Ecology

A total number of 3189 lakes have been spatially delimited and analyzed. The delimitation and spatial distribution of the lakes revealed their uneven distribution within the Romanian territory. The largest share of lakes, (41.5%) are distributed within the low plains, located mainly in the South and West of the country. About 36% of the identified lakes are located in the hilly and plateau units, while 11.5% are in the mountain areas and about 11% in the Danube Delta.
The assessment of the state of degradation of the lentic ecosystems by the GIS based extended WRASTIC model revealed that more than half (57%) of the analyzed lakes are classified as semi-degraded. These are mostly distributed in the plains (46%) and in the plateau areas (33%) (Fig. 1).
Figure 1

Distribution of lentic ecosystems in Romania according to the major topography units (this map was created with Arc GIS 10.5 software).

Full size image

The lakes classified as degraded represent 31% of the total, mostly located in the plains (48%) and plateau (36.5%), the least part being located in the Danube Delta (about 0.5%). The lakes in the natural state represent a small share, respectively about 13%, generally located in the Danube Delta (72%) and the mountain areas (21%) (Supplementary Table 1).
Altitudinal stages represent a restrictive factor in the spatial distribution of lakes throughout the country. Most lakes, about 76%, are located at low altitudes, respectively below an altitude of 200 m. The number of lakes identified at higher altitudes, over 800 m, is reduced, representing about 8% of the total number of analyzed lakes (Fig. 2).
Figure 2

Distribution of lentic ecosystems on the Romanian territory according to the altitudinal stages (this map was created with Arc GIS 10.5 software).

Full size image

Regarding the natural lakes, the largest part of them is represented by natural lakes located at altitudes less than 200 m (about 83%). In the same time, about 75% of the lakes evaluated as degraded are located at altitudes less than 200 m.
About 98.5% of the 412 lakes in the natural state are located, partially or totally, in protected areas of national or international interest, such as national and natural parks, Ramsar sites, Biosphere reserves, UNESCO World heritage sites and Natura 2000 sites (Sites of Community Importance and Special Protection Areas) (Fig. 3.).
Figure 3

Distribution of lake categories according to the state of degradation and the relationship with protected areas of national and international interest in Romania (this map was created with Arc GIS 10.5 software).

Full size image

The percentage of semi-degraded and degraded lakes located in protected areas is lower (about 38% of the semi-degraded lakes, respectively 32.5% of the degraded) (Supplementary Table 2). The other lakes are not included in protected areas and do not own any special protection regime.
As a result of applying the methodology based on WRASTIC-HI index, only 9 lakes out of the total of 412 natural lakes are associated with industrial activities and different forms of small-scale exploitation within their hydrographic basins, while the rest of 98% do not present such activities.
The hydrographic basins of the natural lakes do not cover very large areas, 83% of them stretching on area of less than 39 square km, each. In about 97% of cases, agricultural activities in the reception basin represent below 20% of the economic activity, the irrigation percentage being low and the degree of vegetation cover being high.
Considering the degraded lakes, for a large share of them (87%) of them industrial and exploitation activities, such as mines, quarries or dumps are present within the river basin. A high percentage, about 98%, include treatment plants with different types of processing (primary or secondary) within the reception hydrographic basins. For 96% of the degraded lakes, agricultural activities and permanent irrigation activities are covering over 40% of the related basins area.
Spearman correlation showed that there is a good correlation between the degradation state and several components of the WRASTIC-HI index such as Industrial activities, Recreational activities, Wastewater, Ways of transportation, Irrigation and Agricultural activities (Table 1).
Table 1 Correlation between Degradation state and component indices of the WRASTIC-HI index.
Full size table

Between the state of degradation, on the one hand, and the permeability of the soil, the slope and the vegetation cover of the water lily, on the other hand, the analysis showed that there is no correlation. However, there is a weak correlation between the degradation state and Exposition (Table 2).
Table 2 Correlation between degradation state and the HI index variables, which belong to the WRASTIC-HI index.
Full size table

The computational results indicate a negative correlation between the state of degradation, the percentage of the basin included in the protected areas and the percentage of the basin included in the protected areas of the Natura 2000 network (the probability level of 0.0001, being less than 0.05, indicates that there is a statistical significance) (Table 3).
Table 3 The results of the statistical analysis regarding the relationship between the state of degradation and variables within the river basin.
Full size table

The statistical analysis performed shows that there is no correlation between the Degradation State and Altitude, while between the Degradation state and the Relief units there is a weak negative correlation.
The results indicate also a direct correlation between the state of degradation, the number of inhabitants without access to the sewerage and the population density in the lake basin, the correlation coefficient being 0.024, and respectively 0.235.
It is important to study of the state of the lentic ecosystems both regarding the pressures coming from human activity and the ones originating from climatic changes or other natural phenomena. However, the development of an assessment model that can be applied to all aquatic ecosystems, and lentic ecosystem in particular, is a challenge, because available data are not homogenous, each region and lake having its own particularities. Choosing the proper set of indicators that can be useful for the overall characterization of the quality of lentic ecosystems, will lead to a coherent implementation of biodiversity strategies.
To the best of our knowledge, this is the first evaluation of the quality of lentic ecosystems in Romania by multi-criteria analysis. This assessment is part of a national project for implementation of a national policy on biodiversity, as a response to EU requirements.
Over the time, the scientific literature identified various methodologies for the evaluation of the quality of water resources. Such methods include DRASTIC20,21, and methods derived from DRASTIC22,23,24. Other authors used digital surface model (DSM) and a point dataset as the sources of observation and target locations for Geospatial analysis of lake scenery25.
For integrative water quality management, Feng et al.26, proposed a model-based method. Their method integrated three indices derived from three models for assessment of the risk due to nutrient dynamics26.
A multi-attribute value theory to formulate an integrated water quality assessment method was used by Schuwirth27, for aggregation over multiple pollutants and time.
Another category of indexes that are used in evaluating the state of degradation of lacustrine ecosystems aim at analysis of the presence of degradation sources in supplying basin. For example, Mirzaei et al19 calculated WRASTIC index for assessment of pollution risk, respectively degradation sources, from the watershed that feeds a water body. Potential pollutant load index (PPL) was employed by Romanelli et al18 for analyzing the presence and intensity of potential pollution sources from the drainage area of several lakes, with the purpose of establishing degradation classes of the water body. In the same study, the Lake Vulnerability Index highlighted the capacity of the water body to handle the impact generated by degradation sources, taking into account parameters like slope, soil permeability or aspect of slopes18.
According to the characteristics of the study area, modified versions of WRASTIC index are to be found in the literature, and were implemented by using additional criteria or eliminating some parameters28.
Rahimi et al29 used WRASTIC Index for evaluation of wetland water quality. Their results revealed that the activity in adjacent wetland areas exert a large impact on wetland integrity29.
In another study, aquatic ecosystems pollution risk was evaluated by a combined Fuzzy-WRASTIC method. The model was validated by comparison with samples collected from the case study area. The authors concluded that the method has advantages over other methods, as it includes a wide range of drivers and parameters that influence the water quality. The results obtained pointed that areas with high contamination risk are due to the unbalanced arrangement and compact of land uses in the neighborhood of the aquatic ecosystems30. Using analytical survey and experimental studies Mirzaei et al19 investigated the pollution risk for Zayandehrud river, Iran. Agricultural, industrial activities and population centers were the main causes of pollution in the study case area19.
In Romania, the evaluation of aquatic ecosystems was performed by various researchers, either for a specific area or for a hydrographic basin.
For example, Rosca et al31 studied the impact of anthropogenic activity on water quality parameters of glacial lakes from Rodnei mountains. The factors taken in consideration were tourism and livestock. The pollution index was calculated based on three indices, targeted on heavy metal influences, namely, the heavy metal pollution index (indicating the quality of waters related to the heavy metals content), the heavy metal evaluation index (assessment of the quality of water with respect to heavy metals) and the degree of contamination (used to quantify the contamination level with the heavy metal). The physico-chemical parameters pointed a good quality of the study case lakes. The conclusion of the authors was that minor anthropic alteration and a low anthropogenic impact is exerted in these areas. The only anthropic pressure on the aquatic systems in Rodnei Mountains was reported as being exerted by grazing activities31.
Another paper described the assessment of actual water quality and sedimentological conditions of the Corbu lake, Western Black Sea coast. The ecological status of this lake was found to be from good to weak classes for nitrites, ammonium and phosphates, moderate for sulphates and weak for detergents32.
The impact of human interventions and climate changes on the hydro-chemical composition of Techirghiol lake (Romania) was recently investigated by Maftei et al33. The study identified a degradation of this ecosystem between 1970–1998, due to extensive irrigation in the lake region, followed by a major decrease of the lake’s salinity33. Physico-chemical water quality parameters of lake Brăneşti was investigated by Benciu et al34. The water quality parameters for the last 50 years were correlated with the anthropogenic pressure in the region. Analysis of water and soil samples in the vicinity of this lake, revealed that parameters were within legal norms for both water and soil34.
Another study presented by Dumitran et al35 proposed an eutrophication model for describing the ecological behavior of a eutrophic lake. The physical model was mathematically transposed to a set of equations for analysing the selected parameters linked to eutrophication state. The resulted model showed a good correlation with the measured data35.
It is to be noted that most of the available literature is based on the assessment of the water quality, by measurements of physico-chemical parameters, and calculation of pollution indexes. To our knowledge no extensive studies involved the study of the lentic ecosystems with respect to vulnerability and risk of pollution by using multicriterial analysis.
Generally, the precautionary approach is applied by identifying and analyzing the categories of drivers that influence the degradation of lentic ecosystems, especially in the protected areas36,37,38. Three main categories of activities that generate environmental issues have been identified within protected areas included within the Natura 2000 Sites as follows: (a) agricultural activities and forestry practice; (b) sectoral activities (industrial, commercial and tourism sectors); (c) conservation policies (management of protected areas, protection of different species, etc.)39. A cross-sectoral approach is needed in order to resolve medium-term environmental conflicts, thus being be able to extend the assessment towards various categories of protected areas and generating efficient policies for the management of resources40,41.
Identifying and analyzing the categories of conflicts that may be associated with lentic ecosystems provide the possibility of an efficient ecosystem management22,23.
The lakes from this case study comprise both natural lakes (glacial, karst, karst-saline, ponds, lagoons), as well as ponds accumulation lakes, with an important role in ensuring the resources of water for the population and economic activities, as well as the development and maintenance of habitats and species of community interest (birds, amphibians, reptiles, fish, etc.).
Most of the lakes resulting from the analysis as being degraded and semi-degraded are located in the plains, at low altitudes, within areas covered with agricultural lands, industrial facilities and dense transportation routes.
The lentic ecosystems characterized as being in a natural state resulting from the proposed methodology are mainly distributed in the high mountain areas and in the Danube Delta area. Thus, altitude, fragmentation of the relief and accessibility are favorable factors regarding the natural state of water bodies, including lentic ecosystems. The high number of lakes characterized as degraded or semi-degraded compared to that of natural lakes is justified by the existence of a small number of lakes located at high altitudes, over 800 m.
It is to be taken into account that the degradation state classification is directly influenced by the data used in defining WRASTIC indicators, being generally derived data, which may explain the limitation of the method from this point of view.
The lack of correlation or poor correlation resulting from the statistical analysis between the degradation state and the indicators defining the HI index (component part of the WRASTIC-HI index), respectively the permeability, the exposure and the slope, highlight the insignificant role of these parameters in determining the state of lake degradation. However, the processes of erosion and sediment transport on the surface of the basins and their accumulation in lakes can influence the water quality of the lakes, their clogging, their functionality and the services offered, which are important factors in improving the management of the analyzed lakes42.
The status of protected areas offers a high degree of protection by diminishing the anthropic activities and the negative effects on the lakes, being recommended that all economic activities be located outside these protected areas43 the basins being vulnerable to human activities. This aspect is also highlighted by the correlation between the state of degradation obtained and the percentage of the hydrographic basin existing in different categories of protected areas, between which there is a good correlation, as well as by the high number of natural lakes that are included in protected areas (~ 98%), located especially in the Danube Delta Biosphere Reserve.
The local public administrations are directly interested in the management and protection of lentic ecosystems, many lakes being included in different categories of protected areas. Increasing the number of lakes in the natural state involves identifying degraded or semi-degraded lentic ecosystems outside protected areas and carrying out ecological reconstruction activities or diminishing agricultural and industrial activities in their vicinity.
The state of the lakes may also depend on the dynamics of the hydrophilic and hydrophilic vegetation, respectively on the hedge with vegetation cover of the water lily. In our study, the statistical analysis showed that there is no correlation between the state of degradation and the Coverage with vegetation of the water lily. Thus, in this case, the state of degradation of the lentic ecosystems is not influenced by this parameter, although, in some cases, remote sensing analysis revealed the presence of excess algae and aquatic plants in both natural and semi-degraded lakes44.
The lakes located in the low plain areas are also affected by the eutrophication process, amplified by the reduced depth (which ensures the rapid development of algae during the summer), the contribution of nutrients due to the agricultural activities in the vicinity and the development of recreational activities. More

1.
Clavero, M., Brotons, L., Pons, P. & Sol, D. Prominent role of invasive species in avian biodiversity loss. Biol. Conserv. 142, 2043–2049 (2009).
Article  Google Scholar 
2.
Clavero, M. & García-Berthou, E. Homogenization dynamics and introduction routes of invasive freshwater fish in the Iberian Peninsula. Ecol. Appl. 16, 2313–2324 (2006).
PubMed  Article  PubMed Central  Google Scholar 

3.
Tershy, B. R., Shen, K.-W., Newton, K. M., Holmes, N. D. & Croll, D. A. The Importance of islands for the protection of biological and linguistic diversity. Bioscience 65, 592–597 (2015).
Article  Google Scholar 

4.
Jones, H. P. Seabird islands take mere decades to recover following rat eradication. Ecol. Appl. 20, 2075–2080 (2010).
PubMed  Article  PubMed Central  Google Scholar 

5.
Wolf, C. A. et al. Invasive rat eradication strongly impacts plant recruitment on a tropical atoll. PLoS ONE 13, e0200743 (2018).
PubMed  PubMed Central  Article  Google Scholar 

6.
O’Dowd, D. J., Green, P. T. & Lake, P. S. Invasional ‘meltdown’ on an oceanic island. Ecol. Lett. 6, 812–817 (2003).
Article  Google Scholar 

7.
Rogers, H. S. et al. Effects of an invasive predator cascade to plants via mutualism disruption. Nat. Commun. 8, 14557 (2017).
ADS  PubMed  PubMed Central  Article  Google Scholar 

8.
Jones, H. P. et al. Invasive mammal eradication on islands results in substantial conservation gains. Proc. Natl. Acad. Sci. 113, 4033–4038 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

9.
Towns, D. Eradications as reverse invasions: lessons from Pacific rat (Rattus exulans) removals on New Zealand islands. Biol. Invasions 11, 1719–1733 (2008).
Article  Google Scholar 

10.
Donlan, C. J., Croll, D. A. & Tershy, B. R. Islands, exotic herbivores, and invasive plants: their roles in coastal California Restoration. Restor. Ecol. 11, 524–530 (2003).
Article  Google Scholar 

11.
Tabak, M. A., Poncet, S., Passfield, K., Goheen, J. R. & del Rio, C. M. The ghost of invasives past: rat eradication and the community composition and energy flow of island bird communities. Ecosphere 7, e01442 (2016).
Article  Google Scholar 

12.
Kurle, C. M., Croll, D. A. & Tershy, B. R. Introduced rats indirectly change marine rocky intertidal communities from algae- to invertebrate-dominated. Proc. Natl. Acad. Sci. 105, 3800–3804 (2008).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

13.
Thoresen, J. J. et al. Invasive rodents have multiple indirect effects on seabird island invertebrate food web structure. Ecol. Appl. 27, 1190–1198 (2017).
PubMed  Article  PubMed Central  Google Scholar 

14.
Russell, J. Indirect effects of introduced predators on seabird islands. In Seabird Islands: Ecology, Invasion, and Restoration (eds Mulder, C. et al.) (Oxford University Press, Oxford, 2011).
Google Scholar 

15.
Le Corre, M. et al. Seabird recovery and vegetation dynamics after Norway rat eradication at Tromelin Island, western Indian Ocean. Biol. Conserv. 185, 85–94 (2015).
Article  Google Scholar 

16.
Doherty, T. S., Glen, A. S., Nimmo, D. G., Ritchie, E. G. & Dickman, C. R. Invasive predators and global biodiversity loss. Proc. Natl. Acad. Sci. 113, 11261–11265 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

17.
Bellard, C., Genovesi, P. & Jeschke, J. M. Global patterns in threats to vertebrates by biological invasions. Proc. R. Soc. B Biol. Sci. 283, 20152454 (2016).
Article  Google Scholar 

18.
Towns, D. R., Atkinson, I. A. E. & Daugherty, C. H. Have the harmful effects of introduced rats on islands been exaggerated?. Biol. Invasions 8, 863–891 (2006).
Article  Google Scholar 

19.
Jones, H. P. et al. Severity of the effects of invasive rats on seabirds: a global review. Conserv. Biol. 22, 16–26 (2008).
PubMed  Article  PubMed Central  Google Scholar 

20.
Drake, D. R. et al. Direct Impacts of Seabird Predators on Island Biota other than Seabirds. In Seabird Islands: Ecology, Invasion, and Restoration Mulder (eds Anderson, C. P. H. et al.) 91–132 (Oxford University Press, Oxford, 2011). https://doi.org/10.1093/acprof:osobl/9780199735693.003.0004.
Google Scholar 

21.
Towns, D. R. et al. Impacts of Introduced Predators on Seabirds. In Seabird Islands: Ecology, Invasion, and Restoration Mulder (eds Anderson, C. P. H. et al.) 56–90 (Oxford University Press, Oxford, 2011). https://doi.org/10.1093/acprof:osobl/9780199735693.003.0003.
Google Scholar 

22.
Mulder, C. P. H., Anderson, W. B., Towns, D. R. & Bellingham, P. J. Seabird Islands: Ecology, Invasion, and Restoration (Oxford University Press, Oxford, 2011).
Google Scholar 

23.
Croll, D. A., Maron, J. L., Estes, J. A., Danner, E. M. & Byrd, G. V. Introduced predators transform subarctic islands from grassland to Tundra. Science 307, 1959–1961 (2005).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

24.
Aslan, C. E., Zavaleta, E. S., Tershy, B. & Croll, D. Mutualism disruption threatens global plant biodiversity: a systematic review. PLoS ONE 8, e66993 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

25.
DIISE. The Database of Island Invasive Species Eradications, developed by Island Conservation, Coastal Conservation Action Laboratory UCSC, IUCN SSC Invasive Species Specialist Group, University of Auckland and Landcare Research New Zealand. http://diise.islandconservation.org/ (2018).

26.
Howald, G. et al. Invasive rodent eradication on islands. Conserv. Biol. 21, 1258–1268 (2007).
PubMed  Article  PubMed Central  Google Scholar 

27.
Keitt, B. et al. The Global Islands Invasive Vertebrate Eradication Database: A tool to improve and facilitate restoration of island ecosystems. In Island Invasives: Eradication and Management (eds Veitch, C. et al.) 4 (IUCN, Gland, 2011).
Google Scholar 

28.
Nigro, K. M. et al. Stable isotope analysis as an early monitoring tool for community-scale effects of rat eradication. Restor. Ecol. 25, 1015–1025 (2017).
Article  Google Scholar 

29.
Courchamp, F. et al. Eradication of alien invasive species: surprise effects and conservation successes. In Island Invasives: Eradication and Management (eds Veitch, C. et al.) 285–289 (IUCN, Gland, 2011).
Google Scholar 

30.
Jones, H. & Schmitz, O. Rapid recovery of damaged ecosystems. PLoS ONE 4, e5653 (2009).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

31.
Jones, H. P. et al. Recovery and Restoration on Seabird Islands. In Seabird Islands: Ecology, Invasion, and Restoration (eds Mulder, C. et al.) (Oxford University Press, Oxford, 2011).
Google Scholar 

32.
Buckelew, S., Byrd, V., Howald, G., MacLean, S. & Sheppard, J. Preliminary ecosystem response following invasive Norway rat eradication on Rat Island, Aleutian Islands, Alaska. in Island Invasives: eradicaation and management 5 (IUCN, 2011).

33.
Croll, D. A. et al. Passive recovery of an island bird community after rodent eradication. Biol. Invasions 18, 703–715 (2016).
Article  Google Scholar 

34.
Hanson, K., Goos, M. & Deines, F. G. Introduced arctic fox eradication at Rat Island (Aleutian Islands, Alaska, 1984).
Google Scholar 

35.
ESRI. ESRI ArcMap 10.7.0.10450. (ESRI, 2020).

36.
Lorvelec, O. & Pascal, M. French attempts to eradicate non-indigenous mammals and their consequences for native biota. Biol. Invasions 7, 135–140 (2005).
Article  Google Scholar 

37.
Bellingham, P. J. et al. New Zealand island restoration: seabirds, predators, and the importance of history. N. Z. J. Ecol. 34, 115 (2010).
Google Scholar 

38.
St. Clair, J., Poncet, S., Sheehan, D., Szekely, T. & Hilton, G. Responses of an island endemic invertebrate to rodent invasion and eradication. Anim. Conserv. 14, 66–73 (2011).
Article  Google Scholar 

39.
Monks, J. M., Monks, A. & Towns, D. R. Correlated recovery of five lizard populations following eradication of invasive mammals. Biol. Invasions 16, 167–175 (2014).
Article  Google Scholar 

40.
Whitworth, D. L., Carter, H. R. & Gress, F. Recovery of a threatened seabird after eradication of an introduced predator: Eight years of progress for Scripps’s murrelet at Anacapa Island, California. Biol. Conserv. 162, 52–59 (2013).
Article  Google Scholar 

41.
Brooke, M. L. et al. Seabird population changes following mammal eradications on islands. Anim. Conserv. 21, 3–12 (2017).
Article  Google Scholar 

42.
Bailey, E. P. Introduction of foxes to Alaskan Islands: history, effects on Avifauna, and Eradication. (U.S. Dept. of the Interior, Fish and Wildlife Service ; National Technical Information Service, distributor, 1993).

43.
Byrd G. V., Trapp, J. L., & Zeillemaker, C. F. Removal of Introduced Foxes: A Case Study in Restoration of Native Birds. in vol. 59 317–321 (1994).

44.
Byrd, G. V., Bailey, E. P. & Stahl, W. Restoration of island populations of black oystercatchers and pigeon guillemots by removing introduced foxes. Colon. Waterbirds 20, 253–260 (1997).
Article  Google Scholar 

45.
Ehrenfeld, J. G. Ecosystem consequences of biological invasions. Annu. Rev. Ecol. Evol. Syst. 41, 59–80 (2010).
Article  Google Scholar 

46.
Wootton, J. T. Indirect effects, prey susceptibility, and habitat selection: impacts of birds on limpets and algae. Ecology 73, 981–991 (1992).
Article  Google Scholar 

47.
Ellis, J. C., Chen, W., O’Keefe, B., Shulman, M. J. & Witman, J. D. Predation by gulls on crabs in rocky intertidal and shallow subtidal zones of the Gulf of Maine. J. Exp. Mar. Biol. Ecol. 324, 31–43 (2005).
Article  Google Scholar 

48.
Menge, B. A. Top-down and bottom-up community regulation in marine rocky intertidal habitats. J. Exp. Mar. Biol. Ecol. 250, 257–289 (2000).
CAS  PubMed  Article  PubMed Central  Google Scholar 

49.
Guerry, A. D., Menge, B. A. & Dunmore, R. A. Effects of consumers and enrichment on abundance and diversity of benthic algae in a rocky intertidal community. J. Exp. Mar. Biol. Ecol. 369(2), 155–164 (2009).
Article  Google Scholar 

50.
Wootton, J. T. Effects of birds on sea urchins and algae: a lower-intertidal trophic cascade. Écoscience 2, 321–328 (1995).
Article  Google Scholar 

51.
Ellis, J. C., Shulman, M. J., Wood, M., Witman, J. D. & Lozyniak, S. Regulation of intertidal food webs by avian predators on new england rocky shores. Ecology 88, 853–863 (2007).
PubMed  Article  PubMed Central  Google Scholar 

52.
Freidenburg, T. L., Menge, B. A., Halpin, P. M., Webster, M. & Sutton-Grier, A. Cross-scale variation in top-down and bottom-up control of algal abundance. J. Exp. Mar. Biol. Ecol. 347(1–2), 8–29 (2007).
Article  Google Scholar 

53.
Webster, J. D. Feeding habits of the black oyster-catcher. Condor 43, 175–180 (1941).
Article  Google Scholar 

54.
Trapp, J. L. Variation in summer diet of Glaucous-winged Gulls in the Western Aleutian Islands: an ecological interpretation. Wilson Bull. 91, 412–419 (1979).
Google Scholar 

55.
Irons, D. B., Anthony, R. G. & Estes, J. A. Foraging strategies of Glaucous-winged gulls in a rocky intertidal community. Ecology 67, 1460–1474 (1986).
Article  Google Scholar 

56.
Davis, M. L., Elliott, J. E. & Williams, T. D. Spatial and temporal variation in the dietary ecology of the Glaucous-winged Gull Larus Glaucescens in the Pacific Northwest. Mar. Ornithol. 43, 189–198 (2015).
Google Scholar 

57.
Padilla, D. K. The importance of form: differences in competitive ability, resistance to consumers and environmental stress in an assemblage of coralline algae. J. Exp. Mar. Biol. Ecol. 79, 105–127 (1984).
Article  Google Scholar 

58.
Breitburg, D. Residual effects of grazing – inhibition of competitor recruitment by encrusting coralline algae. Ecology 65, 1136–1143 (1984).
Article  Google Scholar 

59.
Scheibling, R. E. & Hatcher, B. G. Strongylocentrotus droebachiensis. In Developments in Aquaculture and Fisheries Science Vol. 38 (ed. Lawrence, J. M.) 381–412 (Elsevier, Amsterdam, 2013).
Google Scholar 

60.
Estes, J., Tinker, M., Williams, T. & Doak, D. F. Killer whale predation on sea otters linking oceanic and nearshore ecosystems | science. Science 282, 473–476 (1998).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

61.
Estes, J. A., Tinker, M. T. & Bodkin, J. L. Using ecological function to develop recovery criteria for depleted species: sea otters and kelp forests in the aleutian archipelago. Conserv. Biol. 24, 852–860 (2010).
PubMed  Article  PubMed Central  Google Scholar 

62.
Stewart, N. L., Konar, B. & Tinker, M. T. Testing the nutritional-limitation, predator-avoidance, and storm-avoidance hypotheses for restricted sea otter habitat use in the Aleutian Islands, Alaska. Oecologia 177, 645–655 (2015).
ADS  PubMed  Article  PubMed Central  Google Scholar 

63.
Gentemann, C. M., Fewings, M. R. & García-Reyes, M. Satellite sea surface temperatures along the West Coast of the United States during the 2014–2016 northeast Pacific marine heat wave. Geophys Res Lett 44, 312–319 (2017).
ADS  Article  Google Scholar 

64.
Coletti, H. et al. Gulf Watch Alaska: Nearshore Ecosystems in the Gulf of Alaska. Exxon Valdez Oil Spill Restoration Project Annual Report (Restoration Project 18120114-H), Exxon Valdez Oil Spill Trustee Council, Anchorage, Alaska (2019).

65.
Coletti, H. et al. Gulf Watch Alaska: Nearshore Ecosystems in the Gulf of Alaska. Exxon Valdez Oil Spill Restoration Project Annual Report (Restoration Project 18120114-H), Exxon Valdez Oil Spill Trustee Council, Anchorage, Alaska (2020).

66.
Hewson, I. et al. Investigating the Complex Association Between Viral Ecology, Environment, and Northeast Pacific Sea Star Wasting. Front. Mar. Sci. 5, 2018 (2018).
Article  Google Scholar 

67.
Elton, C. S. The Ecology of Invasions by Animals and Plants (Springer, Berlin, 1958).
Google Scholar 

68.
Richardson, D. M. & Pysek, P. Fifty Years of Invasion Ecology: The Legacy of Charles Elton (Blackwell Publishing Ltd., Hoboken, 2008).
Google Scholar 

69.
Courchamp, F. et al. Invasion biology: specific problems and possible solutions. Trends Ecol. Evol. 32, 13–22 (2017).
PubMed  Article  PubMed Central  Google Scholar 

70.
Cassini, M. H. A review of the critics of invasion biology. Biol. Rev. (2020).

71.
Kurle, C. M. Description of the rocky intertidal communities and Norway rat behavior on Rat Island, Alaska in 2003. 21 (2005).

72.
ESRI. ArcGIS 10.7. (ESRI, 2020).

73.
Simberloff D. Reconstructing the ambiguous: can island ecosystems be restored? in Conservation Sciences Publication (New Zealand). no. 2. (1990). More

Comparison of sampling methods for microbes on the surface of tobacco leaves
According to previous research, two sampling methods for microbes on the surface of tobaccos were selected to separately perform extraction and amplification of genome DNAs after sampling the microbes. As shown in Table 1, as for the first sampling method, the DNAs extracted from two tobacco leaf samples (fresh tobacco leaves and tobacco leaves in the later yellowing period) were both unqualified after subjected to amplification. Therefore, the first method was not suitable for extracting the microbes on the surface of tobacco leaves. The two tobacco samples extracted by using the second method both allowed favorably amplification and their amplification results were both proper. Thus, the second method was applied to sample the microbes on the surface of tobacco leaves subsequently.
Table 1 Comparison of effects of the two methods for sampling microbes on the surface of tobaccos.
Full size table

OTU clustering analysis
To explore the species compositions of various samples, OTUs clustering was carried out on effective Tags of all samples based on 97% of identity; afterwards, species annotation was performed on the OTUs sequences. According to OTUs results obtained through clustering and research requirements, the common and specific OTUs among different samples (groups) were analyzed.
OTU clustering analysis of bacteria in tobacco leaves
The result is shown in Fig. 3. Each petal in the petal diagram represents a group (sample) and different colors mean diverse samples (groups); the number at the core stands for the total number of OTUs in all samples; the number in each petal denotes the number of OTUs specific in the sample (group). It can be seen from the figure that the numbers of the core microbial communities subjected to conventional flue-curing procedure and dry-ball temperature set and wet-ball temperature degradation flue-curing procedure were basically consistent, showing no great change.
Figure 3

Petal diagrams of OTUs in samples flue-cured through conventional procedure and temperature- and humidity-controlled procedure under different sampling stages (SB: the surface bacteria of fresh tobacco leaves; EB: endophytic bacteria of fresh tobacco leaves; CSB: the surface bacteria of tobacco leaves flue-cured using conventional procedure; CEB: endophytic bacteria of tobacco leaves flue-cured using conventional procedure; SSB: the surface bacteria of tobacco leaves flue-cured using temperature- and humidity-controlled procedure; SEB: endophytic bacteria of tobacco leaves flue-cured using temperature- and humidity-controlled procedure; 2–6 represent different sampling stages).

Full size image

OTU clustering analysis of fungi in tobacco leaves
The result is displayed in Fig. 4. As shown in the figure, the core microbial communities flue-cured by conventional procedure and temperature- and humidity-controlled procedure showed basically coincident numbers. The latter was only 5–10 core microbial communities more than the former. Similar to the core bacterial communities, the number of core fungal communities presented no great difference in the flue-curing process.
Figure 4

Petal diagrams of OTUs of fungi in samples flue-cured by using conventional procedure and temperature- and humidity-controlled procedure in different sampling stages (SB: the surface fungi of fresh tobacco leaves; EB: endophytic fungi of fresh tobacco leaves; CSB: the surface fungi of tobacco leaves flue-cured using conventional procedure; CEB: endophytic fungi of tobacco leaves flue-cured using conventional procedure; SSB: the surface fungi of tobacco leaves flue-cured using temperature- and humidity-controlled procedure; SEB: endophytic fungi of tobacco leaves flue-cured using temperature and humidity-controlled procedure; 2–6 denote different sampling stages.

Full size image

Analysis of relative abundances of species
According to the results of species annotations, the species of each sample or group with the maximum abundance ranking the top 10–30 at various classification levels were selected to generate the cumulative histogram of relative abundances of species. The species with a high relative abundance in various samples at different classification levels and their proportions can be intuitively found.
Analysis of relative abundances of bacteria in tobaccos
Based on the results of species annotations, the species of each sample or group with the maximum abundance ranking the top 10–30 at various classification levels were selected to generate the cumulative histogram of relative abundances of species. The species with a high relative abundance in various samples at different classification levels and their proportions can be visualized.
As shown in Fig. 5, at the level of phylum, the bacteria in tobaccos mainly contained Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Planctomycetes, Acidobacteria, Chloroflexi, unidentified bacteria, Thaumarchaeota and Gemmatimonadetes. It can be seen that the surface and endophytic bacterial communities of fresh tobacco leaves slightly differed at the level of phylum. Proteobacteria showed the largest content, followed by Actinobacteria and Bacteroidetes, and the contents of the other bacterial phyla were relatively low. By using conventional flue-curing procedure, the bacterial diversity on the surface of tobacco leaves progressively declined as the flue-curing continued, and the relative content of Proteobacteria rose at first and then reduced; the reduction amplitude of Actinobacteria was relatively stable in the flue-curing process while that of Bacteroidetes was relatively large. For the dry-ball temperature set and wet-ball temperature degradation flue-curing procedure, as the flue-curing proceeded, the relative content of Proteobacteria gradually increased and it did not greatly reduce until reaching the last flue-curing stage. However, its relative content was not significantly different from that in fresh tobacco leaves; similar to Proteobacteria, the relative contents of both Actinobacteria and Bacteroidetes also grew at first and then decreased; in terms of endophytic bacteria of tobaccos, as the flue-curing process continued, the relative contents of Proteobacteria and the other main bacterial communities rapidly dropped while those of the other communities sharply increased.
Figure 5

Histogram of relative abundances of species at the level of phylum.

Full size image

As shown in Fig. 6, at the level of genus, the main dominant bacterial communities in endophytic bacteria of fresh tobacco leaves included Pseudomonas, Sphingomonas, Ralstonia, Methylobacterium, Massilia, Sphingobacterium, Rhizobium, Halomonas, Serratia and Rickettsia.
Figure 6

Column chart of species relative abundance at genus level.

Full size image

When employing conventional flue-curing procedure, the bacterial communities on the surface of tobaccos were relatively marginally changed at the level of genus while the endophytic bacteria varied remarkably. As the flue-curing process proceeded, the relative content of 30 main endophytic bacterial communities found before the flue-curing had dropped to 2% even in the early flue-curing stage (35 ℃). In comparison, the relative content of the bacterial communities in the first two flue-curing stages under dry-ball temperature set and wet-ball temperature degradation flue-curing procedure was higher.
Under conventional procedure, the relative abundance of Pseudomonas on the surface of tobacco leaves increased at first and then decreased, so did that of Sphingomonas. Although no signs of Ralstonia solanacearum were visualized on the surface of the sampled tobacco leaf samples, Ralstonia was found in the analysis of bacterial communities. With the ongoing flue-curing process, the relative content of Ralstonia rapidly reduced; the relative content of Methylobacterium on the surface of fresh tobacco leaves declined to some extent in the flue-curing process, and accounted for a large proportion in bacterial communities on the surface of flue-cured tobacco leaves. The relative contents of the other main bacterial communities were all progressively lowered basically.
When implementing dry-ball temperature set and wet-ball temperature degradation flue-curing procedure, the relative contents of the main bacterial communities in the early flue-curing stage were higher than those in fresh tobacco leaves. The relative contents of them marginally differed from those in fresh tobacco leaves even though flue-curing process was ended; the relative content of Pseudomonas gradually increased in the flue-curing process. By contrast, the relative contents of Sphingomonas and Methylobacterium both grew at first and then declined. The relative contents of the other main bacterial communities relatively slowly varied in the flue-curing process and they did not greatly decrease until the flue-curing process was ended. Moreover, the relative contents of some bacterial genera, including Sphingobacterium and Rickettsia, had remarkably dropped in the early flue-curing stage.
Analysis of relative abundances of fungi in tobaccos
As shown in Fig. 7, at the level of phylum, fungi in tobaccos mainly covered Ascomycota, Basidiomycota, Mortierellomycota, Rozellomycota, Glomeromycota, Chytridiomycota, Kickxellomycota, Mucoromycota and Olpidiomycota. It can be seen from the figure that fungi in tobaccos mainly included Ascomycota and Basidiomycota; the other fungi (phylum) took up a relatively low proportion.
Figure 7

Histogram of relative abundances of species at the level of phylum.

Full size image

When being flue-cured by using conventional procedure, the relative abundance of Ascomycota on the surface of tobacco leaves gradually increased while those of Basidiomycotaand the other fungal phyla gradually decreased with the ongoing flue-curing process; under temperature- and humidity-controlled flue-curing, the evolution law of fungal communities was similar to that using conventional procedure at the level of phylum. To be specific, a trend was shown that the relative abundance of Ascomycota gradually rose while those of Basidiomycota and the other fungal phyla were lowered, which was basically similar to that under conventional flue-curing procedure.
Their proportions were higher than those on the surface of tobacco leaves.The change amplitude of the endophytic fungi of tobacco leaves was less significant than that of fungi on the surface of tobacco leaves. Either under conventional flue-curing or temperature- and humidity-controlled flue-curing, the relative abundance of Ascomycota basically increased at first and then declined while that of Basidiomycota reduced at first, then grew and finally dropped.
As shown in Fig. 8, the change trends of community compositions under conventional flue-curing and temperature- and humidity-controlled flue-curing at the level of genus were similar to those at the level of phylum. There was a great difference only in the relative contents of fungal communities. In terms of fungi on the surface of tobacco leaves, the relative content of Alternaria under conventional flue-curing greatly increased at 38.5 ℃ and 54 ℃, with increases at the same time points under temperature- and humidity-controlled flue-curing; however, the growth amplitude of the relative content was less significant than that under conventional flue-curing. Cladosporium was another main fungal community and its relative content slowly decreased in the later stage of temperature- and humidity-controlled flue-curing. The relative content of Symmetrospora progressively decreased when using conventional flue-curing procedure while its reduction rate slowed down under temperature- and humidity-controlled flue-curing. The relative content of Ophiocordyceps on the surface of tobacco leaves was relatively low and it both gradually reduced when using the two flue-curing technologies. Moreover, the relative contents of the other fungal genera also progressively declined as the flue-curing proceeded.
Figure 8

Histogram of relative abundances of species at the level of genus.

Full size image

As for changes of endophytic fungi of tobaccos when using the two flue-curing technologies, the relative content of Alternaria under conventional flue-curing was higher than that under temperature- and humidity-controlled flue-curing. The result can be found even though the flue-curing process was ended. The relative content of Cladosporium marginally varied under conventional flue-curing and greatly increased at 35 ℃. After completing the flue-curing process, the relative content did not significantly differ from the value in fresh tobacco leaves. However, for dry-ball temperature set and wet-ball temperature degradation flue-curing procedure, the relative content of Cladosporium progressively reduced on the whole and the value after ending the flue-curing process was only about half of that in fresh tobacco leaves. The relative content of Symmetrospora showed a same change trend with Cladosporium under conventional flue-curing and temperature- and humidity-controlled flue-curing. Additionally, the reduction rate of the relative content of Symmetrospora was higher than that of Cladosporium under temperature- and humidity-controlled flue-curing. Relative to fungal communities on the surface of tobaccos, although the relative contents of the other endophytic fungal genera gradually dropped with the flue-curing.
Clustered heat maps of species abundances
According to species annotations and abundances of all samples at the level of genus, genera whose abundances ranked the top 35 were selected. Subsequently, based on the abundances of these genera in each sample, a heat map is drawn by conducting clustering from the two aspects: i.e. species and samples. By doing so, it is convenient to ascertain a species with a high abundance or low content and the sample from which it is found.
Clustered heat map of species abundances of bacteria in tobaccos
The result is displayed in Fig. 9. It can be seen from the clustered heat map that bacterial communities mainly reside on the surface and in the interior of the fresh tobacco leaves at first. As the flue-curing proceeded, the contents of the main bacterial communities were changed to some extent: the main bacterial communities reduced in the content and the tobacco leaves became light in color.
Figure 9

Clustered heat map of species abundances at the level of genus.

Full size image

Clustered heat map of species abundance of fungi in tobaccos
According to species annotations and abundances of all samples at the level of genus, the genera whose abundances ranked the top 35 were selected. Based on the abundances of these genera in each sample, a heat map is drawn by conducting clustering from the two aspects, i.e. species and samples. It can be found from Fig. 10 that the distribution of fungi on the surface of tobaccos greatly differed from that of endophytic fungi. Moreover, the distribution of materials also presented a great difference when using the two flue-curing technologies.
Figure 10

Clustered heat map of species abundances at the level of genus.

Full size image

Correlation with environmental factors
Correlation of bacteria with environmental factors
Temperature and humidity were mainly controlled in the flue-curing process of tobacco leaves; and the main environmental factors involved dry- and wet-bulb temperatures. It can be seen from Fig. 11 that Pantoea, Nesterenkonia, Staphylococcus, Variovorax, Chryseomonas, Rhodococcus, Paracoccus, Massilia, Serratia, Ralstonia and Pseudomonas were more likely to be affected by temperature and humidity. Pantoea and Variovorax exhibited a positive correlation with temperature and humidity; Nesterenkonia, Staphylococcus, Chryseomonas, Rhodococcus, Paracoccus, Serratia and Ralstonia presented a negative correlation with temperature and humidity. Actinomycetospora were negatively correlated with the dry-bulb temperature while positively correlated with the wet-bulb temperature; Stenotrophomonas, Cutibacterium and Sediminibacterium were all negatively correlated with both dry- and wet-bulb temperatures while they presented a higher negative correlation with the dry-bulb temperature.
Figure 11

Heat map of correlation with environmental factors at the level of genus.

Full size image

Correlation of fungi with environmental factors
Similar to the analysis method of environmental factors of bacteria, the correlation between the fungi in tobaccos and environmental factors is displayed in Fig. 12. Temperature and humidity were mainly controlled in the flue-curing process of tobacco leaves; the main environmental factors were dry- and wet-bulb temperatures. As shown in the figure, different from the correlation of bacterial communities in tobaccos with environmental factors, the majority of fungal genera in tobaccos presented a negative correlation with temperature and humidity, for example, Rachicladosporium, Vishniacozyma, Symmetrospora, Sarocladium, Ascochyta, Wallemia, Colletotrichum, Fusarium, Claviceps, Cladosporium, etc. A small number of fungal genera (such as Ustilaginoidea, Septoriella and Alternaria) were positively correlated with temperature and humidity.
Figure 12

Heat map of correlation with environmental factors at the level of genus.

Full size image

Function prediction of bacterial communities in tobaccos
According to the annotation result in the database, the functions with the maximum abundance ranking the top 10 in each sample or group at various layers of annotations were selected to generate the cumulative histogram of relative abundances of functions. Thus, it is convenient to check the functions with a high relative abundance in various samples at different layers of annotations and their proportions.
As shown in Fig. 13, bacterial communities with a half of relative abundances participated in the metabolism and a quarter of bacterial communities took part in the genetic information processing; the rest was engaged in the cellular processes and organismal systems and some bacterial communities were implicated to human diseases.
Figure 13

Relative abundances of function annotations of bacterial communities in tobaccos.

Full size image

Function prediction of fungal communities in tobaccos
Based on amplificon analysis of 16S or ITS, the species classification and abundances of fungi present in the environment can be attained. In many cases, people will also concern what role these species found in the environment play in the ecological environment. By applying FunGuild tool, it is feasible to attain the ecological functions of corresponding fungi based on the species classification of fungi. It can be seen from the Fig. 14 that the fungal communities in tobaccos delivered relatively abundant functions, in which the three fungal communities with the highest relative abundances separately showed the following functions: plant saprophytes, plant pathogens and undefined functional fungal communities; the rest of fungal communities participated in plant parasitism,soil-borne plant pathogen, lichenization, dung saprotroph, etc.
Figure 14

Relative abundances of function annotations of fungal communities in tobaccos.

Full size image More

All procedures were approved by the Animal and Environment Ethics Committees of the University of São Paulo, College of Agriculture “Luiz de Queiroz” (USP/ESALQ). All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
Experimental site
Two experiments were carried out at Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, Brazil (22° 42′ S, 47° 38′ W and 546 a.s.l.), during the summer 2017 (January to March). Napier elephant grass (Pennisetum purpureum Schum. cv. Napier) was used as model plant because of its large size, ease of vegetative propagation and the nature of the study. The soil was a high fertility Eutric Kandiudalf with the following chemical characteristics for the 0–20 cm layer: Experiment 1—pH CaCl2 = 5.9; OM = 46.0 g dm−3; P (ion-exchange resin extraction method) = 257.0 mg dm−3; Ca = 148.1 mmolc dm−3, Mg = 80.0 mmolc dm−3; K = 9.1 mmolc dm−3; H + Al = 15.0 mmolc dm−3; sum of bases = 237.1 mmolc dm−3; cation exchange capacity = 252.1 mmolc dm−3; base saturation = 94%; Experiment 2—pH CaCl2 = 5.8; OM = 39.3 g dm−3; P (ion-exchange resin extraction method) = 54.0 mg dm−3; Ca = 62.0 mmolc dm−3, Mg = 22.3 mmolc dm−3; K = 8.6 mmolc dm−3; H + Al = 29.0 mmolc dm−3; sum of bases = 93.1 mmolc dm−3; cation exchange capacity = 122.0 mmolc dm−3; base saturation = 76%. These were considered adequate for the forage species used, with no need for additional fertilisation.
The climate, according to Köppen classification, is Cfa, humid subtropical climate with wet summer40 and an average annual rainfall of 1,328 mm. The average air temperature during the experimental period was 24.2 °C and total precipitation 753.85 mm, from which 424.4 mm corresponded to total precipitation for Experiment 1 (Dec 27, 2016 to Feb 21, 2017) and 502.14.5 mm for Experiment 2 (Dec 09, 2016 to Mar 14, 2017). The greatest precipitation was recorded in January 2017 (336.55 mm).
To avoid soil water deficits, a drip irrigation system was installed in the area used for Experiment 1 and a sprinkler irrigation system was available in the area for Experiment 2. Irrigation in both areas was carried out according to records of precipitation, average air temperature and evapotranspiration. On rainy days, precipitation was recorded and taken into account in calculations for irrigation as a means of ensuring that plants were not submitted to either deficit or excessive soil moisture.
Experiment 1 (leaf morphology and anatomy): establishment and experimental control
Preparation of the experimental area (290 m2) started with the desiccation of previous vegetation (Cynodon dactylon (L.) Pers.) using the broad-spectrum herbicides Glyphosate (N-phosphonomethyl-glycine) and 2.4-D (2.4-Dichlorophenoxyacetic acid) in Sept 09 and Nov 15, 2016, and Paraquat (1.1′-dimethyl-4.4′-bipyridinium dichloride) in Dec 11, 16 days before planting on Dec 27, 2016.
One day before planting of the experimental area (290 m2), planting pits were opened and the desiccated vegetation around them removed. Planting material (stem cuttings with viable lateral buds) was harvested at an 850 m2 pasture of well-established Napier elephant grass41. Stems were fractioned in one-node pieces (one single axillary bud) discarding the basal and the apical portions of the stems to ensure vigorous sprouting from the planting material. Ten buds were placed in each pit at 5 cm depth, covered with soil and gently compressed by hand. The distance between pits in lines was 1.5 m and between planting lines was 2 m, in order to obtain the desired spaced-plant layout. Two weeks after planting, plants were thinned leaving one plant per pit.
Treatments corresponded to phytomer order along the tiller axis and the experimental design was a randomised complete block, with four replications. Plants within blocks were randomised using the statistical package SAS (Statistical Analysis System, v. 9.0).
Weed control during the experiment was carried out manually. Pest (Mocis sp.) and disease (Bipolaris sp.) control was carried out using the water-soluble insecticide Resolva (Lambda-Cyhalothrin) in Jan 07 and 22, 2017 (5 g L−1) and the fungicide Nativo (Trifloxistrobina + Tebuconazol) in Feb 05, 2017 (0.6 L ha−1), respectively.
Sampling followed the ontogenetic programme of plants, beginning with tiller 1, which corresponded to the anatomical evaluation of the 8th leaf (phytomer 8); tiller 2, which corresponded to the anatomical evaluation of the 9th leaf (phytomer 9) and the morphological evaluation of the 8th leaf; tiller 3, which corresponded to the anatomical evaluation of the 10th leaf (phytomer 10) and the morphological evaluation of the 9th leaf in this sequence until full expansion of the 16th leaf (phytomer 16) for morphological evaluation (tiller 10), totalling 40 tillers (4 tillers for anatomical characterisation of the 8th expanded leaf + 32 tillers for anatomical (9th to 16th leaf) and morphological (8th to 15th expanded leaf) evaluations + 4 tillers for morphological characterisation of the 16th expanded leaf). At each harvest, leaves were carefully removed from the tillers, identified and preserved with ice until processing in the laboratory. Sampled tillers were removed from the experimental area. In order to evaluate the effect of leaf age on the deposition of support tissues, all leaves from 8 tillers (4 for anatomical evaluations (tiller 11) and 4 for morphological evaluations (tiller 12)) were collected at a single harvest when the 16th leaf completed expansion following the same procedure described for each leaf separately. Twenty additional plants were grown (five per block) to ensure that all leaves would be harvested as planned, but they were not necessary.
Leaf anatomy
In the laboratory, the leaf blade was cut at the ligule, its length was measured (distance between the tip of the leaf and the ligule) and fractionated in five segments of similar length designated as: (1) basal—closest portion to the insertion on the tiller; (2) mid-basal—middle portion closest to the basal; (3) middle—middle portion of the blade; (4) mid-apical—middle portion closest to the apical; (5) apical—portion closest to the tip of the leaf. Each of the five segments were fragmented in 1-cm cuts and stored according to methodology described by Johansen42. Sample dehydration was carried out using a progressive alcoholic series with tertiary butyl alcohol43, and fragments infiltrated with paraffin and subsequently with paraplast. In sequence, fragments were sectioned (12-µm width) with a Leica Biosystems manual rotary microtome, followed by a triarch quadruple staining of tissues before permanent blade mounting, following the methodology proposed by Hagquist44. Images were captured using the AxioVision Program (V2.05, Carl Zeiss Vision) attached to a Zeiss Axioskop 2 binocular optical microscope and a Zeiss AxioCam MRc (1.388 × 1.040 pixels) digital camera. Images were captured using 20× objective lens from the first large vascular bundle after the central rib as a means of standardising readings. Estimates of the percentage of each anatomical tissue on the samples were made using the AxioVision software (AxioVs40, release 4.8.2.0, Carl Zeiss Micro Imaging GmbH, Germany). Initially, the whole cross-section area projected on the video was measured (STotal). Next in the measurement sequence were the areas of adaxial (EPIada) and abaxial (EPIaba) epidermis, parenchymatic sheath of vascular bundles (PSV), vascular tissue (VT—including xylem, phloem, mestome sheath and pericyclic fibers27) and sclerenchyma (SCL). The mesophyll area was calculated as the difference between STotal and that of all the other tissues, therefore including airspace. Measurements were made in µm2 and the results expressed as percentage of total area.
Leaf morphology
For the morphology measurements the leaf was cut at the ligule, its length was measured (distance between the tip of the leaf and the ligule) and fractionated in ten segments of similar length. At the mid portion of each segment the fragment width (distance between the opposite borders) was measured in millimetres. In the sequence, the central rib from each segment was removed using a scalpel and its width and length were also measured. The fragment parts (central rib and blade tissue) were passed through a LAI-3100 leaf area integrating device (LI-COR) and put to dry in a forced draught oven at 55 °C until constant weight. The results were used to calculated whole segment mass (mg) and specific leaf area (SLA—cm2.mg−1).
Experiment 2 (nutritive value): establishment and experimental control
Preparation of the experimental area (3,000 m2) started with the desiccation of previous vegetation (Arachis pintoi cv. Belmonte) using the broad-spectrum herbicides Glyphosate (N-phosphonomethyl-glycine) and 2.4-D (2.4-Dichlorophenoxyacetic acid) in Sept 08, Oct 01 and Nov 15, 2016. On Nov 30 the whole area was mowed and a final application of Paraquat (1.1′-dimethyl-4.4′-bipyridinium dichloride) was carried out in Dec 06 (blocks 2 and 3) and Dec 11, 2016 (block 1). The next steps followed the same protocol used in Experiment 1. Six buds were placed in each pit at 5 cm depth, covered with soil and gently compressed by hand. The distance between pits in lines and between lines was 1.0 m (Fig. 8).
Figure 8

General view of the experimental site during the establishment phase showing the layout and distribution of elephant grass plants on the area: (a) Pit opening and (b) planting of the stem cuttings.

Full size image

A total of 1,320 plants were cultivated. These were divided in three homogeneous blocks with 440 plants each. The number of plants per block was dimensioned to provide the necessary amount of dried and ground samples for the nutritive value analysis. Twenty days after planting, plants were thinned leaving one plant per pit.
Treatments corresponded to phytomer order along the tiller axis and the experimental design was a randomised complete block, with three replications. Plants within blocks were randomised using the statistical package SAS (Statistical Analysis System, v. 9.0). Weed, pest and disease control was the same as for Experiment 1.
Sampling was carried out when the 16th leaf (phytomer 16) complete its expansion and exposed the ligule. Main tillers had all their leaves identified with permanent marker before harvest. The leaves were stored in ice and taken to the laboratory. Processing involved removal of the sheaths and blades stored in freezer for future segmentation. Leaves 5, 6 and 7 were discarded because they were in advanced stage of senescence and decay, leaving leaves 8 to 16 for the analysis.
Nutritive value
After all field work was finished, leaf blades had their length measured (distance between the tip of the leaf and the ligule) and were fractionated in five segments of similar length, as described for leaf anatomy measurements in Experiment 1 (i.e. chemical analyses included all tissues of the leaf blade). These were pooled into a composite sample per leaf hierarchical order, totalling 135 samples (9 leaves × 5 segments × 3 blocks). These were put to dry into forced draught oven at 55 °C until constant weight.
After drying, because the apical portion of the leaves was too delicate, the dried material was ground in a micro mill with a 1 mm sieve (Wiley Mill, Thomas Scientific, Philadelphia, PA, USA) as a means of reducing dry matter losses. Ground samples were subjected to the following chemical analysis: in vtiro dry matter digestibility (IVDMD), using the artificial rumen fermentation device DAISYII from ANKOM Technology Corporation45; total nitrogen (Ntotal), determined by the Dumas combustion method using the Leco FP 528 System (Leco Instruments Inc., St. Joseph, MI, USA); and ashes (ASH) determined according to Silva & Queiroz46. Crude protein (CP) was calculated as Ntotal × 6.25. For the in vitro trial, rumen liquid was collected from one rumen-cannulated Nellore steer fed only with Tifton-85 (Cynodon dactylon spp.) haylage.
Statistical analysis
Leaf blade morphology and anatomy data were initially analysed using descriptive statistical analysis (means and standard error of the mean). Leaf blade total mass and central rib total mass were obtained by adding values for all ten segments from each leaf and were subjected to a regression analysis as a means of identifying the correlation between these two variables. Regression was performed using the procedure PROC REG of SAS (Statistical Analysis System, v. 9.0).
Nutritive value data were subjected to ANOVA using the procedure PROC GLM of SAS (Statistical Analysis System, v. 9.0), and means compared by Tukey test (P  More

1.
Weihrauch, C. Dynamics need space—a geospatial approach to soil phosphorus’ reactions and migration. Geoderma 354, 113775 (2019).
CAS  Article  ADS  Google Scholar 
2.
Filippelli, G. M. The global phosphorus cycle: past, present, and future. Elements 4, 89–95 (2008).
CAS  Article  Google Scholar 

3.
Du, E. et al. Global patterns of terrestrial nitrogen and phosphorus limitation. Nat. Geosci. 13, 221–226 (2020).
CAS  Article  ADS  Google Scholar 

4.
Hou, E. et al. Global meta-analysis shows pervasive phosphorus limitation of aboveground plant production in natural terrestrial ecosystems. Nat. Commun. 11, 637 (2020).
CAS  PubMed  PubMed Central  Article  ADS  Google Scholar 

5.
Cordell, D. & White, S. Sustainable phosphorus measures: strategies and technologies for achieving phosphorus security. Agronomy 3, 86–116 (2013).
Article  Google Scholar 

6.
Abelson, P. H. A potential phosphate crisis. Science 283, 2015 (1999).
CAS  PubMed  Article  ADS  Google Scholar 

7.
Yuan, Z. Y. & Chen, H. Y. A global analysis of fine root production as affected by soil nitrogen and phosphorus. Proc. R. Soc. B-Biol. Sci. 279, 3796–3802 (2012).
CAS  Article  Google Scholar 

8.
Yang, Y. et al. Stoichiometric shifts in surface soils over broad geographical scales: evidence from China’s grasslands. Glob. Ecol. Biogeogr. 23, 947–955 (2014).
Article  Google Scholar 

9.
Vitousek, P. M., Porder, S., Houlton, B. Z. & Chadwick, O. A. Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen-phosphorus interactions. Ecol. Appl. 20, 5–15 (2010).
PubMed  Article  Google Scholar 

10.
Frossard, E., Condron, L. M., Oberson, A., Sinaj, S. & Fardeau, J. C. Processes governing phosphorus availability in temperate soils. J. Environ. Qual. 29, 15–23 (2000).
CAS  Article  Google Scholar 

11.
Condron, L. M., Turner, B. L., Cade-Menun, B. J., Sims, J. T. & Sharpley, A. N. Chemistry and dynamics of soil organic phosphorus. Agron. Monogr. 46, 87–121 (2005).
Google Scholar 

12.
Ruttenberg, K. C. The global phosphorus cycle: overview. Treatise Geochem. 10, 499–558 (2014).
Article  Google Scholar 

13.
Walker, T. W. & Syers, J. K. The fate of phosphorus during pedogenesis. Geoderma 15, 19 (1976).
Article  Google Scholar 

14.
Monger, C. et al. Legacy effects in linked ecological–soil–geomorphic systems of drylands. Front. Ecol. Environ. 13, 13–19 (2015).
Article  Google Scholar 

15.
Siebers, N., Sumann, M., Kaiser, K. & Amelung, W. Climatic effects on phosphorus fractions of native and cultivated north American grassland soils. Soil Sci. Soc. Am. J. 81, 299–309 (2017).
CAS  Article  ADS  Google Scholar 

16.
Stewart, J. W. B. & Tiessen, H. Dynamics of soil organic phosphorus. Biogeochemistry 4, 41–60 (1987).
CAS  Article  Google Scholar 

17.
Lane, P. N. J. et al. Water balance of tropical eucalypt plantations in south-eastern China. Agric. For. Meteorol. 124, 253–267 (2004).
Article  ADS  Google Scholar 

18.
Cheng, Y. et al. Effects of soil erosion and land use on spatial distribution of soil total phosphorus in a small watershed on the Loess Plateau, China. Soil Tillage Res. 184, 142–152 (2018).
Article  Google Scholar 

19.
Lin, J., Zheng, S. & Lu, X. Storage and spatial variation of phosphorus in paddy soils of China. Pedosphere 19, 798 (2009).
Article  Google Scholar 

20.
Zhang, C. et al. Pools and distributions of soil phosphorus in China. Glob. Biogeochem. Cycles 19, GB1020 (2005).
Article  ADS  CAS  Google Scholar 

21.
Zhang, S. L., Huffman, T., Zhang, X. Y., Liu, W. & Liu, Z. H. Spatial distribution of soil nutrient at depth in black soil of Northeast China: a case study of soil available phosphorus and total phosphorus. J. Soil Sedim. 14, 1775–1789 (2014).
CAS  Article  Google Scholar 

22.
Cheng, Y. et al. Spatial distribution of soil total phosphorus in Yingwugou watershed of the Dan River, China. CATENA 136, 175–181 (2016).
CAS  Article  Google Scholar 

23.
Dixon, J. L., Chadwick, O. A. & Vitousek, P. M. Climate-driven thresholds for chemical weathering in postglacial soils of New Zealand. J. Geophys. Res. Earth Surf. 121, 1619–1634 (2016).
CAS  Article  ADS  Google Scholar 

24.
Hou, E. et al. Effects of climate on soil phosphorus cycle and availability in natural terrestrial ecosystems. Glob. Change Biol. 24, 3344–3356 (2018).
Article  ADS  Google Scholar 

25.
Liu, J. X. et al. Patterns and controlling factors of plant nitrogen and phosphorus stoichiometry across China’s forests. Biogeochemistry 143, 191–205 (2019).
CAS  Article  Google Scholar 

26.
Qiao, J., Zhu, Y., Jia, X., Huang, L. & Shao, M. Vertical distribution of soil total nitrogen and soil total phosphorus in the critical zone on the Loess Plateau, China. CATENA 166, 310–316 (2018).
CAS  Article  Google Scholar 

27.
Yang, W. et al. The influence of land-use change on the forms of phosphorus in soil profiles from the Sanjiang Plain of China. Geoderma 189, 207–214 (2012).
Article  ADS  CAS  Google Scholar 

28.
Zuo, X. et al. Influence of dune stabilization on relationship between plant diversity and productivity in Horqin Sand Land, Northern China. Environ. Earth Sci. 67, 1547–1556 (2012).
Article  Google Scholar 

29.
Güsewell, S. N: P ratios in terrestrial plants: variation and functional significance. New Phytol. 164, 243–266 (2004).
Article  Google Scholar 

30.
García-Velázquez, L. et al. Climate and soil micro-organisms drive soil phosphorus fractions in coastal dune systems. Funct. Ecol. 34, 1690–1701 (2020).
Article  Google Scholar 

31.
Jobbágy, E. G. & Jackson, R. B. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10, 423–436 (2000).
Article  Google Scholar 

32.
Kooch, Y., Samadzadeh, B. & Hosseini, S. M. The effects of broad-leaved tree species on litter quality and soil properties in a plain forest stand. CATENA 150, 223–229 (2017).
CAS  Article  Google Scholar 

33.
Jarvi, M. P. & Burton, A. J. Root respiration and biomass responses to experimental soil warming vary with root diameter and soil depth. Plant Soil 451, 435–446 (2020).
CAS  Article  Google Scholar 

34.
Xu, Z. W. et al. Soil enzyme activity and stoichiometry in forest ecosystems along the North–South Transect in eastern China (NSTEC). Soil Biol. Biochem. 104, 152–163 (2017).
CAS  Article  Google Scholar 

35.
Teng, Z. D., Zhu, Y. Y., Li, M. & Whelan, M. J. Microbial community composition and activity controls phosphorus transformation in rhizosphere soils of the Yeyahu Wetland in Beijing, China. Sci. Total Environ. 628–629, 1266–1277 (2018).
PubMed  Article  ADS  CAS  PubMed Central  Google Scholar 

36.
Chadwick, O. A., Kelly, E. F., Hotchkiss, S. C. & Vitousek, P. M. Precontact vegetation and soil nutrient status in the shadow of Kohala Volcano, Hawaii. Geomorphology 89, 70–83 (2007).
Article  ADS  Google Scholar 

37.
Wang, Y. P., Law, R. M. & Pak, B. A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere. Biogeosciences 7, 2261–2282 (2010).
CAS  Article  ADS  Google Scholar 

38.
Li, X., Chang, S. X., Liu, J., Zheng, Z. & Wang, X. Topography-soil relationships in a hilly evergreen broadleaf forest in subtropical China. J. Soil Sedim. 17, 1101–1115 (2016).
Article  CAS  Google Scholar 

39.
Harrison, A. F. Soil Organic Phosphorus: A Review of World Literature 107–121 (Commonwealth Agricultural Bureaux International, Wallingford, 1987).
Google Scholar 

40.
Tian, H. Regional carbon dynamics in monsoon Asia and its implications for the global carbon cycle. Global Planet. Change 37, 201–217 (2003).
ADS  Google Scholar 

41.
He, X. J., Hou, E. Q., Liu, Y. & Wen, D. Z. Altitudinal patterns and controls of plant and soil nutrient concentrations and stoichiometry in subtropical China. Sci. Rep. 6, 24261 (2016).
CAS  PubMed  PubMed Central  Article  ADS  Google Scholar 

42.
Sundqvist, M. K., Sanders, N. J. & Wardle, D. A. Community and ecosystem responses to elevational gradients: processes, mechanisms, and insights for global change. Annu. Rev. Ecol. Evol. Syst. 44, 261–280 (2013).
Article  Google Scholar 

43.
Korner, C. The use of ‘altitude’ in ecological research. Trends Ecol. Evol. 22, 569–574 (2007).
PubMed  Article  PubMed Central  Google Scholar 

44.
McGill, W. B. & Cole, C. V. Comparative aspects of cycling of organic C, N, S and P through soil organic matter. Geoderma 26, 267–286 (1981).
CAS  Article  ADS  Google Scholar 

45.
Ippolito, J. A. et al. Phosphorus biogeochemistry across a precipitation gradient in grasslands of central North America. J. Arid Environ. 74, 954–961 (2010).
Article  ADS  Google Scholar 

46.
Li, K. et al. Long term increasing productivity of high-elevation grassland caused by elevated precipitation and temperature. Rangel. Ecol. Manag. 73, 156–161 (2020).
Article  Google Scholar 

47.
Alizamir, M. et al. Advanced machine learning model for better prediction accuracy of soil temperature at different depths. PLoS One 15, e0231055 (2020).
CAS  PubMed  PubMed Central  Article  Google Scholar 

48.
Vitousek, P. M. & Chadwick, O. A. Pedogenic thresholds and soil process domains in basalt-derived soils. Ecosystems 16, 1379–1395 (2013).
CAS  Article  Google Scholar 

49.
Tang, Z. Y. et al. Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China’s terrestrial ecosystems. Proc. Natl. Acad. Sci. U. S. A. 115, 4033–4038 (2018).
PubMed  PubMed Central  Article  Google Scholar 

50.
Fang, J. et al. Forest community survey and the structural characteristics of forests in China. Ecography 35, 1059–1071 (2012).
Article  Google Scholar 

51.
Tang, X. et al. Carbon pools in China’s terrestrial ecosystems: new estimates based on an intensive field survey. Proc. Natl. Acad. Sci. U. S. A. 115, 4021–4026 (2018).
CAS  PubMed  PubMed Central  Article  Google Scholar 

52.
Wu, T. et al. Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century. J. Geophys. Res. Atmos. 118, 4326–4347 (2013).
CAS  Article  ADS  Google Scholar 

53.
Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4, 170122 (2017).
PubMed  PubMed Central  Article  Google Scholar 

54.
Liaw, K. A. & Wiener, M. Classification and regression by randomForest. R News 23, 18–22 (2002).
Article  Google Scholar 

55.
Pedro, P.-N., Pierre, L., Stéphane, D. & Daniel, B. Variation partitioning of species data matrices: estimation and comparison of fractions. Ecology 87, 2614–2625 (2006).
Article  Google Scholar 

56.
Oksanen, J. et al. Vegan: Community Ecology Package, R Package Version 2.3-0. https://cran.r-project.org/web/packages/vegan/ (2015). More

1.
Maxwell, S. L., Fuller, R. A., Brooks, T. M. & Watson, J. E. Biodiversity: The ravages of guns, nets and bulldozers. Nature 536, 143–145 (2016).
CAS  PubMed  Article  ADS  Google Scholar 
2.
Scheffers, B. R., Oliveira, B. F., Lamb, I. & Edwards, D. P. Global wildlife trade across the tree of life. Science 366, 71–76 (2019).
CAS  PubMed  Article  ADS  Google Scholar 

3.
Nijman, V. An overview of international wildlife trade from Southeast Asia. Biodivers. Conserv. 19, 1101–1114 (2010).
Article  Google Scholar 

4.
TRAFFIC. Wildlife Trade Monitoring Network, Illegal Wildlife Trade. (2020).

5.
Rosen, G. E. & Smith, K. F. Summarizing the evidence on the international trade in illegal wildlife. EcoHealth 7, 24–32 (2010).
PubMed  PubMed Central  Article  Google Scholar 

6.
Wyler, L. & Sheikh, P. International illegal trade in wildlife: Threats and U.S. policy. (2008).

7.
Baker, S. E. et al. Rough trade: Animal welfare in the global wildlife trade. Bioscience 63, 928–938 (2013).
Article  Google Scholar 

8.
Tingley, M. W., Harris, J. B. C., Hua, F., Wilcove, D. S. & Yong, D. L. The pet trade’s role in defaunation. Science 356, 916 (2017).
CAS  PubMed  Article  ADS  Google Scholar 

9.
Bush, E. R., Baker, S. E. & Macdonald, D. W. Global trade in exotic pets 2006–2012. Conserv. Biol. 28, 663–676 (2014).
PubMed  Article  Google Scholar 

10.
Harris, J. B. C. et al. Measuring the impact of the pet trade on Indonesian birds. Conserv. Biol. 31, 394–405 (2017).
PubMed  Article  Google Scholar 

11.
Morton, O., Scheffers, B. R., Haugaasen, T. & Edwards, D. P. Impacts of wildlife trade on terrestrial biodiversity. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-021-01399-y (2021).
Article  PubMed  Google Scholar 

12.
Flecks, M. et al. Watching extinction happen: The dramatic population decline of the critically endangered Tanzanian Turquoise Dwarf Gecko, Lygodactylus williamsi. Salamandra 48, 12–20 (2012).
Google Scholar 

13.
Natusch, D. J. D. & Lyons, J. A. Exploited for pets: The harvest and trade of amphibians and reptiles from Indonesian New Guinea. Biodivers. Conserv. 21, 2899–2911 (2012).
Article  Google Scholar 

14.
Marshall, B. M., Strine, C. & Hughes, A. C. Thousands of reptile species threatened by under-regulated global trade. Nat. Commun. 11, 4738 (2020).
CAS  PubMed  PubMed Central  Article  ADS  Google Scholar 

15.
Auliya, M. et al. Trade in live reptiles, its impact on wild populations, and the role of the European market. Biol. Conserv. 204, 103–119 (2016).
Article  Google Scholar 

16.
Gibbon, J. W. et al. The global decline of reptiles, déjà vu amphibians. Bioscience 50, 653 (2000).
Article  Google Scholar 

17.
Ngo, H. N., Nguyen, T. Q., Phan, T. Q., van Schingen, M. & Ziegler, T. A case study on trade in threatened tiger geckos (Goniurosaurus) in Vietnam including updated information on the abundance of the Endangered G. catbaensis. Nat. Conserv. 33, 1–19 (2019).
Article  Google Scholar 

18.
Mandimbihasina, A. R. et al. The illegal pet trade is driving Madagascar’s ploughshare tortoise to extinction. Oryx 54, 188–196 (2020).
Article  Google Scholar 

19.
Stuart, B. L., Rhodin, A. G. J., Grismer, L. L. & Hansel, T. Scientific description can imperil species. Science 312, 1137b–1137b (2006).
Article  Google Scholar 

20.
Alacs, E. & Georges, A. Wildlife across our borders: A review of the illegal trade in Australia. Aust. J. Forensic Sci. 40, 147–160 (2008).
Article  Google Scholar 

21.
Vall-llosera, M. & Cassey, P. ‘Do you come from a land down under?’ Characteristics of the international trade in Australian endemic parrots. Biol. Conserv. 207, 38–46 (2017).
Article  Google Scholar 

22.
Tingley, R. et al. Geographic and taxonomic patterns of extinction risk in Australian squamates. Biol. Conserv. 238, 108203 (2019).
Article  Google Scholar 

23.
Tingley, R., Meiri, S. & Chapple, D. G. Addressing knowledge gaps in reptile conservation. Biol. Conserv. 204, 1–5 (2016).
Article  Google Scholar 

24.
Natusch, D. J. D., Lyons, J. A., Mumpuni, Riyanto, A. & Shine, R. Jungle giants: Assessing sustainable harvesting in a difficult-to-survey species (Python reticulatus). PLoS One 11, e0158397 (2016).
PubMed  PubMed Central  Article  CAS  Google Scholar 

25.
Congdon, J. D. Delayed sexual maturity and demographics of Blanding’s turtles (Emydoidea blandingii): Implications for conservation and management of long-lived organisms. Conserv. Biol. 7, 826–833 (1993).
Article  Google Scholar 

26.
Congdon, J. D., Dunham, A. E. & Sels, R. C. V. L. Demographics of common snapping turtles (Chelydra serpentina): Implications for conservation and management of long-lived organisms. Am. Zool. 34, 397–408 (1994).
Article  Google Scholar 

27.
Purvis, A., Gittleman, J. L., Cowlishaw, G. & Mace, G. M. Predicting extinction risk in declining species. Proc. R. Soc. Lond. B Biol. Sci. 267, 1947–1952 (2000).
CAS  Article  Google Scholar 

28.
Chapple, D. G. et al. The Action Plan for Australian Lizards and Snakes 2017 (CSIRO Publishing, 2019).
Google Scholar 

29.
Geyle, H. M. et al. Reptiles on the brink: Identifying the Australian terrestrial snake and lizard species most at risk of extinction. Pac. Conserv. Biol. https://doi.org/10.1071/PC20033 (2020).
Article  Google Scholar 

30.
Webb, J. K., Harlow, P. S. & Pike, D. A. Australian reptiles and their conservation. In Austra l Ark: The State of Wildlife in Australia and New Zealand 354–381 (Cambridge University Press, 2015).
Google Scholar 

31.
Webb, J. K., Brook, B. W. & Shine, R. Collectors endanger Australia’s most threatened snake, the broad-headed snake Hoplocephalus bungaroides. Oryx 36, 170–181 (2002).
Article  Google Scholar 

32.
Webb, J. K., Brook, B. W. & Shine, R. What makes a species vulnerable to extinction? Comparative life-history traits of two sympatric snakes. Ecol. Res. 17, 59–67 (2002).
Article  Google Scholar 

33.
Webb, J. K. & Shine, R. Ecological characteristics of a threatened snake species, Hoplocephalus bungaroides (Serpentes, Elapidae). Anim. Conserv. 1, 185–193 (1998).
Article  Google Scholar 

34.
Burbidge, A. A. & Jenkins, R. W. G. Endangered Vertebrates of Australia and Its Island Territories (Australian National Parks and Wildlife Service, 1984).
Google Scholar 

35.
Sumner, J., Webb, J. K., Shine, R. & Keogh, J. S. Molecular and morphological assessment of Australia’s most endangered snake, Hoplocephalus bungaroides, reveals two evolutionarily significant units for conservation. Conserv. Genet. 11, 747–758 (2010).
Article  Google Scholar 

36.
Ward, M. et al. Impact of 2019–2020 mega-fires on Australian fauna habitat. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-020-1251-1 (2020).
Article  PubMed  Google Scholar 

37.
Webb, J. K. Ecology and conservation of the endangered broad-headed snake Hoplocephalus bungaroides in Morton National Park, Australia. In Strategies for Conservation Success in Herpetology (Society for the Study of Amphibians and Reptiles, 2020).
Google Scholar 

38.
Shine, R. Arboreality in snakes: Ecology of the Australian elapid genus Hoplocephalus. Copeia 1983, 198 (1983).
Article  Google Scholar 

39.
Webb, J. K., Brook, B. W. & Shine, R. Does foraging mode influence life history traits? A comparative study of growth, maturation and survival of two species of sympatric snakes from south-eastern Australia. Austral. Ecol. 28, 601–610 (2003).
Article  Google Scholar 

40.
Webb, J. K. & Shine, R. Out on a limb: Conservation implications of tree-hollow use by a threatened snake species (Hoplocephalus bungaroides: Serpentes, Elapidae). Biol. Conserv. 81, 21–33 (1997).
Article  Google Scholar 

41.
Dubey, S. et al. Genetic connectivity among populations of an endangered snake species from southeastern Australia (Hoplocephalus bungaroides, Elapidae). Ecol. Evol. 1, 218–227 (2011).
PubMed  PubMed Central  Article  Google Scholar 

42.
White, G. C. & Burnham, K. P. Program MARK: Survival estimation from populations of marked animals. Bird Study 46, 120–139 (1999).
Article  Google Scholar 

43.
Burnham, K. P. & Anderson, D. R. Model Selection and Inference: A Practical Information-Theoretic Approach (Springer, 1998).
Google Scholar 

44.
Cooch, E. & White, G. Using MARK—A Gentle Introduction (Springer, 2001).
Google Scholar 

45.
Sibly, R. M. & Hone, J. Population growth rate and its determinants: An overview. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 357, 1153–1170 (2002).
PubMed  PubMed Central  Article  Google Scholar 

46.
Webb, J. K. & Shine, R. A field study of spatial ecology and movements of a threatened snake species, Hoplocephalus bungaroides. Biol. Conserv. 82, 203–217 (1997).
Article  Google Scholar 

47.
Penman, T. D., Pike, D. A., Webb, J. K. & Shine, R. Predicting the impact of climate change on Australia’s most endangered snake, Hoplocephalus bungaroides. Divers. Distrib. 16, 109–118 (2010).
Article  Google Scholar 

48.
Lacy, R. C. & Pollak, J. P. Vortex: A Stochastic Simulation of the Extinction Process. Version 10.2.9. , Brookfield, Illinois, USA. (2017).

49.
Brook, B. W. et al. Predictive accuracy of population viability analysis in conservation biology. Nature 404, 385–387 (2000).
CAS  PubMed  Article  ADS  Google Scholar 

50.
Naujokaitis-Lewis, I. R., Curtis, J. M. R., Arcese, P. & Rosenfeld, J. Sensitivity analyses of spatial population viability analysis models for species at risk and habitat conservation planning. Conserv. Biol. 23, 225–229 (2009).
PubMed  Article  Google Scholar 

51.
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
Google Scholar 

52.
Revelle, W. Psych: Procedures for Personality and Psychological Research. HttpsCRANR-Proj. (2019).

53.
Heppell, S. S., Caswell, H. & Crowder, L. B. Life histories and elasticity patterns: Perturbation analysis for species with minimal demographic data. Ecology 81, 654–665 (2000).
Article  Google Scholar 

54.
Sæther, B.-E. & Bakke, Ø. Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81, 642–653 (2000).
Article  Google Scholar 

55.
Carrete, M., Sánchez-Zapata, J. A., Benítez, J. R., Lobón, M. & Donázar, J. A. Large scale risk-assessment of wind-farms on population viability of a globally endangered long-lived raptor. Biol. Conserv. 142, 2954–2961 (2009).
Article  Google Scholar 

56.
Hitchmough, R., Adams, L., Reardon, J. & Monks, J. Current challenges and future directions in lizard conservation in New Zealand. J. R. Soc. N. Z. 46, 29–39 (2016).
Article  Google Scholar 

57.
Knox, C. D. Habitat requirements of the jewelled gecko (Naultinus gemmeus): Effects of grazing, predation and habitat fragmentation. Masters Thesis, University of Otago, Dunedin. (2010).

58.
Knox, C. D., Cree, A. & Seddon, P. J. Accurate identification of individual geckos (Naultinus gemmeus) through dorsal pattern differentiation. N. Z. J. Ecol. 37, 60–66 (2013).
Google Scholar 

59.
Pike, D. A., Croak, B. M., Webb, J. K. & Shine, R. Subtle—but easily reversible—anthropogenic disturbance seriously degrades habitat quality for rock-dwelling reptiles. Anim. Conserv. 13, 411–418 (2010).
Article  Google Scholar 

60.
Fleishman, E., Ray, C., Sjogren-Gulve, P., Boggs, C. L. & Murphy, D. D. Assessing the roles of patch quality, area, and isolation in predicting metapopulation dynamics. Conserv. Biol. 16, 706–716 (2002).
Article  Google Scholar 

61.
Thomas, J. A. et al. The quality and isolation of habitat patches both determine where butterflies persist in fragmented landscapes. Proc. R. Soc. Lond. B Biol. Sci. 268, 1791–1796 (2001).
CAS  Article  Google Scholar 

62.
Verboom, J., Schotman, A., Opdam, P. & Metz, J. A. J. European nuthatch metapopulations in a fragmented agricultural landscape. Oikos 61, 149 (1991).
Article  Google Scholar 

63.
Croak, B. M., Pike, D. A., Webb, J. K. & Shine, R. Habitat selection in a rocky landscape: Experimentally decoupling the influence of retreat site attributes from that of landscape features. PLoS One 7, e37982 (2012).
CAS  PubMed  PubMed Central  Article  ADS  Google Scholar 

64.
Croak, B. M., Pike, D. A., Webb, J. K. & Shine, R. Using artificial rocks to restore nonrenewable shelter sites in human-degraded systems: Colonization by fauna. Restor. Ecol. 18, 428–438 (2008).
Article  Google Scholar 

65.
Shine, R., Webb, J. K., Fitzgerald, M. & Sumner, J. The impact of bush-rock removal on an endangered snake species, Hoplocephalus bungaroides (Serpentes: Elapidae). Wildl. Res. 25, 285 (1998).
Article  Google Scholar 

66.
Webb, J. K., Pringle, R. M. & Shine, R. Intraguild predation, thermoregulation, and microhabitat selection by snakes. Behav. Ecol. 20, 271–277 (2009).
Article  Google Scholar 

67.
Moilanen, A. & Hanski, I. Metapopulation dynamics: Effects of habitat quality and landscape structure. Ecology 79, 2503–2515 (1998).
Article  Google Scholar 

68.
Iudicello, S., Weber, M. L. & Wieland, R. Fish, Markets, and Fishermen: The Economics of Overfishing (Island Press, 1999).
Google Scholar 

69.
Shine, R. & Fitzgerald, M. Conservation and reproduction of an endangered species: The broad-headed snake, Hoplocephalus bungaroides (Elapidae). Aust. Zool. 25, 65–67 (1989).
Article  Google Scholar 

70.
Bowman, D. M. J. S. et al. Vegetation fires in the Anthropocene. Nat. Rev. Earth Environ. 1, 500–515 (2020).
Article  ADS  Google Scholar  More

1.
d’Errico, F. & Banks, W. E. Identifying mechanisms behind Middle Paleolithic and Middle Stone Age cultural trajectories. Curr. Anthropol. 54, S371–S387 (2013).
Article  Google Scholar 
2.
Richerson, P. J., Bettinger, R. L. & Boyd, R. Evolution on a restless planet: Were environmental variability and environmental change major drivers of human evolution? In Handbook of Evolution: The Evolution of Living Systems (Including Hominids) Vol. 2 (eds Wuketits, F. M. & Ayala, F. J.) 223–242 (Wiley-VCH, New York, 2005).
Google Scholar 

3.
Pedersen, J., Maier, A. & Riede, F. A punctuated model for the colonisation of the Late Glacial margins of northern Europe by Hamburgian hunter-gatherers. Quartär 65, 85–104 (2018).
Google Scholar 

4.
Riede, F. & Pedersen, J. B. Late glacial human dispersals in Northern Europe and disequilibrium dynamics. Hum. Ecol. 46, 621–632 (2018).
Article  Google Scholar 

5.
Langley, M. C., Clarkson, C. & Ulm, S. Behavioural complexity in Eurasian Neanderthal Populations: A chronological examination of the archaeological evidence. Camb. Archaeol. J. 18, 289–307 (2008).
Article  Google Scholar 

6.
Roebroeks, W. & Soressi, M. Neandertals revised. Proc. Natl. Acad. Sci. USA 113, 6372–6379 (2016).
CAS  PubMed  Article  Google Scholar 

7.
Zilhão, J. et al. Last Interglacial Iberian Neandertals as fisher-hunter-gatherers. Science 367, 6485 (2020).
Article  CAS  Google Scholar 

8.
Benito, B. M. et al. The ecological niche and distribution of Neanderthals during the Last Interglacial. J. Biogeogr. 44, 51–61 (2017).
Article  Google Scholar 

9.
Nielsen, T. K. et al. Investigating Neanderthal dispersal above 55°N in Europe during the Last Interglacial Complex. Quat. Int. 431, 88–103 (2017).
Article  Google Scholar 

10.
Bocquet-Appel, J.-P. & Tuffreau, A. Technological responses of neanderthals to macroclimatic variations (240,000–40,000 BP). Hum. Biol. 81, 287–307 (2009).
PubMed  Article  Google Scholar 

11.
Daujeard, C. et al. Neanderthal subsistence strategies in Southeastern France between the plains of the Rhone Valley and the mid-mountains of the Massif Central (MIS 7 to MIS 3). Quat. Int. 252, 32–47 (2012).
Article  Google Scholar 

12.
Discamps, E., Jaubert, J. & Bachellerie, F. Human choices and environmental constraints: deciphering the variability of large game procurement from Mousterian to Aurignacian times (MIS 5–3) in southwestern France. Quat. Sci. Rev. 30, 2755–2775 (2011).
Article  ADS  Google Scholar 

13.
Hublin, J. J. The origin of Neandertals. Proc. Natl. Acad. Sci. USA 106, 16022–16027 (2009).
CAS  PubMed  Article  ADS  Google Scholar 

14.
Rogers, A. R., Bohlender, R. J. & Huff, C. D. Early history of Neanderthals and Denisovans. Proc. Natl. Acad. Sci. USA 114, 9859–9863 (2017).
CAS  PubMed  Article  Google Scholar 

15.
Moncel, M.-H. et al. Early Levallois core technology between Marine Isotope Stage 12 and 9 in Western Europe. J. Hum. Evol. 139, 102735 (2020).
PubMed  Article  Google Scholar 

16.
Castellano, S. et al. Patterns of coding variation in the complete exomes of three Neandertals. Proc. Natl. Acad. Sci. USA 111, 6666–6671 (2014).
CAS  PubMed  Article  ADS  Google Scholar 

17.
Mafessoni, F. & Prüfer, K. Better support for a small effective population size of Neandertals and a long shared history of Neandertals and Denisovans. Proc. Natl. Acad. Sci. USA 114, E10256–E10257 (2017).
CAS  PubMed  Article  Google Scholar 

18.
Prüfer, K. et al. A high-coverage Neandertal genome from Vindija Cave in Croatia. Science 358, 655–658 (2017).
PubMed  PubMed Central  Article  ADS  CAS  Google Scholar 

19.
Moncel, M.-H., Fernandes, P., Willmes, M., James, H. & Grün, R. Rocks, teeth, and tools: New insights into early Neanderthal mobility strategies in South-Eastern France from lithic reconstructions and strontium isotope analysis. PLoS ONE 14, e0214925 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

20.
Peterson, A. T. et al. Ecological Niches and Geographic Distributions (Princeton University Press, Princeton, 2011).
Google Scholar 

21.
Rogers, A. R., Bohlender, R. J. & Huff, C. D. Reply to Mafessoni and Prüfer: Inferences with and without singleton site patterns. Proc. Natl. Acad. Sci. USA 114, E10258–E10260 (2017).
CAS  PubMed  Article  Google Scholar 

22.
Vaissié, E. et al. Techno-économie et signification culturelle de l’occupation moustérienne supérieure de Baume-Vallée (Haute-Loire). C.R. Palevol 16, 804–819 (2017).
Article  Google Scholar 

23.
Bocquet-Appel, J.-P., Demars, P.-Y., Noiret, L. & Dobrowsky, D. Estimates of Upper Palaeolithic meta-population size in Europe from archaeological data. J. Archaeol. Sci. 32, 1656–1668 (2005).
Article  Google Scholar 

24.
Delagnes, A., Jaubert, J. & Meignen, L. Les technocomplexes du Paléolithique moyen en Europe occidentale dans leur cadre diachronique et géographique. In Les Néandertaliens Biologie et cultures (eds Vandermeersch, B. & Maureille, B.) 213–229 (Editions du Comité des Travaux Historiques et Scientifiques, Aubervilliers, 2007).
Google Scholar 

25.
Faivre, J.-P., Gravina, B., Bourguignon, L., Discamps, E. & Turq, A. Late Middle Palaeolithic lithic technocomplexes (MIS 5–3) in the northeastern Aquitaine Basin: Advances and challenges. Quat. Int. 433, 116–131 (2017).
Article  Google Scholar 

26.
Jaubert, J., Bordes, J.-G., Discamps, E. & Gravina, B. A new look at the end of the Middle Palaeolithic Sequence in Southwestern France. In Characteristic Features of the Middle to Upper Paleolithic transition in Eurasia (eds Derevianko, A. P. & Shunkov, M. V.) 102–115 (Asian Palaeolithic Association, Tokyo, 2011).
Google Scholar 

27.
Boëda, E. Levallois: A volumetric construction, methods, A technique. In The Definition and Intrepretation of Levallois Technology (eds Dibble, H. L. & Bar-Yosef, O.) 41–68 (Prehistory Press, Madison, 1995).
Google Scholar 

28.
Boëda, E. L. débitage discoïde et le débitage Levallois récurrent centripède. Bull. Soc. Préhist. Fr. 90, 392–404 (1993).
Article  Google Scholar 

29.
Bourguignon, L. Le Moustérien de type Quina: Nouvelles définitions d’une entité technique (University of Paris 10, Paris, 1997).
Google Scholar 

30.
Turq, A. L. Moustérien de type Quina. Paléo Rev. Archéol. Préhist. 2, 310–343 (2000).
Google Scholar 

31.
Turq, A. Approche technologique et économique du faciès Moustérien de type Quina: Étude préliminaire. Bull. Soc. Préhist. Fr. 86, 244–256 (1989).
Article  Google Scholar 

32.
Collard, M., Vaesen, K., Cosgrove, R. & Roebroeks, W. The empirical case against the ‘demographic turn’ in Palaeolithic archaeology. Philos. Trans. R. Soc. B 371, 20150242 (2016).
Article  Google Scholar 

33.
Soberón, J. & Nakamura, M. Niches and distributional areas: Concepts, methods, and assumptions. Proc. Natl. Acad. Sci. USA 106, 19644–19650 (2009).
PubMed  Article  ADS  Google Scholar 

34.
Cobos, M. E., Peterson, A. T., Barve, N. & Osorio-Olvera, L. kuenm: An R package for detailed development of ecological niche models using Maxent. PeerJ 7, e6281 (2019).
PubMed  PubMed Central  Article  Google Scholar 

35.
Cobos, M. E., Osorio-Olvera, L., Soberón, J. & Peterson, A. T. ellipsenm: An R package for ecological niche’s characterization using ellipsoids. (2020).

36.
Waelbroeck, C. et al. Sea-level and deep water temperature changes derived from benthic foraminifera isotopic records. Quat. Sci. Rev. 21, 295–305 (2002).
Article  ADS  Google Scholar 

37.
Peterson, A. T., Papeş, M. & Soberón, J. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Model. 213, 63–72 (2008).
Article  Google Scholar 

38.
Antoine, P. et al. Paléoenvironnements pléistocènes et peuplements paléolithiques dans le bassin de la Somme (nord de la France). Bull. Soc. Préhist. Fr. 100, 5–28 (2003).
Article  Google Scholar 

39.
Locht, J.-L. et al. Timescales, space and culture during the Middle Palaeolithic in northwestern France. Quat. Int. 411, 129–148 (2016).
Article  Google Scholar 

40.
Raynal, J.-P. et al. Land-use strategies, related tool-kits and social organization of lower and middle Palaeolithic groups in the South-East of the Massif Central, France. Quartär 60, 29–59 (2013).
Google Scholar 

41.
Turq, A., Faivre, J.-P., Gravina, B. & Bourguignon, L. Building models of Neanderthal territories from raw material transports in the Aquitaine Basin (southwestern France). Quat. Int. 433, 88–101 (2017).
Article  Google Scholar 

42.
Mathias, C., Bourguignon, L., Brenet, M., Grégoire, S. & Moncel, M.-H. Between new and inherited technical behaviours: A case study from the Early Middle Palaeolithic of Southern France. Archaeol. Anthropol. Sci. 12, 1–39 (2020).
Article  Google Scholar 

43.
Lebegue, F. & Meignen, L. Quina ou pas ? Révision techno-économique d’un site moustérien charentien en Languedoc oriental: La grotte de la Roquette à Conqueyrac (Gard, France). Bull. Soc. Préhist. Fr. 111, 603–630 (2014).
Article  Google Scholar 

44.
Moncel, M.-H. et al. La grotte du Figuier (Saint-Martin-d’Ardèche): Bilan des travaux récents sur un site du Paléolithique moyen et supérieur de la moyenne vallée du Rhône (Sud-Est de la France). Bull. Soc. Préhist. Fr. 109, 35–67 (2012).
Article  Google Scholar 

45.
Slimak, L. Moustériens Quina Rhodaniens et Quina classiques dans le sud-est de la France. In Territoires, Déplacements, Mobilité, Echanges durant la Préhistoire (eds Jaubert, J. & Barbaza, M.) 95–113 (Comité des travaux historiques et scientifiques, Aubervilliers, 2005).
Google Scholar 

46.
Sánchez Goñi, M. F., Bard, E., Landais, A., Rossignol, L. & d’Errico, F. Air–sea temperature decoupling in western Europe during the last interglacial–glacial transition. Nat. Geosci. 6, 837–841 (2013).
Article  ADS  CAS  Google Scholar 

47.
Antoine, P., Munaut, A.-V. & Sommé, J. Réponse des environnements aux climats du début glaciaire weichsélien: Données de la France du Nord-Ouest [Responses of the environments to Early Weichselian climates. Records in north­western France]. Quaternaire 5, 151–156 (1994).
Article  Google Scholar 

48.
Fletcher, W. J. et al. Millennial-scale variability during the last glacial in vegetation records from Europe. Quat. Sci. Rev. 29, 2839–2864 (2010).
Article  ADS  Google Scholar 

49.
Baena, J., Moncel, M.-H., Cuartero, F., Chacón Navarro, M. G. & Rubio, D. Late Middle Pleistocene genesis of Neanderthal technology in Western Europe: The case of Payre site (south-east France). Quat. Int. 436, 212–238 (2017).
Article  Google Scholar 

50.
Geneste, J.-M., Jaubert, J., Lenoir, M., Meignen, L. & Turq, A. Approche technologique des Moustériens Charentiens du Sud-Ouest de la France et du Languedoc oriental. Paléo Rev. Archéol. Préhist. 9, 101–142 (1997).
Google Scholar 

51.
Geneste, J.-M. & Plisson, H. Production et utilisation de l’outillage lithique dans le Moustérien du sud-ouest de la France: les Tares à Sourzac, Vallé de l’Isle, Dordogne. Quat. Nova 6, 343–367 (1996).
Google Scholar 

52.
Mathias, C. & Bourguignon, L. Cores-on-flakes and ramification during the middle palaeolithic in Southern France: A gradual process from the early to late middle palaeolithic?. J. Archaeol. Sci. Rep. 31, 102336 (2020).
Google Scholar 

53.
Halstead, P. & O’Shea, J. Introduction: Cultural responses to risk and uncertainty. In Bad Year Economics: Cultural Responses to Risk and Uncertainty (eds Halstead, P. & O’Shea, J.) 1–7 (Cambridge University Press, Cambridge, 1989).
Google Scholar 

54.
d’Errico, F. et al. Identifying early modern human ecological niche expansions and associated cultural dynamics in the South African Middle Stone Age. Proc. Natl. Acad. Sci. USA 114, 7869–7876 (2017).
PubMed  Article  CAS  Google Scholar 

55.
Delagnes, A. & Meignen, L. Diversity of lithic production systems during the Middle Paleolithic in France. In Transitions Before the Transition: Evolution and Stability in the Middle Paleolithic and Middle Stone Age (eds Hovers, E. & Kuhn, S. L.) 85–107 (Springer Verlag, New York, 2006).
Google Scholar 

56.
Hiscock, P., Turq, A., Faivre, J.-P. & Bourguignon, L. Quina procurement and tool production. In Lithic Materials and Paleolithic Societies (eds Adams, B. & Blades, B. S.) 232–246 (Wiley-Blackwell, New York, 2009).
Google Scholar 

57.
Binford, L. R. Willow smoke and dogs’ tails: Hunter-gatherer settlement systems and archaeological site formation. Am. Antiq. 45, 4–20 (1980).
Article  Google Scholar 

58.
Dibble, H. L. et al. Context, curation, and bias: An evaluation of the Middle Paleolithic collections of Combe-Grenal (France). J. Archaeol. Sci. 36, 2540–2550 (2009).
Article  Google Scholar 

59.
R Core Team. R: A Language and Environment for STATISTICAL Computing (R Foundation for Statistical Computing, Vienna, 2019).
Google Scholar 

60.
Lê, S., Josse, J. & Husson, F. FactoMineR: An R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).
Article  Google Scholar 

61.
Sarkar, D. Lattice: Multivariate Data Visualization with R (Springer, Berlin, 2008).
Google Scholar 

62.
Fernandes, P., Raynal, J.-P. & Moncel, M.-H. Middle Palaeolithic raw material gathering territories and human mobility in the southern Massif Central, France: first results from a petro-archaeological study on flint. J. Archaeol. Sci. 35, 2357–2370 (2008).
Article  Google Scholar 

63.
Dufresne, J.-L. et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn. 40, 2123–2165 (2013).
Article  Google Scholar 

64.
Argus, D. F. & Peltier, W. R. Constraining models of postglacial rebound using space geodesy: A detailed assessment of model ICE-5G (VM2) and its relatives. Geophys. J. Int. 181, 697–723 (2010).
ADS  Google Scholar 

65.
Petit, J. R. et al. Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399, 429–436 (1999).
CAS  Article  ADS  Google Scholar 

66.
Laskar, J. et al. A long-term numerical solution for the insolation quantities of the Earth. Astron. Astrophys. 428, 261–285 (2004).
Article  ADS  Google Scholar 

67.
Vrac, M., Marbaix, P., Paillard, D. & Naveau, P. Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe. Clim. Past 3, 669–682 (2007).
Article  Google Scholar 

68.
Pfeiffer, M., Spessa, A. & Kaplan, J. O. A model for global biomass burning in preindustrial time: LPJ-LMfire (v1.0). Geosci. Model Dev. 6, 643–685 (2013).
Article  ADS  CAS  Google Scholar 

69.
Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: An open-source release of Maxent. Ecography 40, 887–893 (2017).
Article  Google Scholar 

70.
Cobos, M. E., Peterson, A. T., Osorio-Olvera, L. & Jiménez-García, D. An exhaustive analysis of heuristic methods for variable selection in ecological niche modeling and species distribution modeling. Ecol. Inform. 53, 100983 (2019).
Article  Google Scholar 

71.
Anderson, R. P., Lew, D. & Peterson, A. T. Evaluating predictive models of species’ distributions: Criteria for selecting optimal models. Ecol. Model. 162, 211–232 (2003).
Article  Google Scholar 

72.
Warren, D. L. & Seifert, S. N. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol. Appl. 21, 335–342 (2011).
PubMed  Article  Google Scholar 

73.
Owens, H. L. et al. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas. Ecol. Model. 263, 10–18 (2013).
Article  Google Scholar 

74.
Nuñez-Penichet, C., Cobos, M. E. & Soberon, J. Non-overlapping climatic niches and biogeographic barriers explain disjunct distributions of continental Urania moths. Front. Biogeogr. 13(2), e52142 (2021).
Google Scholar 

75.
Qiao, H. et al. NicheA: Creating virtual species and ecological niches in multivariate environmental scenarios. Ecography 39, 805–813 (2016).
Article  Google Scholar 

76.
Mammola, S. Assessing similarity of n-dimensional hypervolumes: Which metric to use?. J. Biogeogr. 46, 2012–2023 (2019).
Article  Google Scholar 

77.
Van Aelst, S. & Rousseeuw, P. Minimum volume ellipsoid. WIREs. Comput. Stat. 1, 71–82 (2009).
Article  Google Scholar 

78.
Murdoch, D. J. & Chow, E. D. A graphical display of large correlation matrices. Am. Stat. 50, 178–180 (1996).
Google Scholar  More

Sampling stations
Baywatchers sampling stations were generally concentrated in the upper half of estuaries and major sub-estuaries to better characterize water quality changes over time. The program has grown over time and expanded to include additional stations within sub-estuaries as well as adding additional sub-estuaries. In 2012, stations were added in Vineyard Sound, which adjoins Buzzards Bay, and in 2017, sampling began at additional stations in the coastal ponds connected to Vineyard Sound.
We assign each station a unique identification code (station ID) and data are integrated into geographic information systems. Station maps are given to monitors (historically using ArcView GIS overlaid on scanned U.S.G.S. quadrangle maps, but more recently, using Google Earth to produce the maps overlaid on aerial images). In a small number of cases, the location of a monitoring site has varied slightly over time—for example, nutrient samples were collected in the Agawam River in a rowboat 250 feet from shore from 1998 to 2007 (station AG2A), but have been collected from a nearby dock since 2008 (station AG2). When a monitoring site’s location has moved, it is given a unique station ID in the database (i.e., AG2 vs AG2A in the example above).
Field sampling
Sampling occurs from late May to September to document conditions when biological activity is highest. Field water sampling is separated into “basic” sampling and “laboratory” sampling days. On all sampling dates, water temperature, salinity, Secchi depth, and total depth are measured in the field. Monitors record these results on hard copy datasheets along with the station ID, sampling date, collection time, name of person sampling, and name of the sub-estuary.
On basic sampling days, D.O. is measured in the early morning (between 6:00 and 9:00 am) to capture typical daily minimum oxygen concentrations before peak daytime photosynthetic oxygen production. Basic sampling occurs on a schedule roughly every five days between late May and mid-September. On laboratory sampling days, oxygen measurements are only made if the monitor has a water quality sonde, as the focus is the collection of samples for laboratory analysis of NH4+, NO3− + NO2−, PO43−, TDN, PON, POC, Chl a, and Pheo. At designated fresh water and low salinity stations, TP and DOC are also measured. Laboratory sampling occurs on four scheduled days each summer (2 in July, 2 in August) during the last three hours of an outgoing tide when concentrations of solutes in estuarine water are expected to most strongly reflect the influence of watershed inputs. While the vast majority of observations were made between late May and mid-September (Fig. 3), some additional basic and laboratory sampling occurred at other times of the year when short-term projects provided opportunities for expanded sampling.
Fig. 3

Frequency of Baywatchers samples collected by month between 1992 and 2018. Note difference in y-axis scale for panel c.

Full size image

The Buzzards Bay Coalition pairs some nearby basic sampling stations with laboratory sampling stations for analysis of sub-estuary water quality. These station pairs have station IDs that end in either the suffix X or N to indicate that they are sampled on basic or laboratory sampling days, respectively.
Basic sampling procedures
Water samples are collected for water temperature, salinity, and D.O. from near the bottom of the water column (0.3 m above the bottom). Where the water column is deeper than 1.2 m, a sample near the surface (0.15 m depth) is also collected to provide information on potential water column stratification. The depth of 0.15 m below the surface prevents entrainment of floating particles and overlying air into the sample bottles. Sampling 0.3 m above the bottom prevents resuspension and capture of bottom sediments by the sampling apparatus.
Water samples for temperature, salinity, and D.O. are collected either with a steel sampling pole or measured in situ with water quality sondes (YSI models 600XL, 600XLM, 6600, EXO2, ProDSS). Sampling poles are 1.5 or 3 m long and marked in 5 to 10 cm depth increments. Sampling poles have 1 L and 0.5 L plastic (HDPE) bottles with rubber stopper closures connected to strings. Poles are lowered to the appropriate depth and then bottles are opened by pulling the strings, first the 0.5 L bottle is opened, followed by the 1 L bottle. D.O. is measured from the 0.5 L bottle, so it is opened first to prevent entrainment of air bubbles into the D.O. sample. Temperature and salinity are measured from the 1 L bottle. Water temperature is measured directly in the 1 L bottle using a thermometer that is calibrated annually. Monitors have primarily used analog thermometers; however, some digital thermometers have been used since 2016. Salinity is measured by then transferring 0.5 L of sample from the 1 L bottle to a 0.5 L graduated cylinder. Specific gravity is measured using a hydrometer that is calibrated annually. Temperature is measured in the graduated cylinder and salinity is determined from a table of specific gravity and temperature.
The 0.5 L bottle has been modified with plastic fittings and tubing at the bottom so that water can be extracted from the bottom of the bottle. Water is siphoned through the tubing to the bottom of a glass-stoppered bottle, overflowing the glass bottle until the 0.5 L bottle is only one-quarter full. Monitors measure D.O. in the glass bottle directly in the field using a modified Winkler titration (Hach Test Kit, Model OX-2P). Briefly, pre-weighed aliquots of manganese sulphate and a lithium hydroxide monohydrate/potassium iodide mixture are added to the sample bottle, which is stoppered and vigorously shaken. The resultant floc is allowed to settle, then reshaken and settled again, before the addition of a pre-weighed aliquot of a sodium phosphate dibasic/sodium sulphate/citric acid mixture. The sample is shaken until this dissolves and the sample is clear, then an aliquot of sample is measured into a separate vial. The sample aliquot is titrated drop-wise using a sodium thiosulphate standard until the sample becomes colorless. The D.O. concentration (mg L−1) is calculated from the number of titration drops.
Secchi depth is recorded by lowering a Secchi disk into water slowly from the shady side of a boat, dock or pier until it just disappears from view. It is then raised and lowered slightly to ensure the proper average depth of disappearance. If the Secchi disk hits the bottom before it disappears, no Secchi depth value is recorded. Total depth is determined when slack is felt in the measuring tape of the Secchi disk.
On basic sampling days, monitors also record the tidal direction (ebb or flood) and the time of the nearest low tide according to the Eldridge Tide and Pilot Book, wave conditions according to the Beaufort scale, and weather status (based on eight potential choices: cloudless, partly cloudy, overcast, fog/haze, drizzle, intermittent rain, rain, snow). Precipitation in the previous 24 hours is noted as either none, light, or heavy. Wind direction is also recorded. All data are recorded on a paper data sheet.
Approximately 20,000 of the temperature, salinity, and D.O. and roughly 5,000 of the pH and Chl a measurements were made in situ using water quality sondes. The majority of these measurements were made since 2000 (YSI models 600XL, 600XLM, 6600, EXO2, ProDSS), though a few were made in the early years of the program (YSI model 51B). The sonde measurements are made following the manufacturers’ standard operating procedures. Instruments are calibrated for temperature, salinity, D.O., pH and Chl a at the beginning of each sampling season. The instrument D.O. calibration is checked prior to each sampling day and re-calibrated in the field if necessary.
Laboratory sampling procedures
On laboratory sampling days, water samples for analysis of dissolved and particulate constituents are primarily collected from near the surface (0.15 m), though a small portion have been collected from near the bottom (0.3 m above bottom). Bottom water samples were generally collected near where there is significant freshwater input that could cause water column stratification. Station ID, water temperature, salinity, Secchi depth, total depth, sample depth, and collection time are recorded in the field on hard copy data sheets. Monitors with sondes also record D.O.
Samples are collected directly into 1 L acid-washed plastic HDPE bottles either by hand or using the sampling pole. All bottles used in water collection were acid washed by the analytical laboratory. Samples bottles are rinsed once with sample prior to filling with the sample. When using the sampling pole, sample bottles are attached and removed using hose clamps.
Monitors filter 60 mL of sample from the 1 L bottle using a 0.2 μm cellulose acetate membrane filter. Filters are first rinsed with 30 mL of sample, which is discarded. A subsequent 30 mL of filtered sample is used to rinse the 60 mL sampling bottle before an additional 60 mL are filtered directly into the 60 mL bottle that was previously acid washed by the analytical laboratory. The remaining unfiltered sample and the 60 mL filtered sample are stored in coolers with ice packs and delivered on the day they are collected to the analytical laboratory. A new membrane filter is used for each sample and the filter holder and syringes are rinsed with tap water after a sample is filtered.
Laboratory analyses
Laboratory analyses were conducted under the supervision of B. Howes at the Woods Hole Oceanographic Institution (1992–1997) and at the University of Massachusetts, Dartmouth (1998–2007), and under H. Ducklow (2008–2012) and C. Neill (2013–2018) at the Marine Biological Laboratory. The methods and instruments described below are those currently used. In some cases, the instruments used have changed, but there has been a significant effort to maintain consistency over the lifetime of the program and to intercalibrate methods/instruments when a change has been made.
Laboratory analyses are designed to accommodate the samples that range from fresh water to nearly full strength seawater and analyte concentrations that range from at or below the detection limit for a method to 1,000 times the detection limit in some cases. Laboratory staff used aliquots of the 60 mL field-filtered sample to perform the dissolved analyses (NH4+, NO3− + NO2−, PO43−, TDN). The filtration for the particulate analyses (Chl a, Pheo, PON, POC) was performed by laboratory staff using water from the 1 L dark sample bottle.
NH4+ is measured colorimetrically by the indophenol-hypochlorite method18. Analyses are conducted in pre-reacted test tubes to reduce blank corrections and absorbance is read on a Cary spectrophotometer with an automatic sipper attachment. NH4+ is analysed on the day samples are collected.
NO3− + NO2− is measured colorimetrically after cadmium reduction19 on a Lachat flow injection analyser (Hach, Loveland, CO). The method was modified for flow injection analysis by Lachat Instruments20. Prior to analysis, samples are refrigerated at 4 °C. Samples are analysed within one week of collection if collected July-August, or if collected outside of July-August, frozen and analysed within 90 days.
PO43− is measured colorimetrically by the molybdenum blue method21 on a Lachat flow injection analyser (Hach, Loveland, CO). The method was modified for flow injection analysis by Lachat Instruments22. Samples are analysed within one week of collection if collected July-August, or if collected outside of July-August, frozen and analysed within 90 days.
TDN is analysed by persulphate digestion23 that oxidizes dissolved nitrogen to NO3− and subsequent analysis of NO3− by colorimetry on a Lachat flow injection analyser. To reduce the magnitude of the reagent blank, persulphate is recrystallized prior to analysis. Samples are stored at 4 °C prior to analysis and are analysed within two weeks of collection if collected July-August, or collected outside of July-August, frozen and analysed within 90 days.
Chl a and Pheo are measured with method of Arar et al.24 by filtering a known volume of water through a 25 mm glass fiber filter (GFF). On the day of sample collection, samples are filtered under low vacuum pressure ( More