late rice-transplanting schedules.Because breeding buzzards were thought to prefer mosaic landscapes of farmland and forest17,19, we established 62 study blocks that included edges between farmland and forest in each study region (Fig. 2c–f; northern-early: 17 central-early: 11 northern-late: 17 central-late: 17). The study blocks were 400 m square and located at least 700 m apart from each other, a distance determined from the knowledge that buzzards intensively use an area of 200 m from their nests18. To examine the presence/absence of breeding buzzards in each block, we conducted 2 days of 30-min observations during the breeding season (April to July). Using a pilot study, we determined that this observation time was enough to minimize the possibility of missing buzzards. We identified breeding individuals based on displays, feeding behaviors, and territorial behaviors.Land use surveyDuring the brood-rearing period (late June to early July) in 2019, we recorded the land use (forest, grassland, flooded paddies, non-flooded paddies) in each block. We then used these data to create a land use map in each block using QGIS3.16.228 and overlaying it on Google Earth aerial photographs in 2017.Prey species surveyWe surveyed the distribution of prey species in paddies and grasslands in the study regions in 2019 and 2020. Based on the previous studies on the feeding habits of buzzards17,18,19,20,21, we surveyed the distribution of frogs and orthopterans larger than 3 cm as prey of this size is considered their main prey. We established survey transects in paddies and grasslands in our study blocks. We conducted surveys twice each year during the brood-rearing period (late June to early July), when breeding buzzards need a large amount of prey. We walked along the transects and counted the number of prey species observed within 0.5-m of both sides. This survey method is suitable to assess prey availability29 because buzzards visually search for prey (e.g.20,30). A total of 148 20 m-transects were placed in paddies in 34 blocks and 157 15-m transects were placed in grasslands in 37 blocks, and each transect was surveyed in both or either 2019 and 2020. In the paddy transects, we recorded the height and coverage of vegetation, the ditch characteristics (none, concrete ditch, earthen ditch), the surrounding land use (10 m width from the transect: flooded paddy, non-flooded paddy, grassland, forest, stone wall, and road), and flooding or non-flooding in the paddy field adjacent to transects. In grassland transects, we recorded the height and coverage of vegetation and the grassland types on which the transect was located (abandoned land, orchard, farmland, bank, forest edge).Statistical analysisBuzzard modelTo investigate the habitat selection of buzzards, we used a generalized linear model with a binomial error distribution. We used the edge length between the landscape elements and forest as independent variables, because the edge length, rather than the area of the landscape elements, is known to be an important determinant for buzzard distribution19. We prepared a land use map and calculated the edge length between the landscape elements and forest by using the field calculator of QGIS, and values were standardized (mean = 0 and SD = 1).To explore the variation in habitat selection across regions with different transplanting schedules, we first used a model that included the interaction term of transplanting schedules and landscape elements as independent variables. The length of paddy-forest edges, grassland-forest edges, the transplanting schedules, the interaction term of the edge length and the transplanting schedules, and the study regions were included as independent variables (details of independent variables: Supplementary Table S4). The presence/absence of breeding buzzards was included as a dependent variable. We analyzed the full model and all sub-models containing different combinations of all independent variables, including the null model. We regarded models that had ΔAIC values (the difference between the AIC value of the focal model and that of the best-fit model) of  0.6) to avoid serious multicollinearity.We performed all analyses in R 4.0.333, using the glmmTMB packages34 for model fitting, the MuMIn package35 for model selection and averaging, and the ggplot236 for graphic illustration or results. More

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    Developing water, energy, and food sustainability performance indicators for agricultural systems

    Case studyThe Zayandeh-Rud basin (Fig. 1), a arid region of Iran, was selected to evaluate the SPIs. The Zayandeh-Rud basin is located in the central part of Iran. It has an area of 26,972 km2 area, where there are multiple water stakeholders such as agriculture, industry, urban and the environment sectors, with agriculture being the main user of the basin. Water resources in the basin are divided into surface water and groundwater. Approximately 100,000 ha among 113,000 ha of the agricultural area is irrigated by Zayandeh-Rud dam, and 3100 mm3 of water resources are used in the agricultural sector. The main surface water source in the basin, Zayandeh-Rud River originates in the Zagros Mountains and is about 350 km long in a west to east direction passing by the city of Isfahan. The Zayandeh-Rud River is an important water source for the agricultural, industrial, health, and urban sectors in Central Iran and the Chaharmahal-Bakhtiari and Isfahan provinces.Figure 1The location of the Zayandeh-Rud basin in Iran.Full size imageMulti-criteria decision makingMulti-criteria decision making includes two categories of multi-objective decision making and multi-criteria decision making, which are implemented to select the best decision among several alternatives or to evaluate decisions. This work applies decision making as a multi-criteria decision to achieve a goal. Each decision includes objectives, alternatives, and criteria. A problem’s goal is first defined. Alternatives are different options for wastewater management in this instance that are assigned weights based on their contribution to achieving the goal. Criteria are also factors that are measured by the purpose of the alternatives23. The AHP method helps achieve a defined goal after completing the steps outlined below.The AHP methodThe Analytical Hierarchy Process (AHP), developed by Saaty24, is a multi-criteria decision-making method for solving complex problems. It combines objective and quantitative evaluation in an integrated manner based on multi-level comparisons, and helps organize the essential aspects of a problem into a hierarchical format. It regularly organizes tangible and intangible factors and offers a structured and a relatively simple solution to decision problems. The AHP method ranks alternatives propose to tackle a decision-making problem. The ranking is based through a sequence of pairwise comparisons of evaluation criteria and sub-criteria.The AHP structureIn a hierarchical structure the communication flow is top-down. First, indicators and evaluation criteria are defined from experts who are asked for their expert opinions. The criteria serve the purpose of determining the relative worth of alternatives entertained to solve a multi-criteria decision-making problem. Thereafter, the problem is divided into criteria and sub-criteria for the evaluation of alternatives. Figure 2 depicts a generic AHP structure depicting a goal to be met with (n) = 4 evaluation criteria, and (m=3) alternatives to cope with a problem (in our case SIPs).Figure 2Goal, criteria, and alternatives in a generic hierarchical structure.Full size imageThe pairwise comparison matrixThe pairwise comparison matrix ((A)), called the Saaty Hierarchy Matrix, measures the importance of each criterion (or sub-criterion) relative to other criteria based on a numeric scale ranging from 1 to 9. Criteria that are extremely preferred, very strongly preferred, strongly preferred, moderately preferred, and equally preferred are assigned the values 9, 7, 5, 3, and 1, respectively, in the scale of preference; intermediate values are assigned to adjacent scales of preference. Thus, the values 8, 6, 4, and 2 are assigned respectively to the adjacent scales (9,7), (7,5), (5,3), and (3,1)24. These numerical assignment of values is made based on the opinion of experts25. The pairwise comparison matrix ((A)), therefore, represents a set of relative weights assigned to the criteria23. The general form of a pairwise comparison matrix when there are (n) evaluation criteria is written in Eq. (1):$$A=left[{a}_{ij}right]=left[begin{array}{cccc}{1=w}_{1}/{w}_{1}& {w}_{1}/{w}_{2}& dots & {w}_{1}/{w}_{n}\ {w}_{2}/{w}_{1}& 1={w}_{2}/{w}_{2}& dots & {w}_{2}/{w}_{n}\ .& .& dots & .\ .& .& dots & .\ .& .& dots & .\ {w}_{n}/{w}_{1}& {w}_{n}/{w}_{2}& …& 1={w}_{n}/{w}_{n}end{array}right]$$
    (1)

    where ({w}_{i}/{w}_{j}) denotes the weight assigned to the (i)-th criterion relative to the (j)-th criterion24. Clearly, ({a}_{ji}=1/{a}_{ij}), with ({a}_{ji}={a}_{ij}=1) when (i=j).The ratio matrixThe ratio matrix ((R)) has elements ({r}_{ij}) is calculated by Eq. (2):$$R=left[{r}_{ij}right]=left[begin{array}{cccc}1& {a}_{12}& dots & {a}_{1n}\ 1/{a}_{12}& 1& dots & {a}_{2n}\ .& .& .& .\ .& .& .& .\ .& .& .& .\ 1/{a}_{1n}& 1/{a}_{2n}& dots & 1end{array}right]$$
    (2)

    clearly, ({r}_{ij}={a}_{ij}) when (jge i), and ({r}_{ij}=1/{a}_{ji}) when (j More

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    Reconciling biome-wide conservation of an apex carnivore with land-use economics in the increasingly threatened Pantanal wetlands

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